journal of special education technology exploration of unknown

Journal of Special Education Technology. 19(3), Summer 2004 5

Journal of Special Education Technology

Having the ability to write accurately and effectively is anecessary skill at school and in daily activities. Students withphysical disabilities often have difficulty with the mechanicsof writing, including speed and spelling issues. To helpincrease writing efficiency in these areas, students are oftentaught to use various forms of assistive technology, such asword prediction software. Although word prediction softwarehas been successfully used with other populations of studentsto increase typing speed and decrease spelling errors,systematic studies have not been performed examining theeffectiveness of this approach with students who have physicaldisabilities that affect hand use.

The physical act of writing can be difficult for studentswith physical disabilities. For some students with physicaldisabilities, handwriting may not be an option due tolimitations in motor control, difficulty forming letters,illegible writing, or slow speed. Typing is often a more feasibleoption since it eliminates legibility problems and is consideredfaster than handwriting for skilled typists who do not havedisabilities (MacArthur, 1996, 1999a). However, studentswith physical disabilities can find typing to be laborious due tolimitations in motor control, slow typing speed, andunfamiliarity with the standard keyboard arrangement (Lewis,Graves, Ashton, & Kieley, 1998).

To make typing a more feasible option, some studentswith physical disabilities may need to use a different means ofaccessing the computer rather than a standard keyboard. Inthese instances, before students with disabilities can accessthe computer, it is imperative that a reliable method forinputting information is in place (Merbler, Hadadian, &Ulman, 1999). There are several different types of assistivetechnology that may be used to assist students with motorproblems in gaining computer access. In some instances,

alternative keyboards may be necessary for students to useinstead of the standard QWERTY keyboard (Logwood &Hadley, 1996). According to Merbler et al. (1999) there arefour types of alternative keyboards: (a) programmablekeyboards, (b) chording keyboards, (c) miniature keyboards,and (d) on-screen keyboards. Programmable keyboards allowfor customization of the keyboard, such as varying the repeatrate, keyboard sensitivity, and keyboard layout. Chordingkeyboards typically have fewer keys and work by the userpressing key combinations. Miniature keyboards are smallerthan standard keyboards, requiring less range of motion.Finally, on-screen keyboards appear on the computer screenand can be accessed by using a mouse, joystick, trackball,touch screen, switch (with scanning), touch screen, or otherinput device. Due to the wide variety of alternate keyboards,these keyboards are often a viable alternative to standardkeyboards for many individuals with physical disabilities.However, students with physical disabilities who are usingappropriately selected alternative keyboards may continue totype at a slow rate.

In addition to slow typing rates, students with physicaldisabilities may also have spelling errors. Spelling errors mayoccur due to mechanical writing errors resulting from motorcontrol issues. This can occur whether students are using astandard keyboard or an appropriate alternate input devicethat has been selected for them. It is important to assesswhether spelling errors are due to the inability to spell a wordor due to erratic motor patterns and keyboarding mistakes.

Outside of the mechanics of writing, the actual ability tospell can also be problematic for students with physicaldisabilities. Phonological awareness is said to predict spellingability, and Sandberg (1998) indicated that this is true for non-speaking students with cerebral palsy as well. Sandberg (2001)

Using Word Prediction Software to Increase Typing Fluency with Students with Physical Disabilities

JENNIFER TUMLIN

KATHRYN WOLFF HELLER

Georgia State University

Although word prediction software was originally developed for individuals with physicaldisabilities, no previous research was found that included participants with significant physicaldisabilities that affected hand use. Using two-minute trials, two participants improved their typingrate using word prediction software, one participant had mixed results, and the participant with thefastest pre-intervention typing speed had a decreased typing rate with word prediction. This studyindicates that the effectiveness of using word prediction software to increase typing speed may varydue to the severity of physical disability or pre-intervention typing rate.

Word Prediction6


also reported that there is often a discrepancy betweenintelligence and literacy skills of students with cerebral palsyand speech impairments. Reasons for this can include motorproblems, difficulty with expressive and receptivecommunication, memory problems, and phonological skills.Results from a three-year longitudinal study, showed studentsstill far below their peers in spelling, but they were attemptingto spell more words. However, children with severe speechimpairments and physical disabilities tended to makeomission errors, a different type of spelling error than theirpeers made (Sandberg, 2001).

One solution that may address both the slow speed ofaccessing a standard or alternate keyboard and spelling issuesis word prediction software. Most word prediction programscan be used with any word processor, with the student typingin a window separate from the word processor. As the studenttypes, word prediction software begins predicting the word thestudent is trying to type and provides a list from which acorrect word can be selected. The student can select the goalword by either clicking on it with the mouse or by typing thenumber of the corresponding word. If the correct word is notin the list, the student continues to type and the list ofpredicted words changes accordingly. When the student typesa period or presses enter, the sentence is transferred from theword prediction software to the word processor (MacArthur,1999a; 1999b). Lewis et al. (1998) stated that the wordspredicted are typically based on “word frequencies andgrammatical algorithms” (p. 97) and that advanced programscan actually learn new words that the user inputs.

In relationship to physical disabilities, MacArthur (1999a)stated that “word prediction software was originally developedfor individuals with physical disabilities to reduce the numberof keystrokes required to type words” (p. 178). Word predictionsoftware can be beneficial for students with fine motorproblems who are poor typists, who have difficulty withhandwriting, or who need help with spelling tasks. MacArthur(2000) suggested that word prediction could be an option forstudents who could not read their own handwriting or forstudents whose spelling was so poor that a spell checker couldnot offer usable suggestions. Merbler et al. (1999) suggestedthat word prediction software was suitable for any student whohad keyboarding difficulties because it reduced the number ofkeystrokes, thereby allowing the student to click on a wholeword before the word had been completely typed.

Benefits to word prediction include helping with spellingproblems, especially students whose spelling is toounrecognizable for spell checkers (MacArthur 1998a, 1999a).MacArthur (1998a, 1998b) stated that word prediction couldsupport correct spelling as well as expand the use ofvocabulary. Limitations, however, included the user needingto type the initial letter of the word correctly (MacArthur,1998a). Also, it should be noted that if the word prediction

program incorrectly predicts the student’s intended word bynot including the student’s target word in the group of wordsit displays, it may take longer and require more keystrokes tofinally have the desired word displayed.

Research examined the use of word prediction forindividuals with learning disabilities. For example, Lewis etal. (1998) assessed students’ writing and found that studentswith learning disabilities could handwrite the fastest, withword prediction next, and typing in a word processor last.They reported that teachers believed that for more advancedtypists, word prediction software slowed down their typingrate. Lewis et. al. (1998) indicated that slower typing speedswith word prediction could be due to a lack of practice andkeyboard unfamiliarity. They surmised that if students hadmore typing practice, the results might have been different.This conclusion does not necessarily carry over to physicaldisabilities, however, because these students might never beable to increase their rate of typing due to motor coordinationproblems unless there are compensatory devices in place.

In another study (Golden, 2001) with students withlearning disabilities using word prediction software, thekeyboarding rate of one student with learning disabilitiesdecreased when using word prediction. This student had thehighest words per minute rate when copying from text andhad a good knowledge of character placement on the standardkeyboard. In this instance, it was thought that the time ittook to search the word prediction list could have interruptedthis faster typist and resulted in slower typing speed.

As these studies suggest, word prediction performancecan rely on several factors. Student characteristics such as theamount of time it takes to press a key and the amount of timeit takes for a student to search the word prediction list caninfluence writing rate. Also, word prediction systemcharacteristics such as searches per character and keystrokesavings can also influence word prediction performance(Koester & Levine, 1998; Koester & Levine, 1997). Forstudents with physical disabilities, the keypress time is thefactor that is most divergent.

Although the use of word prediction holds promise forstudents with physical disabilities in increasing writingefficiency, further research is needed. The purpose of thisstudy was to examine the use of word prediction software toincrease typing speed and decrease spelling errors for studentswho have physical disabilities that affect hand use. Studentperceptions regarding the effectiveness of word prediction wasexamined as well as their typing rates and spelling accuracy.

METHODParticipants and Setting

Four students with physical disabilities were selected forthis study. Criteria for participation included: (a) having aphysical disability with fine motor problems, (b) meeting the

Tumlin and Heller 7


Georgia requirements for orthopedic impairments (i.e., studentswith physical disabilities having mild intellectual disabilities orabove), (c) receiving services through an orthopedic impairmentsspecial education program, (d) being high school age, (e) havingutilized word processing for a minimum of two years, (f) havinga below average handwriting rate, typing rate, and/or makingspelling errors on over 5% of their work (either due to motoric orlearning issues), (g) having had no formal instruction of the useof word prediction software, and (h) having had prior experiencewith accessing a computer (either with standard keyboard oralternate access devices).

The four students selected for this study had eithercerebral palsy or brain injury, the severity of which affected thefine motor coordination of their hands. These specificdisabilities were targeted since individuals with these types ofdisabilities can have difficulty with typing speed and themechanics of spelling. Also, cerebral palsy and brain injurycan both have similar motor patterns including difficultieswith manipulation, fine and gross motor coordination, motorplanning, finger strength, eye-hand coordination, and visualscanning skills (Lueck, Dote-Kwan, Senge, & Clarke, 2001).

Van was a 21-year-old student who had traumatic braininjury and severe dysarthric speech. He needed to use awheelchair for independent mobility, although he could walkusing a walker with support. He had poor gross and fine motormanipulation due to tremors that resulted in an inability towrite with a pencil. He was left-handed prior to his accident,but preferred using right hand for most tasks after theaccident. He had double vision and was unable to auditorilyprocess sound due to his brain injury. However, he was able tosee a font on the computer of 22 point or larger size. Allinformation was presented visually due to his auditoryprocessing impairment. Prior to his accident, Van had beengiven formal keyboarding instruction through a high schoolkeyboarding class that provided him with basic wordprocessing skills. Due to the severity of his physicalimpairment he used a programmable alternative keyboard

(IntelliKeys) to type with the repeat rate adjusted due toproblems of repeatedly hitting keys. However, his typing wasslow so he completed all of his assignments by dictating to ascribe. Of the four students, he had the slowest typing speed.

Sam was a 16-year-old who had spastic, quadriplegiccerebral palsy and dysarthric speech. He used a powerwheelchair for independent mobility and he could pick objectsoff his wheelchair tray and release them, but was unable tomanipulate objects well. He was not able to write using apencil. Despite the severity of his physical impairment, Samwas able to access a standard keyboard on a laptop computer,and he had basic word processing skills. However, hecompleted most of his work by dictating to a scribe becausehis typing rate was so slow. He often needed to reset orreposition his arm to achieve the desired motor pattern.

Nick was 18 years old, had athetoid and ataxic cerebralpalsy, and had moderate dysarthric speech. He was able towalk, although unsteadily. He had uncontrolled movement inhis hands and arms and often needed to stabilize one armwith the other to execute certain movements. He could pickup objects and manipulate them, although his fine motorcontrol was poor. He could write approximately two words perminute using a pencil, but his handwriting was illegible. Hewas able to type much faster using a laptop computer whichhe would use two hand to access. For assignments he woulduse either a laptop computer with word processing or dictateto a scribe.

Frank was 17 years old and had a brain injury due to abrain stem aneurysm. He used a wheelchair for independentmobility, but could use crutches with stand-by assistance. Healso had mild dysarthric speech, memory problems, as well assome vision and hearing loss on the left side. Although he wasable to manipulate small objects, hand coordination issuesresulted in slow handwriting that was often laborious andinefficient. He completed assignments by handwriting andusing basic word processing on the computer. When given achoice, he would choose not to use technology. Frank took a

Table 1.Participants

Student Age Disability Spelling Error Rate Words per minute AT or Modifications for writingVan 21 years Traumatic brain injury 8.0 % 2.9 Wpm Desktop computer IntelliKeys

Auditory processing impairment Font of 22 or largerDysarthric speech Tremors in both hands Scribe

Sam 16 years Spastic quadriplegic 6.2 % 4.7 Wpm Laptop computer Standard keyboard cerebral palsy ScribeDysarthric speech

Nick 18 years Athetoid and ataxic 13.12 % 10.9 Wpm Laptop computer Standard keyboard cerebral palsy ScribeDysarthric speech

Frank 17 years Brain injury 4.4 % 14.6 Wpm Pencil gripDesktop computer Standard keyboard

Word Prediction8


Although three-minute sessions are often used in thelearning disabilities literature (Lewis et. al., 1998), a differentcriterion for students with physical disabilities was needed.Students with severe physical impairments have motorplanning and fatigue issues that interfere with continuoustyping. Pauses or breaks interfere with calculating words perminute and this may vary greatly from day to day due to theirphysical disability and other issues. Therefore, two minuteswas selected to decrease pauses and fatigue.

Co-Writer instruction. Prior to the study, the studentsreceived individual instruction on the use of Co:Writer from theclassroom teacher during their resource technology class. Theteacher explained and modeled the features of the software andthen provided guided and independent practice. Students wereinstructed to type a word letter-by-letter and look at the wordlist after each letter typed (Koester & Levine, 1998). They wereinstructed to select the correct word by typing thecorresponding number. Instruction in the use of Co:Writer andits features continued for each student until he was able toachieve 100% accuracy on the checklist as demonstratedthrough observation. Items on the checklist included openingCo:Writer with Microsoft Word, typing, scanning the list aftereach typed letter, selecting the word from the list, sending textto Microsoft Word, and returning to the Co:Writer interface.Once students were observed completing all items on thechecklist with 100% accuracy, intervention began.

Writing sessions. The writing sessions consisted of thestudents being instructed to type a short paragraph aboutdaily events. This type of passage was selected so the studentswould not have to concern themselves with writing processesand could concentrate on typing and spelling. Students wereprovided with a writing prompt (e.g., what did you have fordinner?). The teacher then discussed the writing prompt withthe students and had them tell her what they were going totype. Rehearsal was important to eliminate pauses and toensure that there was a continuous flow and the students didnot have to stop to think about what they were writing. Theteacher then timed the student typing for two minutes.

During writing sessions, an observer stood behind thestudent to ensure that word prediction was being used. Whenthe student completed typing, he was directed to print a copyand the teacher then analyzed the permanent product for wordsper minute and spelling errors. Words per minute and spellingerrors were calculated as the same way as determined forbaseline word per minute rate and percent of spelling errors.

DesignIn this study, the dependent variables were typing rate

and percentage of spelling errors. The independent variablewas the use of word prediction software. A reversal design(Baer, Wolf, & Risley, 1968) was selected for this study inorder to display a functional relationship between the use of

formal keyboarding class after his aneurysm and was able toaccess the computer with both hands. However, during theclass, Frank’s keyboarding goals were modified and decreaseddue to his fine motor difficulties. Frank had the fastest typingspeed of the four students.

All students were instructed in the orthopedicimpairments (OI) classroom by the OI teacher with standardmaterials (e.g., laptop, alternative keyboard). Observationduring word processing tasks in the classroom indicated thatall students were able to use word processing to type. Since allstudents were most familiar with Microsoft Word, it wasselected as the word processing software.

Word Prediction SoftwareCo:Writer was selected as the word prediction software to

be used in the study due to its ease of use and having thedesired features (e.g., highly visible word choices, easyselection of target word). This commercial word predictionprogram can be used with virtually any word processor. Theuser types in a window separate from the word processor. Asthe student types, Co:Writer begins predicting the word thestudent is trying to type and provides a list from which thecorrect word can be selected. The user can select the correctword by either clicking on it with the mouse or by typing thenumber of the corresponding word. If the correct word is notin the list, the user continues to type and the list of predictedwords changes accordingly. When the user types a period orpresses enter, the sentence is transferred from Co:Writer tothe word processor.

During this study, the Co:Writer program preference wasset to the intermediate dictionary, which consists of 12,000words. The program was set to display five word choices at atime. The speech synthesis feature was turned off for allstudents because it was hypothesized that the speech synthesiswould slow the text entry process (Lewis et. al., 1998).

Procedure Determining baseline. During participant selection, each

student’s baseline typing rate and percent of spelling errorswere assessed to determine if participants were candidates forthe study. This occurred by providing five sessions in whichthe participants typed using only word processing. Typing ratewas determined by counting four characters as a word andwas reported as words per minute (MacArthur, 1998b).Spelling errors were calculated and reported as the percent ofwords spelled incorrectly. Unlike the typing rate, the wordswere viewed as individual words, not as a set number ofcharacters. Percent of spelling was calculated by dividingnumber of spelling errors by total words typed. Determinationof baseline typing rate and percent of spelling errors occurredacross five sessions. Students were timed for two minutes foreach session.

Tumlin and Heller 9


word prediction on spelling errors and typing rate. The five-session pretest that established their typing rate and spellingerrors was used as baseline. During this time, the participantsused only a word processor to write.

After baseline was complete, the first intervention phasewas started. During the intervention phase, the students usedthe Co:Writer word prediction program with the word processingprogram. Typing rates and spelling errors were calculated foreach session. Due to the variability and unpredictability ofmotor skills of students with physical disabilities, this phase(and all phases) were conducted for five sessions.

A return to baseline phase occurred next, during whichthe students wrote using only the word processor. Thiscontinued for five sessions and was followed by a secondintervention phase. In the second intervention phase, thestudents wrote using word prediction.

It was anticipated that some students would continueusing word prediction software after the conclusion of thisstudy. It was decided that a two-session probe would be takenwith and without word prediction one year after thecompletion of the study for students who continued to useword prediction software. This probe would be an indicationof the consistency of results over time. In addition, a five-minute probe would be taken at this time to compare thedifferences between two minute and five minute typing ratefor students whose physical impairment may affect writingfor longer periods of time.

Reliability & Social ValidityInter-observer reliability (IOR) was calculated in 20% of

the sessions, occurring once per phase, and the classroomparaprofessional served as the second observer. Both observerscalculated rate of typing in words per minute andpercentage of spelling errors. IOR was 100%.Treatment integrity was provided throughfollowing a checklist of daily events.

Social validity was also assessed through apre-treatment and post-treatment questionnairewith the students. The questionnaire consistedof eight questions that asked questions assessingtheir perception of Co:Writer (i.e., it will help metype faster; I’ll like using it; I’ll use it in otherclasses; I’ll use it outside of high school). It askedtwo value questions regarding importance oftyping faster and spelling words correctly. Itasked if they would recommend it to otherpeople. The posttest asked the same questionsbased on their experience having used Co:Writerduring the study. The students responded toquestionnaire items using a 3-point Likert Scale(with 3 being agree and 1 being disagree).

RESULTSWords Per Minute

One of the purposes of this study was to determinewhether word prediction software would increase typing rateof students with physical disabilities. The number of wordstyped per minute with and without word prediction softwarewas calculated for each student and is displayed in Figure 1and 2. The use of word prediction software on typing ratevaried across the four students.

Van. Van’s results, indicated in Figure 1, showed abaseline mean of words typed per minute of 2.9, with a rangeof 2.4 – 3.4. With the introduction of word prediction softwarein intervention 1, mean words per minute typed rose to 3.4,with a range of 2.1 – 4.4. In Baseline 2, Van’s mean droppedback to 2.5 words per minute with a range of 2.3 – 2.6. Withthe reintroduction of Intervention 2, mean words per minuterose to 3.8 with a range of 3.0 – 5.4. Percent of overlap wascalculated and indicated a 40% overlap between Baseline 1and Intervention 1; 100% between Intervention 1 andbBaseline 2; and 0% between Baseline 2 and Intervention 2,indicating great variability and similarity between somephases. Because percent of overlap was so great between thephases, a weak relationship existed between treatment andoutcome (Tawney & Gast, 1984).

Sam. Figure 1 results indicate that word predictionprovided an increase in typing rate for Sam. Baseline 1indicated a mean of 4.7 with a range of 3.9 – 5.5. Intervention1 results display a mean of 6.8 with a range of 5.3 – 7.8.Returning to Baseline 2, Sam’s mean words per minute was5.2 with a variable range of 3.9 – 7.6. With the reintroductionof word prediction software in Intervention 2, his meanincreased to 6.4 with a range of 3.6 – 9.0 words per minute.

Figure 1. Number of words typed per minute for Van and Sam across baseline (usingMicrosoft Word only) and intervention (using Co:Writer word prediction software).

Word Prediction10


across all phases, indicating a clear impact oftreatment on behavior (Tawney & Gast, 1984).These results indicated that Frank’s overalltyping rate was faster without word predictionsoftware. A functional relationship existed, inthat there was clear difference in levels betweenbaseline and treatment phases.

Probe DataOne year after the study, Sam and Nick

continued using word prediction software atschool. As seen in Table 2, probe data on twominute sessions for Sam and Nick indicatedhigher word per minute rate with wordprediction than without. During the two-minutesessions, Sam’s mean rate without wordprediction was 7.88 words per minute (range7.50- 8.25), and with word prediction, he had amean rate of 9.38 words per minute (range 9.13- 9.63). Nick’s mean rate without wordprediction was 12.06 words per minute (range11.75 - 12.38) and with word prediction, he had

a mean rate of 14.56 words per minute (range 13.50 - 15.63).Probe data taken on five-minute sessions indicated a lowerword per minute rate than with two minute probes.

Spelling Table 3 displays the percent of spelling errors for each

participant. During Baseline 1, Van made an average of 8%spelling errors. When word prediction software wasintroduced, his spelling errors decreased to 0%. With thereintroduction of baseline, spelling errors rose to 5%.Intervention 2 yielded 0% errors. Sam’s results were similar.During Baseline 1, Sam made 6.2% spelling errors. With theintroduction of word prediction, his spelling errors decreased

Sam showed an increase in words typed per minute whenusing word prediction software in both intervention phases.Percent of overlap was calculated and indicated a 20% overlapbetween Baseline 1 and Intervention 1; 40% betweenIntervention 1 and Baseline 2; and 40% between Baseline 2and Intervention 2, indicating a weak relationship betweenintervention and outcome (Tawney & Gast, 1984).

