Enriching STEM Education throughPersonalization and Teaching Collaboration

(Invited Paper)

Ali R. Hurson† and Sahra Sedigh‡†Department of Computer Science

‡Department of Electrical and Computer EngineeringMissouri University of Science and Technology

Rolla, Missouri 65409–0040Email: {hurson,sedighs}@mst.edu

Les MillerDepartment of Computer Science

Iowa State UniversityAmes, Iowa 50011-1041

Email: lmiller@cs.iastate.edu

Behrooz ShiraziSchool of Electrical Engineering

and Computer ScienceWashington State University

Pullman, Washington 99164–2752Email: shirazi@wsu.edu

Abstract—Advances in databases, computational intelligence,and pervasive computing, which allow “anytime, anywhere”transparent access to information, provide fertile ground forradical changes in pedagogy. Cyberinfrastructure leveragingthese technological advances can yield improvements in bothinstruction and learning, supporting a networked curricularmodel, facilitating collaboration within and among groups ofstudents and instructors, and providing continuous access toinstructional material. The trajectory followed by each studentthrough the curriculum can be intelligently personalized, basedon prior knowledge and skills, learning styles, and interests ofthe student, among other attributes.

We propose to achieve these objectives by developing PervasiveCyberinfrastructure for Personalized Learning and InstructionalSupport (PERCEPOLIS), which serves as the centerpiece of anexperiment to create a community of faculty and students over aset of campuses, focusing on STEM disciplines. While numerousdistance learning methods exist, we believe that the best way toprovide STEM education is to use a blended approach - one thatembraces both online components and classroom mentoring byqualified faculty members. The goal is to provide high-qualitySTEM education for the students, while raising the skill set ofthe entire community through teaching collaboration.

I. INTRODUCTION AND MOTIVATION

The need for transformative change in higher education isespecially pressing in Science, Technology, Engineering, andMathematics (STEM) disciplines, where courses and curriculashould keep abreast of rapid technological advances. Thecritical role of STEM education in the knowledge-based globaleconomy has been articulated in Rising Above the GatheringStorm, a report issued in 2005 by the National Academies[1]. The America Creating Opportunities to MeaningfullyPromote Excellence in Technology, Education, and Science(COMPETES) Act (2007-2010) was signed into law in re-sponse to this need. However, the five-year review - RisingAbove the Gathering Storm, Revisited: Rapidly ApproachingCategory 5, released by the National Academies in September2010, concluded that despite stimulus funding, the qualityof STEM education in the United States has worsened [2].

This work was supported in part by the U.S. National Science Foundationunder Grant No. IIS-0324835 and by the Missouri University of Science andTechnology Intelligent Systems Center.

Recent statistics that place the United States far behind otherindustrialized countries in education offer further testament tothe urgent need for revitalizing higher education [3].

Several principle shortcomings of current undergraduate en-gineering education programs were identified in Educating En-gineers: Designing for the Future of the Field, a report by theCarnegie Foundation for the Advancement of Teaching. Oneof the main problems described is the linearity of the dominantcurricular model. A networked curricular model was proposedto remedy this shortcoming. The report also emphasizes thatthe trajectory followed by each student through the curriculumcan and should differ. The importance of personalizing thistrajectory is underscored by the selection of personalizedlearning as one of fourteen Grand Challenges for Engineeringidentified by the National Academy of Engineering [4].

The predominant instructional model is also in need ofa paradigm shift. The majority of endeavors undertaken byfaculty members are carried out in disjoint and isolated fash-ion. Collaboration, at best, is typically limited to sharing ofinstructional content for specific courses within a program,resulting in duplication of effort, and inconsistency from oneoffering of the course to the next. For many schools, the lackof expertise and/or resources for effective delivery of subjectmatter are very pressing issues, especially in light of financialconstraints that prevent hiring, training, and expansion.

