Measuring the effectiveness of blended learningenvironment: A case study in Malaysia

Cho Cho Wai & Ernest Lim Kok Seng

# Springer Science+Business Media New York 2013

Abstract Learning environment has always been traditionally associated with thephysical presence of classrooms, textbooks, pen-and-paper examinations and teachers.However, today’s evolving technology has rapidly changed the face of education.Online learning, teleconferencing, internet, Computer Assisted Learning (CAL),Web-Based Distance Learning (WBDL) and other technologies are integrated ineducation. This blended learning environment has become the major role in trainingand education scene. This paper focuses on a set of quantitative data pertaining to theperception of blended learning, attitude towards technology, effectiveness and efficien-cy of blended learning by using path analysis. Data were drawn from a group ofbusiness students who were engaged in blended learning environment. This studyintends to find out the effectiveness and efficiency of blended learning in Malaysiatertiary institutions. The empirical results confirm that blended learning does enhancestudent’s learning experience and learning outcomes.

Keywords Blended learning . Regression . Effectiveness

JEL Classification I10 . C13 . C10

1 Introduction

Blended Learning (BL) isa popular topic nowadays, but has different interpretations.Early references to BL come from industry and workplace, although recently it hasbeen widely adopted in higher learning institutions. The term is commonly associatedwith the introduction of online media into a course; at the same time recognizing thatthere is merit in retaining face-to-face contact and other traditional approaches. It is also

Educ Inf TechnolDOI 10.1007/s10639-013-9293-5

C. C. Wai (*) : E. L. K. SengTaylor’s Business School, Taylor’s University, Subang Jaya, Selangor, Malaysiae-mail: chowai.cho@taylors.edu.my

E. L. K. Senge-mail: KokSeng.lim@taylors.edu.my

used asynchronous media such as email and video conferencing in conjunction withsynchronous technologies, commonly known as text chat or audio (MacDonald 2006)

The use of online media either distance or campus-based environments offersopportunities for learners. Lecturers use website to post lecture notes or slide presen-tations; at the same time, they continue to conduct lectures, face-to-face tutorials orseminars. However, how effective are these strategies in terms of cost-effective andacceptance level are still unknown. This study focuses on students’ perceptions of BL,attitude towards technology, effectiveness and efficiency of BL in teaching and learn-ing. Therefore, the specific objectives of this study are threefold. First, it seeks todetermine student’s accessibility to technology in BL environment. Then, it providesinsights into the effectiveness as well as efficiency of BL tools in teaching and learning.

2 Literature review

The definition of BL varies considerably. Some researchers said BL could be a mixtureof face-to-face instructor led and self-paced online learning (Graham 2005). Someeducational researchers believe BL should include the use of mixed media as adefinition (Osguthorpe and Graham 2003). Another generic example, a course whichuses a web-site or a course management system plus a classroom experience would beBL. Nevertheless, a significant group of educational scholars seem to prefer definingblended as simply the combination of online (mostly asynchronous) and face-to-facelearning environments.

Since 1998, the University of Central Florida(UCF) has been using a similardefinition for its BL courses termed mixed-mode courses (Dziuban et al. 2004). TheUCF data revealed that BL was effective and could lead to higher student success ratesin specific academic disciplines (Dziuban et al. 2004). Research by Niemiec and Otte(2006) posited that BL was not only an acceptable methodology but a transformativeone for higher education. This finding is coincided with Hiltz and Turoff’s (2005)study. They strongly support that the introduction of asynchronous learning networksinto campus courses serve as a critical breakthrough in improving learning. McCombsand Vakili (2005) reached a similar conclusion that BL could lead to a more learner-centered approach.