Nick. Nick’s words per minute results are shown in Figure2. In baseline 1, Nick averaged 10.9 words per minute, with arange of 13.8 – 15.4. When word prediction software wasintroduced in Intervention 1, his mean increased to 13.5 witha highly variable range of 11.9 – 17.9. When returning tobaseline, mean words per minute performance increased to12.8with a range of 11.8 – 14.3. Intervention 2 indicated a decreasein words per minute, with a mean of 11.2 and a range of 10.0– 14.3. Percent of overlap was calculated and showed a 40%overlap between Baseline 1 and Intervention 1; 80% betweenIntervention 1 and Baseline 2; and 20% between Baseline 2 andIntervention 2. A functional relationship does not exist,indicating that a clear effect for improvement in typing rateusing word prediction software was not present for Nick.

Frank. The results for Frank are shown in Figure 2. InBaseline 1, Frank’s mean words per minute was 14.6 with arange of 13.8 – 15.4. When word prediction software wasintroduced, his mean words per minute dropped to 9.8 with arange of 7.9 – 12.3. Going back to baseline, his mean wordsper minute increased to 14.0 with a range of 12.9 – 14.6.When word prediction software was reintroduced, the meanwords per minute fell to 10.4 with a range of 7.3 – 12.9.Percent of overlap was calculated and indicated a 0% overlap

Table 2.Mean and range data for Sam and Nick during study and probe sessions

Sam (mean, range) Nick (mean, range)

Baseline 1 4.73 (3.88 – 5.50) 10.88 (8.75 – 12.13)Intervention 1 6.80 (5.25 – 7.75) 13.36 (11.88 – 17.88)Baseline 2 5.23 (3.88 – 7.63) 12.78 (11.75 – 14.25)Intervention 2 6.43 (3.63 – 9.00) 11.15 (10.00 – 14.25)Probe without word prediction 7.88 (7.50 – 8.25) 12.06 (11.75 – 12.38)Probe with word prediction 9.38 (9.13 – 9.63) 14.56 (13.50 – 15.63)Probe without word prediction 5 min. 6.25 (6.10 – 6.40) 7.35 (6.95 – 7.75)

Probe with word prediction 5 min. 10.68 (10.00 – 11.35) 10.58 (9.55 – 11.60)

Figure 2. Number of words typed per minute for Nick and Frank across baseline (usingMicrosoft Word only) and intervention (using Co:Writer word prediction software).

Tumlin and Heller 11


to 0%. Returning to baseline, Sam made 10.9% errors. Withthe reintroduction of intervention, spelling errors fell to 3.3%.

Nick began Baseline 1 with 13.1% spelling errors. Withintroduction of word prediction, his spelling errors fell to1.8%. During Baseline 2 however, Nick made 0 spellingerrors. In Intervention 2, Nick made 1.1% spelling errors.Frank began Baseline 1 with 4.4% errors. During Intervention1, spelling errors fell to 0%. During Baseline 2, spelling errorswere .76% and during Intervention 2 1.1% errors.

In the case of Sam and Van, mean percentage of spellingerrors was lower in both intervention phases than in bothbaseline phases. In the case of Frank and Nick, meanpercentage of spelling errors was lower in Intervention 1 thanin Baseline 1 but was slightly higher in Intervention 2 thanBaseline 2.

Treatment Integrity & IORNo changes were made to the original plan for the study.

Each student was assigned a computer, and default settingswere configured and maintained individually for each studentthroughout the study. A treatment integrity checklist wasprepared and followed 100% of the time by the classroomteacher and paraprofessional throughout the study.

Inter-observer reliability (IOR) data were taken in 20% ofthe sessions. A classroom paraprofessional was trained toserve as the second observer and calculated words per minuteand percent of typed spelling errors one time per phase acrossall students from permanent products. IOR was 100% acrossall phases and all students.

Social ValidityPrior to the study and immediately following the study,

students were given social validity surveys. The surveys,displayed in Table 4, consisted of nine questions and used athree-point Likert Scale (with 3 being agree and 1 beingdisagree). Three out of four students indicated that they feltthat Co:Writer helped them type faster, and two out of fourindicated that they felt that Co:Writer helped them spellbetter. Three out of the four reported that they liked usingCo:Writer and expected that they would prior to using it.None of the students expected to use it outside of the OIclassroom and only one student planned on using it outside

of school. The two students with the most severe physicaldisabilities (Van and Sam) responded that they felt less tiredafter using word prediction software.

DISCUSSIONThe purpose of this study was to determine if the use of

word prediction software would increase the typing rate anddecrease spelling errors of students with physical disabilitiesaffecting hand use. Because some physical disabilities canseverely limit typing speed and accuracy of pressing thecorrect letters, it is necessary to find ways to increaseefficiency of output for these individuals. In this study, theresults indicated that word prediction software had a smallpositive effect on overall typing rate and decreased spellingerrors for two out of four students. For one student, the wordprediction software program was found to negatively impacttyping rate.

The two students (Van and Sam) who showed animprovement in words per minute when using wordprediction software had the most severe physical disabilitiesof the four students. They also had the slowest typing speeds.Based on Van’s mean words-per-minute baseline of 2.9, it wascalculated that he made an average of 11.6 keypresses (orkeystrokes) per minute and an average of 5.2 seconds to makeone keypress. Calculated the same way, Sam was similarlyslow by taking an average of 3.2 seconds to make onekeypress. This is much slower than the values found inDoester and Levine’s (1997) study in which it tookapproximately one second or less to make one keypress.These students' severe physical disabilities were accompaniedwith more abnormal motor patterns that resulted in slowerkeypress times. In these two instances with students withsevere physical disabilities, word prediction appeared to haveincreased typing speed while decreasing the number ofkeystrokes required to type words. This aligns with theoriginal intent of the development of this type of technologyfor individuals with physical disabilities.

In this study, two other students did not show animproved typing speed while using word prediction. Nickshowed no consistent change in words per minute using wordprediction software while Frank’s word-per-minute ratedecreased with word prediction software. Nick and Frank hadless severe physical disabilities than the other two students inthe study. Based on baseline typing rate, Nick took an averageof 1.38 seconds to make one keystroke. Frank was the fastesttypist in the study, taking 1.03 seconds to make onekeystroke. With these students having the physical capabilityto access the keyboard faster, it is possible that it took aboutthe same time or longer to scan the word prediction selectionsas type the whole word. This aligns with studies withstudents with learning disabilities indicating that more fluenttypists may have a decrease in typing speed when using word

Table 3.Percent of Spelling Errors

Student Baseline 1 Intervention 1 Baseline 2 Intervention 2

Van 8.0 0 5.0 0Sam 6.2 0 10.9 3.3Nick 13.1 1.8 0.8 1.1Frank 4.4 0 0.8 1.1

12 Word Prediction


readjust arm position due to abnormal motor patterns. Thisindicated that typing for longer periods of time may result indecreases in typing speed due to motoric and fatigue factors.However, despite the different session lengths, both Sam andNick had similar results during the five-second probe sessionsas with the two minute sessions in the reversal design. Samhad higher words per minute with word prediction and Nickshowed no clear difference. Although Van, who had the mostsevere physical disability, could not be part of the one-yearfollow-up due to graduating, his teacher reported that he wasphysically incapable of typing for five minutes due to severemotor planning and fatigue issues. This indicates theimportance of considering the impact of these additionalfactors on typing performance.

When examining the typing speed of these students, animportant issue is raised regarding the effect of wordprediction in functional classroom situations with studentswith severe motor planning issues and fatigue. Improvementin typing speed with word processing may be very minimal ifincreasing fatigue occurs when typing over the course of atypical classroom period or assignment. However, anyincrease in typing speed (and spelling accuracy) can be viewedas beneficial when students type so slowly. Further studies areneeded to examine the effect of fatigue and motor planningissues on word prediction use during a typical fifteen totwenty minute writing period in the classroom.

In the area of spelling, results indicated that the use ofword prediction did produce lower rates of spelling errors inthe case of Van and Sam. The improvement in spelling

prediction software (Golden, 2001; Lewis et. al., 1998).Since there was a range of typing speeds among the four

students with physical disabilities, questions arise if theirtyping speeds would improve with additional practice assuggested for students with learning disabilities (Lewis et al.,1998). For the two students who continued to use wordprediction one year following the study, it is noted that Sam’styping speed was faster with and without word predictionthan in the original study and Nick’s typing speed was higherwith word prediction than the original study. These data showsome increases in typing speed with one year’s practice usingword prediction, but the small amount of improvement tendsto support that there are additional factors to consider withstudents with physical disabilities.

Fatigue, attention, keypress rate, and motor planningissues are additional factors that affect the performance ofindividuals with physical disabilities that must be carefullyconsidered. Having to concentrate on motor planning canaffect the student’s ability to type. When all energy needed tocomplete a task is concentrated on the physical act ofperforming the task, the overall result can become inefficientand the student can become fatigued. This was observedwhen typing sessions were increased to five minutes duringthe follow-up probe sessions. During the five-minute probesessions, the word-per-minute rate was lower for both Samand Nick than during the two-minute probe sessions. Duringobservation, it was noted that Sam and Nick had considerablymore pauses during the five-minute sessions. The teacher feltthat this was primarily from fatigue issues and having to

Table 4.Social Validity

Van Sam Nick Frank Overall Mean1. I think Co:Writer will help/helped me type faster. Pre 3 3 3 2 2.75

Post 3 3 3 2 2.752. It is important for me to type faster. Pre 1 3 2 2 2.0

Post 2 2 2 2 2.03. I think Co:Writer will help/helped me spell words more accurately. Pre 2 3 3 2 2.5

Post 2 3 3 2 2.54. It is important for my work to be spelled correctly. Pre 3 3 3 2 2.75

Post 2 3 3 2 2.55. I would recommend Co:Writer to other people. Pre 1 2 3 2 2.0

Post 1 3 2 2 2.06. I think I’ll like/liked using Co:Writer. Pre 2 3 3 3 2.75

Post 2 3 3 3 2.757. I will use Co:Writer in other classes. Pre 1 2 2 2 1.75

Post 1 2 2 1 2.08. I will use Co:Writer outside of school. Pre 1 3 2 1 1.75

Post 2 3 2 1 2.09. I felt less tired after using Co:Writer. Post only 3 3 1 1 2.0

13Tumlin and Heller


The data from this study indicated that there can bepotential benefits of word prediction software for someindividuals with physical disabilities that affect hand use. Twoout of four students are continuing into their second year ofusing word prediction for their primary means of independentwork output. If word prediction software improves motivationto type, decreases spelling errors, increases typing rate, orreduces fatigue, it can be a valuable tool for individuals withphysical disabilities.

REFERENCESBaer, D. M., Wolf, M. W., & Risley, T. R. (1968). Some current

dimensions of applied behavior analysis. Journal of AppliedBehavior Analysis, 1, 91-97.

Golden, S. (2001). Word prediction and students with LD andsevere spelling difficulties. Unpublished Ed.S. thesis,Georgia State University, Atlanta.

Koester, H. H., & Levine, S. P. (1998). Model simulations of userperformance with word prediction. AAC Augmentative andAlternative Communication, 14, 25-35.

Koester, H. H., & Levine, S. P. (1997). Keystroke-level models foruser performance with word prediction. AAC Augmentativeand Alternative Communication, 13, 239-257.

Lewis, R. B., Graves, A. W., Ashton, T. M., & Kieley, C. L. (1998).Word processing tools for students with learning disabilities:A comparison of strategies to increase text entry speed.Learning Disabilities Research & Practice, 13, 95-108.

Logwood, M., & Hadley, F. (1996). Assistive technology in theclassroom. The Technology Teacher, October, 16-19.

Lueck, A. H., Dote-Kwan, J., Senge, J. C., & Clarke, L. (2001).Selecting Assistive Technology for Greater Independence.Re:View, 33, 21-34.

MacArthur, C. A. (1996). Using technology to enhance thewriting processes of students with learning disabilities.Journal of Learning Disabilities, 29, 344 - 348.

MacArthur, C. A. (1998a). From illegible to understandable: Howword recognition and speech synthesis can help. TeachingExceptional Children, July/Aug, 66-71.

MacArthur, C. A. (1998b). Word processing with speechsynthesis and word prediction: Effects of the dialogue journalwriting of students with learning disabilities. LearningDisability Quarterly, 21, 151-166.

MacArthur, C. A. (1999a). Overcoming barriers to writing:Computer support for basic writing skills. Reading & WritingQuarterly, 15, 169-192.

MacArthur, C. A. (1999b). Word prediction for students withsevere spelling problems. Learning Disability Quarterly, 22,158-172.

MacArthur, C. A. (2000). New tools for writing: Assistivetechnology for students with writing difficulties. Topics inLanguage Disorders, 20(4), 85-100.

Merbler, J. B., Hadadian, A., & Ulman, J. (1999). Using assistivetechnology in the inclusive classroom. Preventing SchoolFailure, 34, 113-118.

occurred with the two students with the most severedisabilities. Van made zero spelling errors during bothintervention phases, demonstrating that the use of wordprediction software worked effectively to eliminate spellingerrors. Although Van made no spelling errors using wordprediction, in session 18, he did select the wrong word on theword prediction list (parts instead of part). Having studentscarefully examine the list of words is important to teach. InIntervention 2, Sam misspelled one word. He was trying totype the word metal but began typing "ma" instead. In thiscase, he was not able to locate the correct word in the wordprediction list and therefore typed the whole word incorrectly(as "matal"). At the time of the study, Co:Writer 4000, whichhas flexible spelling, was not available. It is anticipated thatthe use of word prediction programs with more flexiblespelling rules may be of even greater benefit to poor spellersand may help to reduce spelling errors even further.

There are several limitations of the study that need to beconsidered. First, as with most single subject designs, thisstudy used a small number of individuals. Further replicationsof this study needs to be conducted to determine the effects ofword prediction across a greater number of students withphysical disabilities that affect hand use. Having multiplereplications of this study utilizing a single subject design orutilizing a group research design will verify the results of thedata over and beyond the small number of students in thisstudy.

Another limitation of this study is that the variation instudent’s motor ability may have been responsible for themixed results. Although the results of this study raiseimportant issues regarding the severity of motor movementand fatigue on word prediction use, more studies are neededacross various types and severities of physical disabilities.Closer examination of the effects of word prediction softwarewith students with more limited motor movement who usealternate access modalities would also be beneficial. Since thenumber of keypresses may be linked to fatigue, and wordprediction software can reduce the number of keypresses,further studies are needed that assess keypresses and physicalefficiency. Utilizing a fatigue measure as part of a future studywould help determine the effects of fatigue on students’writing.

Although this study did a one-year follow-up probe,further studies are needed examining the use of wordprediction over time. Differences in typing speed may occurover multiple years. Also this study examined high school agestudents. Examining the effects of younger students who arebeginning to learn to type and use word prediction mayproduce divergent results. Also, as technology continues toimprove, studies are needed to examine the use of wordprediction with newer features such as flexible spelling, aswell as a variety of word prediction programs.

14 Word Prediction


Sandberg, A. D. (1998). Reading and spelling among nonvocalchildren with cerebral palsy: Influence of home and schoolliterary environment. Reading and Writing: AnInterdisciplinary Journal, 10, 23-50.

Sandberg, A. D. (2001). Reading and spelling, phonologicalawareness, and working memory in children with severespeech impairments: A longitudinal study. AACAugmentative and Alternative Communication, 17, 11-26.

Tawney, J. W., & Gast, D. L. (1984). Single subject research inspecial education. New York: Merrill.

Jennifer Tumlin is a doctoral student in Special Education inthe Department of Educational Psychology and SpecialEducation at Georgia State University. Kathryn Wolff Heller isProfessor of Special Education in the Department ofEducational Psychology and Special Education at GeorgiaState University. Send correspondence to: Kathryn WolffHeller, Ph.D., Educational Psychology and Special Education,MSC 6A0820, Georgia State University, 33 Gilmer Street SEUnit 6, Atlanta, GA, 30303-3086. Email to: [email protected].

15Journal of Special Education Technology. 19(3), Summer 2004


The ability to explore unknown spaces independently,safely and efficiently is a combined product of motor, sensory,and cognitive skills. Normal exercise of this ability directlyaffects an individual’s quality of life. Mental mapping ofspaces and of the possible paths for navigating these spaces isessential for the development of efficient orientation andmobility (O&M) skills. Most of the information required forthis mental mapping is gathered through the visual channel(Lynch, 1960). People who are blind lack this information,and in consequence they are required to use compensatorysensorial channels and alternative exploration methods(Jacobson, 1993). This research is based on the assumptionthat the supply of appropriate spatial information throughcompensatory sensorial channels, as an alternative to the(impaired) visual channel, may help to enhance the ability ofpeople who are blind to explore unknown environments(Mioduser, in press).

The research on the exploration process of known andunknown spaces by people who are blind refers to the use ofboth low and high technologies. These technologies serve asalternative sensorial or cognitive channels to the impairedvisual channel. There are two types of information-technology devices: (a) passive devices - providing the userwith information before her/his arrival to the environment

(e.g., verbal description, tactile maps and physical models)and (b) dynamic devices - providing the user with informationin-situ (e.g., Sonicguide, Kaspa, Talking Signs and PersonalGuidance System). Ungar, Blades and Spencer, (1996) reporton differences in exploration performance of people who areblind using various technologies (e.g., verbal description,tactile maps and physical models). Warren and Strelow (1985)studied the use of the Sonic-guide device and Easton andBentzen (1999) focused on the users’ ability to navigate usingthe Kaspa laser-guided device. Additional examples of O&Msupport under study are the talking signs embedded in theenvironment (Crandall, Bentzen, Myers, & Mitchell, 1995),and the global positioning system (GPS), based on satellitecommunication (Golledge, Klatzky, & Loomis, 1996).

Research on mobility in known and unknown spaces bypeople who are blind (Golledge, Klatzky, & Loomis, 1996;Ungar, Blades, & Spencer, 1996), indicates that support forthe acquisition of spatial mapping and orientation skillsshould be supplied at two main levels, perceptual andconceptual. At the perceptual level, hearing, smell, and touchare powerful information suppliers about known as well asunknown spaces. The auditory channel supplies essentialinformation about events, or the presence of other people (ormachines or animals) in the environment. In indoor spaces

Exploration of Unknown Spaces by People Who Are BlindUsing a Multi-sensory Virtual Environment

ORLY LAHAV

DAVID MIODUSER

Tel Aviv University, School of Education

Exploration of unknown spaces is essential for the development of efficient orientation andmobility skills. Most of the information required for the exploration is gathered through thevisual channel. People who are blind lack this crucial information, facing in consequencedifficulties in mapping as well as navigating spaces. This study is based on the assumptionthat the supply of appropriate spatial information through compensatory sensorial channelsmay contribute to the spatial performance of people who are blind. The main goals of thisstudy were (a) the development of a haptic virtual environment enabling people who are blindto explore unknown spaces and (b) the study of the exploration process of these spaces bypeople who are blind. Participants were 31 people who are blind: 21 in the experimental groupexploring a new space using a multi-sensory virtual environment, and 10 in the control groupdirectly exploring the real new space. The results of the study showed that the participants inthe experimental group mastered the navigation of the unknown virtual space in a short time.Significant differences were found concerning the use of exploration strategies, methods, andprocesses by participants working with the multi-sensory virtual environment, in comparisonwith those working in the real space.

16 Multi-sensory Virtual Environment


people who are blind can use echo feedback (i.e., by whistling,clapping hands, or talking) to estimate distances (Hill, Rieser,Hill, Hill, Halpin & Halpin, 1993). The smell channelsupplies additional information about particular situations(e.g., perfumery, bookstore, or bakery in a shopping center) orabout people. Haptic information appears to be of greatpotential for supporting appropriate spatial performance.Fritz, Way, and Barner (1996) define haptics as encompassingtouch along with kinesthetic information, or a sense ofposition, motion, or force. For people who are blind, hapticinformation is commonly supplied by the cane for low-resolution scanning of the immediate surroundings, by palmsand fingers for fine recognition of objects form, texture andlocation, and by the feet regarding surface information.

As for the conceptual level, the focus is on supporting thedevelopment of appropriate strategies for the efficientexploration of the space and the generation of efficientnavigation paths. For example, Jacobson (1993), describedindoor environment familiarization process by people who areblind as one that starts with the use of a perimeter-recognition-tactic -walking along the room's walls andexploring objects attached to the walls, followed by a grid-scanning tactic, aiming to explore the room's interior.

Advanced computer technology offers new possibilitiesfor supporting acquisition of orientation and mobility (O&M)skills by people who are blind, and the development ofalternative navigation strategies, at both the perceptual andconceptual levels. Current virtual reality (VR) technologyfacilitates the development of rich virtual models of physicalenvironments and objects to be manipulated, offering peoplewho are blind the possibility to undergo learning orrehabilitation processes without the usual constraints of time,space, and a massive demand of human tutoring (Loomis,Klatzky & Golledge, 2001; Schultheis & Rizzo, 2001;Standen, Brown & Cromby, 2001). Research on theimplementation of haptic technologies within VR spatialsimulation environments reports on its potential forsupporting rehabilitation training with sighted people(Darken & Banker, 1998; Darken & Peterson, 2002; Waller,Hunt & Knapp, 1998; Witmer, Bailey, Knerr & Parsons 1996),and perception of virtual textures and objects by people whoare blind (Colwell, Petrie, & Kornbrot, 1998; Jansson, Fanger,Konig, & Billberger, 1998;).

The research reported in this paper follows theassumption that the supply (via technology) of compensatoryperceptual and conceptual information may contribute toeffective acquaintance with unknown environments bypeople who are blind. This approach differs from previousresearch lines and practices in several ways. First, it integratesexisting knowledge from different disciplines (namely O&M,learning processes by people who are blind, virtualenvironments and haptic devices R&D) into a common

conceptual framework for the study of O&M skillsacquisition using technology. At an additional level it dealswith two main drawbacks of technologies currently in use: (a)the need for prerequisite knowledge about the space to benavigated (e.g., the talking signs or GPS systems) and (b) thelack of appropriate resolution of the information suppliedabout the unknown space (e.g., verbal descriptions or tactilemaps). The virtual tool used in this study supplies all requiredprerequisite knowledge, at a resolution compatible with thefeatures of the simulated environment. To examine the aboveassumption we developed a multi-sensory virtualenvironment (MVE) and studied the exploration process of anunknown space by subjects who are blind using the MVE.Their performance was compared to that of a control group ofpeople who are blind who explored the real environmentsimulated in the MVE. The main research questions of thisstudy were:

1. What exploration strategies do people who are blinduse working with the MVE, in comparison to thoseused by people whom are blind working directly in thereal environment?

