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Open edX Adaptive Tools 


Pearson's Decoding Adaptive Tool TypeAdaptivity
MS/Harvard VPAL using TutorGen's SCALEAdaptive AssessmentProblems presented according to difficulty level, learning objectives and student mastery
Dillon's research project (Review xBlock)Adaptive ContentSpaced repetition based on failed attempts
Domoscio's integration for FUNAdaptive ContentSpaced repetition, using Domoscio's engine

MS/Harvard VPAL 

  • Designing Adaptive Learning and Assessment
    • Adaptive = dynamically change in response to student interactions within the MOOC, rather than on the basis of preexisting information such as a learner’s gender, age, or achievement test score.
    • The order of problems in a sequence is determined by a personalized learning progression, using learners’ real-time performance and statistical inferences on sub-topics they have mastered.
    • All problems in the course were manually tagged with one or several learning objectives.
    • Uses TutorGen's adaptive engine, SCALE®  - Student Centered Adaptive Learning Engine
      • Provides knowledge tracing, skill modeling, student modeling, adaptive problem selection, and automated hint generation for multi-step problems.
      • Knowledge components / skills (KCs) are tagged at the right level of granularity. Scale refines the tagging of these KCs after data has been collected from actual student interactions.
      • TutorGen extended SCALE algorithms to consider not only individual learning objectives (KCs), but also problem difficulty and problem selection within modules that group together various concepts and problems.
  • The Adaptive Experiment : Implementation
    • VPAL LTI tool
      1. receives learner activity data from edX
      2. passes a sanitized version to SCALE
      3. receives updates from SCALE
      4. provides appropriate next activity to learners
    • LTI tool provides a pass-through frame with an "activity sequence" (sequence of problems) and iframes XBlock URLs.
    • Hiding assessments
      • Relies on XBlock URLs not enforcing content experiment groups.
      • All assessments must be available to the control group.
      • Experiment group sees ONLY the LTI tool.
    • Passing grades and data
    • No one noticed: "Invisible implementation is a definite win."
  • The Bridge for Adaptivity
    • 2 endpoints on SCALE
      • Transaction: submit student problem attempts with student, activity, and grade data.
      • Activity: get ID representing the next activity recommended by the engine for the student.
  • Analyzing Data from an Adaptive MOOC
    • Performance (effectiveness)
    • Speed (efficiency)
    • Engagement (engaging)


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