However, not all research is positive about the usage of BL. A recentexperiment of a course taught in all three modalities concluded that fully onlinewas the best compared to blended and face-to-face approaches (Reasons et al.2005). Vaughan and Garrison (2005) did not find any evidence that BLimproved student cognitive presence while exclusive Asynchronous LearningNetworks (ALN) environments did show that evidence. Wu and Hiltz’s (2004)study of students in blended courses found that online discussions were mean-ingful, but no evidence was shown to support the hypothesis that blended wassignificantly better than fully online. Proponents of learner-centered design andinstitutional transformation would argue that the focus must be on individualsand educational progress from a set of outcomes to a competency based criteriafor a curriculum (Weimer 2002; Tagg 2003; McCombs and Vakili 2005).Instructional technologists might also argue that educational improvementcomes from more highly interactive technologies like gaming and simulations

Educ Inf Technol

(Dede 2005). However, institutional limitations such as funding, user-friendlytechnology, culture, organizational structure and staff are not always availableto support those kinds of dramatic changes. BL however is a relatively simpleand effective change that institutions can indeed adopt.

One of the problems facing the field is whether BL is effective as measuredthrough grades, course completion, retention and graduation rates. An evengreater question is whether BL is “better” than other learning environments.The results from fully online learning courses show mixed results but overallmeta-analyses show that online courses are at least as effective as traditionalclassroom instruction (Russell 2001; Zhao et al. 2005). In Zhao et al. research,the meta analyses certainly support no significant difference findings but it alsosupports the fact that distance learning can be better than face-to-face wheninstructor involvement, interaction, content studied, learner capabilities and theright mix of human interaction and technology.

The research available on BL measuring the same attributes is harder to findand currently more ambiguous. Retention of students is important for mostuniversities and is measured by course completion rates, program completionsand graduation. Much of the data on fully online ALNs suggest that retentionrates are not as high as for face-to-face instruction. Some research suggests thatthe comparisons are not as easy to make as the headlines have indicated datareported are inconsistent (Howell et al. 2004).

The best extrapolations come from the Department of Education, Institutional Post-secondary Educational Data and Statistics where graduation rates must be reported forall 4- and 2-year programs. Associate degree colleges graduate approximately 35 % oftheir students versus a 50 % graduation rate at traditional 4-year colleges. No similardata is yet reported for fully online programs. Allen and Seaman’s (2004, 2005) studyshowed that nearly 50 % of the institutions offering ALN courses are associate degreecolleges. Thus, when comparisons of graduation rates are made, it should be noted thatmore ALN courses and programs are offered by colleges which already have a low rateof graduation.

Generally, previous studies measured the effectiveness of BL by comparingthe traditional teaching and fully online courses. Most of them are evaluated bycourse and program completion rates and graduations. However, most of thestudies were lack in measuring the effectiveness and efficiency of BL tools inteaching and learning. Therefore, this study not only identifies the potential ofstudent technology usage, but also emphasizes how effective and efficient ofBL tools in the eyes of students.

3 Methodology

3.1 Data collection

This study used a set of quantitative data based on student’s perception of BL, attitudetowards technology, effectiveness and efficiency of BL tools. Data were drawn from agroup of 150 business school students who were engaged in BL environment. Studentswere chosen randomly and population was homogeneous in nature. This study is taken

Educ Inf Technol

under the form of survey research that yields descriptive information about factorsrelated to the BL. The survey questionnaires comprised of information student’stechnology usage, usage of online tools and effectiveness of BL in teaching andlearning. The first part of these survey questionnaires covered student’s generalinformation of technology such as knowledge of the technology usage, years ofcomputer usage, frequency of the usage, location of access and usage of emailand internet. Then, usage of the online tools such as social networks (MySpace,Flicker, Face book, Twitter, etc.), online chat, online discussion, online games,personal space (web pages, blogs, etc.), other social and communication toolswere prepared in second part of the questionnaires. Finally, PowerPoint presen-tation, video/movie presentation and usage, online lectures, online exercises,computer software usage, telephone call, SMS, e-mail, online chatting wereused as the measurement variables for effectiveness of BL tools.