2. What characterizes the exploration processes used bypeople whom are blind working with the MVE, incomparison to the exploration processes used bypeople whom are blind working in the realenvironment?

3. What information collection and storage didparticipants use, in both the experimental and controlgroups?

THE HAPTIC VIRTUAL ENVIRONMENTThe MVE prototype developed for this study comprised

two modes of operation: (a) developer/teacher mode and (b)learning mode. The core component of the developer/teachermode was the virtual environment editor, which includedthree tools: (a) a 3D environment builder, (b) a force-feedbackeffects editor, and (c) an audio feedback editor (see Figure 1).By using the 3D-environment editor the developer can definethe physical characteristics of the space, e.g., size and shapeof the room, or type and size of the objects (i.e., doors,windows and furniture). Using the force feedback effects (FFE)editor the developer was able to attach haptic effects to allobjects in the environment. Examples of FFE’s werevibrations or attraction/rejection fields surrounding objects.The audio editor allowed the attachment of three kinds ofauditory feedback to the objects: (a) labels (e.g., bird chirps) asrepresentative for the windows, (b) explicit names (e.g., firstdoor or second cube), and (c) a guiding agent reporting onfeatures of the objects (e.g., the proximity of corners orrequired turns). All environments used in this study werecomposed by the researchers using the system editing tools.

Lahav and Mioduser 17


In the learning mode, the users navigated theenvironment by means of the force feedback joystick (FFJ).While walking via the FFJ they interacted with the simulatedspace components (i.e., they perceived the form, dimensions,and relative location of objects; or identified the structuralconfiguration of the room including presence and location ofwalls, doors, and windows. As part of these interactions theusers got haptic feedback through the FFJ along with audiofeedback. Figure 2 shows the user-interface screen. The redcircles indicate the hot spots that triggered the guiding agent’sintervention.

Several additional features were offered to the teachersduring and after the learning session. Monitoring frames, forexample, presented updated information on the user’s

navigation performance (e.g., position or objects alreadyreached). Another feature allowed the recording of the user’snavigation path and its replay for analysis and evaluationpurposes, as shown in Figure 3.

METHODParticipants

The study included 31 participants who were selected onthe basis of the following seven criteria: (a) total blindness, (b)minimum of 12 years old, (c) not multi-handicapped, (d)received O&M training, (e) Hebrew speaker, (f) onset ofblindness at least two years prior to the experimental period,and (g) comfortable with the use of computers. Theparticipant age range was 12-70 years old. We defined twogroups that were similar in gender, age and age of vision loss(i.e., congenitally blind or late blind. The experimental groupincluded 21 participants who explored the unknown space bymeans of the MVE, and the control group had 10 participantswho explored the real unknown space (see Table 1).

To evaluate the participants’ initial O&M skills, allcompleted a questionnaire on O&M issues. The

Figure 1. Multisensory environment editor

Figure 2. The user interface

Figure 3. Recorded log and monitoring data

Table 1.The study’s participants

Gender Age Age of vision loss

Group Female Male Adult Teenage Congenitally Lateblind blind

Experimental group (n=21) 11 10 15 6 11 10

Control group (n=10) 6 4 8 2 6 4

Multi-sensory Virtual Environment18


questionnaire results showed no differences in initial abilityamong both groups’ participants.

VariablesThe independent variable in this study was the type of

environment (i.e., the multi-sensory virtual environment(MVE) and the real environment.

Three groups of dependent variables were defined,concerning (a) exploration strategies, (b) characteristics of theexploration process, and (c) the use of information and storageaids during the exploration.

Variables related to the exploration strategies included:1. Exploration strategies – alternative strategies used by

the subjects in their navigation: the “perimeter” strategy –walking along a room’s walls (see Figure 4, Route 1); the “grid”strategy – exploring a room’s interior by scanning the room(see Figure 4, Route 2); the “object-to-object” strategy –walking from one object to another (see Figure 4, Route 3); the“points-of-references” strategy – walking in the environmentand creating landmarks (see Figure 4, Route 4), or other (new)strategies.

2. Frequency – the number of times each strategy wasimplemented during the exploration.

3. Distance traversed – distance traversed using eachstrategy.

Variables related to the characteristics of the explorationprocess:

1. Total duration – the total time spent accomplishing thetask.

2. Total distance – the total distance traversed.3. Strategy-switch – the frequency of strategy changes

during the exploration task.4. Sequence – the first sequence of two strategies used in

the exploration (e.g., pattern strategy first then grid strategy).

5. Stops – the number of pauses made during theexploration. Two values were defined: short pauses (4-10seconds) introduced for technical purposes (e.g., changing thehand that holds the joystick) and long pauses (more then 10seconds) supposedly used for cognitive processing (e.g.,memorization or planning).

Variables related to the use of information and storageaids included:

1. Aids – use of aids of two types: measurement aids (e.g.,counting steps or using echo feedback) and information-retaining-aids (e.g., producing a verbal reconstruction oflandmarks or using metaphors).

Research instrumentsThe main instruments used in the study were:1. The unknown space – the space to be explored, both as

real physical space and as virtual representation in the MVE(see Figures 5-6). The space was a 54 square meters roomwith three doors, six windows and two columns. There wereseven objects in the room, five of them attached to the wallsand two placed in the inner space.

2. Exploration task – each participant was askedindividually to explore the room, without time limitations.The experimenters informed the participants that they wouldbe asked to describe the room and its components at the endof their exploration.

In addition a set of three instruments was developed forthe collection of quantitative and qualitative data:

1. Orientation and mobility (O&M) questionnaire –comprising 46 questions concerning the participants O&Mability indoors and outdoors, in known and unknownenvironments. Most of the questions were taken from O&Mrehabilitation evaluation instruments (e.g., Dodson-Burk &Hill, 1989; Sonn, Tornquist & Svensson, 1999). The O&M

Figure 4. Exploration strategies

Figure 5. The Virtual Environment

19Lahav and Mioduser


questionnaire included four parts: (a) 19 descriptive questions(e.g., age; gender; age of vision loss); (b) 8 questions on thesubject’s O&M ability in known indoor environments (e.g.,home; school; work; etc); (c) 12 questions about the subject’sO&M ability in known outdoor environments (e.g., streetcrossing; using public transportation; walking in shoppingcenters; etc); (d) 7 questions on subject’s O&M ability inunknown indoor environments (e.g., what are the O&Mdevices you use in unknown indoor environments?; nextweek you are going to move to a new office or classroom. Youwill be visiting the new place today. What do you need to doto ensure yourself appropriate orientation in the new spacenext time?). Among the questions 23 O&M-related questionswere answered in a four-level ability scale: (i) I cannot do thetask, (ii) I need assistance from a sighted person, (iii) I need touse an O&M device, (iv) I can do the task independently.

2. Observations were video-recorded – the participant’sexploration was video-recorded during the task. Theinformation from these recordings was combined with thecomputer recording.

3. Computer recording – The computer's recording dataenabled the researchers to track the user’s exploration in theMVE, in two ways: through a data log and through a film.This enabled the researcher to collect information aboutusers’ exploration strategies, distances, total duration,switches of strategies and stops (see Figure 3).

Two data evaluation and coding schemas were developed,one for the participant’s O&M skills and the other for his orher acquaintance process with the new space.

ProcedureAll participants worked and were observed individually.

The study was carried out in three stages. The first stagefocused on the evaluation of the participants’ initial O&Mskills using the O&M questionnaire. In the second stage the

experimental group became acquainted with the virtualenvironment’s components and operation modes. The seriesof tasks administered at this stage included (a) freenavigation, (b) directed navigation, and (c) a task aimed tointroduce the auditory feedback. This stage lasted about threehours (two meetings). At the end of it participants learned towork independently with the FFJ, were able to walk directlytoward the objects, could say when they bumped into anobject or got to one of the room's corners, and could walkaround the objects and along the walls by using the FFJ andthe audio feedback. The third stage, the main part of thestudy, focused on participants’ exploration of the unknownspace. The experimental group explored the space using thevirtual environment, while the control group directly exploredthe real environment. This stage lasted about 1.5 - 2.5 hours,the task was video-recorded. For the experimental group thevideo-recording was combined with computer-recording. Thelast stage consisted of the processing and analysis of thecollected data.

The research results and conclusions are based andrepresent only the research participants’ performance andachievements (n=31). The population target on this researchwere Israeli people who are blind, selected using the sevencriteria above mentioned and that agree to take a part on thisstudy. The actual size of the study’s population did not allowa detailed examination of the effect of otherwise relevantvariables (e.g., gender or age).

RESULTSThe results regarding the exploration strategies,

methods, and processes manifested by the participantsworking with the MVE, in comparison with those working inthe real space, are presented according to our main researchquestions.

Research Question 1: What exploration strategies dopeople who are blind use working with the MVE, incomparison to those used by people whom are blindworking directly in the real environment?The participants in both groups implemented similar

exploration strategies, mostly based on the ones they used intheir daily navigation in real spaces. Examples of strategiesimplemented were: (a) perimeter (e.g., walking along theroom’s walls and exploring objects attached to the walls), (b)grid (e.g., exploring the room’s inner-space), (c) object-to-object (e.g., walking from one object to another), and (d)points-of-references (e.g., walking in the environment andcreating landmarks). However, an interesting additionalfinding surfaced in that several participants in theexperimental group developed a few new strategies whileworking within the virtual environment. A constant scanningstrategy was identified by which the user collectedinformation about the room’s interior while simultaneously

Figure 6. The Real Environment



collecting perimeter information (e.g., resemblingthe use of a long cane in real space - as shown inFigure 7). Those strategies could be generated onlywithin the MVE, representing an important addedvalue of the work with the computer system.

As already mentioned, no substantial differencebetween groups was observed as regards the types ofstrategies used, but significant difference was foundconcerning the frequency of use of the strategies,and distance traversed using each strategy. Data inTable 2 indicate that the strategy most frequentlyused by the experimental group was grid, followed bythe perimeter strategy. In contrast, the control grouppreferred to explore the room’s perimeter, and nextto use the object-to-object strategy. Examining the distancetraversed using each strategy, we found that both groupstraversed the longest distance using the perimeter strategy.

Research Question 2: What characterizes the explorationprocesses used by people who are blind working with theMVE, in comparison to the exploration processes used bypeople whom are blind working in the real environment?Five aspects are of interest as regards to the exploration

processes used in the two groups: (a) the duration of theexploration, (b) the distance traversed, (c) the number ofswitches among strategies, (d) the sequence of mainimplemented strategies, and (e) the number and kinds ofstops made while examining the new space.

Concerning the duration of the exploration, it should benoted that the participants were not limited in time foraccomplishing the task. Participants from the experimentalgroup needed four times more time to explore the newenvironment (average time of 38 minutes) than the ones fromthe control group (average time of 10 minutes). This differencewas significant (t (28)=7; p=.000). Significant difference wasfound also for the total length of the exploration path

(t (29)=5.44; p=.000). Participants in experimental grouptraversed an average of three times more distance (M=6.3 m)than the control group subjects (M=1.9 m).

The experimental group made frequent switches ofstrategy during their walk in the MVE, in contrast with thecontrol-group performance in the real space. This behavior isreflected in the total and average frequency of use of thevarious strategies by both groups (see Table 2), total frequencyof 292 and mean of 14 for the experimental group, and totalfrequency of 64 and mean of 6.4 for the control group.

Significant difference was also found between the groupsin the sequence of main strategies implemented (c2(2)=7.55;p<.05). Data in Table 3 indicate that most experimental-group participants (62%) used the grid strategy first and thenthe perimeter strategy. In contrast, most control-groupparticipants (90%) preferred first to explore the room’sperimeter and then the objects located in the inner space ofthe room.

Participants from both groups made many pauses duringtheir walk, suggesting that different cognitive operationsrelated to the task in process were activated during theseintervals. In terms of duration and function, we defined twotypes of pauses, short and long. Short pauses (i.e., 4-10seconds) were used for technical purposes (e.g., changing thehand that holds the force-feedback joystick) or for reflectionon a recent action. Long pauses (i.e., more than 10 seconds)were used for memorizing spatial information, reflection on a

Table 2.Exploration strategies, frequency and length

Experimental group (n=21) Control group (n=10)Exploration patterns Frequency Length of the Frequency Length of the

path (in meters) path (in meters)Perimeter 86 53.9 28 14.6Grid 116 26.3 9 .97Object to object 22 7.8 14 2.3Points of reference 50 26.6 13 1.8New strategies 18 18.2 – –Sum 292 132.8 64 19.67Mean 14 6.3 6.4 1.9

Figure 7. New exploration strategies

Table 3.Sequence of strategies

Group Perimeter then grid Grid then perimeter GridExperimental group (n=21) 8 8 5

38% 38% 24%Control group (n=10) 9 1

90% 10% –(x 2 (2)=7.55; p<.05)



recently implemented exploration strategy, or planning. Asshown in Table 4, significant difference was found betweenthe groups (t(26)=7.65; p<.001; t(25)=2.56; p<.05 ) for bothshort and long pauses. The experimental group made about 3times more short pauses, and 6 times more long pauses.

As the results indicate, significant differences were foundbetween the experimental group and the control groupconcerning the characteristics of the exploration process.These differences were related to four dependent variables: (a)the total duration of the exploration, (b) the total distancetraversed, (c) the sequence of main implemented strategies,and (d) the number of pauses made while exploring theunknown space. The experimental group participants, incomparison with the control group, used a more varied rangeof strategies to explore the room, walked a longer distance tocomplete the exploration, and made more pauses for technicalor reflective purposes.

Research Question 3: What information collection andstorage did participants use, in both the experimental andcontrol groups?The collection and storage of relevant information is

inherent to the process of exploring an unknown space.Although only a few participants in this study reportedexplicitly on the use of tactics and aids for performing thesefunctions, their account on this matter is of interest. Excerptsof these participants’ references to the use of such aids follow.

One important category of information-collection aidswas related to measurement to support the estimation ofdimensions and distances. One example is the case of T, a 25-year-old, late blind, woman who explored the room using theMVE. After 2 minutes in the system T began to walk andcount out aloud steps: “The blackboard… ok, the wall, one,two, three, four, five…”.

The use of echo was another useful measurement aid. Forexample, the control-group participants used echo formeasuring their distance from the wall or from other objects,or the room size. During their exploration those participantsspoke, sang or whistled to get echo information.

The participants in this study used various kinds ofinformation-retaining means. One was verbal reconstructionof landmarks, by which the subject recalled out loud her/hisexploration of the space. For example, G, a 25-year-old, late

blind man who explored the room by using the MVE, afterexamining the room’s perimeter for 13 minutes said: “I haddoor, a prism, a corner, when I walked I had a window at theleft side and then I reached the cube, I passed it and in frontof it I had a window, column, window, window, column,window…”. A variant of this was to complement the verbalreconstruction with virtual drawing (i.e., accompanying theverbal description with hand movements mimicking thephysical presence and distribution of spatial components). Forexample, G, a 12-year-old, congenitally blind girl workingwith the MVE, after 22 minutes of exploration discovered thesecond cube in the room and began to describe out loud:”second cube, this cube is in the corner of the lower wall, andthe wall is here…so the cube is in this corner...of the leftwall…[during this verbal reconstruction G moved with herhand on the table indicating where the surveyed objects werelocated] yes the left wall, yes this wall corner and that wallcorner ...there is a cube...”.

Another interesting aid for the reinforcement of acquiredinformation was the use of metaphors. For example, M, a 39-year-old, congenitally blind woman, after 32 minutes ofexploration said: ”…now I am a tourist guide, you arestanding in front of the room entrance, now you are going tofollow me, we are turning to the left, ok follow me... you havereached the prism, look at the prism, it is a beautiful object.We can not walk to the left, we are stuck in… we are walkingforward… and we are arriving at the wall…”.

Only some of the participants explicitly reported on theuse of any aid. Table 5 indicates that the participants from theexperimental group who reported on the use of aidsmentioned mainly retention reinforcement aids (54%). Incontrast, half of the control group mentioned such aids (50%),and even more mentioned the use of measuring aids (70%).

DISCUSSIONThe research reported here is part of an effort aimed to

understand if and how, the work with a MVE supports theexploration of unknown environments by people who areblind . Gathering comprehensive information about newspaces is a prerequisite for the construction of effectivecognitive maps of these spaces, and for supporting people’sability to navigate them. The results of this study helpeduncover several issues concerning the contribution of theMVE to the exploration strategies and learning process ofunknown spaces by people who are blind.

Exploration Strategies in the Virtual Environment. Walking in the MVE gave participants a comprehensive

and thorough acquaintance with the target space. The highdegree of compatibility between the components of the virtualsystem and of the real space on one hand and the exploringmethods supported by the MVE on the other, contributed to

Table 4.Short and long breaks

Group Long stops Short stopsExperimental group (n=21) 17 81Control group (n=10) 6 13

* ***p<.05; **p<.001



the users’ relaxed and safe walking. These features alsoenabled participants to implement exploration patterns theycommonly used in real spaces, but in a qualitatively differentmanner. The use of real walking strategies in virtualenvironments was reported in previous studies on spatialperformance by sighted participants (Darken & Peterson,2002; Witmer, Bailey, Knerr & Parsons 1996). But this study’sMVE participants applied the known strategies in novel ways.For example, they preferred to explore the inner part of theroom first and only then its boundaries, in contrast with theexploration patterns described by Jacobson, 1993. Moreover,the MVE participants created new exploration strategies, suchas the one simulating walking with a long cane enabling themto walk the perimeter of the room and at the same time toexplore its corresponding inner areas – a strategy only possiblewithin the MVE.

Exploration process in the Virtual Environment. Operation features of the MVE (e.g., the game-like

physical interface, various types of feedback) contributed toparticipants’ performance with the system while exploring theunknown space. As a result, the exploration process showedinteresting qualities concerning spatial, temporal, andthinking-related aspects. Examples of spatial and temporalqualities were the range of scanning strategies implemented,the inclusion of a large number of long and short breaks, orthe time spent in examining the space. In addition, the MVEusers traveled as much as three times more distance than thecontrol-group participants, allowing them to collectinformation about the environment at different resolutionlevels, and to re-evaluate the information already gathered. Allthese were indications of the richness and comprehensivenessof the exploration process as accomplished by the MVEparticipants. Although the time measures collected weresimilar to those reported in Darken and Banker (1998) andWaller et al. (1998), both studies of sighted participantsexploring spaces by means of VEs, it could be expected thatexploration time would become shorter as participants gotgradually used to working with these systems as tools forlearning unknown spaces.

Concerning thinking-related aspects of the process,interesting examples were the long breaks made by the

participants with the aim to reflect on the exploration steps orto memorize data concerning an explored area, or the use ofvirtual drawing of spatial features under examination on thetable’s surface as a reinforcement aid.

An important byproduct of the study is related to thedefinition of specifications and constraints for the appropriatedesign of haptic virtual learning environments for people whoare blind (e.g., force-feedback in high resolution, audiofeedback). We expect these virtual environments to becomepowerful tools for people who are blind in learning processesin which spatial information is crucial, both forunderstanding new concepts and phenomena, as well as foracting and performing in the real world.

Further ResearchFurther studies should examine the participants’

construction of spatial cognitive maps of spaces using theMVE and, consequently, their use of these maps fornavigating in the real environments. Additional variables tobe studied should relate to properties of the environment (e.g.,indoor or outdoor spaces, complex public spaces, and irregularsurfaces). Finally, a comparison with traditional methods usedby people who are blind to learn about unknownenvironments (e.g., tactile maps, verbal descriptions, humanguidance) may serve for comprehensive evaluation of thecontribution of the virtual tools to people’s spatialperformance.

Finally, at the implementation level the virtual tool couldplay a central role in training and rehabilitation processes aswell. One possible application is for supporting theacquisition of O&M skills and strategies by persons who arelate blind as part of their rehabilitation process. At anotherlevel, the development of more comprehensive environment-editing tools for the MVE will support the creation of a varietyof models of spaces (e.g., public buildings, shopping areas)enabling pre and post-visit exploration and recall of unknownspaces by people who are blind. These implementations mayalso serve the research and practitioners community asmodels for the further development of technology-based toolsfor supporting learning processes and performance of peoplewith special needs.

Table 5.Exploring aids

Information-retaining MeasurementGroup Verbal reconstruction of landmarks Verbal reconstruction with virtual drawing Use of metaphor Measuring units EchoExperimental group (n=21) 3 5 3 1 –

15% 24% 15% 5%Control group (n=10) 4 1 – 4 3

40% 10% 40% 30%



REFERENCESColwell, C., Petrie, H., & Kornbrot, D. (1998). Haptic virtual

reality for blind computer users. Paper presented at theAssets ‘98 Conference, Los Angeles, CA. Available in:http://phoenix.herts.ac.uk/sdru/pubs/VE/colwell.html.

Crandall, W., Bentzen, B.L., Myers, L., & Mitchell, P. (1995).Transit accessibility improvement through talking signsremote infrared signage, a demonstration and evaluation.San Francisco, CA: The Smith-Ketlewell Eye researchInstitute, Rehabilitation Engineering Research Center.

Darken , R.P., & Banker, W. P. (1998). Navigating in naturalenvironments: A virtual environment training transfer study.Paper presented at the IEEE Virtual Reality AnnualInternational Symposium. Atlanta, GA.

Darken , R.P., & Peterson, B. (2002). Spatial orientation,wayfinding and representation. In K. M. Stanney (Ed.),Handbook of virtual environments design, implementation,and applications (pp. 493-518). Hillsdale, NJ: Erlbaum.

