Mcms and ids sig

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Mcms and ids sig

  1. 1. Mining Course Management System (MCMS)andIntelligent Decision Support Special Interest Group (IDS-SIG)<br />Tony Clark<br />Centre for Model Driven Software Engineering<br />School of Computing<br />Thames Valley University<br />
  2. 2. Project Aims<br />MCMS is a JISC funded project that aims to:<br />Detect patterns in institutional data that indicate issues leading to student retention problems<br />Develop an approach to real-time student support and intervention that addresses retention issues.<br />Provides high-quality information in support of institution decision making processes.<br />2<br />MCMS & IDS-SIG<br />
  3. 3. The MCMS Process<br />3<br />MCMS & IDS-SIG<br />
  4. 4. Data Mining can Answer Questions and Test Hypotheses<br />Is the student performance, such as average mark, drop out, pass/fail related to student background profile?<br />Student performance is not related to:<br /><ul><li> Gender
  5. 5. Race
  6. 6. Age
  7. 7. Disability
  8. 8. Nationality.</li></ul>Student performance is related to:<br /><ul><li> Year of study
  9. 9. VLE usage
  10. 10. Library Usage </li></ul>4<br />MCMS & IDS-SIG<br />
  11. 11. What is the profile of students of students that transfer courses after year 1 and those that transfer after year 2?<br /> They are mostly UG student, enroll with lower certificate, but get higher marks.<br />5<br />MCMS & IDS-SIG<br />
  12. 12. What are the characteristics of students transferring from other institutions?<br />Student transfer from other institutions are mainly UG student, enroll with higher certificate, use library & BB less, and get lower marks and are mainly overseas.<br />6<br />MCMS & IDS-SIG<br />
  13. 13. Intervention<br />1. Intervention process (email, SMS, ...)<br />iMCMS System<br />2. Motivate student <br />3. Report risky students<br />Student<br />4.Module data<br />5. Give feedback <br />Module Tutor/staff<br />7<br />MCMS & IDS-SIG<br />
  14. 14. 8<br />MCMS & IDS-SIG<br />
  15. 15. Module Tutor Page<br />9<br />MCMS & IDS-SIG<br />
  16. 16. Intelligent Decision Support in HE<br />Issues:<br /><ul><li> Management and Strategic requirements for decision support.
  17. 17. Available technologies and gap analysis.
  18. 18. Multiple Data Sources:
  19. 19. Data Integration
  20. 20. Data Cleansing
  21. 21. Reusable processes
  22. 22. Engagement and motivation:
  23. 23. Students
  24. 24. Staff
  25. 25. Institution processes and committees
  26. 26. Supplier engagement</li></ul>10<br />MCMS & IDS-SIG<br />
  27. 27. Intelligent Decision Support SIG<br /><ul><li> Planning a submission to become an STG Pathfinder member.
  28. 28. Aims:
  29. 29. Address issues above.
  30. 30. Engage with key institutional stakeholders.
  31. 31. Identify sector-side requirements and develop IDS roadmap.
  32. 32. Identify scope for sector-wide reusable solutions (shared service?)
  33. 33. Identify synergy with other activities.
  34. 34. Contact tony.clark@tvu.ac.uk with expressions of interest in SIG.</li></ul>11<br />MCMS & IDS-SIG<br />

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