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  • 1. Mining Course Management System (MCMS)andIntelligent Decision Support Special Interest Group (IDS-SIG)
    Tony Clark
    Centre for Model Driven Software Engineering
    School of Computing
    Thames Valley University
  • 2. Project Aims
    MCMS is a JISC funded project that aims to:
    Detect patterns in institutional data that indicate issues leading to student retention problems
    Develop an approach to real-time student support and intervention that addresses retention issues.
    Provides high-quality information in support of institution decision making processes.
    2
    MCMS & IDS-SIG
  • 3. The MCMS Process
    3
    MCMS & IDS-SIG
  • 4. Data Mining can Answer Questions and Test Hypotheses
    Is the student performance, such as average mark, drop out, pass/fail related to student background profile?
    Student performance is not related to:
    Student performance is related to:
    • Year of study
    • 9. VLE usage
    • 10. Library Usage
    4
    MCMS & IDS-SIG
  • 11. What is the profile of students of students that transfer courses after year 1 and those that transfer after year 2?
    They are mostly UG student, enroll with lower certificate, but get higher marks.
    5
    MCMS & IDS-SIG
  • 12. What are the characteristics of students transferring from other institutions?
    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.
    6
    MCMS & IDS-SIG
  • 13. Intervention
    1. Intervention process (email, SMS, ...)
    iMCMS System
    2. Motivate student
    3. Report risky students
    Student
    4.Module data
    5. Give feedback
    Module Tutor/staff
    7
    MCMS & IDS-SIG
  • 14. 8
    MCMS & IDS-SIG
  • 15. Module Tutor Page
    9
    MCMS & IDS-SIG
  • 16. Intelligent Decision Support in HE
    Issues:
    • 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
    10
    MCMS & IDS-SIG
  • 27. Intelligent Decision Support SIG
    • 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.
    11
    MCMS & IDS-SIG