Dodson-Burk, B., & Hill, E.W. (1989). Preschool orientation andmobility screening. A publication of division IX of theassociation for education and rehabilitation of the blind andvisually impaired. New York, NY: American Foundation forthe Blind.

Easton, R.D., & Bgentzen, B.L. (1999). The effect of extendedacoustic training on spatial updating in adults who arecongenitally blind. Journal of Visual Impairment andBlindness, 93(7), 405-415.

Fritz, J., Way, T., & Barner, K. (1996). Haptic representation ofscientific data for visually impaired or blind persons.Proceedings of the Eleventh Annual Technology and Personswith Disabilities Conference, California State University,Northridge, Los Angeles, CA.

Golledge, R., Klatzky , R., & Loomis, J. (1996). Cognitivemapping and wayfinding by adults without vision. In J.Portugali (Ed.), The construction of cognitive maps (pp. 215-246). The Netherlands: Kluwer.

Hill, E., Rieser, J., Hill, M., Hill, M., Halpin, J., & Halpin R.(1993). How persons with visual impairments explore novelspaces: Strategies of good and poor performers. Journal ofVisual Impairment and Blindness, 295-301.

Jacobson, W. H. (1993). The art and science of teachingorientation and mobility to persons with visual impairments.New York, NY: American Foundation for the Blind.

Jansson, G., Fanger, J., Konig, H., & Billberger, K. (1998). Visuallyimpaired persons’ use of the PHANToM for informationabout texture and 3D form of virtual objects. In J. K.Salisbury & M. A. Srinivasan (Ed.) Proceedings of the ThirdPHANToM Users Group Workshop, MIT, Cambridge, MA.

Loomis, J. M., Klatzky, R. L., & Golledge, R. G. (2001).Navigating without vision: Basic and applied research.Optometry and Vision Science, 78, 282-289.

Lynch, K. (1960). The image of the city. Cambridge, MA: MITPress.

Mioduser, D. (in press). From real virtuality in Lascaux to virtualreality today: cognitive processes with cognitivetechnologies. Educational Technology Review.

Schultheis, M. T., & Rizzo, A. A. (2001). The application ofvirtual reality technology for rehabilitation. RehabilitationPsychology, 46(3), 296-311.

Sonn, U., Tornquist, K., & Svensson, E. (1999). The ADLtaxonomy – from individual categorical data to ordinalcategorical data. Scandinavian Journal of occupationaltherapy, 6, 11-20.

Standen, P.J., Brown, D.J., & Cromby, J.J. (2001). The effectiveuse of virtual environments in the education andrehabilitation of students with intellectual disabilities.British Journal of Education Technology 32 (3) 289-299.

Ungar, S., Blades, M., & Spencer, S. (1996). The construction ofcognitive maps by children with visual impairments. In J. Portugali (Ed.), The construction of cognitive maps(pp.247-273), The Netherlands: Kluwer.

Waller, D., Hunt, E., & Knapp, D. (1998). The transfer of spatialknowledge in virtual environment training. Presence:Teloperators and Virtual Environments 7(2), 129-143.

Warren, D.H., & Strelow, E.R. (1985). Electronic spatial sensingfor the blind. Boston: Martinus Nijhoff.

Witmer , B.G., Bailey, J. H., Knerr, B. W., & Parsons, K.C. (1996).Virtual spaces and real world places: Transfer of routeknowledge. International Journal of Human-ComputerStudies, 45, 413-428.

Orly Lahav is a researcher at the School of Education, Tel-AvivUniversity and is currently a postdoctoral fellow at theMassachusetts Institute of Technology. David Mioduser isProfessor of Communication and Computers in Education atthe School of Education, Tel-Aviv University. This researchwas partially supported by grants from the Israeli Ministry ofEducation, Microsoft Research Ltd., and Israel FoundationTrustees. Send correspondence to Orly Lahav, KnowledgeTechnology Lab, School of Education, Tel-Aviv University,Ramat Aviv, Tel Aviv, 69978, Israel. Email to:[email protected].

24


25


Live, Interactive Paraprofessional Training Using Internet Technology: Description and Evaluation

ROBERT L. MORGAN

DAVID E. FORBUSH

JON NELSON

Utah State University

Recent federal mandates have increased training requirements of special education and Title Iparaprofessionals. State and local education agencies face challenges in meeting the mandates, suchas locating and selecting from available training options, deploying local experts to deliver training,and funding development and delivery efforts. One alternative is to deliver a live, Internet-basedcourse with real-time video and audio. In a 10-week course, an instructor interacted with groups of16 to 20 paraprofessional participants at three remote sites. Site coordinators managed instructionand assisted participants at each site. In this article, authors describe the curriculum, instructionalformat, and technology, then summarize course evaluation data, and finally, examine the capacityof the delivery system in relation to training mandates.

Two federal legislative mandates require statedepartments of education and local school districts to provideincreased training of paraprofessionals, that is, the re-authorization of the Individuals with Disabilities EducationAct of 1997 (IDEA) (U.S. Department of Education, 1998) andthe No Child Left Behind Act of 2001 (NCLB) (Public Law107-110). First, IDEA stated the need for training ofparaprofessionals serving children in special education.According to IDEA, appropriately trained and supervisedparaprofessionals may assist in providing special educationand related services. Second, the NCLB Act mandated trainingof paraprofessionals serving children in Title I programs andschools. The NCLB Act was directed towards local educationagencies receiving Title I funding, and mandated agenciesensure all paraprofessionals hired after January 2002demonstrate two years of postsecondary education, possess anassociate’s degree, or demonstrate evidence of being highlyqualified by passing a state-sponsored assessment.Paraprofessionals employed prior to enactment of thislegislation must meet this requirement by January 2006. TheNCLB Act applies to all paraprofessionals working in Title Iprograms and Title I schools. About 18% of the 1,000,000 plusparaprofessionals in the United States are employed in Title Ischools or programs (Roles for Educational Paraprofessionalsin Effective Schools, 1997). Therefore, the NCLB mandate hasprompted many school districts to increase their trainingpriority for paraprofessionals (ERIC/OSEP Special Project,2003). Collectively, the federal mandates call for a rapid shiftin paraprofessional training expectations.

Problems Faced by Districts in Delivering TrainingSome state and local education agencies face problems in

training paraprofessionals, including (a) lack of expertise todevelop or select training programs, (b) lack of personnel withexpertise and time to deliver training, and (c) limited fundingfor developing and delivering training. To some extent, theseproblems were present prior to legislative mandates. However,given legislative pressure, their priority is heightened. Theproblems are described below.

Development or selection of programs. In some state andlocal education agencies, staff development efforts haveplaced greater emphasis on improving skills of professionalpersonnel, especially teachers (ASPIIRE IDEA PartnershipGroup, 2001; French & Pickett, 1997). Now, in light oftraining mandates, agencies must shift a portion of theirtraining to paraprofessionals. If agencies create their ownprograms, they must arrange for local experts to assessparaprofessional training needs and find time to develop thecurriculum. If agencies select from existing paraprofessionaltraining programs, they must review alternatives, comparestrengths and weaknesses in relation to local needs, and makedecisions. Sometimes, these decisions consume time andrequire group consensus. For example, in Oklahoma, a statetask force compared paraprofessional training programs overa two-year period before making a decision (K. Riddle,personal communication, May 21, 2003).

Deployment of local experts to deliver training. Prior tothe NCLB Act, primary responsibility for paraprofessionaltraining rested on the shoulders of classroom teachers who,

Journal of Special Education Technology. 19(3), Summer 2004

26 Live Internet-based Training


for the most part, conducted on-the-job training (Salzberg &Morgan, 1995). However, given the NCLB mandate, formalpost-secondary education is necessary. Yet, many agencieshave few, if any, trainers available to work withparaprofessionals outside the classroom. In rural areas,trainers and paraprofessional trainees may be dispersed acrosswide geographic areas (Collins, 1997). These challengesrequire state and local education agencies to examine theirresources and find creative ways to deliver training.

Lack of funding. Cost efficiency has served as the primarystimulus for employing paraprofessionals, because they workfor relatively low wages while carrying out essential directservices. Agencies must now explore ways to compensateparaprofessionals for training or share costs with them.

In summary, state and local education agencies needaccess to experts, available locally or at a distance, who candeliver cost efficient training. Ideally, agencies should have theopportunity to select from a variety of training deliveryoptions because needs of local districts vary. Some districtsmay deliver local training while others may need distance-based delivery due to limited resources. This article describesand evaluates a new alternative: distance-based training usinglive video and audio courses transmitted via the Internet.This alternative may address each of the problems describedabove, that is, it may provide a distant expert who selects anddelivers training to paraprofessionals in a cost efficientmanner. Because the course is a live broadcast, the instructorcan teach in an interactive manner by presentinginformation, obtaining responses from paraprofessionalparticipants at a distance, adjusting instruction if necessary,and addressing questions.

The authors found no research literature on live,distance-based education involving special educationparaprofessionals. Therefore, this evaluation is a basic one inwhich participants and advisory board members responded totopics related to technology, course content, and coursedelivery. The article describes an initial attempt to evaluatethe alternative in regards to functionality of technology anddelivery of distance-based instruction. There is no attempt tocompare or contrast this alternative to other training formats.

Project OverviewA federally funded grant project was designed to develop

and evaluate a distance education model for training specialeducation paraprofessionals. The project proposed to delivertraining to groups of paraprofessionals at three sites using alive Internet-based, two-way audio/video system. Theproject’s technology, training program, instructionalprocedures, site selection and development activities, andevaluation methods are described below.

Technology

Two project technicians developed a live, Internet-baseddelivery system with a high degree of technological control atthe broadcast site and a low degree of complexity at thetraining sites. Selection of distance delivery technology wasdriven by three primary factors: (a) restriction of costs to sites,(b) ease of use, and (c) portability.

Computers and associated equipment. Project staffrequested that site personnel identify a computer with at leasta 90 MHz processor, 16 MB RAM, and Windows95/98/2000/ME/XP. Staff requested the computer be locatedin a large classroom or district meeting room and dedicatedfor exclusive use for course delivery purposes so settings werenot changed). One site used a laptop computer and two sitesused desktop computers. Each of three site computers wasconnected to the Internet via a broadband T1 line. Each siteused a PC computer. Project staff experimented withMacintosh computers and determined that they could beadapted to the same system, but adaptations were necessaryin regards to compatibility with video streaming technology.

At the broadcast site, project staff used a Dell Poweredge2400 server, Canon XL1 Mini-DV camcorder, BehringerMX802A Eurorack eight-channel audio mixer, Behringer XM8500 microphone, and a teleprompter device developed by theproject technician. The teleprompter displayed the computerscreen in front of the camera, allowing the instructor tomaintain direct visual contact with participants and othermedia, such as slides or video. Cost of broadcast siteequipment was approximately $8,000.

Software. Project staff used a software applicationdeveloped by Eyematic called iVisit. This software offeredthree advantages. First, it was free as a download file from theInternet. Second, iVisit supported two-way audio and videoand did not require additional hardware. Third, it requiredonly Internet access and three setting changes to beoperational.

Audio equipment. Project technicians foundcommercially available computer microphones were unableto transmit audio signals with the fidelity and quality neededfor course communications. After examining severalalternatives, technicians requested each site to purchase twoRadio Shack unidirectional dynamic microphones,microphone stands, audio cables, and a Behringer MX802AEurorack audio mixer. Costs for audio equipment was $200.

Slide tool for class presentations. Many instructors usepresentation tools such as Microsoft PowerPoint or CorelPresentation to organize lessons, summarize points, anddeliver content. Project staff needed a slide presentationprogram, but the iVisit software did not accommodate suchtools. However, the software supported sharing of Web pages.Therefore, technicians made each Powerpoint slide its ownWeb page and then linked each page together into one Website. The course instructor could then navigate to the web site

27Morgan et. al.


and move through each page (theindividual slides). When the instructorprogressed from slide to slide, the iVisitapplication automatically updated allsite computers. The chief expense wastime required by the instructor andtechnicians to make slide presentationsand then convert them into Web pages.

Video streaming. The selectedparaprofessional training curriculumincluded video exercises. The videoexercises were originally formatted onVHS videotapes for convenience of localinstructors. However, project staffneeded to deliver exercises to each sitesimultaneously, therefore, it wasnecessary to digitize video segments forcomputer-based delivery. Projecttechnicians digitized each videosegment using Windows MediaStreaming technology and createdseparate files. Technicians created aWeb page linked to a central serverwhere all video segments were stored.The instructor simply accessed the Webpage to play the next video segment in a manner similar tothe navigation of the slide presentation. Windows MediaStreaming was compatible with Macintosh but requiredseveral setting adaptations, and occasionally resulted incompromised video quality.

Project staff requested each site use a LCD projector toproject images from the computer onto a wall or screen.When projected, the image was about 6 ft. by 4 ft. Themonitor display resolution was set at 1024 x 768 pixels.Figure 1 presents a sample screen shown during a coursesession as it appeared to sites.

Paraprofessional Training General goals of the project were to provide training to

paraprofessionals leading to competence in special educationsettings, and to demonstrate the functionality of the Internet-based delivery system. According to the Council forExceptional Children (CEC) statements of knowledge andskills for beginning paraprofessionals, these classroompersonnel must (a) describe philosophical, historical, and legalfoundations, (b) identify characteristics of learners, (c)conduct basic data collection and assessment strategies, (d)assist the teacher with instruction content and practice, (e)support the teaching and learning environment, (f) managestudent behavior and social skills, (g) develop effectivecommunication and collaborative skills, and (h) practiceprofessional behavior and ethical practice (CEC, 1998).

The project used a text and video curriculum calledEnhancing Skills of Paraeducators, 2nd edition (ESP: 2)(Morgan, Forbush, & Avis, 2001). This program, which wasdesigned to address each of the CEC knowledge and skillareas, had been developed and evaluated in a previous grantfrom the U.S. Department of Education (Salzberg, Morgan,Gassman, Pickett, & Merrill, 1993). The content of ESP: 2was identified from (a) analysis of survey data gathered fromparaprofessionals and teachers at multiple sites across theU.S. (Salzberg et al., 1993), (b) field evaluation (Salzberg et al.,1993), (c) experimental analysis (Gassman, 1995), (d) reviewsof literature (Salzberg & Morgan, 1995), (e) interviews withexperts in the field, and (f) feedback from consumers of thefirst edition of ESP. In its final form, ESP: 2 includedinstructor and paraprofessional manuals, an instructor’sguide, and video exercises. The video exercises displayedschool-based situations allowing paraprofessionals to analyzeproblems, make decisions, and decide how they wouldrespond in similar situations.

The project presented a 10-week course on two of fiveunits of ESP: 2. This course, entitled Effective BehaviorManagement Practices for Paraeducators, introduced theparaprofessional to applied behavior analysis and classroommanagement procedures. Specific topics included identifyingthe paraprofessional’s role in managing behavior andpresenting instruction, specifying behavior, collecting data onacademic performance and classroom behavior, applying

Figure 1. A sample screen shown during a course session as it appeared to viewers at the distance sites.



reinforcement procedures, assisting with instructionaldelivery, and managing instruction. Under a teacher’ssupervision and the instructor’s guidance, participants wererequired to carry out assignments demonstrating competencyin activities such as identifying and defining a student’s targetbehavior, collecting data and developing a graph to displaystudent behavior, identifying potential positive reinforcers foran individual student, carrying out a behavioral intervention,conducting a task analysis, preparing and presentinginstruction to a student, and checking for a student’sindependent responses. For example, participants carried outan assignment requiring that they supervise a group ofstudents in a classroom during an independent seatworkactivity, circulating among the students to check work andprovide feedback. The assignment required circulating in arandom manner, tutoring individual students no more than10 – 15 seconds, observing others in the group whenconducting individual tutorial, and praising students whowere working on the assignment. The supervising teacherchecked each participant’s performance on the assignment.

Course development activities included developing thesyllabus and schedule, constructing a Web site, and creating alesson plan and timeline for each session. Two college creditswere optional. At the beginning of the federal grant project,staff analyzed the ESP: 2 program, established a sequence oflessons, developed quizzes and activities, and rehearsed coursedelivery procedures.

Instructional ProceduresA Utah State University instructor delivered the course

via live video and audio transmission to paraprofessionalparticipants at three sites. A site coordinator managedinstruction at each site. The coordinator was a teacher orspecial education district director who recruited localparaprofessional participants and organized each coursesession by answering questions, grading quizzes, referringquestions to the instructor at the broadcast site, andcoordinating upcoming sessions with the instructor bytelephone or email. A site technician managed broadcasttechnology at each site. The technician was a districtcomputer services staff member who established Internetconnections, set up equipment (e.g., computer, camera,microphones, audio mixer, etc.), and met periodically withproject technicians.

One hour prior to instruction, technicians logged onto theteleconferencing Web site. Using a projector and a computercamera, site personnel viewed the instructor and participantsat other sites. Microphones and speaker systems allowed theinstructor and paraprofessionals to speak to one anotheracross sites. The instructor began sessions by welcomingparticipants, reviewing course activities and sessionobjectives, and answering questions. Between sessions,

individual participants were required to read brief assignmentsfrom the ESP: 2 text. During most sessions, the instructorpresented slides summarizing text content and briefly lecturedon particular topics. Periodically, the instructor addressedparticipant questions from various sites. Following thelecture/questions, the instructor led participants through aseries of ESP: 2 video exercises addressing the reading topics.Each video exercise was followed by 2 – 5 minutes of inter-sitegroup discussion. Discussion provided the instructor, sitecoordinator, and participants with opportunities to describesolutions to problems shown on video. To facilitatediscussion, site coordinators prompted participants to respondand passed microphones around the room to individualparticipants. During discussion, site coordinators signaledwhen a participant wished to respond by motioning with a flagin view of the camera. In turn, the instructor recognized thesite and the participant offered questions or discussion. Theinstructor awarded a certificate of completion toparaprofessionals who passed the course. Paraprofessionalswho failed the course could retake it at a later time or arrangealternative training through their school district.

Selection and Development of Distance Education SitesInitially, project staff identified prospective sites by

following leads from national and state educational leaders inparaprofessional development. Staff established criteria forselection of sites based on (a) estimates of numbers ofparaprofessional trainees, (b) availability of the requiredhardware, and (c) availability of technicians and teachersinterested in serving as site coordinators. Using these criteria,four sites emerged; in Utah, Delaware, Idaho, andPennsylvania. One site discontinued course delivery becauseof firewall restrictions (i.e., a security system on the localnetwork). Firewall restrictions were imposed by the stateeducation agency because of security concerns. Threeunsuccessful attempts had been made to broadcast to the siteprior to discontinuation. While other sites continued toparticipate, project staff supported the discontinued site inproviding local training.

Site characteristics. Communities represented by threesites were relatively small, ranging in size from a populationof 1,000 to a population of 20,000. Each of the sites waslocated in a rural area. Student populations in these schooldistricts ranged from 1,970 to 10,659.

Participant characteristics. A total of 54 paraprofessionalsparticipated across three sites. Numbers at each site rangedfrom 16 to 20. One of 54 participants was male. Participantsranged in age from 21 to 59 years (mean age = 41.5 years).Years of special/general education experience inparaprofessional and other positions ranged from 0 – 25 years(mean experience = 7.4 years). Participants reported a range of0 – 228 clock hours of additional inservice training (mean

29Morgan et. al.


training = 59.4 hours). Of 39 participants whoreported ethnicity, three were Hispanic and 36were Caucasian (15 participants did not identifyethnicity). Across sites, 39 of 54 participantsreceived university credit.

Training Site Coordinators and TechniciansSite coordinators included two special

education program directors and a specialeducation teacher. In seven sessions (about 20hours), site coordinators were trained to log ontothe course Web site and establish courseconnections, respond to technical difficulties,stream video, facilitate local discussion, gradequizzes, and register students for universitycredit. Although site coordinators were notexpected to take primary responsibility fortechnology, they were trained in fundamentalprocedures in the event technicians wereunavailable. Technicians included two districtcomputer technicians and a high school studentwith computer experience. Technicians weretrained individually by the project technicians(average time per technician = 2 hours).Technician training addressed logging onto thecourse web site, establishing course connections,responding to technical difficulties, andstreaming video.

Evaluation ProceduresEvaluation of participant performance.

Participants were evaluated on a pass/fail basisdetermined by quiz and final test scores, sessionattendance, and completion of applicationexercises. Participants who successfully passedthe course received a certificate of completion.Participants who failed the course were allowedto retake it or receive other training.

Evaluation of the course. Course evaluationprocedures consisted of examiningparaprofessional participant feedback.Participants responded to 35 items on a courseevaluation form by rating each one on a five-point Likert-type scale (5 = excellent, 1 = poor).Evaluation items are listed in Table 1. For eachitem, space was provided for participants to writeobservations. Two undergraduate studentsunrelated to the project computed mean ratingscores on each item. After identifying the 10highest and 10 lowest-rated items, theundergraduate students compiled statementsrepresenting participant feedback on the same

Table 1.Course Evaluation Form

General Topic Rated Items Within General Topic General Information

Overall quality of the course.Instructor’s effectiveness.

Information about the courseClarity of course objectivesClarity of the readingsClarity of the video exercises.Relevance of assignments.Relevance of the text content.Relevance of the video scenes.Relevance of the in-class exercises.Relevance of application (i.e., school-based) exercises.Appropriateness of the work load.Extent to which quizzes match instructional content.Clarity of participant’s responsibilities.

Information about instructionCourse organization.Use of class time.Instructor’s preparation for class.Site coordinator’s preparation for class.Instructor’s helpfulness in resolving problems/questions.Site coordinator’s helpfulness in resolving problems/questions.Opportunity to comment and express opinion.

Information about technologyAudio/visual clarity.Streaming video.Clarity of presented images.Clarity of the audio signal.“Synch” between the audio and the video.Launching of Media Player.

Classroom audioClarity of audio.Access to microphones.Time lag between when a comment is offered and when it is heard.Clarity of the audio from other sites.

Classroom videoClarity of the image of the instructor.Clarity of the image of other sites.