3.2 Research methodology

Path analysis is a method of decomposing correlations into different pieces for inter-pretation of effects (e.g., how does BL tools are effect to their teaching and learning).Path analysis is closely related to multiple regression and it is a special case ofregression analysis. The reason for using this techniques is it allow us to test theoreticalpropositions about cause and effect without manipulating variables. Therefore, Pathanalysis was employed in this study to measure the effectiveness and efficiency of BLtools. The extension of the regression model is used to test the fit of the correlationmatrix against two or more causal models in this study. Path analysis will provideestimates of the magnitude and significance of hypothesised causal connections be-tween sets of variables Fig. 1.

This model is specified by the following two general equations:

Effectiveness of BL ¼ β1 þ β11X1 þ β12X2 þ e1 ð1Þ

Efficiency of BL ¼ β2þβ21X3 þ e1 ð2Þwhere,

X1 usage of onlie tools in teachingX2 usage of onlie tools in learningX3 effectiveness of BLe1 residual

In order to investigate relationships among the above variables, correlation andasymptotic covariance matrices was used in the analyses; whereas, KMO and Bartlett’stest were employed to investigate the reliability of the measurements. This study usedstatistical analysis to determine whether to accept or reject the hypotheses. Therefore,the hypotheses for this study are:

H1 Students have the potential to access to the technology in BL environment. i.e.,Proportion of technology usage are high and significant value.

Educ Inf Technol

H2 How effective of BL tools perceived by the students. i.e., β11 and β12 are positiveand significant coefficient value.

H3 How efficient the usage of BL tools in teaching and learning. i.e., β21 is positiveand significant coefficient value.

4 Findings

Course delivery has been changed over the decades. Almost all lecturers use onlinemethod to deliver their course content. At the same time, students can study on theirown based on the online materials. Students need to acquire the basic knowledge oftechnology in order to access online materials. Therefore, information pertaining tostudent’s technology usage was investigated thoroughly in this study.

4.1 General information of student’s technology use

Majority of the students are able to use modern technology nowadays. It is clear thattoday’s students rely mainly on electronic devices. However, how students use thesedevices and how they access to the internet are important for BL. Therefore, years andfrequency of computer usage and how they access to the online tools were beinginvestigated. According to the result, more than 65 % of the students had more than8 years of computer experience (Fig. 2). Students used computer, email/internet andsocial network everyday (Appendix A, Table 5). Chatting and online games had highestpercentage usage compared to the others and web page/blogs had lowest percentage in

Fig. 1 General path regression model for BL

Educ Inf Technol

everyday usage. Student’s technology usage could be seen satisfactorily in this study.Furthermore, students acquired the knowledge of using BL tools.

4.2 The usage of technology and online tools

Although students acquire the knowledge of using BL tools, however, how studentsaccess to these devices, how this technology affect their learning experiences and whateffect it on student’s studies are important in BL environment. Therefore, BL tools suchas PowerPoint, video/movies, online exercise, online lecture, emails, SMS, onlinechatting, webpage usage were used in this study. Most of the lecturers used BlackBoard 7 (BB7) to deliver their course content to the students before lectures. Suchdelivery method made it possible for students to study on their own path.

4.2.1 PowerPoint

PowerPoint is the main presentation medium in classrooms since 1990s. Most of thestudies investigated the link between PowerPoint and student’s engagement, the relation-ship between PowerPoint handouts and student’s performance and the effect ofPowerPoint on classroom interactions (Noppe et al. 2007). Therefore, PowerPoint playsan important role in BL. Table 6 (Appendix A) shows that 93 % of students downloadedPowerPoint lectures from students’ portal and 97 % of their lecturers used PowerPoint inclass. This high percentage of PowerPoint usage by the lecturers and students indicatedthat PowerPoint was an important BL tool in teaching and learning. The summary ofPowerPoint usage is presented in Table 6 (Appendix A) and usage of PowerPoint was atsatisfactory level.