This paper describes an innovative, practical, and com-prehensive alternative to the traditional linear curriculumand lecture-based static pedagogy inherited from a socio-economical platform where higher education was not a ne-cessity, but a privilege. The objective of the proposed ef-forts is to establish a growing community of educators wholeverage shared cyberinfrastructure for teaching collaborationand personalization of STEM courses and curricula. Expectedoutcomes are increased enrollment, retention, and graduationrates for a diverse set of STEM disciplines, rather than anysingle program. The ultimate result will be a highly-qualifiedSTEM workforce, equipped with critical thinking ability, andcomputational knowledge and skills well-suited to advancesin technology and socio-economical needs. Figure 1 furtherarticulates the objectives and outcomes of the project.

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Increased enrollment Improved retention Increased graduation

Improved quality of STEM education

PERVASIVE CYBERINFRASTRUCTURE FORPERSONALIZED LEARNING AND INSTRUCTIONAL

Achieves

SUPPORT(PERCEPOLIS)

Support for networkedFacilitates

Teaching collaboration Reform of teaching practices PersonalizationSupport for networked

curricular model

Elevating knowledge and experience

Resource sharing Blended instructionand learning

Active and peer learning

Fig. 1. The overall objectives and outcomes of PERCEPOLIS.

Pervasive Cyberinfrastructure for Personalized Learningand Instructional Support (PERCEPOLIS) leverages a plethoraof enabling technologies to facilitate resource sharing and col-laboration across multiple disciplines and institutions. PERCE-POLIS views each course as a set of topics - some mandatory,as dictated by the curriculum to satisfy degree objectives andaccreditation requirements; and elective topics that can bechosen to supplement a student’s knowledge of prerequisites,or to engage an interested student in advanced content. Oncea critical mass of educational artifacts is developed, linkageof topics across courses can facilitate support of a networkedcurriculum - potentially eliminating redundancy.

Increasing enrollment, retention, and graduation throughgrass-root efforts that enrich and facilitate STEM educationrequires attention to both teaching and learning. The intelligentpersonalization offered by PERCEPOLIS can be leveragedto both ends, as it facilitates sharing and navigation of andaccess to two possibly overlapping sets of educational artifacts:i) a set of teaching artifacts, which is accessible by theinstructor; and ii) a set of learning artifacts that is intended forstudents. The learning artifacts made available to the studentsare selected by the instructor of the course, and can includeas few or as many teaching artifacts as the instructor deemsappropriate. Intelligent software agents will aid instructorsin personalizing courses to their teaching style and view ofpivotal topics, recommending an appropriate set of teachingartifacts. The learning artifacts recommended to each studentfor a course can be similarly personalized, based on attributessuch as academic profile, learning style, needs, and interests.

As depicted in Figure 2, the proposed cyberinfrastructurewill be in the form of middleware that links databases,e.g., PeopleSoft, and instructional platforms, e.g., Blackboard,Angel, currently in use at academic institutions, facilitatingincremental adoption of the networked and modular curricularmodel at low cost. Moreover, the ability to connect toolsalready in use, without requiring customized computing re-sources, enables instructors at different academic institutions

to collaborate on and exchange educational materials and in-formation, creating an environment conducive to collaborationon both teaching and educational research.

Current efforts are focused on STEM disciplines, due tothe teaching and research expertise of the authors. However,the cyberinfrastructure and personalization methodology areapplicable to a broad range of disciplines. This article isnot intended to compare and contrast different approachesto “personalization of courses” as advanced in the literature.It is intended to articulate the importance of personalizationand networked curricula, while introducing PERCEPOLIS andenumerating its features.

II. INTRINSIC CHARACTERISTICS OF PERCEPOLIS

A. Novelty

Fundamental to PERCEPOLIS is the modular approachto course development, which allows for finer granularity inpersonalization. PERCEPOLIS: i) offers a teaching methodol-ogy that is more in-tune with technology savvy generation-Yand millennial college students, ii) leverages pervasive andubiquitous computing and communication through the use ofintelligent software agents, and iii) provides assessments thatgauge the student’s mastery of concepts at the module leveland allow self-paced progression through the course.