Classroom audio/videoThe “synch” between the audio and the video (of instructor or sitesto classroom).Extent to which audio/video facilitates understanding of instructor.

Slide presentation toolAbility to read information presented on the slides.

Technical DifficultiesExtent to which technical difficulties were resolved.

General reaction: Please list and describe positive elements of this course. Be specific.General reaction: Please list and describe negative elements of this course. Be specific.



topics. Participants were also asked to write generalreactions in boxes designated for positive/negativeelements of the course. One of the authors countedthe number of statements on positive/negativeelements and noted representative ones.

In addition to participant feedback, project staffcompiled advisory board feedback from courseevaluation forms. Six advisory board membersincluded two national experts on paraprofessionaltraining, one community college instructor, oneformer teacher who had supervisedparaprofessionals, one paraprofessional, and oneparent of a child with special needs. Board membersprovided feedback after watching a videotape of acourse session. Project staff established a rotatingschedule for board members to receive videotapes.Board members evaluated sessions five through 10of the course; the first four sessions were notevaluated to allow the instructor to become familiarwith instructional procedures and technology. Boardmembers rated and commented on 24 items on thecourse evaluation form. They did not rate theremaining 11 items on the form because some itemswere irrelevant or information was unavailable (e.g.,clarity of readings, relevance of text content, extentto which quizzes matched instructional content,etc.). Each board member was compensated forcourse evaluation. Identical to participant evaluationprocedures, undergraduate students identified 10highest and lowest rated topics and general reactionstatements representing board member feedback.

Evaluation ResultsParticipant performance results. All 54

participants passed the course. At the conclusion ofthe course, the instructor distributed certificates ofcompletion.

Course evaluation results. Fifty participantsprovided course evaluation data. Data from fourparticipants were not obtained. Across items, meanratings for sites ranged from 4.07 to 4.57. Theoverall mean rating for the course was 4.36. Meanratings for individual items ranged from 3.60 (clarityof audio from sites) to 4.93 (site coordinator’sassistance).

Table 2 presents course evaluation data according to the10 highest and 10 lowest-rated items. For participants,highest rated items pertained to activities of local sitecoordinators (i.e., the coordinator ’s assistance andpreparation). Representative participant statements on courseevaluation forms included the following:

1. [The site coordinator was] always willing to help with

any problems and was very understanding. She was warmand enthusiastic.2. [The site coordinator was] had everything ready to gobefore each session. She was well-organized and helpedmake the course a success.The next two highest rated items related to the

instructor’s activities (i.e., the instructor’s assistance andpreparation). The instructor’s effectiveness was also rated as

Table 2.Course Evaluation Data from Paraprofessional Participants andAdvisory Board Members

Participant Evaluation Data (5 = excellent, 1 = poor)Highest Rated Items (mean rating)

Site coordinator’s helpfulness in resolving problems/questions. (4.93)Site coordinator’s preparation for class. (4.92)Instructor’s preparation for class. (4.68)Instructor’s helpfulness in resolving problems/questions. (4.67)Ability to read information presented on slides. (4.58)Extent to which quizzes matched instructional content. (4.54)Opportunity to comment and express opinion. (4.49 — tie)Instructor’s effectiveness. (4.49 — tie)Overall quality of the course. (4.40)

Lowest Rated Items (mean rating)Clarity of images of other sites. (3.50)Clarity of audio from other sites. (3.60)Clarity of classroom audio. (3.68)“Synch” between audio and video (of instructor or sites to classroom). (3.70)Audio/visual clarity. (3.80)Clarity of presented images (streaming video). (3.88)“Synch” between audio and video (streaming video). (3.94)Launching Media Player. (4.03)Time lag between when a comment is offered and when it is actually heard. (4.09)

Advisory Board Member Evaluation Data (5 = excellent, 1 = poor)Highest Rated Items (mean rating)

Clarity of course objectives. (4.72 — tie)Clarity of the image of the instructor. (4.72 — tie)Ability to read information presented on slides. (4.72 — tie)Relevance of the class exercises. (4.66 — tie)Course organization. (4.66 — tie)Instructor’s preparation for class. (4.66 — tie)

Lowest Rated Items (mean rating)Clarity of audio from other sites. (3.15)Clarity of images of other sites. (3.32)Opportunity to comment and express opinion. (3.79)Time lag between when a comment is offered and when it is actually heard. (3.82)Audio/visual clarity. (4.15 — tie)Clarity of presented images. (4.15 — tie)

31Morgan et. al.


one of the top 10 items. Representative participantstatements on course evaluation forms included thefollowing:

1. The instructor always had things set up on time. Shewas very knowledgeable and explained a lot of details.2. [The instructor] is always very well prepared.Other highly rated items pertaining to instruction

included the extent to which quizzes matched instructionalcontent, access to microphones, and the opportunity tocomment or express opinion. Highly rated items pertaining totechnology included ability to read information presented onslides and overall course quality.

The lowest items rated by participants were clarity of theimage of other sites and clarity of the audio from other sites.Representative statements included the following:

1. It was hard to understand what other sites were saying.The audio was delayed and either too loud or too soft.2. We had problems at times but it was alwaysimmediately remedied.3. I wish we could have seen them (i.e., other sites) better.Participants wrote 66 general reaction statements

regarding positive elements and 25 statements regardingnegative elements of the course. Representative statementsregarding positive elements included the following:

1. [The class] was a great opportunity to share andcompare ideas used by other paras that we would nothave the opportunity to learn from.2. Course content is excellent for helping us becomemore effective working with the students in our schools.It helped us clarify different ways of handling situationsin the classroom. 3. I learned a lot of practical, useful techniques. It wasvery informative and really applied to my job. The videoexamples were good.4. I think this class has helped me do my job better.Representative statements from participants regarding

negative elements of the course included the following:1. The audio from the sites was hard to understand.2. [We experienced] down time or problems with videoand audio. Sometimes we had to wait and it could getdiscouraging.3. The down time at the sites was a problem.Table 2 presents course evaluation data from advisory

board members. Of 24 total items rated by board members,only the six highest and six lowest are shown. The highestrated items were clarity of course objectives and clarity of theimage of the instructor. Representative statements includedthe following:

1. I like how the instructor starts a session by reviewingobjectives. I feel that the session objectives were madeextremely clear and concise, which allowed this contentto be easily acquired.

2. The clarity of the instructor’s image was very goodthroughout the session. Movement resulted in very littledistortion.The items rated lowest by board members were clarity of

audio from other sites and clarity of the presented videoimages. Representative statements included the following:

1. I could barely hear the comments from the sitelocations. The technical quality of the audio is a problem.2. Cannot see much detail [of the video image]. But it isexcellent to have them there as a reminder that others arewatching and that they need to stay on task.General reaction statements from board members

regarding the positive and negative elements of the courseincluded the following:

1. The lesson content was right on target for paras. Thematerial was relevant and important. The instructor’sknowledge of content was good. Excellent presentation ofdifficult material. Video clips were applicable andrelevant. 2. The audio difficulty from the site locations was aproblem. 3. Not enough time was spent on difficult material toensure that participants acquired both knowledge andapplication skills. Both participants and board members assigned relatively

high ratings to the instructor’s preparation for class. Otherhigh-rated items for participants and board members weredifferent. However, several items were rated relatively low byboth groups, including clarity of audio from other sites, clarityof the presented video images, audio/visual clarity, and timelag between when a comment was offered and when it wasactually heard. One item rated high by participants was ratedlow by board members (i.e., opportunity to comment andexpress opinion).

DISCUSSIONParaprofessional participants and advisory board

members assisted in evaluation of a course delivered to threesites across the United States using Internet technology.Based on course evaluation results, the live, Internet-baseddelivery system may represent an additional training deliveryoption. As such, this particular system may provide agencieswith standards-based, instructor-delivered, and cost-efficienttraining. However, subsequent iterations of course deliverywill need to address limitations identified in participant andboard member evaluations, particularly the clarity of audioand video from the sites.

Generally, course evaluation items were rated positivelyby both groups. However, participants and board membersassigned relatively low ratings to some topics, particularlythose related to audio and video signals from the sites. Threealternative explanations are provided. First, audio/video



components of interactive courses on the Internet maysimply be an emerging technology whose current standard ofquality involves occasional technical difficulties. Like anytechnology, the standard is refined and improved as problemsare solved, but encountering them is a necessary part of theprocess. Project technicians have made numerous audio/videorefinements during and after the first course. It should benoted that board members evaluated sessions fromvideotapes, therefore audio difficulties, and perhaps othertechnology-related problems as well, increased because theoriginal digital signal had been recorded to VHS tape. Second,the current standard of audio/video technology on theInternet may not meet expectations of evaluators. Indeed,researchers have shown participants evaluate technology-mediated instruction in terms of how well it emulates liveinstruction (Kelly & Leckbee, 1998; Zhang & Fulford, 1994).Perhaps course evaluators held the same expectations ofdistance education technology held for a live courseexperience (Ludlow, 2001). If so, distance learners may needmore information in advance of courses regarding differencesin learning experience between distance-based courses andlive ones. Third, participants’ previous experience withdistance education technology may have biased theirexpectations in a negative direction. Although project staffgathered information on the amount of previous inservicetraining experiences of participants, they gathered no specificinformation on their distance education experience. Futureresearch should investigate the relationship betweenevaluations by participants with and without previousexperience with distance education technology.

Several course evaluation items were rated differently byparticipants and board members. Obviously, these groupsevaluated the course from different perspectives. Unfortunately,project staff did not delineate the different perspectives ofparticipants and board members prior to course evaluation. Itmight be presumed that because participants had to pass thecourse to receive a certificate, they were concerned aboutreceiving and distinguishing relevant information, performingsatisfactorily on quizzes, and applying the information in theirschool classrooms. Understandably, participants assignedhighest ratings to preparation and assistance of site coordinatorand instructor, and assigned lowest ratings to clarity ofaudio/video information because these items were critical totheir success in class. On the other hand, board members wereprobably concerned with how well instruction was deliveredand how well participants were supported. Despite differences,ratings from the two groups provide valuable information toassist staff in refining technology and curriculum for futurecourse delivery.

Course evaluation was limited to feedback fromparticipants and board members. Project staff did not seekinput from district administrators on the relative merits of

live, interactive, distance-based courses for paraprofessionalsversus other formats. This information would be valuable asan index of consumer validation and cost efficiency of thesystem. Future course evaluation efforts should gatherinformation from administrators and other stakeholders,such as state education agency representatives.

Given federal training mandates for paraprofessionalsand the limited timeline for meeting requirements, state andlocal agencies need a variety of training delivery options.Multiple options would allow agencies to assess their needs,assets, and resources, then select the best match. The live,Internet-based system may represent a good match foreducation agencies having no local experts who can delivertraining and districts located in rural areas. For theseagencies, and those whose teacher trainers are busy withother priorities, the system provides an outside instructor anda functional delivery method, albeit one in need of technicalrefinement. Hypothetically, a state educational agency couldhire an instructor, set up technology, and deliver training todistant sites. Alternatively, an agency could contract with ateacher/personnel preparation program to broadcast to distantsites. The system may also be tailored to state and localagencies needing a cost efficient alternative for seminars,meetings, consultation, and other professional endeavors.Although start-up costs to the project were high, costs to siteswere relatively modest. Savings in costs of travel and timewould make the system an efficient alternative forprofessionals with busy schedules. Additional evaluation willdetermine the extent to which the system is adaptable toeducation agencies, community colleges, universities, andother organizations.

REFERENCESASPIIRE IDEA Partnership Group. (2001). IDEA partnerships:

Paraprofessional initiative. Report to the U.S. Department ofEducation, Office of Special Education Programs, December2001. Arlington, VA: Council for Exceptional Children.

Collins, B. C. (1997). Training rural educators in Kentuckythrough distance learning: A model with follow-up data.Teacher Education and Special Education, 20, 234 – 248.

Council for Exceptional Children. (1998). What every specialeducator should know: Common core knowledge and skillsstatements for paraeducators. Arlington, VA: Council forExceptional Children.

ERIC/OSEP Special Project. (Spring 2003). Paraeducators:Providing support to students with disabilities and theirteachers. Research Connections in Special Education (No.12). Arlington, VA: ERIC Clearinghouse on Disabilities andGifted Education.

French, N. K., & Pickett, A. L. (1997). Paraprofessionals in specialeducation: Issues for teacher educators. Teacher Educationand Special Education, 20, 61 – 73.

33Morgan et. al.


Gassman, G. W. (1995). A multiple method approach to theformative evaluation of a unit on behavior management fortraining paraeducators in special education classrooms.Unpublished doctoral dissertation, Utah State University.

Kelly, J. T., & Leckbee, R. (1998). Reality check: What do we reallyknow about technology and how do we know it? Syllabus, 12(1), 24 – 26.

Ludlow, B. L. (2001). Technology and teacher education in specialeducation: Disaster or Deliverance? Teacher Education andSpecial Education, 24, 143 – 163.

Morgan, R. L., Forbush, D. E., & Avis, D. (2001). Enhancingskills of paraeducators (2nd ed.). Logan, UT: Technology,Research, and Innovation in Special Education.

Public Law 107-110, The No Child Left Behind Act of 2001, 34CFR 115.1425, 2001.

Roles for Educational Paraprofessionals in Effective Schools.(1997). Paraprofessionals and their work. http://www.ed.gov/pubs/paraprofessionals/roles2.html

Salzberg, C. L., & Morgan, J. (1995). Preparing teachers to workwith paraeducators. Teacher Education and SpecialEducation, 18, 49-55.

Salzberg, C. L., Morgan, R. L., Gassman, G. W., Merrill, Z., &Pickett, A. L. (1993). Enhancing skills of paraeducators: Avideo-assisted program. (Final Report H029K10031). Logan,UT: Utah State University. (ERIC Document ReproductionService No. ED461971.

U.S. Department of Education. (1998). Twentieth annual reportto Congress on the implementation of the Individuals withDisabilities Education Act. Washington, D.C: Author.

Zhang, S., & Fulford, C. P. (1994). Are interaction time andpsychological interactivity the same thing in the distancelearning television classroom? Educational Technology, 34(6), 58 – 64.

Robert L. Morgan is Associate Professor in the Department ofSpecial Education and Rehabilitation at Utah StateUniversity. David E. Forbush is Assistant Professor in theDepartment of Special Education and Rehabilitation at UtahState University. Jon Nelson is a doctoral student in theDepartment of Instructional Technology at Utah StateUniversity.

The authors would like to thank Trisha Butterfield, CourseInstructor; Todd Christensen, Project Technician; andparticipants and site coordinators from the Warrior Run, PA,School District, Madison School District, ID, and Box ElderSchool District, UT, who participated on this project. Thismanuscript was supported with a grant from the Office ofSpecial Education and Rehabilitation Services, U.S.Department of Education, H325N000048. The opinionsexpressed in this article do not necessarily represent those ofthe funding agency.

Correspondence concerning this article should beaddressed to Robert L. Morgan, Ph.D., Department of SpecialEducation and Rehabilitation, Utah State University, 2865Old Main, Logan, UT, 84322-2865. Email to:[email protected].

34


35


The concern that Hispanic students aredisproportionately referred to and placed in special educationhas been a significant national educational concern sinceDunn (1968) declared that special education was unjustifiedfor many students. There appears to be a consensus among asignificant number of educators and policy makers, past andpresent, outside of and within the field of special education,that many students are erroneously referred for and placed inspecial education (Artiles & Trent, 1994; Bay & Lopez-Reyna,2000; Trent & Artiles, 1998; Tyler & Smith, 2000; USCensus Bureau, 2000). A common explanation foroverrepresentation of Hispanics in special education relates tobiases in assessment. Implicit in the assessment biasargument is the notion that educators fail to consider that theacademic difficulties experienced by students who are limitedin English proficiency might be related to second languageacquisition, cultural differences, or the family’s child rearingpractices rather than cognitive disabilities.

Efforts to address this educational problem indicatethat the solution is more complicated than simply reducingthe number of students in categories of exceptionality. Agrowing number of educators are concerned with the under-representation of Hispanics in special education categoriesof disability (Artiles & Trent, 1994; Baca & Valenzuela,1998; Grossman, 1998; Hallahan & Kauffman, 2003;Ochoa, 2003). Ochoa and her colleagues posited that asignificant number of Hispanic students who experience

considerable academic difficulty in school, in particularthose with limitations in the English language, are likely tobe under-referred for special education evaluation bygeneral education teachers for fear of making a mistake orbeing accused of racial discrimination (Ochoa, 2003; Ochoaet al., 2001). Unless disabilities impact Hispanic studentswith English language limitations differently than theyaffect the general population, a significant number of thesestudents who have disabilities will not be provided with theeducational services their disabilities require unless generaleducation teachers make the initial referral for specialeducation evaluation.

In an effort to reduce bias in the evaluation andplacement of students in special education and improveservices to students with disabilities and their families, theIndividuals with Disabilities Education Act of 1997 mandatesthe use of multidisciplinary teams (MDTs) to make decisionsabout students before they are formally evaluated fordisabilities or during the process of providing services to them(Parette, VanBiervliet, & Hourcade, 2000). According toKnotek (2003), the rationale behind the use of MDTs is thata group of professionals, and to the extent possible thestudent and his or her family using a variety of assessmenttools and strategies, makes less-biased referral decisions thanan individual acting alone. Concerns for the problem ofdisproportional representation of Hispanics in specialeducation persist (Llagas & Snyder, 2003).

The Impact of PBL Technology on the Preparationof Teachers of English Language Learners

THERESA A. OCHOA

MARY L. KELLY

Indiana UniversitySHANNON STUART

DIANA ROGERS-ADKINSON

University of Wisconsin Whitewater

This article presents qualitative results of the instructional usefulness of a Web-basedmultimedia problem-based learning module designed to simulate the special educationreferral process. The multicultural special education (MUSE) module uses three interactivephases to highlight the complexity of determining the nature of academic difficulties when astudent has English language limitations. Interviews with instructors and pre-service teachersindicated that the multimedia components of the module created a realistic portrayal of thespecial education referral process. Furthermore, the group work within the module provideda unique opportunity for pre-service teachers to begin to collaborate with a team to makeeducational decisions for students they will likely encounter in their future professions.

Journal of Special Education Technology. 19(3), Summer 2004

36 Technology and Teacher Preparation


In addition, multiple challenges exist within teacherpreparation, but one of considerable concern has beenaddressing the changing demographics in America’s schools(US Census Bureau, 2000). The composition of students inAmerican public schools has changed over the last quartercentury. The population of students from non-whitebackgrounds was at 37% in 1998 and the population ofstudents from Hispanic backgrounds is expected to continueto grow (Gallegos & McCarty, 2000). These issues are oftenaddressed in a discussion format in the traditional teachereducation curriculum with little opportunity for directexperience regarding the role of future educators in supportingminority students. In light of the continued growth ofHispanic students in schools in the United States, teachersneed to increase their practical knowledge about thedifferences between academic difficulties related to Englishlanguage limitations and academic difficulties related tocognitive delays (Bay & Lopez-Reyna, 2000; Solorzano &Solorzano, 1999; Trent & Artiles, 1998; Tyler & Smith, 2000).

To address the need to prepare teachers of students fromHispanic backgrounds, Leafstedt, Ochoa, and Gerber (2000)developed a problem-based learning module for the purpose ofproviding pre-service teachers an opportunity to grapple withthe problem of differentiating between academic difficultiesrelated to second language acquisition and those related tocognitive deficiencies.

PROBLEM-BASED LEARNINGProblem-based learning (PBL) is a way of motivating

students to integrate diverse sources of knowledge to solvereal-world problems (Boud & Feletti, 2001; Engel, 2001;Norman & Schmidt, 1992; Shore & Shore, 2003). PBL is alsoa way of handling conflicting information, including thatfrom different professional fields. The goals of PBL are to (a)familiarize participants with the types of ill-structuredproblems they will face in the future, (b) make availablerelevant knowledge, (c) foster the application of skills, (d)develop group problem-solving skills, and (d) strengthen theexecution and implementation of solutions.

Meta-analyses conducted by Albanese and Mitchell(1993) and Vernon and Blake (1993) found PBL to besufficiently engaging and was preferred by students andinstructors as compared to more traditional lectureapproaches to teaching and learning. For example, one study(Schwartz et al., 1998) with 62 sixth-grade students showedthe benefits of PBL simulated activities. Judges blind to thestudy rank ordered the written plans for a school carnivalbooth and rated the experimental group’s plan higher than thecontrol group’s. The researchers concluded that the controlgroup did not have the benefit of a prior simulated task,compared to the experimental group that carried out asimulated plan during a classroom activity. Doucet, Purdy,

Kaufman, and Langille (1998) compared the differencebetween lecture versus problem-based delivery approacheswith primary care physicians and also found empiricalsupport for the PBL approach. While differences in favor ofthe PBL group were only slight on a pre/post knowledgeinventory, the PBL group performed significantly better on akey features problem that focused on clinical reasoning skills.Furthermore, participants in the PBL group also indicatedhigher ratings of satisfactions for the program. The authors,however, also pointed out that the PBL group required ahigher teacher-learner ratio and raised the issue of costeffectiveness.

One method for making instruction not only moreengaging but perhaps also making PBL more cost effective is theintegration of PBL tenets into technology. Albion and Gibson(2000), Gerber, English, and Singer (1999), and Ochoa (2003)have merged the tenets of PBL with multimedia modules andhave begun to evaluate their effectiveness. Gerber, English, andSinger (1999) conceptualized and developed a set of PBLcomputer-supported multimedia modules for the preparation ofteachers of students with disabilities. In a study by Ochoa et al.(2001), 127 pre- and in-service teachers reported that amultimedia, problem-based learning module was successful inteaching pre-service educators about the special educationreferral process and the complexity of referring students fromdifferent cultural backgrounds for special education services.While these studies and others in special education (e.g.,Fitzgerald & Semrau, 1996; Langone, Malone, Clinton, 1999;Watson, Fitzgerald, & Semrau, 1999) showed the benefits ofusing multimedia technology in coursework, others cautionedthat multimedia technology may, in some cases, increase thecognitive demands of learners (Ochoa, Vasquez, & Gerber, 1999)or actually impede learning (Mayer, Heiser, & Lonn, 2001).

