...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
Open edX Adaptive
...
Tools
| Anchor | ||||
|---|---|---|---|---|
|
| Pearson's Decoding Adaptive Tool Type | Adaptivity | |
|---|---|---|
| MS/Harvard VPAL using TutorGen's SCALE | Adaptive Assessment | Problems presented according to difficulty level, learning objectives and student mastery |
| Dillon's research project (Review xBlock) | Adaptive Content | Spaced repetition based on failed attempts |
| Domoscio's integration for FUN | Adaptive Content | Spaced repetition, using Domoscio's engine |
MS/Harvard VPAL
| Anchor | ||||
|---|---|---|---|---|
|
- 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
- receives learner activity data from edX
- passes a sanitized version to SCALE
- receives updates from SCALE
- 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
- https://adaptive-edx-v4.vpal.io/ called by https://studio.edx.org/asset-v1:HarvardX+SPU30x+3T2017+type@asset+block@EveryProblemScript.js
- Data: username, problem's block_usage_key, score, max_score
- Hack: waits 2secs after problem is submitted and page is reloaded
- No one noticed: "Invisible implementation is a definite win."
- VPAL LTI tool
- 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.
- 2 endpoints on SCALE
- Analyzing Data from an Adaptive MOOC
- Performance (effectiveness)
- Speed (efficiency)
- Engagement (engaging)
...