To maintain a sense of community, advanced students whoprogress through the course more rapidly will serve as groupleaders. This peer learning approach fosters skills such ascommunication and negotiation. Furthermore, the proposedcyberinfrastructure facilitates the collection of data on studentperformance and learning at a resolution that far exceeds whatis currently available. Knowledge discovery from this richdata set can yield invaluable insights, such as the efficacy ofparticular instructional techniques and strategies embedded inthe learning artifacts. The capabilities envisioned for PERCE-POLIS subsume currently existing technology, which includesanimated textbooks and similar electronic artifacts; online

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Student

Student

PERCEPOLISDetermines appropriate modules,

educational artifacts and schedule based on

Instructor/Advisor

StudentStudent profile

academic recordFor each course:

modules taken Course For each course:

Studentperformance

Module profile

educational artifacts, and schedule based onstudent and module profiles

Student profile

StudentDatabase

(PeopleSoft)

- academic record- interests- learning style- special needs

-modules taken-grade on each Database

(Blackboard)-modules offered-educationalartifacts for each

Fine-grainedstatistical

data

Fine-grainedstatistical

data

Data analysisData analysis

Fig. 2. PERCEPOLIS as middleware.

homework repositories, e.g., Sapling Learning; or standard-ization efforts for web-based learning, e.g., SCORM [5]. Ourefforts rise to the grand challenge of personalized education.

B. Support of Cognitive Apprenticeship

A significant body of research [6] has concluded thateffective learning takes place in the course of a “cognitiveapprenticeship” that fosters the learner’s intellectual develop-ment [6]–[8]. Four concepts have been identified as essential tothe critical examination and improvement of education; eachconcept represents a stage in the cognitive apprenticeship:

1) Modeling: enabling observation of an expert in action.2) Scaffolding: provide support for emulating expert per-

formance.3) Coaching: providing students with deliberate, planned

feedback that guides their performance from novice- toexpert-level.

4) Fading: removing the scaffolding as students becomemore competent.

PERCEPOLIS facilitates all four stages of cognitive ap-prenticeship. In the modeling stage, the classroom instructorprovides in-class access to an expert. The material providedas supplementary material for each module, such as solvedproblems, design examples, and guided exercises with “hints”are among the learning artifacts useful in the scaffolding stage.Online assessments, some of which are graded instantaneously,are examples of artifacts that facilitate coaching. Allowing thestudents to work on their own schedule and pace on the moreadvanced learning artifacts provides a gradual fading of thestudent’s reliance on the classroom instructor. In conjunctionwith the frequent and detailed feedback that PERCEPOLIS canaid in providing to the students, this allows for a “metacogni-tive” approach to instruction, where students define their ownlearning goals and monitor their progress towards them. Evi-dence for the effectiveness of the metacognitive approach hasbeen documented in numerous studies, a seminal example ofwhich is How People Learn: Bridging Research and Practice- a report by the National Research Council [9].

C. Building a Community of Educators

Mentoring less experienced faculty members who may, bynecessity, be teaching courses outside of their main areas ofexpertise by more experienced faculty members is a powerfulaspect of PERCEPOLIS. Multi-institutional collaboration willcreate a richer pool of teaching expertise, such that in caseswhere the local faculty member designated to teach the classdoes not have all of the required skill set (either contentknowledge or teaching strategies), PERCEPOLIS can assigna faculty member from another institution to mentor the localfaculty member. An important aspect of this approach is itsbidirectional nature. While content knowledge is likely to bestronger at the larger universities, instructors at smaller insti-tutions are more likely to utilize unique teaching approaches.