4.2.2 Video/movies in lecture

With the advance in technology, lecturers are able to access authentic audiovisual resourcesdirectly such as friction.tv, beeline.tv, lonelyplanet.tv and YouTube. These resources bringbenefit to the modern classroom. Hence, usage and effectiveness of videos/movies inteaching and learning are being considered in this study. 70 % of the lecturers used videoin their teaching and 45 % of the students used it for their assignments.

Fig. 2 Years of computer use

Educ Inf Technol

4.2.3 Online lectures and online exercises

Beside power point and video, online lectures and exercises are important in BLsetting. Online lecture and exercises can reduce the cost and allow flexible studytime. Although the percentage of subjects incorporate online lecture was very lowor rarely use (Table 8, Appendix A). The usage of online exercise was highercompared to online lecture. Many students had problem to download the coursecontents. Students were looking for up-graded software in order to speed up theirdownloading time.

4.2.4 Computer software

Many subjects require the usage of ICT such as Mathematics, Statistics, Accountancyand Finance. Students felt that ICT enhanced their learning in term of calculation andtime. Although not all lecturers used computer software but the results of computerusage were at satisfactory level (Table 6, Appendix A).

4.2.5 Other online tools for discussion

Advance technology allows students to discuss online tools via telephone, SMS, emailand online chatting. However, this study showed that the percentages of using these BLtools were still very low (Table 6, Appendix A). To develop BL in teaching, these toolsneed to use widely in university. Telephone call is more costly compared to SMS, emailand online chatting. However, students used g-talk or other online talks to save cost.The main problem for online discussion is that lecturers need to spend time with theirstudents during the discussion session.

The results (Appendix Table 9) also showed that business school students hadacquired the significant knowledge of technology. Thus, hypothesis 1 was acceptedand students had the potential to access to the technology in BL environment.

4.3 Effectiveness of BL tools

The reliability of BL variables were acceptable level. Statistically, KMO values of morethan 0.5 and 0.7 can be considered mediocre and good. Table 1 shows that all the

Table 1 Reliability measures for BL variables: KMO and Bartlett’s test

BL variables Kaiser-Meyer-Olkin measureof sampling adequacy

Bartlett’s test ofsphericity (p-value)

PowerPoint 0.519 0.000

Video 0.676 0.000

Online lectures 0.633 0.000

Online exercises 0.697 0.000

Computer software 0.618 0.000

Telephone/SMS/email/online chatting 0.756 0.000

Educ Inf Technol

variables were significantly acceptable for reliability test. Therefore, path regressionanalysis could be carried out to identify the BL effectiveness model.

There are two stages of path analysis. First, it measures the effectiveness ofBL tolls in teaching and learning. Then, it measures the efficient teaching andlearning through BL tools. In the second stage, these BL tools are calculateddifferently in order to measure their magnitude according to each of the BLtool.

Table 2 shows the first stage of path analysis results. PowerPoint usage forlecturer showed significant result compared to the students’ usage. Students’PowerPoint usage showed insignificant result. Therefore, it shows that PowerPoint

Table 3 Path regression results of effectiveness and efficiency BL usage

Equation BL variables Coefficient of effectiveness Significance F (p-value) R2

1 PowerPoint 0.407a 0.001 0.166

2 Video/movies 0.537a 0.000 0.288

3 Online lecture 0.171 0.298 0.029

4 Online exercises 0.414a 0.002 0.171

5 Computer software 0.554a 0.003 0.307

6 Telephone 0.293a 0.000 0.990

SMS 0.288a

E-mail 0.315a

Online chatting 0.347a

a Significant at 1 % level

Table 2 Path regression results of effectiveness in BL tools

Equation Variables Path coefficient of usageof BL tools (lecturer)

Path coefficients of usageof BL tools (students)

SignificanceF (p-value)

