Image de couverture de livre

Uncovering Student Engagement Patterns in Moodle with Interpretable Machine Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Johnston, Laura J., Griffin, Jim E., Manolopoulou, Ioanna, Jendoubi, Takoua
Format:	Preprint
Publié:	2024
Sujets:	Computers and Society
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A real-time metric of online engagement monitoring
par: Johnston, Laura J., et autres
Publié: (2025)

Evaluating Pedagogical Incentives in Undergraduate Computing: A Mixed Methods Approach Using Learning Analytics
par: Johnston, Laura J., et autres
Publié: (2024)

Enhancing Engagement and Learning in Computing Education: Automated Moodle-Based Problem-Solving Assessments
par: Jayasekara, Charith, et autres
Publié: (2025)

Predicting and Understanding College Student Mental Health with Interpretable Machine Learning
par: Chowdhury, Meghna Roy, et autres
Publié: (2025)

Moodle Usability Assessment Methodology using the Universal Design for Learning perspective
par: Montes, Rosana, et autres
Publié: (2024)

Uncovering Students' Inquiry Patterns in GenAI-Supported Clinical Practice: An Integration of Epistemic Network Analysis and Sequential Pattern Mining
par: Wei, Jiameng, et autres
Publié: (2025)

Global Patterns in Student Stress and Academic Performance: A Machine Learning Study Using PISA 2022
par: Ghazanchyan, Ani, et autres
Publié: (2026)

Engineering Students' Self-Efficacy, Perceptions, and Performance in a Flipped CS1 Course
par: Pitts, Griffin, et autres
Publié: (2026)

Assessment of Personalized Learning in Immersive and Intelligent Virtual Classroom on Student Engagement
par: Weng, Ying, et autres
Publié: (2025)

GPT-4 as a Homework Tutor can Improve Student Engagement and Learning Outcomes
par: Vanzo, Alessandro, et autres
Publié: (2024)

Tracing GenAI Literacy: Uncovering Student-AI Interaction Patterns in Academic Writing through Epistemic Network Analysis
par: Chen, Angxuan, et autres
Publié: (2026)

Bayesian Nonparametric Models for Multiple Raters: a General Statistical Framework
par: Mignemi, Giuseppe, et autres
Publié: (2024)

The Conspiracy Money Machine: Uncovering Telegram's Conspiracy Channels and their Profit Model
par: Imperati, Vincenzo, et autres
Publié: (2023)

Enhancing Student Engagement in Large-Scale Capstone Courses: An Experience Report
par: Shakil, Asma, et autres
Publié: (2024)

Student-AI Interaction in an LLM-Empowered Learning Environment: A Cluster Analysis of Engagement Profiles
par: Hao, Zhanxin, et autres
Publié: (2025)

Tracing the Unseen: Uncovering Human Trafficking Patterns in Job Listings
par: Zhou, Siyi, et autres
Publié: (2024)

Starting Seatwork Earlier as a Valid Measure of Student Engagement
par: Gurung, Ashish, et autres
Publié: (2025)

Translating Machine Learning Interpretability into Clinical Insights for ICU Mortality Prediction
par: Liao, Ling, et autres
Publié: (2025)

The Impact of Live Polling Quizzes on Student Engagement and Performance in Computer Science Lectures
par: Zhao, Xingyu
Publié: (2023)

That's Not the Feedback I Need! -- Student Engagement with GenAI Feedback in the Tutor Kai
par: Jacobs, Sven, et autres
Publié: (2025)

Excited, Skeptical, or Worried? A Multi-Institutional Study of Student Views on Generative AI in Computing Education
par: Alpizar-Chacon, Isaac, et autres
Publié: (2025)

Signals in the Noise: Decoding Unexpected Engagement Patterns on Twitter
par: Yu, Yulin, et autres
Publié: (2025)

Do Students Learn Better Together? Teaching Design Patterns and the OSI Model with the Aronson Method
par: Martin, Daniel San, et autres
Publié: (2025)

Reflection-Satisfaction Tradeoff: Investigating Impact of Reflection on Student Engagement with AI-Generated Programming Hints
par: Choi, Heeryung, et autres
Publié: (2025)

BoundarEase: Fostering Constructive Community Engagement to Inform More Equitable Student Assignment Policies
par: Overney, Cassandra, et autres
Publié: (2025)

Interpretable Machine Learning for Resource Allocation with Application to Ventilator Triage
par: Grand-Clément, Julien, et autres
Publié: (2021)

Towards Public Administration Research Based on Interpretable Machine Learning
par: Liu, Zhanyu, et autres
Publié: (2026)

Student Engagement with GenAI's Tutoring Feedback: A Mixed Methods Study
par: Jacobs, Sven, et autres
Publié: (2025)

Pre-trained Transformer Uncovers Meaningful Patterns in Human Mobility Data
par: Najjar, Alameen
Publié: (2024)

Personalized Worked Example Generation from Student Code Submissions Using Pattern-based Knowledge Components
par: Pitts, Griffin, et autres
Publié: (2026)

Teaching Students to Question the Machine: An AI Literacy Intervention Improves Students' Regulation of LLM Use in a Science Task
par: Clerc, O., et autres
Publié: (2026)

Machine Learning Algorithms for Detecting Mental Stress in College Students
par: Singh, Ashutosh, et autres
Publié: (2024)

Evaluating AI-Powered Learning Assistants in Engineering Higher Education: Student Engagement, Ethical Challenges, and Policy Implications
par: Sajja, Ramteja, et autres
Publié: (2025)

An XAI Social Media Platform for Teaching K-12 Students AI-Driven Profiling, Clustering, and Engagement-Based Recommending
par: Pope, Nicolas, et autres
Publié: (2024)

Uncovering Intervention Opportunities for Suicide Prevention with Language Model Assistants
par: Ranjit, Jaspreet, et autres
Publié: (2025)

Teachers' Vocal Expressions and Student Engagement in Asynchronous Video Learning
par: Suen, Hung-Yue, et autres
Publié: (2026)

The Impact of Virtual Laboratories on Active Learning and Engagement in Cybersecurity Distance Education
par: Kebande, Victor R.
Publié: (2024)

ETHNO-DAANN: Ethnographic Engagement Classification by Deep Adversarial Transfer Learning
par: Kamal, Rossi
Publié: (2023)

Exploring Student Interactions with AI-Powered Learning Tools: A Qualitative Study Connecting Interaction Patterns to Educational Learning Theories
par: Muzumdar, Prathamesh, et autres
Publié: (2025)

How to Manage My Data? With Machine--Interpretable GDPR Rights!
par: Esteves, Beatriz, et autres
Publié: (2024)