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Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
Mcms and ids sig
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Mcms and ids sig

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  • 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. 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. The MCMS Process<br />3<br />MCMS & IDS-SIG<br />
  • 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. Race
  • 6. Age
  • 7. Disability
  • 8. Nationality.</li></ul>Student performance is related to:<br /><ul><li> Year of study
  • 9. VLE usage
  • 10. Library Usage </li></ul>4<br />MCMS & IDS-SIG<br />
  • 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. 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. 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. 8<br />MCMS & IDS-SIG<br />
  • 15. Module Tutor Page<br />9<br />MCMS & IDS-SIG<br />
  • 16. Intelligent Decision Support in HE<br />Issues:<br /><ul><li> Management and Strategic requirements for decision support.
  • 17. Available technologies and gap analysis.
  • 18. Multiple Data Sources:
  • 19. Data Integration
  • 20. Data Cleansing
  • 21. Reusable processes
  • 22. Engagement and motivation:
  • 23. Students
  • 24. Staff
  • 25. Institution processes and committees
  • 26. Supplier engagement</li></ul>10<br />MCMS & IDS-SIG<br />
  • 27. Intelligent Decision Support SIG<br /><ul><li> Planning a submission to become an STG Pathfinder member.
  • 28. Aims:
  • 29. Address issues above.
  • 30. Engage with key institutional stakeholders.
  • 31. Identify sector-side requirements and develop IDS roadmap.
  • 32. Identify scope for sector-wide reusable solutions (shared service?)
  • 33. Identify synergy with other activities.
  • 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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