R2

1 PowerPoint 0.246a 0.131 0.001 0.094

2 Video 0.562c 0.113 0.005 0.272

3 Online lecture 0.085 0.613c 0.000 0.434

4 Online exercises 0.225 0.333b 0.001 0.225

5 Computer software 0.037 0.915c 0.000 0.855

6 Telephone 0.810c 0.000 0.656

7 SMS 0.767c 0.000 0.588

8 E-mailing 0.932c 0.000 0.868

9 Online chatting 0.739c 0.000 0.545

a Significant at 10 % levelb Significant at 5 % levelc Significant at 1 % level

Educ Inf Technol

is effective BL tools in teaching and learning. The usage of video was moreeffective and significant than PowerPoint presentation. Students could get clear-er pictures of the subject through video presentation. Online lectures wereeffective tools for the lecturers and the students. 64 % of the students haddifficulty to download their online lectures. It will be an efficient BL tool if thesystem can be up-graded in the future. The coefficient for online media washighly significant. Students mainly used telephone, SMS, emails and onlinechatting for their studies.

Fig. 3 Effectiveness and efficiency of technology usage in BL

Educ Inf Technol

Table 3 indicates that PowerPoint and video presentation showed significanteffect on students’ learning. Students’ usage of online lectures, online exercises,computer software, telephone, SMS, e-mail and online chatting had significanteffect on their studies. PowerPoint and video were widely used in teaching andlearning. These BL tools showed high efficient results. Although the effective-ness of other BL tools showed significant results, but the percentage of usage

Fig. 4 Path analysis diagram for importance of blended learning in teaching and learning

Educ Inf Technol

was still very low. The results suggest that increase in the usage of online toolsin teaching and learning. Hypothesis 2 was accepted and the effectiveness ofthe BL tools showed statistically significance with positive value.

4.4 Efficiency of BL tools

For the efficiency of BL, path regression analysis was used to measure themagnitude between effectiveness and efficiency of BL tools. Path regressionresults and Path diagram for each of the BL tools are presented in Table 3 andFig. 3 respectively. It was clear that almost all BL tools were important inteaching and learning. Among these tools, video and computer software showedthe highest effectiveness. PowerPoint, online exercises, online chatting, email,telephone and SMS were highly significant at 1 % level (α=0.01).

Overall picture of path analysis for this study can be seen in Fig. 4. Theregression analysis of each BL efficiency and overall BL performance was calculated inTable 4.

Based on Table 4, Hypothesis 3 was accepted and the efficiency of BL tools showedstatistical significance in teaching and learning.

Figure 4 shows the regression analysis of BL efficiency and overall BLperformance. The magnitude of PowerPoint, video/movie, online lecture, onlineexercise, computer Software, telephone, SMS, emails and online discussioncontribute to the efficiency of BL can be seen easily in Fig. 4. PowerPointand video/movies usage contributed highest and the second highest to theefficiency of BL tools, followed by online lecture and computer software.The results suggested that online discussion is an important contributor toBL. Surprisingly, online exercises had a low contribution even it was one ofthe important BL tool. Therefore, further improvements are necessary for theonline exercises.

5 Conclusion

This study investigates students’ perceptions of BL, attitude towards technology,effectiveness and efficiency of BL tools in teaching and learning. The analysisresults showed that almost all the students were able to access modern tech-nology. Majority of the students used computer, internet and social networkdaily. Students’ technology usage could be classified as satisfactory level and

Table 4 Path regression result of overall BL performance and BL efficiency

PowerPoint Video/movies

Onlinelecture

Onlineexercises

Computersoftware

Other onlinediscussion tools

Standardized coefficients Beta 0.501 0.283 0.221 0.044 0.206 0.226

t-statistic 49.465 28.916 21.88 5.046 15.174 17.753

Significance 0.000 0.000 0.000 0.000 0.000 0.000

Educ Inf Technol

students also acquired the knowledge of using BL tools in their studies.Lecturer’s PowerPoint and video presentation showed significant results. Stu-dents’ online lecture, online exercises, computer software, telephone, SMS, e-mail and online chatting demonstrated significant effect in this study.

