Data Science Methods for Digital Learning Platforms Training Program

The Data Science Methods for Digital Learning Platforms certificate program teaches advanced learners how to use both algorithms designed specifically for digital learning platforms and how to effectively apply algorithms developed for more general purposes to digital learning platform data.

To apply to the next cohort of the program, click on Apply Here.

This program is offered in partnership between the University of Pennsylvania and the University of Florida

This webpage contains public materials from the Fall 2024 run of the program.

Syllabus

Make account to access assignments

Module 1: Introduction, Challenges, and Framework
Instructor: Ryan Baker
Video: [YouTube]
Slides: [pptx]
Assignment contents: [link]

Module 2: Prediction Modeling and Metrics
Instructor: Anthony Botelho
Video: [YouTube]
Slides: [pptx]
Assignment contents: [link]

Module 3: Feature Extraction and Feature Engineering
Instructor: Haiying Li
Video: [YouTube]
Slides: [pptx]
Colab: [ipynb]
Assignment contents: [link]

Module 4: Neural Networks and Deep Learning
Instructor: Anthony Botelho
Video: [YouTube]
Slides: [pptx]
Assignment contents: [link][csv]

Module 5: Data Visualization
Instructor: Jaclyn Ocumpaugh
Video: [YouTube]
Slides: [pptx]
Assignment contents: [link1][link2][link3][link4][link5][link6][link7]

Module 6: Ethics, Equity, and Algorithmic Bias
Instructor: Shamya Karumbaiah
Video: [YouTube]
Slides: [pdf1][pdf2][pdf3][pdf4][pdf5]

Module 7: Data Management and Database Access
Instructor: Michael Mogessie
Video: [YouTube]
Slides: [pptx]
Colab: [ipynb]
Assignment contents: [link]

Module 8: Knowledge Graphs
Instructor: Seth Adjei
Video: [YouTube]
Slides: [pptx]
Assignment contents: [link]

Module 9: Knowledge Tracing
Instructor: Ryan Baker
Video: [YouTube]
Slides: [pptx]
Assignment contents: [link][zip]

Module 10: Data and Measurement Validity
Instructor: Wendy Chan
Video: [YouTube]
Slides: [pptx1][pptx2][pptx3][pptx4]
Assignment contents: [link1][link2][link3][link4]

Module 11: Cluster Analysis
Instructor: Alex Bowers
Video: [YouTube]
Slides: [docx]
Assignment contents: [link]

Module 12: Network Analysis
Instructor: Bodong Chen
Video: [YouTube]
Slides: [html]
Colab: [ipynb1][ipynb2][ipynb3][ipynb4]
Assignment contents: [link]

Module 13: Sequential Pattern Mining and Temporal Analysis
Instructor: Bodong Chen
Video: [YouTube]
Slides: [html1][html2]
Assignment contents: [link]

Module 14: Causal Reasoning
Instructor: Walter Leite
Video: [YouTube]
Slides: [pptx1][pptx2][pptx3][pptx4]
Assignment contents: [link1][link2][link3][link4]

Module 15: Natural Language Processing
Instructor: Scott Crossley
Video: [YouTube]
Slides: [html1][html2]

Module 16: Transformer and Foundation Models
Instructor: Jinnie Shin
Video: [YouTube]
Slides: [pptx]
Assignment contents: [link]

Acknowledgements: Sincerest thanks to Seiyon Lee and Zhongtian Huang for their assistance in assembling the course and this webpage, and to all participating instructors and project members. These materials were created with generous support from the US Department of Education, Institute of Education Sciences, Award #R305B230007. The content represents the views of the authors, and does not necessarily represent the views of the National Science Foundation.

You may also be interested in Professor Baker's free video textbook Big Data and Education

All materials here are copyright of the individual instructors or their institutions, 2023-2024.
This work is licensed under a Creative Commons Attribution 4.0 International License.