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EWS using Sakai

EWS using Sakai

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    Sakai la-ewsv2 Sakai la-ewsv2 Presentation Transcript

    • Early Warning System for Identifying students at risk of failing
      Roger Brown
      Center for Educational Technology
      University of Cape Town
      roger.brown@uct.ac.za
    • Overview
      PART 1
      Why we started looking at EWS
      The functional requirements of the system
      Institutional fit
      Matching Vula (Sakai) affordances to the functional requirements
      Developments that would allow Sakai to act as an EWS (well some of them anyway!)
      How UCT is moving forward
      PART 2 - Discussion
      Activity and course grade
      Your ideas
      12th Sakai Conference – Los Angeles, California – June 14-16
      2
    • Part1: Introduction
      In 2009 Senate Re-admission Review Committee recommended that greater attention needed to be given to Faculty EWS.
      The SRRC report recommended that:
      the SRRC monitors data from the Faculty EWS with the aim of assessing and reporting on the impact mid-year exclusions have on throughput rates, and
      Investigate the EWS issue to assess the most effective approach to adopt a single system thereby providing consistency across faculties.
    • EWS – Functional requirements
      The ability to record a standard number of “in course”results/performance/grade
      The ability to create a current class list of all valid registered students in a course, populate this list with “in course results”, and load these to the students’ PeopleSoft record.
      Specification of an “at risk” threshold value for these results
      Recording of comments against a student
      Generation of communication to identified students 
      Retentions of a permanent record of these communications
      Specified reporting of student performance
      For a student within a course across all courses
      For a specified cohort of students
      Access and authorisations to entry grades, viewing of grades and running of reports, course conveners and/or mentors and/or other “intervention” managers
    • EWS – Institutional criteria
      Technical Implementation
      Technical Integration
      Usability and User Support Requirements
      Technical Support
      Security and Authorisations
      Student Access
      Overall Reporting Capacity
      Cost (of licensing, implementation and support)
      Vendor and Product Sustainability
    • EWS Functional requirements and Vula (Sakai 2.7) - Integration
      PeopleSoft
      HEDA - Higher Education Data Analyzer
      Demographic and K12 data (currently used by IPD)
      IDvault
    • Vula: Affordances vs Requirements
      Groups: Easily created and populated
      Configurable Roles:
      Access
      and authority
      Gradebook
    • Vula: Affordances vs Requirements
      Communication:
      Email
      Internal message
      SMS
      • Secure
      • Familiar
      • Widely accepted by admin/academic staff (2474 staff used Vula in 2010)
    • Vula: Affordances vs Requirements -Gradebook
      1. Import marks from excel
      3. Integrates with Vula testing tools
      2. Weighting and Categories
    • Assessing students at risk?
      Back to My Workspace
      Out of Gradebook
    • Vula: Limitations (currently)
      “At Risk” assessment would need to be done outside Vula
      Not all lecturers/course convenors use Vula
      Vula is not the authoritative source of marks
      Vula does not “push” data to PS
      Staffing
    • Vula: R&D for EWS application
      Automated Gradebook export to ETL platform or preferably an internal logic
      Internal or external algorithm development for risk analysis
      Auto grouping based on risk analysis
      Reporting communications, display, etc
      Predictive logic based on previous student performance
    • How UCT is moving forward
      The task team recommended in phase 1
      EWS to utilise the functionality of PeopleSoft (some developments required)
      Improve the integration of Sakai and PS
      gradebook export to PS (it’s easier to get grades into GB than into PS )
      Samigo& Asn => GB => PS
      12th Sakai Conference – Los Angeles, California – June 14-16
      13
    • Part 2: Vula: Final grade vs all events (PSY1001W)
    • Your Ideas
      12th Sakai Conference – Los Angeles, California – June 14-16
      15
      Predictive modelling
      GB in students’ “My workspace”
      ?
      Using ETL
      Communicating “failure”
      Learning analytics
      A “read only” SU role in Sakai
      Data mining – automating and exposing
      More than grades only? – is attendance a predictor?