たまに追加される論文メモ
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Updated
Dec 13, 2025 - HTML
たまに追加される論文メモ
⚙️ Ralph, the ultimate Learning Record Store (and more!) for your learning analytics
My Learning Analytics (MyLA)
EdOptimize is an open-source learning analytics platform for K-12 digital learning systems.
An AI-driven productivity tracking app built with Python, Streamlit, SQLite, and Machine Learning. It logs and analyzes study sessions, predicts productivity using Random Forest models, and visualizes key insights to help learners improve focus, habits, and overall academic efficiency.
The collection of related papers and resources for the paper Time Series Analysis for Education: Methods, Applications, and Future Directions.
Terracotta (a portmanteau of Tool for Education Research with RAndomized COnTrolled TriAls) is a plug-in to the learning management system that allows the contents of online assignments to be differentiated for experimental treatment variations, and to be assigned randomly to different groups of students. Terracotta also enables privacy protecti…
This workshop introduces participants to the Learning Analytics (LA), and provides a brief overview of LA methodologies, literature, applications, and ethical issues as they relate to STEM education.
Scikit-learn style implementation of Deep Knowledge Tracing models based on pytorch.
Transition Network Analysis R package
An annotated corpus of discussion forum threads from Massive Open Online Courses.
Text Mining in Education Learning Labs demonstrate how text mining can be applied in STEM education research and provide LASER Institute scholars hands-on experience with popular techniques for collecting, processing, and analyzing text-based data.
This is a work-in-progress repository for a deep learning based moderator agent for critical discourse in discussion forums.
Aggregation of GitHub activities and transformation in Pandas Dataframes
Personalized Learning System
Module Progress is a Python script and Tableau workbook for visualizing students progress in a Canvas course.
Research implementation on students' success with Data Analytics
Helper functions to analyze Moodle data
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