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Adaptive Web-Based Leveling Courses Shunichi Toida, Chris Wild, M. Zubair Li Li, Chunxiang Xu Computer Science Department Old Dominion University.

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Presentation on theme: "Adaptive Web-Based Leveling Courses Shunichi Toida, Chris Wild, M. Zubair Li Li, Chunxiang Xu Computer Science Department Old Dominion University."— Presentation transcript:

1 Adaptive Web-Based Leveling Courses Shunichi Toida, Chris Wild, M. Zubair Li Li, Chunxiang Xu Computer Science Department Old Dominion University

2 Outline Motivation and background Objectives System Overview functional requirements implementation Status Course structure Jtree Artificial intelligence in discrete math Student/peer awareness Future Work Conclusions

3 Needs Non-traditional Student Second Career Transfer Second Major Non-traditional Delivery At Work/Home - Anywhere Evenings?weekends – Anytime Less expensive

4 Technology Inexpensive/Ubiquitous Multi-media PCs Improving Communications (internet) Effective Utilization will require Learning models Methods of organization and delivery Motivational mechanisms

5 Background ODU CS Dept TechEd initiative BS degree for AA graduates Target non-traditional students Web-centric delivery of course material

6 Background ODU CS Dept TechEd initiative BS degree for AA graduates Target non-traditional students Web-centric delivery of course material Problem: Diverse backgrounds of entering students

7 Background ODU CS Dept TechEd initiative BS degree for AA graduates Target non-traditional students Web-centric delivery of course material Problem: Diverse backgrounds of entering students Solution: Leveling courses in discrete math and programming

8 Objectives To develop courses that are adaptive web based leveling supported by AI technologies managed

9 System Overview

10 Use Case Summary

11 Functional Requirements Students Navigate the course based on his profile and progress Get status on his/her progress and his relative performance Immediate feedback where possible Instructor Specify courses structure Classify course contents Monitor students performance Trouble Alerts

12 Architectural Features Course description including pre- requisite structure (Oracle) IEEE Learning Objects Metadata Standard Student profile and progress (Oracle) Browsing support for course structure using applet Content access based on student progress

13

14 Status

15 Query-based content selection

16 Student/Peer Awareness Problem: motivating in a self-paced course Show progress relative to peers Show current class averages in assessment material

17

18 Artificial Intelligence in Discrete Math Theorem prover and symbolic computation are used for exercises on: English to logic translation Checking inferences Checking induction proofs

19 Proving Equivalences of Natural Language to Logic Translate the following sentence into predicate calculus using “likes(x,y)” predicate “Nobody likes JOHN” There are multiple correct answers

20 Proving Equivalences of Natural Language to Logic Translate the following sentence into predicate calculus using “likes(x,y)” predicate “Nobody likes JOHN”

21 Handling Multiple Solutions Restrict response to unique canonical form Compare student response to “all” correct/obvious answers Prove equivalence of student response to any correct answer

22 Handling Multiple Solutions Restrict response to unique canonical form Compare student response to “all” correct/obvious answers Prove equivalence of student response to any correct answer TPS: Theorem Proving System

23 Induction Proofs Built on the MAPLE symbolic computation system of MATLAB Example 1+2+… + n = n(n+1)/2

24 Example of Jtree/and some content

25 On-going and Future Work Continue development of course materials (adaptability, exercises) Integrate pieces Define evaluation metrics (market, effectiveness) Run assessment

26 Conclusions Need to serve non-traditional students Need to adapt to diverse backgrounds Need learning environment architectures and technologies Need effective learning strategies which leverage the potential of web connectivity

27 End of Presentation

28 Student Profile <lesson title="What Is Proposition" href="course=cs381,block=cs381-1- block1.2,lesson=cs381-lesson01">

29 Course Navigation Java applet navigation of high level course structure Access controlled by student profile

30 Course Development XML Course Mark-up Language Customized for course structure e.g. course, block, lesson (marks) Web-based Development Tools Servlet (Tomcat) Java Server Page (Tomcat) Java

31


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