Description of the Multicultural Special Education (MUSE)Module

The MUSE module is a multimedia, computer-supported, problem-based learning (CS-PBL) unit thatprovides users with a simulation of the special educationreferral process. The module, developed by Leafstedt et al.(2000) depicts an elementary Hispanic student who islimited in English proficiency and is also experiencingacademic difficulties. The module is available for viewing athttp://www.caselinks.education.ucsb.edu . The simulationprovides pre-service teachers an opportunity to grapple withthe complexity of determining the nature of academicproblems (i.e., are the student’s academic difficultiesrelated to English language limitations or a disability?). Themodule serves as an adjunct to lectures and readings inteacher preparation courses and consists of three sequentialphases: (a) narrative, (b) role strands, and (c) problemresolution.

37Ochoa et. al.


In the narrative (phase one), users are introduced toAndres, the 1st grade student depicted in the module (seeFigure 1). Through a combination of multimedia (e.g., video,audio, text, digitized examples of actual coloring and writingassignments), the Narrative provides information aboutAndres’ school and home life. For example, as shown inFigure 1, the digitized examples of student work provide usersan opportunity to compare Andres’ work to another studentin his class. Another option includes clicking on the video ofhis schoolteacher to hear her express concerns about Andres’lack of academic progress. They also learn about his socialstrengths. The Narrative ends with an activity that consists ofthe following three open-ended questions: (a) What areAndres’ strengths and weaknesses, (b) What problems do youthink Andres is having in school, and (c) What do you see isbeing done to address these problems.

The second phase of the module is called the role strands.The activity in this section is the cornerstone of the module.Participants work in small groups with eachperson representing the typical roles in anMDT. There are six role strands: (a) schoolpsychologist, (b) parent advocate, (c) specialeducator, (d) school principal, (e) generaleducator, and (f) bilingual educator (see Figure2). Each strand provides discipline-specificinformation related to issues in the educationof English Language Learners (ELLs). Forexample, users access information aboutculturally sensitive assessments through theschool psychologist role strand. The generaleducator role strand provides informationabout what to do when a teacher thinks astudent has a disability, while the specialeducator strand suggests instructionalstrategies to teach students in the ELLprogram. The parent advocate strand, asshown in Figure 2, contains information aboutthe student’s home environment, a critical

aspect of the child’s backgroundeducators need to understand inorder to facilitate parent involvement(Parette, VanBiervliet, & Hourcade,2000). The bilingual educator strandhas information about the rate ofsecond language acquisition. Lastly,the school principal role strandinforms users of the various types ofbilingual education programs and theresources available in schools forparents who do not speak English.

The role strands activity iscarried out in three parts. In the first

part, each participant is required to write a goal for Andresfollowing step-by-step instructions within the module (seeFigure 2). Then he or she meets with a working group, similarto a typical individualized education program (IEP) team inpublic schools, to develop a three-goal plan for the targetstudent. Because there are six members within thiscomponent, the team has to discuss and select from allavailable goals. In the last part of the activity, the teamdevelops an educational plan for Andres. The team views anexisting classroom schedule and charts goals by makingmodifications to the schedule indicating what they proposefor Andres to achieve, who will work with Andres (e.g.,resource teacher, bilingual teacher, parents, general educationteacher), for how long (e.g., 20 minutes, 1 hour), and thelocation in which instruction will take place (in or outside thegeneral education classroom).

The problem resolution phase is the final, and briefest,phase of the MUSE module. As shown in Figure 3, users are

Figure 1. Narrative Phase of MUSE module.

Figure 2. Role Strands Phase of MUSE module.



provided access to Andres’ actual goals, schedule, andassessments recommended by his actual school team. In theactivity, the participants compare and contrast the team’sgoals and schedule to those proposed by the professionals. Asthe culminating activity of the special education referralprocess unit, each team makes a final recommendation onwhether or not Andres should be referred to special educationservices.

Problem-based learning multimedia like the MUSE holdpromise as tools to respond to the need to improve thepreparation of teachers of students from diverse culturalbackgrounds, however, these new tools require research-basedsupport. The purpose of this study was to investigate theinstructional usefulness of the MUSE for teacher preparationpurposes from the perspective of teachers and instructorsusing the multimedia problem-based learning module.

METHODQualitative research is a multi-method approach to

studying phenomena in natural settings. To do this, thequalitative researcher uses interpretive and naturalisticmethods. The purpose of a qualitative study is to interpret themeaning individuals bring to the phenomenon under study(Denzin & Lincoln, 2000). One particular qualitative methodis grounded theory. According to Strauss & Corbin (1990), aresearcher should use grounded theory “to explainphenomenon in light of a theoretical framework that evolves

during the research itself [and not a]previously developed theory that mayor may not apply” (pp. 49-50).Grounded theory was selected as theframework to use because the researchquestion, “What is the instructionalusefulness of a multimedia problem-based module designed to simulate thespecial education referral process?”could not be answered sufficiently witha response survey. It was imperative tointerpret participants’ perceptions ofproblem-based learning (PBL) withdirect input from participantsthemselves.

Participants and ProceduresSix students and their two instructors volunteered to be

interviewed for this study. The student volunteers wereundergraduates majoring in general education enrolled in twointroductory special education courses at two differentMidwestern universities (see Table 1). An announcement wasmade on the first day that the module was presented solicitingvolunteers for interviews at the conclusion of the module.Students were told the interviews would take approximately90 minutes and could be arranged according to theirschedules. The students who volunteered were representativeof the typical course participants in terms educationalbackground (see Table 2).

The instructor participations had taught the coursepreviously and had used Hallahan and Kauffman’s (2003)textbook for the course. One was an associate professor whohad previously utilized PBL modules in her teaching, whilethe other was a second year doctoral student new to PBL (seeTable 3). Both were interested in testing the efficacy of PBLthrough the MUSE module, and agreed to allow nine 75-minute class periods to complete the module. The instructornew to PBL received a manual for the MUSE case, viewed andused the module prior to the beginning of the course, andconsulted with Ochoa, the developer of the module, asneeded. The list of the MUSE module activities and

Figure 3. Problem Resolution Phase of MUSE module.

Table 1.Demographics for Students Interviewed

University 1 University 2Student 1 Student 2 Student 3 Student 4 Student 5 Student 6

Gender Female Male Female Female Female FemaleEthnicity Caucasian Caucasian Caucasian Caucasian Caucasian CaucasianClass Freshman Junior Sophomore Junior Junior SeniorMajor English Education Social Studies Education English Education Elementary Education Elementary Education Elementary Education

39Ochoa et. al.


assignments is provided in Table 4. Each activity illustrated inthis table corresponds to different topics related to the specialeducation referral process.

Interview ProceduresAt the end of the module, students enrolled in the courses

were asked to complete the learning and satisfaction survey(see Appendix A) to determine overall satisfaction with theMUSE module. A total of 107 students, of the 110 totalenrolled in both classes, completed this survey. The overallresponse was positive. The responses from this large surveywere used to develop an in-depth interview protocol (seeAppendix B). The protocol was developed to ensure that theinterviews covered the same basic format, promptedparticipation, and/or guided conversation back to the topic ofthe MUSE case study, while allowing participants to addinformation freely. The interviews ranged from 45 minutes to

90 minutes. A similar interview protocol was used with theinstructors. Bogdan and Biklen’s (2001) in-depth and semi-structured interview procedures were used with the eight (sixstudents, two instructors) participants.

Data Analysis All data were analyzed using the constant comparative

method (Glasner & Strauss, 1967), which consists of fouroverlapping stages. In Stage 1, data were collected and thencoded into as many analysis categories as possible. After thelearning and satisfaction survey was conducted, results werecoded to formulate questions for the in-depth interviews.After the in-depth interviews were conducted, they werecoded to develop emergent themes. Three researchers skilledin qualitative analysis provided input during this codingprocess by reading the in-depth interview transcripts. Areconciliation method was used to reach consensus on thecoded text. When a disagreement related to a coding categoryoccurred, the majority code was used.

During Stage 2, data were sorted and reorganizedinductively and deductively by chunking and clustering theminto similar categories and then reorganizing them to identifyany similar connections between or among categories (Strauss& Corbin, 1990). Initial categories included: (a) referralprocess, (b) group process, (c) instructor use of case, (d)technology issues, (e) relevance to future teaching, (f) teachingstudents with ELL, (g) need more knowledge to make decision,(h) effectiveness of Andres’ school, and (i) effectiveness ofmodule. In Stage 3, the codes were refined and combined,which gradually led to the development of theory (see Table 5).

In the final stage of data analysis, the following threethemes were solidified: (a) overall referral experience, (b)technology issues, and (c) PBL impact on learning (see Table6). Group process and instructor use of case were merged withthe code PBL impact on learning while nature of Andres’difficulties and referral process were coded as overall referralexperience. Technology issues was kept as a category. Thesefinal themes were consistent with the focus of the researchquestion: What is the instructional usefulness of amultimedia problem-based module designed to simulate thespecial education referral process?

RESULTSOverall Referral Experience

Both instructors perceived the MUSE case as a “veryuseful tool” for teaching students about the special educationreferral process. One instructor said, the “case had a greatereffect than anything else completed in this class.” They agree,however, that while the tool “brings the referral process tolife,” it should not be used as a stand-alone instructionalstrategy in the classroom. Background information about theroles of special educators and the referral process is necessary

Table 2.Demographics for MUSE Module Users

University 1 University 2Number of Students 50 60Gender

Female 36 54Male 14 6

ClassFreshman 1 0Sophomore 10 11Junior 19 28Senior 17 21Graduate 3 0

MajorEducation 42 57Non-Education 8 3

Course GradeA 34 41B 12 15C 3 4D 1 0F 0 0

Table 3.Demographics for Instructors

University 1 University 2Gender Female FemaleEthnicity Caucasian CaucasianTitle Associate Professor Doctoral StudentYears teaching 10 5Expertise Emotional Disorders Assistive Technology

Language Delay Systems ChangeCultural Issues Emotional Disorders



before the class begins the case. One instructor scaffoldedsupplemental case studies to the MUSE case while the otherhad students formulate questions as homework after viewingthe narrative phase.

Participants had much to say about their experiencesusing the MUSE case. Responses such as, “My groupdiscussed Andres like he was a real student and we wereactually on his study team” and “We gained the experience ofworking with teams like we will in the future” were common.Although students were challenged by the case’s intentionallyill-structured problem, they worked together to formdecisions. Positive comments such as, “The case reallyopened my eyes as to what teachers are actually doing” and“This is like having our first field experience” were typical.

Technology IssuesThe primary challenges to implementing the MUSE case

stemmed from technology. Instructors needed to be sure thatthe technology departments provided enough server space andthat students had the computer skills necessary to completethe case. A few students expressed initial anxiety over notbeing computer literate. Web-links that no longer worked

were especially frustrating to some students; as was the soundquality at times.

There were, however, predominately positive responses to thetechnology, both from students and instructors. One instructorcommented, “My students would come to class, excited andasking, What will we be doing today.” Students liked the multi-media effects; they appreciated seeing the body language ofAndres’ teacher and hearing how the teacher gave directions.

PBL Impact on LearningBoth instructors reported that they had used problem-

based learning throughout the course and felt that theirstudents benefited from “the thinking process involved inproblem-based learning.” Students also discussed theirperceptions of the benefits that stemmed from having thetime to construct meaning and solutions through listeningand sharing knowledge. As one student clearly stated, “I likedhow it was not an open and shut case and we had to apply allour knowledge to form conclusions and opinions”.

Instructors and students also appreciated the group workaspect of the MUSE case. Comments from all intervieweesindicated that most students were afraid to let their group

Table 5.Stage 3 Thematic Coding for Interview Responses

Participant PBL Impact on Learning GroupProcess Instructor Use of Case Technology Issues Nature of Andres’ Difficulties Referral ProcessStudent 1 10 7 2 3 8 1Student 2 7 5 4 4 5 10Student 3 0 3 4 2 5 7Student 4 16 4 3 4 5 2Student 5 2 4 3 0 8 8Student 6 9 0 0 0 4 1Instructor 1 20 9 4 5 5 0Instructor 2 8 8 9 7 3 3Note. Nature of Andres’ Difficulties (Effectiveness of Andres’ School, Need More Knowledge to Make Decision, and Teaching Students With ELL combined), Impact ofPBL on Learning (Relevance to Future Teaching and Effectiveness of Module combined).

Table 4.MUSE Module Activities and Assignments by Class Session

Activities Location Out of class assignmentIntroduction to PBL lecture & IEP group assignments Classroom NoneSPED referral process and continuum of services lecture Classroom Read ‘Working with families’Module activity: Introduction to Andres’ case and Narrative Lab Read ‘Culturally & linguistically diverse students’ Culturally and linguistically diverse students lecture Classroom Complete MUSE activity evaluationModule: Problem Identification Lab Complete activity as needed and select role strandIndividual work on Role Strand: Review role and write 1 IEP goal Lab Read ‘Teaching students with ADHD’Group work: Teams develop Andres’ educational plan Lab Complete Role Strand activity, as neededMovie: ADHD in the classroom (Barkley, 1994) Classroom Complete MUSE activity evaluationGroup discussion on special education referral decision Classroom Complete Problem Resolution activity

41Ochoa et. al.


members down by coming to class unprepared. Interviewsalso revealed that both instructors and students felt relief instudents’ opportunities to “take in all the content withoutfeeling the frustration of feeling lost or confused all alone.”

Although students and instructors reported excitementabout the benefits of problem-based learning, these benefitswere sometimes discussed with caution. Several students, forexample, indicated that viewing, rather than reading, the casestudy strengthened their emotional connections to Andresand his situation. These strong emotional ties led to feelingsof frustration when group members could not come to aconsensus about a decision or when groups felt uncertainabout their decisions. It was difficult for many students toaccept that there was not a “clear cut right or wrong answer.”Several students also expressed concern over what reallyhappened to Andres and how do they ensure that they makethe right decisions as practitioners. One instructor’s sageadvice cautioned that because the issues in problem-basedlearning cases could be “very real, very emotional for somestudents, instructors must allow enough class time to processthe content.” The MUSE case and the implications forstudents like Andres are clearly etched in these students’minds. As one student passionately shared:

It completely changed my views on whether kids shouldbe taught in Spanish if they are not fluent in English.Before doing the case study, I felt that if a child couldn’tspeak English he would eventually catch on ifmainstreamed in an English-speaking class. I neverrealized how severe of an impact it could have on a child.It made me realize how necessary it is to have a bilingualeducator in school to help kids like Andres.

DISCUSSIONOverall, pre-service teachers and instructors were positive

about the usefulness of the MUSE module to teach and learnabout the special education referral process. One instructorindicated that the MUSE case was the activity with greatest

significance in her semester-long course. While this statementmay be an extremely favorable assessment, previousinstructors using the module with different students (N=127)in three other courses found the MUSE case to be similarlybeneficial as an instructional tool (Ochoa et al., 2001).Perhaps the multimedia components of the module and thefact that pre-service teachers interacted with authenticmaterial (e.g., they see Andres in the playground, viewexamples of his work, and hear information about him fromhis teacher and family advocate) were uniquely salientcompared to text-based non-PBL cases.

In addition to the benefits of the multimedia componentsthat seem to bring a realistic flavor to the special educationreferral process, pre-service teachers made repeated referencesto the benefits of the activities within each phase of theMUSE module. Overall, comments from students about themodule’s value for their learning relates to the opportunity toengage in a real process of solving an educational issue withina group. Students seemed to find benefit in the process ofworking within a group to assess the problem at hand and toarrive at a decision. In fact, one of the most often-notedproblems students indicated they encountered was coming toa consensus about the nature of the target student’seducational problems in the special education referral processactivity. When queried about the way the group resolved thechallenges, the most common response from the participantswas that the group talked about their opinions until theycame to an agreement. From an instructional point of view,the fact that student teams encountered such a problem isexactly in line with the aim of the PBL process and theirsolution to discuss and make a group decision was what themodule’s developers anticipated in the design of the moduleand its activities.

Another aspect of the MUSE module that seems to holdvalue for students was the open-ended possibilities ofsolutions. Informal observations of students working with theMUSE case suggested that the task of having to articulatetheir opinions about what they believe was right for Andresand hearing others make similarly well-articulated argumentsfor other possibly correct answers was valuable for them asfuture teachers. It was this process of hearing others’ opinionsand having to compromise and learn to disagree with theirgroup peers that allowed pre-service teachers a preview ofwhat they will encounter in their future careers.

An important instructional consideration when using thePBL approach, and the MUSE case, in particular, is theallocation of sufficient time for debriefing or putting closureon the case. As indicated previously, many students viewedthe simulation as sufficiently realistic to treat Andres like hewas real and their interactions with their IEP members weredescribed as “like being on Andres real team.” Thesecomments suggested that the pre-service teachers’ level of

Table 6.Stage 4 Thematic Coding for Interview Responses

Participant PBL Impact Technology Overall Referral on Learning Issues Experience

Student 1 19 3 9Student 2 16 4 15Student 3 7 2 12Student 4 23 4 7Student 5 9 0 16Student 6 9 0 5Instructor 1 33 5 5Instructor 2 25 7 6



engagement in this referral process unit was beyond thetraditional engagement in class activities. The MUSE caseseemed very real to the participants. It may have been that thetime students spent on the case and the energy they expendedcompleting the simulation had, in a very real sense, created inthe users’ minds a sense of ownership for Andres’ situation.

In conclusion, instructors and students viewed theproblem-based learning module as a valuable instructional toolthat facilitated the application of content knowledge of thespecial education referral process. The multimedia aspects ofthe module and the nature of the real-life nature of groupactivities were highlighted as significant educationalcomponents of the module. The information gathered from theinterviews conducted with students and their instructors whoused the multimedia module will serve as a platform fromwhich to continue to study its impact on student learning.

REFERENCESAlbanese, M. A., & Mitchell, S. (1993). Problem-based learning:

A review of literature on its outcomes and implementationissues. Academic Medicine, 68, 52-81.

Albion, P. & Gibson, I. (2000). Problem-based learning as amultimedia design framework in teacher education. Journalof Technology and Teacher Education, 8, 315-326

Artiles, A. J., & Trent, S. C. (1994). Overrepresentation ofminority students in special education: A continuing debate.The Journal of Special Education, 27, 410-437.

Baca, L., & Valenzuela, J. S. (1998). Background and rationale forbilingual special education. In L. M. Baca & H. T. Cervantes(Eds.), The bilingual special education interface (pp. 2-25).Upper Saddle River, NJ: Prentice Hall.

Bay, M., & Lopez-Reyna, N. (2000). Preparing future bilingualspecial educators: The lessons we’ve learned. TeacherEducation and Special Education, 20, 1-10.

Bogdan, R. C., & Biklen, S. K. (2001). Qualitative research foreducation: An introduction to theory and methods.Needham Heights, MA: Allyn & Bacon.

Boud, D., & Feletti, G. (Eds). (2001). The challenge of problem-based learning. London: Kogan Page.

Denzin, N. K., & Lincoln, Y. S. (2000). Introduction: Thediscipline and practice of qualitative research. In N. K.Denzin & Y. S. Lincoln (Eds.), The handbook of qualitativeresearch (2nd ed., pp. 1-29). Thousand Oaks, CA: SagePublications, Inc.

Doucet, M. D., Purdy, R. A., Kaufman, D. M., Langille, D. B.(1998). Comparison of problem-based learning and lectureformat in continuing medical education on headachediagnosis and management. Medical Education, 32, 590-596.

Dunn, L. M. (1968). Special education for the mildly retarded: Ismuch of it justifiable? Exceptional Children, 23, 5-21.

Engel, C. E. (2001). Not just a method but a way of learning. InD. Boud & G. Feletti (Eds.), The challenge of problem-basedlearning (2nd ed., pp.23-33). London: Kogan Page.

Fitzgerald, G. E., & Semrau, L. P. (1996). Hypermedia and directinstruction: Do the paradigms fit? A demonstration ofclassroom observation skills. Education and Treatment ofChildren, 18, 348-59.

Gallegos, A., & McCarty, L. L. (2000). Bilingual multicultural specialeducation: An integrated personnel preparation program.Teacher Education and Special Education, 23, 264-270.

Gerber, M. M., English, J., & Singer, G. S. (1999). Bridgingbetween craft and academic knowledge: A computersupported, problem-based learning model for professionalpreparation in special education. Teacher Education andSpecial Education, 22, 100-113.

Glasner, B. G., & Strauss, A. L. (1967). The discovery of groundedtheory: Strategies for qualitative research. New York: Aldine.

Grossman, H. (1998). Ending discrimination in specialeducation. Springfield, IL: Charles C. Thomas, LTD.

Hallahan, D. P., & Kauffman, J. M. (2003). Exceptional learners:Introduction to special education (9th ed.). NeedhamHeights, MA: Allyn & Bacon.

Individuals with Disabilities Education Act of 1997, Pub. L. No.101-476 x 300.308 (1997).

Knotek, S. (2003). Bias in problem solving and the social processof student study teams: A qualitative investigation. TheJournal of Special Education, 37, 2-14.

Langone, J., Malone, D. M., & Clinton, G. N. (1999). The effectsof technology-enhanced anchored instruction on theknowledge of preservice special educators. TeacherEducation and Special Education, 22, 85-96.

Leafstedt, J., Ochoa, T. A., & Gerber, M. M. (2000). Case III: Story ofAndres [Web-based software]. Santa Barbara: CASELINK, Universityof California Santa Barbara. Retrieved May 21, 2003, fromhttp://www.caselinks.education.ucsb.edu/caselink/case3/intro.html

Llagas, C., & Snyder, T. D. (2003). Status and trends in theeducation of Hispanics (NCES Publication No. 2003-008).Washington, DC: U.S. Government Printing Office.

Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraintson multimedia learning: When presenting more materialresults in less understanding. Journal of EducationalPsychology, 93, 187-198.

