mlsanityData to 7 Oct 2026

Engaging with Massive Online Courses

arXiv 1403.3100 ↗First posted 12 Mar 2014cs.SI physics.soc-ph stat.MLcited by 20

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Abstract (arXiv)

The Web has enabled one of the most visible recent developments in education---the deployment of massive open online courses. With their global reach and often staggering enrollments, MOOCs have the potential to become a major new mechanism for learning. Despite this early promise, however, MOOCs are still relatively unexplored and poorly understood. In a MOOC, each student's complete interaction with the course materials takes place on the Web, thus providing a record of learner activity of unprecedented scale and resolution. In this work, we use such trace data to develop a conceptual framework for understanding how users currently engage with MOOCs. We develop a taxonomy of individual behavior, examine the different behavioral patterns of high- and low-achieving students, and investigate how forum participation relates to other parts of the course. We also report on a large-scale deployment of badges as incentives for engagement in a MOOC, including randomized experiments in which the presentation of badges was varied across sub-populations. We find that making badges more salient produced increases in forum engagement.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Mar 2014.

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Citing papers per year: 2021: 4; 2022: 4; 2023: 3; 2024: 8; 2025: 0; 2026: 1.

20 papers.

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  1. 2021Enhancing Knowledge Tracing via Adversarial Trainingcited by 30
  2. 2022Self-supervised Graph Learning for Long-tailed Cognitive Diagnosiscited by 13
  3. 2024Endowing Interpretability for Neural Cognitive Diagnosis by Efficient Kolmogorov-Arnold Networkscited by 12
  4. 2023Symbolic Cognitive Diagnosis via Hybrid Optimization for Intelligent Education Systemscited by 7
  5. 2023Counterfactual Monotonic Knowledge Tracing for Assessing Students' Dynamic Mastery of Knowledge Conceptscited by 5
  6. 2021LANA: Towards Personalized Deep Knowledge Tracing Through Distinguishable Interactive Sequencescited by 4
  7. 2022Automatic Context-Driven Inference of Engagement in HMI: A Surveycited by 4
  8. 2024DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosiscited by 4
  9. 2023Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture Searchcited by 2
  10. 2024Domain Generalizable Knowledge Tracing via Concept Aggregation and Relation-Based Attentioncited by 2
  11. 2024A Dual-Fusion Cognitive Diagnosis Framework for Open Student Learning Environmentscited by 2
  12. 2021Graph-based Exercise- and Knowledge-Aware Learning Network for Student Performance Predictioncited by 1
8 more
  1. 2022DIGMN: Dynamic Intent Guided Meta Network for Differentiated User Engagement Forecasting in Online Professional Social Platformscited by 1
  2. 2024Subgroup Discovery in MOOCs: A Big Data Application for Describing Different Types of Learnerscited by 1
  3. 2024Dual-State Personalized Knowledge Tracing with Emotional Incorporationcited by 1
  4. 2021MOOCRep: A Unified Pre-trained Embedding of MOOC Entitiescited by 0
  5. 2022Heterogeneous Line Graph Transformer for Math Word Problemscited by 0
  6. 2024Modeling and predicting students' engagement behaviors using mixture Markov modelscited by 0
  7. 2024Generalized Encouragement-Based Instrumental Variables for Counterfactual Regressioncited by 0
  8. 2026Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Educationcited by 0