The two-pronged approach of the proposed efforts aims forimprovements in both learning and teaching. Efforts relatedto teaching center on mentoring of less-experienced (with aparticular topic, or teaching in general) faculty, by those withgreater expertise. This approach has been shown to improveboth the instructor’s experience and the quality of her/histeaching [10]–[13]. Mandernach et al. [14] have shown similareffectiveness for mentoring of online instructors. The use oftechnology in mentoring has been a useful tool for cost-effective communication between mentors and instructors.Gentry et al. [15] discuss three successful technology mediatedapproaches to mentoring studied in the literature; namely,technology-enhanced professional development coupled withaccess to a mentor, electronic mail, and online discussionforums. PERCEPOLIS goes beyond these tools to providean intelligent platform for sharing and navigation of teachingresources, where pervasive computing is utilized to personal-ize the resources (including mentoring) recommended to aninstructor, based on needs, preferences, and teaching style.

D. Support of Blended Learning

The PERCEPOLIS community enables blended learning,where the classroom instructor has the choice of using online,

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computer-mediated instruction to supplement traditional class-room activities, as well as supporting personalized enrichmentmaterial for the students. Blended learning is an emerging phe-nomenon well-suited to the learning styles and expectations oftoday’s students, who are digital natives [16].

E. Support of Peer and Active Learning

The peer and active learning opportunities offered by in-class activities can strengthen interpersonal skills and facil-itate interaction among students. PERCEPOLIS allows theinstructor to make use of online forum tools in existingcourse management platforms to initiate and scaffold bothasynchronous, written group activities (discussion boards) andsynchronous, live team negotiations (voice boards, onlineconferencing tools). These activities can be monitored bythe instructor, advanced students serving as peer leaders, orboth. The involvement of peer leaders will help students buildleadership skills, strongly valued by the future employers.Furthermore, the engagement of multiple STEM disciplinesexposes students to interdisciplinary applications of the topicsthey study - tangible motivation for learning the material.

The ability of the instructor to utilize computing technologyto support rich educational content has the added benefitof facilitating the accommodation of differences in learningstyles. The average learner retains about 20% of what is heard,40% of what is seen and heard, and 75% of what is seen,heard, and performed [17]–[19]. A traditional classroom set-ting mainly offers visual and auditory content; print or video-based distance study does the same. The ability to providetactile content, whether in reality, in a classroom setting, orthrough remote access and virtual reality, is especially helpfulin the modeling stage of the cognitive apprenticeship, butcan also be exploited to increase the efficacy of other stages.Furthermore, the predominant learning style of a student canbe assessed and used in personalizing courses and curriculartrajectories for each student. The ability to track the perusalof educational content by each student allows more accuratedetermination of his/her learning style [20].

III. DESIGN OF PERCEPOLIS

PERCEPOLIS views a degree-granting program as four setsof entities: i) instructors, 𝐼; ii) (teaching) mentors, 𝑀 ; iii)students, 𝑆; and iv) courses, 𝐶. An instructor, 𝑖 ∈ 𝐼 , hasexpertise in one or more subjects. A mentor, 𝑚 ∈ 𝑀 , is afaculty member with a high level of expertise in one or moreareas. A student, 𝑠 ∈ 𝑆, is studying towards a degree andis required to take courses from 𝐶, in an orderly fashion, tosatisfy degree requirements. Each 𝑐 ∈ 𝐶 represents a coursein the curriculum, and is tagged as required or elective. Thecourses are interrelated, per the structure of the curriculum.

Each of 𝐼 , 𝑀 , 𝑆, and 𝐶, respectively, is represented by acommunity of software agents that communicate and negotiatewith each other according to the defined tasks, e.g., recom-mending a personalized set of teaching (learning) artifacts toeach instructor (student), and in effect, personalizing his or herexperience of a course (or curriculum). Mentors are assigned

to courses as required. As described in Section III-A, we use amodular approach in the development and delivery of courses,so that each course 𝑐 ∈ 𝐶 can be viewed as a collection ofinterrelated topics, where the degree of connectivity amongtopics can vary from course to course.

