KT Module Overview

Introduction

Welcome!

Your instructor: Ryan Baker, Richard Scruggs

Your facilitator: Yilin Liu

KT Lab 1: Bayesian Knowledge Tracing

Intro Presentation:

Key Concepts

Essential Readings:

KT Lab 2: Performance Factors Analysis

Intro Presentation:

Key Concepts

Essential Readings:

KT Lab 3: Item Response Theory

Intro Presentation:

Key Concepts

Essential Readings

KT Lab 4: Deep Knowledge Tracing

Intro Presentation:

Key Concepts

Essential Readings:

Week Schedule Review

Monday 1115a-1230p Track introduction
Monday 130p-2p ASSISTments setup
Tuesday 940a-11a KT basics
Tuesday 11a-1230p BKT lecture/discussion
Tuesday 130p-2p BKT activity in ASSISTments
(challenge activity: get BKT-BF running)
Wednesday 940a-1130a BKT activity in ASSISTments (continued)
Wednesday 1130a-1230p, 130p-2p PFA and LKT lecture/discussion

Week Schedule Review

Thursday 940a-1130a PFA activity in ASSISTments
Thursday 1130a-1230p, 130p-2p IRT and ELO lecture/discussion
Friday 940a-11a Deep Knowledge Tracing lecture/discussion
Friday 11a-1230p Memory algorithms lecture/discussion
Friday 130p-2p How to Apply BKT in Research/Practice activity

Tell us about yourself

Name

Job

Past experience in teaching

Past experience with Learning Analytics or Data Science

Past experience with Digital Learning Platforms

Any other questions?

References

Choffin, Benoı̂t, Fabrice Popineau, Yolaine Bourda, and Jill-Jênn Vie. 2019. “DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills.” arXiv Preprint arXiv:1905.06873.
Corbett, Albert T, and John R Anderson. 1994. “Knowledge Tracing: Modeling the Acquisition of Procedural Knowledge.” User Modeling and User-Adapted Interaction 4: 253–78.
Gervet, Theophile, Ken Koedinger, Jeff Schneider, Tom Mitchell, et al. 2020. “When Is Deep Learning the Best Approach to Knowledge Tracing?” Journal of Educational Data Mining 12 (3): 31–54.
Kang, Jina, Ryan Baker, Zhang Feng, Chungsoo Na, Peter Granville, and David F Feldon. 2022. “Detecting Threshold Concepts Through Bayesian Knowledge Tracing: Examining Research Skill Development in Biological Sciences at the Doctoral Level.” Instructional Science 50 (3): 475–97.
Pandey, S, and G Karypis. n.d. “A Self-Attentive Model for Knowledge Tracing. arXiv 2019.” arXiv Preprint arXiv:1907.06837.
Pavlik Jr, Philip I, Hao Cen, and Kenneth R Koedinger. 2009. “Performance Factors Analysis–a New Alternative to Knowledge Tracing.” Online Submission.
Pavlik, Philip I, Luke G Eglington, and Leigh M Harrell-Williams. 2021. “Logistic Knowledge Tracing: A Constrained Framework for Learner Modeling.” IEEE Transactions on Learning Technologies 14 (5): 624–39.
Yeung, Chun-Kit, and Dit-Yan Yeung. 2018. “Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization.” In Proceedings of the Fifth Annual ACM Conference on Learning at Scale, 1–10.