This study can be summarized into three areas. First, student’s technologyusage was satisfactory in BL environment. In particularly, students mainly usedPowerPoint for their studies and presentation purposes. Video presentation andonline exercises were used moderately by the students. Secondly, PowerPointand Video were effective of BL tools for the lecturers; whereas online lecture,online exercise, computer software and other online tools were significant forthe students. The efficiency of BL tools either through lecturers or studentsshowed significant results. PowerPoint and video/movies usage were the twomain contributors in BL efficiency. However, there are a few weaknesses to berectified in this study. The usage of online discussion tools was still low.Students had problem to download online lectures and online lecture showedinsignificant results. Online exercises contributed lightly to BL in teaching andlearning.

The results suggest that the usage of online discussion tools such astelephone, SMS, e-mail and online chatting, among students and lecturersneed to be improved. The system needs to be up-graded in the future so thatall the online materials will be accessible to the students. Moreover, lecturersneed to use more online lectures, online exercises in their teaching. Ingeneral, the results showed significant in the usage of BL tools in teachingand learning. The usage of BL tools not only enhancing students’ campuslearning experiences but providing quality and friendly learning environmentas a whole.

Appendix A

Table 5 General information of technology use

Use ofcomputer (%)

Access ofemail/internet (%)

Use ofsocial network (%)

Use ofsynchronouschat tools (%)

Use ofonlinegame (%)

Use of onlinepersonalspace(web pages,blogs)(%)

Every day, I’maddicted!

69.5 52.5 65.4 25.0 31.4 18.8

A few timesa week

22.0 32.5 23.1 34.7 37.1 25.0

Occasionally 7.3 11.3 9.0 26.4 18.6 26.6

Very rarely,if ever

1.2 3.8 2.6 13.9 12.9 29.7

Total 100.0 100.0 100.0 100.0 100.0 100.0

Educ Inf Technol

Table 6 Technology use in teaching and learning

(%)

Technology tools of BL Yes No

Usage of PowerPoint in the lecture 97.22 2.78

Student’s usage of PowerPoint 93.24 6.76

Use of video/movie presentation in the class 69.86 30.14

Student’s usage of video/movie 45.07 54.93

Subject include any on-line lecture 8.82 91.18

Subject include any on-line exercise 62.12 36.36

Computer software 51.61 48.39

Other online tools for discussion

Any telephone call to support your lecture 11.86 88.14

Any SMS text to support your lecture 11.67 88.33

Any e-mailing to support your lecture? 37.93 62.07

Any online chatting to support your lecture 6.90 93.10

Table 7 Frequency of technology usage in BL

Every lecture(%)

A few times aweek (%)

Occasionally(%)

Very rarely,if ever (%)

How often use PowerPoint slides inthe lecture

91.89 4.05 4.05 0.00

How often students’ use PowerPoint slides 23.61 58.33 16.67 1.39

How often student use video/moviepresentation in their assignment

2.99 25.37 49.25 22.39

How often students’ use video/movie presentation

7.84 25.49 37.25 29.41

How often does your lecturer useon-line lecture

2.33 11.63 4.65 81.40

How often does your lecturer useon-line exercise in his/her lecture

10.53 28.07 31.58 29.82

How often does your lecturer usecomputer software in his/her lecture

28.89 33.33 26.67 11.11

Table 8 Download rate for online lectures and online exercises

Very easy(%)

Easy(%)

Moderate(%)

Difficult(%)

Very difficult(%)

How easy/convenient can youdownload the on-line lecture

2.33 4.65 25.58 53.49 9.30

How easy/convenient can you locate/answer/download the on-line exercise?

9.09 20.00 61.82 7.27 1.82

Educ Inf Technol

References

Allen, I. E., & Seaman, J. (2004). Entering the mainstream: The quality and extent of online education in theUnited States, 2003 and 2004. Needham: Sloan-C.

Allen, I.E., & Seaman, J. (2005).Growing by degrees: Online education in the United States, 2005. Needham,MA: Sloan-C. Annotated bibliography on technology for distance education: As reported in 355 researchreports, summaries and papers. Montgomery, AL: International Distance Education Certification Center.Retrieved January 28, 2005, from http://www.nosignificantdifference.org/.