When a student, 𝑠, is required to take a course, 𝑐, an agent,𝐴𝑠𝑐 is created to represent the student in that course. 𝐴𝑠𝑐

acquires information about the student’s profile and determinesthe student’s academic background, interests, and accumulatedprerequisite knowledge, among other required information.𝐴𝑠𝑐 interacts with the agents of course modules to identifya personalized trajectory of modules and learning artifacts forthe student. Furthermore, 𝐴𝑠𝑐 ensures that the student perusesrequired material - notes, sample programs, exercises, and thelike. PERCEPOLIS also creates a course agent, 𝐴𝑐𝑠, whichrepresents the personalized course, 𝑐, for the student, 𝑠. 𝐴𝑐𝑠

interacts with the agents of the instructors to identify the mostknowledgeable instructor for the personalized course for thisstudent (assuming that more than one instructor is available).If only one instructor is available for the course, a singleinstructor agent 𝐴𝑖𝑐 will interact on behalf of the instructorwith all student agents. The student’s agent, 𝐴𝑠𝑐, then alertsthe student to timelines, class schedules, learning/discussionschedules, project deadlines, appointments with the instructor,and corresponding preparations. The instructor identified isrepresented by an agent, 𝐴𝑖𝑠𝑐, who ensures that the studentmeets all requirements for each mandatory module, and collab-orates with 𝐴𝑠𝑐 to ensure that the student is supplied with allrequired course material. 𝐴𝑖𝑠𝑐 also informs the instructor aboutthe progress of the student and alerts the instructor wheneverthe student is progressing too slowly or too rapidly .

A. Modular Course Development

As described in Section I, the modular approach to coursedevelopment is fundamental to PERCEPOLIS. Each course isviewed as a set of mandatory and elective topics, where eachtopic is associated with educational (teaching and/or learning)artifacts, which can include experiential artifacts intendedto reemphasize key issues through hands-on individual andgroup projects. The experiential artifacts are dynamic, as theircontents can be determined based on topics that a majority ofthe students in a given class find challenging or confusing.Figure 3 illustrates a sample environment for a course ondesign and analysis of algorithms.

The learning artifacts that comprise a course are self-contained, allowing for self-paced perusal and designed topromote active, rather than passive learning. Self-assessmentquestions at the end of each module can take a variety offorms, including objects to be “dragged” into place, andmultiple-choice or short-answer questions. The most interac-tive learning artifacts are the design challenges, in which thestudent must make decisions and respond to “hints” and otherfeedback in order to find a solution for the problem at hand.Graphics and animation can be used to demonstrate complexconcepts. Text, narration, charts, and diagrams can be used toreinforce concepts during animation.

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Greedy StrategyDijkstra’s AlgorithmNetwork Routing

QuizzesExams

Student

Instructor

Sample ProgramsSource Code

Programming Project

ChallengesResearch Problems

TopicsPreliminariesRecurrence RelationsSorting AlgorithmsGraphsQuantitative ModelsDynamic ProgrammingComputational GeometryString MatchingAlgorithmsNP Complete Problems

GraphsGraph DefinitionsDepth First SearchBreadth First SearchSpanning TreesSingle Source Shortest pathAll Pairs Shortest PathBipartite Graphs

Fig. 3. Sample environment for a course on design and analysis of algorithms.

Some topics require prior knowledge; if the student does nothave this background, he/she will be able (and expected) toperuse learning artifacts associated with the prerequisite topic.Assessments that gauge the student’s mastery of conceptsat the topic level are used to allow self-paced progressionthrough the elective, and at the discretion of the instructor, themandatory material. If these assessments indicate that a studenthas already mastered the basic concepts of particular topic,more advanced learning artifacts related to that topic will berecommended to him or her. To maintain a sense of communityat the class level, advanced students are encouraged to serve asleaders of group activities. This peer learning approach fosters“soft” skills, such as communication and negotiation.