Norman, G. R., & Schmidt, H. G. (1992). The psychologicalbasis of problem-based learning: A review of the evidence.Academic Medicine, 67, 557-565.

Ochoa, T. A. (2003). Bilingual special education. In C. J. Ovando,V. P. Collier, & M. C. Combs (Eds.), Bilingual and ESLclassrooms: Teaching in multicultural contexts (3rd ed., pp.358-378). Boston: McGraw Hill.

Ochoa, T. A., Gerber, M. M., Leafstedt, J. M., Hough, S., Kyle, S.,Rogers-Adkinson, D., & Kumar, P. (2001). Web technologyas a teaching tool: A multicultural special education case.Educational Technology & Society, 4(1), 50-60.

Ochoa, T. A., Vasquez, L. R. & Gerber, M. M. (1999). New generation of computer-assisted learning tools forstudents with disabilities. Intervention in School and Clinic,34, 251-254.

43


Parette, P., VanBiervliet, A., & Hourcade, J. J. (2000). Familycentered decision making in assistive technology. Journal ofSpecial Education Technology, 15 (1), 45-55.

Schwartz, D. L., Vye, N. J., Moore, A., Petrosino, A., Zech, L.,Bransford, J. D., & The Cognition and Technology Group atVanderbilt (1998). Doing with understanding: Lessons fromresearch on problem- and project-based learning. TheJournal of the Learning Sciences, 7, 271-311.

Shore, M. A. & Shore, J. B. (2003). An integrative curriculumapproach to developmental mathematics and the healthprofessions using problem based learning. Mathematics andComputer Education, 37, 29-38.

Solorzano, R. W., & Solorzano, D. G. (1999). Beginning teacherstandards: Impact on second-language learners andimplications for teacher preparation. Teacher EducationQuarterly, 26, 37-70. Retrieved August 21, 2003, fromhttp://www.teqjournal.org/sample_issue/article_3.htm

Strauss A. I., & Corbin, J. (1990). Basics of qualitative research:Grounded theory perspectives and techniques. Beverly Hills,CA: Sage.

Trent, S. C., & Artiles, A. J. (1998). Multicultural teachereducation in special and bilingual education: Exploringmultiple measurement strategies to assess teacher learning.Remedial and Special Education, 19, 2-6.

Tyler N. & Smith, D. D. (2000). Welcome to the TESE specialissue: Preparation of culturally and linguistically diversespecial educators. Teacher Education and Special Education23, 261-263.

U.S. Census Bureau (2000). U.S. Hispanic population Census2000. Retrieved August 21, 2003, from http://www.census.gov/pubinfo/www/hisphot1.html

Vernon, D. T. A., & Blake, R. L. (1993). Does problem-basedlearning work? A meta-analysis of evaluative research.Academic Medicine, 68, 550-563.

Watson, P., Fitzgerald, G. E., & Semrau, L. P. (1999). The virtualresources center in behavioral disorders: Dissemination andevaluation of instructional supports via the World Wide Web(Information Resources 019665). Washington, DC: U.S.Department of Education. (Eric Document ReproductionService No. ED432295).

Theresa A. Ochoa is Assistant Professor of SpecialEducation at Indiana University. Mary L. Kelly is a doctoralstudent in Special Education at Indiana University.Shannon Stuart is Assistant Professor and Coordinator ofthe Autism Specialist Certificate at the University ofWisconsin-Whitewater. Diana Rogers-Adkinson is AssociateProfessor and Coordinator of the Emotional DisordersProgram at the University of Wisconsin-Whitewater.

The authors thank Michael M. Gerber and George Singerat the University of California at Santa Barbara forpermission to use the CASELINK special education module,the students who participated in the study, and Ms. AngelaBruick who conducted all interviews of students andinstructors.

Address correspondence to Theresa A. Ochoa, IndianaSchool of Education, W.W. Wright Building 3222, 201 NorthRose Avenue, Bloomington, IN 47405-1006. Email to:[email protected].

Ochoa et. al.



APPENDIX ALearning and Satisfaction Survey

For the statements below, indicate the level of agreement or disagreement, or satisfaction or dissatisfaction, by circling the numberthat best expresses what you think about the statement. Your replies to these statements can range from strongly agree (1) tostrongly disagree (7).

SA SD

1. All educators need to know about the special education referral process. 1 2 3 4 5 6 7

2. I do not need to learn about the special education referral process because I am a general educator and don’t need this information. 1 2 3 4 5 6 7

3. Computer-mediated technology is useful for learning about special education. 1 2 3 4 5 6 7

4. The MUSE Problem was useful for learning about the special education referral process. 1 2 3 4 5 6 7

5. The MUSE Problem was useless and I did not learn about the special education referral process from it. 1 2 3 4 5 6 7

6. Other classes I take in the School of Education use similar computer-supported PBL cases. 1 2 3 4 5 6 7

7. Compared to other classes, I liked using the MUSE Problem to learn about students like Andres who have English language limitations & academic deficits. 1 2 3 4 5 6 7

8. Other classes I have also use cases or vignettes of students to illustrate a point but they don’t use computer supported PBL problems. 1 2 3 4 5 6 7

9. Andres’ simulation taught me about what to do with student who do not speak English and have learning difficulties. 1 2 3 4 5 6 7

10. I disliked Andres’ simulation and I don’t think it will have any relevance to the types of cases I will face in my class. 1 2 3 4 5 6 7

11. I liked Andres’ simulation but I don’t think it has any relevance to the types of problems I will face as a teacher. 1 2 3 4 5 6 7

12. I liked the video clips in Andres’ case 1 2 3 4 5 6 7

13. I liked the still pictures in Andres’ case. 1 2 3 4 5 6 7

14. I liked the group work in Andres’ case. 1 2 3 4 5 6 7

15. I like my instructor and she used Andres’ case well. 1 2 3 4 5 6 7

16. I like my instructor but I don’t think she used Andres’ case well. 1 2 3 4 5 6 7

45Ochoa et. al.


APPENDIX BMUSE Case Implementation Interview Protocol

Student Interview Questions

1. What do you remember most about Andres’ case?

2. Describe your overall experience with the MUSE case.

3. Describe your groups’ response to the MUSE case.

4. What challenges did you experience using the MUSE case?

5. What recommendations would you make the next time your instructor uses the case?

6. What were some of the difficulties you experienced using the MUSE case?

7. What modifications did you/your group make to the MUSE case? Why?

8. How useful was the MUSE case for learning about the special ed referral process?

10. Describe how you/your group interfaced with the computer.

Instructor Interview Questions

1. Describe your overall experience with the MUSE case. Challenges? How’d you resolve?

2. Describe your students’ response to the MUSE case.

3. Describe how your students interfaced with the computer.

4. Describe your experience with individual versus group work. What worked? Challenges?

5. What recommendations would you make to other instructors about PBL?

6. How did your students respond to PBL? What aspects impacted student learning?

7. What modifications did you make to the MUSE case? Why?

8. How useful was the MUSE case for teaching about the special education referral process?

9. Assuming you will use the MUSE again, what improvements can/should be made?

10. Anything else I have not asked you want me to convey to the developers of MUSE?

46


47

Assistive Technology Associate Editor’s Column

Tamarah M. Ashton, California State University, Northridge

Assistive Technology Teams: A Model forDeveloping School District Teams

Guest Columnist: Deborah A. NewtonThe Individuals with Disabilities Education Act (IDEA),

the federal law that provides for a free appropriate publiceducation for all children with disabilities, was amended andreauthorized in 1997. The amendments are notable forincluding assistive technology (AT) as one of the specialfactors that must now be considered by the team responsiblefor developing individualized education programs (IEP) for allstudents receiving special education services. In mandatingthe consideration of AT, the law echoes the belief that it hasthe “potential for enhancing access, inclusion, productivity,and the quality of life of individuals with disabilities” (Derer,Polsgrove, & Rieth, 1996, p. 62-63).

IDEA mandates the provision of both AT devices andservices. Assistive technology devices are defined as “any item,piece of equipment, or product system, whether acquiredcommercially off the shelf, modified, or customized, that isused to increase, maintain, or improve functional capabilitiesof individuals with disabilities” (20 U.S.C. § 1401(1)). ATservices are defined as “any service that directly assists a childwith a disability in the selection, acquisition, and use of an ATdevice” (20 U.S.C. § 1401 (2)). AT services include trainingand technical assistance for students who use AT, as well asothers substantially involved in the major life functions of thechild (e.g., family members, teachers, other educationalpersonnel).

The inclusion of training and technical support in thedefinition of AT services mirrors the importance placed onthese services by researchers and other professionals in thefield. Long, Huang, Woodbridge, Woolverton, and Minkel(2003) stated “. . . if the child is to be truly successful usingthe technology, the delivery day actually marks just thebeginning. . . . implementation must begin with training . . .on how to use the product” (p. 281). Day and Huefner (2003)assert “training of all significant persons is also pivotal to thesuccess of the student’s AT goals” (p. 31). McGregor andPachuski (1996) found, “To make assistive technology a viablesupplemental aide and service that assists students toparticipate in general education classrooms, teachercompetence in its use and the availability of support arecritical concerns” (p. 13).

Despite clear needs for competency with AT use andreadily available technical support and training, the reality isthat many special education teachers and other educationalpersonnel have no expertise in this area. Pre-service training

programs often do not include courses, or even class sessions,devoted to AT (Todis, 1996). In-service educators may be nomore informed or skilled in its use. In a three-state study,Derer at al. (1996) found that knowledge and training wereamong the major teacher-identified barriers to using assistivetechnology.

Currently there is an interesting paradox concerning ATconsideration and the provision of AT services within theschool setting. The AT needs of over six million studentseligible for special education (OSEP, 2002) must be considered,but many school districts lack educational professionals whoare knowledgeable and trained in this area. These districtslack personnel who can adequately consider AT needs orprovide the training and technical assistance needed foreffective implementation.

IDEA reflects the recognition that a gap exists betweenthe ability level of educational personnel and the level ofexpertise needed to meet the AT needs of students withdisabilities. Accordingly, Subpart C, Services, requires eachstate to have a Comprehensive System of PersonnelDevelopment (CSPD) and mandates that states describe theirstrategies to:

. . . address the identified needs for inservice and pre-service training to ensure that all personnel who workwith children with disabilities (including bothprofessional and paraprofessional personnel who providespecial education, general education, related services, orearly intervention services) have the skills and knowledgenecessary to meet the needs of children with disabilities.IDEA does not specify how the CSPD requirements are to

be met, i.e., what should be taught or what strategies shouldbe used. One southern state used CSPD funds to train ATteams with members from various local education agencies(LEAs). This paper details the training of one CSPD-fundedAT team. The training method is offered as a model for otherschool districts. The initial and on-going professionaldevelopment activities employed to foster a sense of teamownership and responsibility, as well as build competency inAT knowledge and skills, are presented. Lastly, informationregarding expanded AT services is shared.

Forming a Multi-Disciplinary TeamCSPD funds were provided to regional AT centers

throughout the state for the development of AT teams. Staffmembers at each regional center were responsible forrecruiting participants from LEAs and for providing training,support, and mentoring services to those who responded torecruitment efforts. LEAs were responsible for providing

48


release time for team member training and for supporting ATteam members’ professional development. The LEA also hadto agree to utilize the team within the district as an ATresource.

This large, rural school district was the only district tomake a commitment to participate in the CSPD-fundedtraining offered by the staff of one of the AT centers. Thedirector of special education services for the district selectedfive staff members to comprise an AT team and participate inthe training. Two of the AT team members were speechlanguage pathologists, one was an occupational therapist, onewas a certified occupational therapy assistant (COTA), andone member was a teacher of the hearing impaired. Thisconformed to recommendations that AT teams have amultidisciplinary composition (QIAT, 2003). Each teammember had some knowledge of AT as it related to her specificfield, but none could be considered an AT expert. The COTAleft the district at the end of the team’s first year and thevacancy on the team was not filled. The team continued withthe four remaining members, in association with thetrainer/consultant.

Developing a Service Delivery ProcessThe initial training for the team focused on developing

effective procedures for delivering assistive services within thedistrict, rather than on specific devices. Thetrainer/consultant believed concentrating on meeting theneeds of students had to be the first priority. In her opinion,knowledge about AT tools could come later. She elected to usea case study approach, centering on one particular student inthe district, to structure the first day. The trainer/consultantreasoned that if the team could decide on services andprocesses needed to meet the AT needs of this particularstudent, it could use that information as a starting point todetermine the AT needs of other students.

Utilizing this approach, the team developed a preliminaryAT service delivery process (SDP) that was refined thefollowing day. The SDP that evolved was an eight-step processcomprised of (a) referral/screening, (b) preliminaryassessment, (c) assessment review, (d) diagnostic trial withtraining provided for educators who would be using the ATwith the student, (e) review of trial use, (f) acquisition of theAT for the student, (g) intervention/integration of the AT, and(h) follow-up.

During the third and fourth days of training, the teamidentified and developed forms and related procedures tosupport the service delivery process. The trainer/consultantpresented a variety of sample forms for review. From theseforms, team members selected and modified the ones theybelieved would facilitate the delivery of AT services withintheir district (e.g., AT assessment referral forms, studentinformation forms). Because they were insiders, they could

utilize what they knew about the workings of their district toestablish procedures for such things as initiating referrals anddistributing and collecting student information forms thataligned with special education procedures already in placewithin the district.

Developing AT Knowledge and SkillsAfter the service delivery process was established,

attention and training focused on development of teammembers’ AT knowledge and skills. As part of the schooldistrict’s commitment to AT professional development, itfinanced the team members’ attendance at Closing The Gap(CTG), a major AT conference. At CTG, team members wereintroduced to a vast array of the most current AT devicesthrough vendor exhibits and demonstrations. In the myriad ofconference sessions, team members learned how others wereutilizing and implementing the technology. Attendance atCTG built a solid, beginning knowledge base.

This knowledge base was built on throughout the firstyear as the trainer/consultant provided professionaldevelopment experiences during weekly team meetings. Todevelop team members’ ability to effectively apply theirdeveloping knowledge, the trainer/consultant arrangednumerous opportunities to directly model AT service deliveryin authentic situations. The AT team accompanied her as sheprovided direct services to students or consulted withclassroom teachers. In addition to modeling, thetrainer/consultant purposefully drew team members into theprocess to gain experience and confidence.

Primary responsibility for service delivery was graduallyshifted to the AT team; members began to take the lead inproviding AT services. As a result, during the first year, eachclassroom visit or assessment was a knowledge and skillbuilding opportunity for all team members. They had anopportunity to hone their skills and build their confidence ina risk-free manner.

Increased services. Prior to the formation of the AT team,these services within the district were provided by thetrainer/consultant through a contract for the equivalent of oneday per week of her time. This afforded her enough time toprovide assessment services to the neediest students withinthe district, but not as much time as she would have liked forsupport services. During the year just before the formation ofthe team, she provided AT services for 35 students.

Teachers throughout the district became familiar with theavailability of the AT team as members provided services andreceived on-going mentoring during their first year. Asawareness of the team increased, so did referrals and calls forassistance. By the end of the team’s second year, the numberof students receiving AT services increased by 85%.Accompanying the increase in the number of students was anincrease in training, technical support, and other services

49Ashton


team members provided to facilitate AT implementation.In addition to direct services to students, team members

provided on-the-spot training for teachers and staff memberswhen they delivered or installed new AT hardware orsoftware, and if necessary, additional training sessions werescheduled. Team members contacted students and teachers tocheck on utilization, progress, and appropriateness of the ATas specified in their service delivery process. As teammembers became aware of AT that had been stockpiled inindividual classrooms, they provided consultation andtechnical support so teachers could use these items moreeffectively or begin using them for the first time. Teammembers offered formal AT professional developmentopportunities for faculty and staff on district-wideprofessional development days.

The team has assumed responsibility for the distributionand collection of AT at the beginning and end of the schoolyear. This has especially impacted students who transitionfrom one school to another. Team members delivered AT in atimely manner at the start of the new school year; studentsdid not have to wait weeks or months before teachersdiscovered they were AT users. Of course, along with ATdelivery came the training and technical support the teachersneeded.

SummaryInitial training activities for this assistive technology

team focused on meeting students’ needs rather than on thetechnology itself. This student- and service-centered focus ledto the creation of a service delivery process that now guidesthe work of an enduring, effective team. Four factors enablethe team to provide quality AT services within the SDP. First,they are a multi-disciplinary team so each membercontributes a particular expertise and perspective. Second,they have a strong knowledge base that began with and is keptcurrent by attending major AT conferences. Third, ongoingmentoring provided team members with excellent modeling,support, and encouragement. Last, but not least, the team is

more than just a group of people; the members are supportiveand encouraging of each other and committed to empoweringstudents through the use of assistive technology.

REFERENCESDay, J. N., & Huefner, D. S. (2003). Assistive technology: Legal

issues for students with disabilities and their schools.Journal of Special Education Technology, 18(2), 23-34.

Derer, K., Polsgrove, L., & Rieth, H. (1996). A survey of assistivetechnology applications in schools and recommendations forpractice. Journal of Special Education Technology, 13(2), 62-80.

Individuals with Disabilities Education Act Amendments of1997, 20 U.S.C. § 1400 et seq. (1997).

Long, T., Huang, L., Woodbridge, M., Woolverton, M., & Minkel,J. (2003). Integrating assistive technology into an outcome-driven model of service delivery. Infants and Young Children,16, 272-283.

McGregor, G., & Pachuski, P. (1996). Assistive technology inschools: Are teachers ready, able, and supported? Journal ofSpecial Education Technology, 13(1), 4-15.

Office of Special Education Programs. (2002). Twenty-fourthannual report to congress on the implementation of theIndividuals with Disabilities Education Act. Washington,DC: U. S. Department of Education.

QIAT Consortium. (2000). Quality indicators for assistivetechnology services. Retrieved March 8, 2004, fromhttp://sweb.uky.edu/~jszaba0/QIAT.html

Todis, B. J. (1996). Tools for the task? Perspectives on assistivetechnology in educational settings. Journal of SpecialEducation Technology, 13, 49-61.

Deborah Newton is a faculty member in Department ofSpecial Education and Reading at Southern Connecticut StateUniversity, New Haven.

Associate Editor Note: The author participated in thetraining of the AT team for a portion of its first year.Subsequent to this, data related to the team were collectedand are the basis for the author’s doctoral dissertation.Information contained is this article is a result of that study.

50

Teacher Education Associate Editor’s Column

Sean Smith, Ph.D., University of Kansas

Using Technology to Provide New TeacherSupport: A University/District CollaborativeProject

Guest Columnist: Susan D’Aniello, University ofNevada Las Vegas

INTRODUCTIONTechnology, specifically Internet-based resources, is

increasingly being used to support the ongoing developmentof novice teachers working in the field. In this column, welearn about a collaborative project between the University ofNevada Las Vegas and the Clark County School Districtfocused on beginning teacher’s need for ongoing support andassistance through collaboration of university/districtpersonnel. This column provides a literature review of newteacher follow-up studies and the use of technology in newteacher support studies. Additionally, how a university anddistrict used the Internet to facilitate a collaborative newteacher support project is described.

According to the National Council for Accreditation ofTeacher Education (NCATE, 2001), teacher preparationprograms must collect data from a variety of sources onteacher candidates’ performance at each stage of theirprogram, including the first years of teaching followinggraduation. Additionally, the Council for Exceptional Children(CEC, 1998) requires evidence of arrangements with districtsto provide assistance to graduates during their first year ofteaching. Data are to be obtained from graduates and othermembers of the community for the purpose of improving thequality of the teacher preparation program. Theserequirements seem reasonable in an evaluation process,however, a review of the literature found few published follow-up studies suggesting that additional research in the area ofbeginning special education teacher follow-up is an area ofneed. Fortunately, the growth of the Internet and Internet-based applications offered a medium in which colleges ofeducation and recent graduates can better interact tounderstand novice teacher needs and related supports.

This column provides an overview of how the Internethas been used to enhance teacher preparation in and out ofthe higher education environment. Additionally a descriptionof a collaborative project between The Student SupportServices Division of Clark County School District (CCSD)and the Department of Special Education of the University ofNevada Las Vegas (UNLV) will be summarized withdiscussion and future goals.

Technology in New Teacher Support StudiesSeveral benefits have been recognized when the Internet

was used to deliver instruction and/or facilitatecommunication and collaboration among students (Karayan& Crowe, 1998; Murphy, Drabier, & Epps, 1998). Benefitsincluded the ability to facilitate equal access for interaction,promote collaboration, promote learner reflection, supportlearner interaction, expand courses to those in remote distantareas, provide opportunities for collaboration at times andplaces more convenient to the student, and expand thestudent’s educational experiences beyond the classroom.Challenges associated with online instruction andcommunication included the chance of unequal access tohardware and software, creation of a steep learning curve forsome students, absence of comfort associated with previoustext-based communication, and the need to manage largeamounts of information and communication dialogue(Murphy, Drabier, & Epps, 1998).

The quality and skills of the university faculty whofacilitated the online courses are essential components thatdirectly impact the quality of online instruction (Angulo &Bruce, 1999). Thus, institutions of higher education mustoffer their faculty support in appropriate use of the Internetfor instructional purposes to minimize challenges forlearners. Additionally, systems that used the Internet as amethod of expanding communication and collaborationamong participants must incorporate components tofacilitate learner interaction and collaboration. For example,situations must exist that require responses to questions andcomments from each participant. Attention to strategies thatestablish trust among participants also increasedcommunication and collaboration in online courses(Thomas, Clift, & Sugimoto, 1996).

There is evidence to support the use of the Internet in thedevelopment of a system of support for beginning teachers.Participants in online collaborative groups reported that theexperience expanded their knowledge of their peers’experiences, gave them a broader sense of school cultures, andassisted in application, critique, and reflection of their ownknowledge and skills. Internet communication has proveneffective in the reduction of feelings of isolation, and providea safe, nonjudgmental environment for beginning teachers todiscuss issues related to learning to teach. Participants inInternet facilitated teacher preparation programs report thatthe support system helped them to be successful in their firstyear of teaching (Boehmer & Waygh, 1997; Lan, 1999;Meehan & Burns, 1997; Schlaga, Trathen, & Blanton, 1996).