Dede, C. (2005). Planning for ‘neomillennial’ learning styles: Implications for investments in technology andfaculty. In D. Oblinger & J. Oblinger (Eds.), Educating the net generation (pp. 15.1–15.22). Boulder:Educause.

Dziuban, C., Hartman, J., Moskal, P., Sorg, S., & Truman, B. (2004). Three ALN modalities: An institutionalperspective. In J. Bourne & J. C. Moore (Eds.), Elements of quality online education: Into the mainstream(pp. 127–148). Needham: Sloan-C.

Graham, C. R. (2005). Blended learning systems: Definition, current trends, and future directions. In C. J.Bonk & C. R. Graham (Eds.), Handbook of blended learning: Global perspectives, local designs (pp. 3–21). San Francisco: Pfeiffer Publishing.

Hiltz, S. R., & Turoff, M. (2005). Education goes digital: the evolution of the online learning and therevolution in higher education. Communications of the ACM, 48(10), 59–65.

Howell, S. L., Laws, R. D., & Lindsay, N. K. (2004). Reevaluating course completion in distance education:avoiding the comparison between apples and oranges. The Quarterly Review of Distance Education, 5(4),243–252.

MacDonald, J. (2006). Blended learning and online tutoring: A good practice guide, gower publishingcompany. ISBN13: 9780566086595.

McCombs, B., & Vakili, D. (2005). A learner-centered framework for e-learning. Teachers College Record,107, 1582–1600.

Niemiec, M., & Otte, G. (2006). Blended learning in higher education: A report from the Sloan-C 2005Workshop. Needham: Sloan-C.

Noppe, I., Achterberg, J., Duquaine, L., Huebbe, M., Williams, C. (2007). PowerPoint presentation handoutsand college student learning outcomes. International Journal for the Scholarship of Teaching andLearning (IJSOTL), Vol. 1: No. 1, Article 9.

Osguthorpe, R., & Graham, C. (2003). Blended learning environments: definitions and directions. TheQuarterly Review of Distance Education, 4(3), 227–233.

Reasons, S.G., Valadares, K., & Slavkin, M. (2005). Questioning the hybrid model: student outcomes indifferent course formats. Journal of Asynchronous Learning Networks, 9(1), 83–94.

Table 9 Significance of technology usage

Test value = 2

t d.f Sig. (2-tailed) Mean difference 95 % confidenceinterval of the difference

Lower Upper

PowerPoint slides −17.313 73 0.0000 −0.878 −0.98 −0.78Video/movie presentation 9.638 66 0.0000 0.91 0.72 1.1

On-line lecture 13.823 42 0.0000 1.651 1.41 1.89

On-line exercise 6.155 56 0.0000 0.807 0.54 1.07

Computer software 1.959 44 0.0253 0.878 0.13 0.49

Other online tools 7.768 32 0.0000 1.758 1.3 2.22

Educ Inf Technol

Russell, T. (2001). The no significant difference phenomenon: A comparative research. Technology fordistance education. Montgomery, AL: IDECC.

Tagg, J. (2003). The learning paradigm. Bolton: Anker.Vaughan, N., & Garrison, D. R. (2005). Creating cognitive presence in a blended faculty development

community. The Internet and Higher Education, 8(1), 1–12.Weimer, M. (2002). Learner-center teaching: Five key changes to practice. San Francisco: Jossey-Bass.Wu, D., & Hiltz, S. R. (2004). Predicting learning from asynchronous online discussions. Journal of

Asynchronous Learning Networks, 8(2), 139–151.Zhao, Y., Lei, J., Lai, B. Y. C., & Tan, H. S. (2005). What makes the difference? A practical analysis of

research on the effectiveness of distance education. Teachers College Record, 107(8), 1836–1884.

Educ Inf Technol