Figure 4 depicts the possible trajectories of a studentthrough one topic of a course. The figure also demonstratesthe student tracking process as incorporated in the topic. Eachtopic reinforces background knowledge and provides optionsto study more advanced concepts and/or to gain missing basics.

To summarize, modular course design offers:

∙ Adaptability/flexibility: to a certain extent, course con-tents can be personalized based on the needs and interestsof both the students and the instructor.

∙ Continuity: the modular approach to course design, com-bined with the ability to personalize the contents of acourse, allow greater continuity in the curriculum, whilesatisfying the needs of some students without sacrificingthe needs of others.

B. Blended Learning and Instruction

Common experience shows that online availability, e.g.,through a course management system such as Blackboard, of

lecture notes and other instructional content generally leads tolow class attendance by students. Even students who continueto regularly attend classes may become inattentive in theclassroom and passive in any discussions that take place.Furthermore, there is increasing expectation that the coursecoverage and examinations must be limited to whatever isavailable online, and any topics discussed outside of classshould not be covered on the tests. Periodic examinations andpop quizzes (though extremely unpopular among the students)can be used to address this problem to some degree, but arebecoming harder to implement, due to large class sizes.

We seek to adopt a new teaching practice that is attunedto advances in technology, is interactive and motivates activeclass participation, enforces continuous learning, and fostersinterpersonal skills that may be neglected in a traditionalclassroom. To achieve these objectives, we propose to modifythe traditional lecture-based teaching environment, by supple-menting the standard lecture notes in the teaching artifactswith examples and solved problems that the instructor can useduring class time to hold the student’s attention and encourageclass discussion. The examples will be technology based, e.g.,utilize animation. In addition we apply a blended approach tolearning and instruction by providing students with a rich setof learning artifacts that are personalized to take advantage ofthe students needs and optimal learning styles.

We expect that these artifacts will result in classes that aremore dynamic, supporting the following features:

∙ Students are required to peruse specified learning artifactsbefore class. Group study (facilitated by experientiallearning artifacts) is highly encouraged.

∙ The combination of the learning artifacts and support for

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Glossary of prerequisitetopics

NoFamiliar with the topics?

No Review background material

Yes

Take Test

N

Enforcement ofbackground

At the end, give atest record the

Remedial actionYes

No

Pass?

Glossary of topics

No test, record thescore, and imposeremedial action ifnot successful

NoTake the ModuleFamiliar with the topics?

Yes

Take PreTestCurrent Module

NoPass?

Yes

Options

No

Extra credit through advanced topics orpeer tutoring

Study next module

Fig. 4. Possible trajectories through one topic of a course.

online communication tools such as discussion boardsallows students to share their concerns and questions withtheir peers and the instructor.

∙ The class period then is dynamically organized to ad-dress major issues raised by students and enhance theirunderstanding of subject matter in the learning artifacts.

∙ To encourage independent learning and reflection andenforce continuous involvement, at the beginning of eachclass period, students are quizzed based on the keyconcepts of the topic they have been asked to study. Theremainder of the session will be devoted to addressingstudents’ questions, and discussing and analyzing themore complex concepts.

∙ Traditional periodic homework assignments and projectswill be introduced and supported by learning artifacts.Both online and traditional examinations will continueto be utilized to reinforce learning and determine thestudents’ overall mastery of course concepts.

∙ To maintain a sense of community within the class,students who already know the material on a topic will begiven a learning artifact on a related, but more advancedtopic and will be asked to take part in class by leadingdiscussions on some of the more advanced concepts.

∙ Finally, some of the examples in the teaching and learningartifacts will be designed to encourage, promote, andreward group activities and instill missing basics suchas leadership, communication skills, and ethics.

In summary, our view of the classroom is an environmentconducive to experimentation and discovery, which can betailored to focus on topics considered pivotal by the instructor.