51Smith


DISTRICT/UNIVERSITY COLLABORATIVE PROJECT

BackgroundClark County School District (CCSD) is the sixth largest

public school district in the United States and encompasses allof Clark County, Nevada, which covers 7,910 square miles.CCSD provides education for students in metropolitan LasVegas, and many outlying communities and rural areas. In 2001CCSD had an enrollment of approximately 231,000 studentswith about 25,000 students who received special educationservices. Enrollment has grown approximately 6% annually forseveral years. Consequently, approximately 10 new schoolsopen each year. About 1,775 licensed special education teachersprovide services for students with disabilities (CCSD, 2003).The recruitment and retention of teachers, especially specialeducation teachers, is an ongoing need.

The University of Las Vegas Nevada (UNLV) had anenrollment of 24,965 students for the 2001-2002 school year(UNLV, 2003). Total enrollment is also growing by about 6%annually. In 2001-02 the Department of Special Educationreported 192 graduates with the requirements necessary toobtain a Nevada license to teach special education (T. Pierce,personal communication, May 5, 2003). A majority of thesegraduates seek and obtain employment in CCSD.

Over a five-year period (1997-2002), CCSD and UNLVworked collaboratively to increase the number of specialeducation graduates through a variety of teacher preparationprograms. In 1990-91, UNLV graduated 26 special educationteachers. Ten years later, 192 special education teachersgraduated (T. Pierce, personal communication, May 2, 2002).The numbers suggest that these collaborative efforts haveresulted in an increased number of special education teachers.

In 2001, Student Support Services Division of CCSD andthe Department of Special Education of UNLV entered into acollaborative agreement to augment the collaborative teacherpreparation projects with a beginning teacher support project,AppleTREE (Teaching Resources for Effective Education). Thepurpose of the agreement was to support teachers during theirfirst year of service as special education teachers in CCSD.

Collaborative ProjectThe use of the Internet to provide a system of support for

beginning teachers was chosen. A support system facilitatedthrough the Internet made it possible to expand supportacross large distances as well as increase opportunities forinteraction for a large number of beginning teachers. Theschool district provided a part time director for the teacherassistance project through UNLV’s Department of SpecialEducation and UNLV provided an office, materials, andclerical/technical support. All beginning teachers in CCSDwere provided Internet access that was necessary to

participate in the project. All participants had access to theInternet through the district if a personal system wasunavailable.

During pre-student teaching seminars, students wereprovided a short informational handout and presentationabout AppleTREE (see www.unlv.edu/faculty2/daniello). Nearthe end of the student teaching semester, student teacherswere provided specific information about the project. At thesame time a survey was completed. The survey askedprospective new teachers to identify skill areas in which theyfelt additional assistance would be beneficial during theirupcoming first year of teaching. The survey was completed by43 student teachers during the spring and summer semestersof 2002.

The survey consisted of one question requiring studentteachers to select from a list of skills adapted from CEC’s(1999) common core of skills essential for all beginningspecial education teachers. Each informant was asked tocheck the skill areas in which they desired more assistance.Table1 contains a list of skills beginning with those receivingthe most checks to those receiving the least. Additionally, thesurvey consisted of 4 open-ended questions designed toextend the understanding of the perceived needs ofprospective first year teachers.

Table 1.Skill Areas for which Beginning Teachers RequestedAssistance

Skill area Number of teachers requesting assistance for each skill area

Behavior management 33Individual Education Pan (IEP)/Individual Family Service Plan (IFSP) development/implementation 26

Assessment 22Learning strategies 18Assessment results interpretation 15Curriculum modifications 14Lesson plans 11Schedules 11Data collection/analysis 10Parent communication 9Transition services 9Inclusive activities 8Collaborative skills 7Guidance/direction of paraprofessional staff 7Procedural safeguards 6Assistive technology 6

52


Project ImplementationThe collaborative project was facilitated through three

main sources: a Web site specifically designed for beginningteachers, an Internet-based three-credit graduate course alsodesigned specifically for beginning teachers, and an onsitenew teacher seminar. The skill areas identified by prospectiveteachers were used to create informational sources on theproject’s Web site as well as content for instructionalobjectives and activities in the Internet-based universitycourse. The goals of the project were:

1. Provide first year teachers a supportive avenue tocollaborate and communicate among themselves aswell as with university and district personnel.

2. Provide first year teachers an opportunity to selfevaluate and reflect on teaching skills.

3. Provide first year teachers with current informationand resources.

4. Provide first year teachers with opportunities to extendtheir skills and knowledge.

The project’s Web site (see www.unlv.edu/faculty2/daniello) provided teachers information on skill areas identifiedby participants, a variety of resources, and an avenue tocommunicate with each other and university staff. Links wereprovided to UNLV’s Website and libraries. Students could alsoaccess the Internet-based courses directly from the Website bya link to UNLV’s e-learning provider, WebCT. The Web site wasmodified and updated on a consistent basis. First year teacherssubmitted informational bulletins that were posted on the site.These informational bulletins addressed topics of interestidentified by teachers.

The Internet-based graduate course offered via WebCTwas taught fall semester 2002. Seventeen students wereenrolled. Three dropped the class during the semester leavinga total of fourteen students who completed the course.

Attention was paid to findings in the literature regardingthe design and implementation of online courses (Angulo &Bruce, 1999, Thomas, Clift, & Sugimoto, 1996). Theinstructor was provided training and ongoing support in thedesign of online classes as well as technical support. Thecourse syllabi included required components that facilitatedactive learner interaction and collaboration. The instructorresponded to students’ questions, responses, and assignmentsin a timely manner in an effort to create a feeling of trust anddedication among students and instructor.

The Internet-based course again provided an avenue forcollaboration and interaction through structured andnonstructured opportunities. Structured communication andcollaboration was facilitated through mandatory weeklydiscussion questions. Students were required to respond toeach discussion question and the instructor provided feedbackand probing questions to student’s responses that facilitatedfurther discussion and analysis. For example, in one online

posting to the Discussion Forum, a first year teacher reflectedon a problem situation, shared the intervention strategy, andsuccessful outcomes with other first year teachers. Other firstyear teachers responded with similar situations, supportedthe teacher who posted the message, and elaborated withfurther discussion around the ever-popular topic of behaviormanagement.

Nonstructured communication was available throughWebCT ‘s private chat rooms. These chat rooms were onlyavailable to instructors and students enrolled in onlinecourses. The chat rooms provided a private venue to facilitateinformal discussion, collaboration, and relationship building.

Other Internet-based course assignments included self-evaluations of instruction, skill extension projects, Web siteinformational bulletins, and an Internet activity log. Allactivities were related to areas of need identified by the surveycompleted earlier by prospective new teachers. Someadditional topics were added as teachers identified new areasof need throughout the first few months of teaching. Allcourse requirements were included in the syllabus that wasposted on the WebCT site. In addition, a specific activityguide was provided for each individual assignment and postedin the course content/assignment section of the WebCTcourse.

Approximately two weeks before the semester ended amandatory two-hour after school seminar was scheduled aspart of course requirements. University and district staffcollaboratively presented information on the topics offunctional behavior assessments, behavior intervention plans,and procedural safeguards. All participants submittedevaluations anonymously. Through written feedbackparticipants indicated that the speakers and sessions wereinformative and relative to new teacher’s needs.

Project EvaluationAfter the course was completed and after final grades

were posted, participants were asked to complete anevaluation of the Internet-based graduate course and thesupporting project Web site. The purpose of the evaluationwas to determine the project’s overall strengths andweaknesses. The evaluation contained four open-endedquestions that asked participants to list ways the courseassisted them in their role as a new special education teacher,positive components of the course, areas needingimprovement, and reasons for encouraging or dissuadingfuture new teachers to take the class. Additionally, extendedinterviews were conducted with new teachers who hadparticipated in the project. Feedback was positive about theWeb site, Internet-based course, and the new teacher seminar.One suggestion for improvement was given in relationship tochat room discussion. One teacher felt that moreparticipation would have occurred via chat rooms if the chat

53Smith


room participation were a mandatory course requirement. SeeTable 2 for a summary of participant’s comments.

Discussion and Future ImplicationsThe new teacher support project received positive

feedback from its participants. The project components andobjectives were based upon information provided through aliterature review regarding online instruction andcommunication and a needs assessment completed byparticipants. Project evaluations and interviews indicated thatthe project was successful in meeting the needs of newteachers. In addition, it provided them a convenient avenue toparticipate in a university class while maintaining the busyschedule of a new teacher.

To enhance further participation, steps have been takento provide prospective new teachers with informationregarding the new teacher assistance project. First yearparticipants have visited and spoken at the student teacherseminars encouraging new teachers to take the Internet-basedcourse. Prior participants indicated that the new teachersupport project course and Web site were designed to helpnew teachers improve their skills and knowledge during thatcrucial first year of teaching. They emphasized that courserequirements complimented the activities of the new teacher.They also acknowledged that the benefits gained from theproject far outweighed the time and effort needed to complete

the activities. As the project enters the second year, 37 of 39students who will have completed their student teacherexperience by fall semester 2003 have indicated an interest inparticipating in the new teacher support project and plan toregister for the Internet-based class.

CONCLUSIONThe review of the literature indicated that teachers desire a

structured system of support during their first years of teaching.In addition, they have requested that this support system befacilitated through the collaboration of the school district anduniversity personnel. Additionally, the literature supports theuse of Internet-based systems to provide teachers with support,interaction, and collaboration. Participants indicated a highdegree of satisfaction and support for the technology facilitateduniversity/district collaborative project described in this article.Feedback will be used to further improve the project as the nextparticipants enter into the second year of implementation.

REFERENCESAndrew, M. D. & Schwab, R. L. (1995). Has reform in teacher

education influenced teacher performance? An outcomeassessment of graduates of an eleven-university consortium.Action in Teacher Education, 17(3), 43-53.

Angulo, A. J. & Bruce, M. (1999). Student perception ofsupplemental web-based instruction. Innovative HigherEducation, 24,105-125.

Table 2.New Teacher Evaluation and Interview Comments

CommentsAccess to other new teachers, it was nice to get their opinions and help.It was nice to see that other new teachers had the same questions and they didn’t seem so stupid when posted in the class discussion pages and chat rooms.More teachers would participate in chat room discussions if they were part of the course requirements.I liked being able to complete course requirements at times convenient for me rather than going to the university at a specified time.Access to other new teachers and well experienced instructor as well as teacher. She gave us valuable web sites and great information.It was a great class and couldn’t find two ways to improve.I absolutely would recommend this class to other first year teachers because the instructor directed us in the right way to find information.The communication and collaboration with other new teachers was great. It was exciting to finally meet people at the seminar that I had been talking with all semester.Valuable information was provided. Really, everything was so helpful.I feel more clued in to meeting the needs of my students.Thanks for your efforts.The course was wonderful. I always looked forward to checking the WebCT.Being a first year teacher is overwhelming. This course provided me support and it was helpful knowing I was not alone.All the assignments were things that helped me become a better teacher.I am still using the Internet resources. Thank you for including on the Website those provided by us.First year teachers should be required to take this course.I would have liked more information on data collection and analysis.I learned a lot about my teaching abilities and know I will do better next year.

54


Bland, S. J., & Hecht, J. B. (1997). One year later: Follow-up on aprofessional development school. Bloomington-Normal:Illinois State University. (ERIC Document ReproductionService No. ED430954)

Boehmer, R. F. & Waugh, M. L. (1997). Developing a distributedlearning community: Undergraduate education majors usethe Internet to engage in early teaching experiences in biology.Journal of Computing in Teacher Education 13, 7-15.

Clark County School District. (2002, March). Clark County SchoolDistrict: Facts and figures. Retrieved May 4, 2003, fromhttp://www.ccsd.net/news/geninfo/facts_figs/index.html

Council for Exceptional Children. (1998). What every specialeducator must know: The international standards for thepreparation and licensure of special educators (3rd ed.)Reston, Virginia: Author.

Council of Exceptional Children. (1999). Professional standards:Institutional and program requirements. RetrievedNovember 2, 2001, from http://www.cec.sped.org/ps/ps-req.html

Drummond, R. J. (1991). Beginning teachers: What they have tosay about their performance and preparation. Jacksonville:University of North Florida (ERIC Document ReproductionService No. ED340670)

Holste, D., & Matthew, D. (1993). Survey of 1991 teachereducation graduates conducted in May 1992. Champaign:University of Illinois Urbana. (ERIC DocumentReproduction Service No. ED364535)

Housego, B.E., & Badali, S. J. (1996). One year later: Beginningteachers revisit their preparation program experiences.Alberta Journal of Educational Research, 42, 378-394.

Karayan, S. & Crowe, J. A. (1997). Student perceptions ofelectronic discussion groups. T.H.E. Journal, 4, 69-71.

Kilgore, K., Ross, D., & Zbikowski J. (1990). Understanding theteaching perspectives of first-year teachers. Journal ofTeacher Education, 41, 28-38.

Lan, J. J. (1999, February). The impact of Internet-basedinstruction on teacher education: The “paradigm shift.”Paper presented at the annual meeting of the AmericanAssociation of Colleges for Teacher Education, Washington,D.C. (ERIC Document Reproduction Service No.ED428053).

Meehan, M. L., & Burns, R. C. (1997, March). E-mail survey ofa listserv discussion group: Lessons learned from surveyingan electronic network of learners. Paper presented at theannual meeting of the American Educational ResearchAssociation, Chicago. (ERIC Document ReproductionService No. ED411292)

Murphy, K. L., Drabier, R. & Epps, M. L. (1998). Interaction andcollaboration via computer conferencing. College Station,Texas A&M University. (ERIC Document ReproductionService No. ED423852)

National Council for Accreditation of Teacher Education. (2001).Professional standards for the accreditation of schools,colleges, and departments of education. Washington, D.C.:Author.

Rankin, W. (2000). A survey of course web sites and onlinesyllabi. Educational Technology, 40, 38-42.

Schlagal, B., Trathen, W., & Blanton, W. (1996). Structuringtelecommunications to create instructional conversationsabout student teaching. Journal of Teacher Education, 47,175-183.

Simpson, K. J., & Sandidge, R. F. (1994). Determining the successof teacher preparation by assessing what teacher educationgraduates know and are able to do. Lexington: University ofKentucky. (ERIC Document Reproduction Service No.ED378164)

Thomas, L., Clift, R. T., & Sugimoto, T. (1996).Telecommunication, student teaching, and methodsinstruction: An exploratory investigation. Journal of TeacherEducation, 46 165-174.

University of Nevada Las Vegas. (2003, May). Office ofInstructional Analysis and Planning Factbook. RetrievedMay 4, 2003, from http://www.unlv.edu/PAIR/IR/

Wilkerson, T. (1997). The preparation of teachers for Kentuckyschools: A survey of new teachers. Summary Report.Frankfort: Kentucky Institute for Education Research. (ERICDocument Reproduction Service No. ED447072)

55

CAST eReader version 3.0

Guest Reviewer: Michael J. Krikonis, CentralConnecticut State University

CAST eReader is a universally designed text-to-speechsoftware tool that supports users who have difficulty readingindependently. eReader can be used to help learners improvereading comprehension and increase reading pace. Thesoftware can be used by learners of any age; however,managing application settings without additional supportmay be difficult, especially for younger or less independentlearners.

eReader’s primary function is to read electronic files outloud to the user. It is a versatile application that supportsthree file types: HTML (internet or local files), RTF, and Daisy(Digital Audio Based Information System) documents.eReader will convert text to speech in both synthesized andhuman voices while presenting synchronous visual highlightsover the text as it is read. The learner can control thehighlighting function, which can be set to highlight individualwords or entire sentences and paragraphs.

The following minimum hardware and OS requirementsare needed to install and run eReader: Windows98/2000/ME/XP; Pentium 166 MHz (Pentium 133 MHz ifnot reading Web pages or HTML files); 32 MB of RAM (16MB if not reading Web pages or HTML files) ; 125 MB of freedisk space available (20 MB if not using Web readingcapability); Windows-supported sound card; 2 inch or largermonitor with 800 x 600; Internet Explorer 4.x or higher (onlyfor reading Web pages or HTML files); or, MAC OS 7.5 - 9.x.(does not support Web browsing and Daisy documents);68030 processor; 12 MB of RAM; 2 MB of free disk spaceavailable (8 MB if Plaintalk is not installed); 12 inch monitorwith 256 color support.

An extensive amount of product support is availablebeginning with the eReader Starter File. This introductorydocument launches by default and is helpful when gettingstarted with the eReader, but can be disabled or replaced, ifdesired. The Starter File provides a quick overview of thesoftware and instructions for reading the different types offiles. Additional support is available through the Help menu.eReader Help is well-organized and addresses many questionsthat frequently are asked by users. The Help file alsoreferences websites for additional support, includingMicrosoft’s troubleshooting website, Cast’s eReader Web site,and Daisy’s Web site. This file also provides informationabout how to use additional peripheral equipment to digitizedocuments for use in eReader.

Instructors who plan to use eReader will need to read theuser manual and can expect to spend an hour or two to learnthe software and become familiar with the interface. Manytext to speech applications run simply by turning the softwareon, but the many features found in eReader make using itmore involved. Instructors will find that specific tools andfunctions are available for each file type that may be viewed.For example, a Daisy book read with a human voice will onlysupport synchronous highlighting of paragraphs rather thansingle words. To benefit from synchronous highlighting ofindividual words, the user must enable a synthetic voice andset application preferences correctly. Another example is thebook-marking feature, which is only available for RTF files. Fornew users, remembering when certain features are availableand when they are not can be bewildering. Additionally,instructors will not find tools for data collection and progressreporting; however, the book-marking tool can mark a locationto return to when a file is reopened. Instructors will alsoappreciate eReader’s printing capabilities, which can be usefulto provide a hard copy of the file being read.

Learners can customize eReader settings to match theirindividual learning styles and personal preferences. TheChange Skin feature allows a user to customize the theme ofthe application, and learners can select from either a limitedor full toolbar. The toolbar commands include font size, audiolevel, and a split screen view that opens a second windowwhere a user can write and listen to notes. Learners canfurther customize eReader by adjusting the amount of texthighlighted as it is spoken (word, sentence, paragraph) andcan set the application to automatically stop or continuereading aloud after a sentence or paragraph is completed.Learners can also adjust the type, pitch and speed of thesynthesized voice.

eReader’s strength is in its versatility. For example,toolbars and speech settings can be customized to supportmany learning styles and individual needs, and eReader canread three different file formats: HTML, RTF, and Daisy.eReader continues to stand out among the competition withDaisy support, the Starter file, and split screen functionality.

The DAISY 2.02 file support is worth highlighting becauseit is an industry standard that uses human voice on MP3 files.The benefit of the human voice is that it provides the user witha true reading experience where the user can identify with theemphasis and tone. The human voice is a welcome changefrom the synthesized voice associated with most readerapplications. For added flexibility, eReader also allows Daisydocuments to be read by a synthetic voice. Daisy files areavailable on the web and many can be downloaded for free.

Book and Software Review Associate Editor’s Column

Barbara L. Ludlow, Ed.D., West Virginia University & John D. Foshay, Ed.D., Central Connecticut State University

56


The Starter file, a document that gives the user alaunching pad to begin from is another strong feature ofeReader. This file will load when the application is started andprovides helpful information to support new users in gettingstarted. The experienced user can customize the starter file tomeet specific needs of students and teachers; for example, ateacher can create a starter file with specific notes and linksto reading assignments, and / or web sites.

The split screen functionality allows a user to view theapplication in two windows. One window contains thedocument to be read and the other contains an editable textfield that can be read, saved and printed. This capabilityallows a user to type notes as s/he listens to a document, withthe option to read the text either as the words are typed or asan entire block of text.

Although eReader is an application with obviouseducational potential, there are areas for improvement. Thegreatest frustration stems from the interaction between thespeech-enabled menus and buttons and the menucommands. For example, a user can inadvertently cancel theRead Highlighted Text command after the Read Menudisappears because the button positioned below the mousepointer is identified and read by the synthesizer. A simple andimmediate solution is to disable the speech-enabled-buttonssetting to avoid canceling the Read command, however, it isunclear whether the users who most benefit from speech-enabled menus and buttons would be able to solve thisproblem.

Another area for improvement is the Change Skinfeature, which is not as well developed initially as would beexpected. Several themes exhibit poor color contrast, and twothemes, which have a graph paper background, aredistracting. Although some skins were poorly designed, thesolid color skins were acceptable. Above all, the WinAqua

theme, which mimics the Macintosh OSX interface, offered adelightful user experience.

Overall, CAST eReader is an excellent learning softwarepackage. For beginning users, the program’s features andsteep learning curve will require an investment of time;however, there is an adequate amount of support embedded inthe program. Experienced users will find that eReader’spowerful capabilities can enhance instruction for lessindependent learners. eReader can be used most effectivelywhen (a) the instructor is familiar with the software and setsup the program and develops a customized Starter File thatprovides information about objectives, tasks and hyperlinksto files for a user to read and (b) the learner knows how to useeReader and possesses basic computing skills to use the menusystem, change settings, and operate the applicationcommands.

If the user is not physically able to operate a computer,the operating system or software, he or she may requireadditional support in the form of immediate human supportor assistive software or devices. eReader will be leastsuccessful when instructor and learner attempt to use it theprogram before taking the time to learn how to use it. Withproper preparation, instructor and learner will find eReadercan promote a positive learning experience and achievementof desired educational outcomes.

CAST eReader version 3.0 Center for Applied Special Technology40 Harvard Mills Square, Suite 3, Wakefield, MA 01880-3233http://www.cast.orgavailable for Mac OS 7, 8, 9 or Windows 98/2000/ME/XP;requires at least 12 MB of RAM (Mac) or 16 MB of RAM (Win)$199.00 (Mac) and $229.00 (Win) (discount pricing for sitelicenses; 30 day free trial version available)

journal of special education technology exploration of unknown

Documents