C. Intelligent Access Tools

We leverage our research in multidatabases, mobile agenttechnology, pervasive computing, and mobile data access

systems to develop middleware that serves as global informa-tion sharing cyberinfrastructure [21]–[25]. The middleware ispositioned on top of existing database and course managementsystems, and allows anytime, anywhere intelligent and trans-parent access to learning artifacts that comprise the coursesof a curriculum. Our research within the scope of globalinformation sharing, multidatabases, and multimedia data pro-cessing has resulted in the design and implementation of anintelligent search engine, denoted as the Summary SchemasModel (SSM) [24], [25], that supports automatic identificationof semantically similar/dissimilar data that have different/samenames and representations in a wired or wireless platform.The model uses word relationships, i.e., hypernym, hyponym,synonym, defined in a standard thesaurus such as Roget’s, toautomatically build hierarchical metadata of local access termsexported from underlying local databases. The embeddeddynamic nature and bottom-up design approach of the SSMmakes it particularly suitable for extending the scope of thisproposal beyond a single discipline or educational unit. Thesummary schemas concept will be used to develop a semanticnetwork and semantic metadata that integrate course modules,and hence courses, within and across multiple curricula.

Furthermore, with the aid of the navigational tools andimprecise content-based search capability of the SSM, users,e.g., students, instructors, and advisors, can browse throughlearning artifacts from a range of courses and curricula todetermine an appropriate learning trajectory. The choice ofthe SSM stems from: i) its ability to perform semantic searchand imprecise queries; ii) the small size of its metadata; whichit automatically generates; iii) its robustness and efficiency.

In the context of PERCEPOLIS, the SSM metadata hi-erarchy, at the root level, represents the curriculum, e.g.,CS and CpE curricula, with semantic terms that specify

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curriculum objectives and content requirements. We mainlyutilize the computational and software facilities available inparticipating organizations and UNIX-based operating sys-tems. The relational data model will be used to model coursetopics. Local data sources can be built on top of variousdatabase management systems, ranging from Microsoft Accessto PeopleSoft. As a security measure, provisions will be madeto provide different access capabilities to different classesof users, e.g., students, administrators, or course developers,based on their individual profiles. All artifacts developed inthe course of the proposed work will adhere to SharableContent Object Reference Model (SCORM) [5] standards tofacilitate interoperability with other educational platforms, andthe navigational tools will be cognizant of SCORM metadata,to allow query of artifacts external to PERCEPOLIS.

IV. CONCLUSIONS

The concept of modular offering of courses, in a limitedfashion, was implemented in a senior/graduate computer ar-chitecture course with an enrollment of seventeen (mainlygraduate) students. The course was composed of seven distinctmodules. Three sets of questionnaires were given to thestudents throughout the course; at the beginning, middle, andend of the semester. We are in the process of analyzingthe results. In general, the students appreciated the modularapproach; common complaints were due to i) unfamiliarity ofthe students with the new teaching approach and expectations,and ii) the frequency of examinations and testing.

The goal of the PERCEPOLIS project is to create acommunity of faculty and students, supported by powerfulcyberinfrastructure that facilitates a) the provision of diverseeducational opportunities to students and b) the mentoring offaculty who may, by necessity, be teaching courses outsideof their main areas of expertise. To reach these goals, thePERCEPOLIS cyberinfrastructure utilizes teaching tools, ani-mation techniques, and remote access to information to presentthe same information in different ways and accommodatedifferences in learning styles; allow self-paced, private, andflexible perusal of learning artifacts; and make more efficientuse of resources, potentially lowering costs for both studentsand institutions.

Furthermore, the proposed efforts can enable a shift toprofessional practice, rather than technical skills, as the focusof educational efforts; by providing a rich set of teaching andlearning artifacts, facilitating more efficient use of class time,and encouraging active and peer learning. Finally, PERCEPO-LIS can be used to increase the efficacy of student advising, byproviding the advisor with information at the topic, rather thancourse level; and allowing him or her to leverage the intelligentpersonalization and pervasive computing capabilities of thecyberinfrastructure to guide the efforts of the student.

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