Handbook of Educational Data Mining

By Cristóbal Romero, Sebastián Ventura, Mykola Pechenizkiy, R. Baker. 2010

456 citations recorded by the source corpus.

Preface, Joseph E. Beck Introduction, Cristobal Romero, Sebastian Ventura, Mykola Pechenizkiy, and Ryan Baker Basic Techniques, Surveys, and Tutorials Visualization in Educational Environments, Riccardo Mazza Basics of Statistical Analysis of Interactions Data from Web-Based Learning Environments, Judy Sheard A Data Repository for the EDM Community: The PSLC DataShop, Kenneth R. Koedinger, Ryan Baker, Kyle Cunningham, Alida Skogsholm, Brett Leber, and John Stamper Classifiers for EDM, Wilhelmiina Hamalainen and Mikko Vinni Clustering Educational Data, Alfredo Vellido, Felix Castro, and Angela Nebot Association Rule Mining in Learning Management Systems, Enrique Garcia, Cristobal Romero, Sebastian Ventura, Carlos de Castro, and Toon Calders Sequential Pattern Analysis of Learning Logs: Methodology and Applications, Mingming Zhou, Yabo Xu, John C. Nesbit, and Philip H. Winne Process Mining from Educational Data, Nikola Trcka, Mykola Pechenizkiy, and Wil van der Aalst Modeling Hierarchy and Dependence among Task Responses in EDM, Brian W. Junker Case Studies Novel Derivation and Application of Skill Matrices: The q-Matrix Method, Tiffany Barnes EDM to Support Group Work in Software Development Projects, Judy Kay, Irena Koprinska, and Kalina Yacef Multi-Instance Learning versus Single-Instance Learning for Predicting the Student's Performance, Amelia Zafra, Cristobal Romero, and Sebastian Ventura A Response-Time Model for Bottom-Out Hints as Worked Examples, Benjamin Shih, Kenneth R. Koedinger, and Richard Scheines Automatic Recognition of Learner Types in Exploratory Learning Environments, Saleema Amershi and Cristina Conati Modeling Affect by Mining Students' Interactions within Learning Environments, Manolis Mavrikis, Sidney D'Mello, Kaska Porayska-Pomsta, Mihaela Cocea, and Art Graesser Measuring Correlation of Strong Symmetric Association Rules in Educational Data, Agathe Merceron and Kalina Yacef Data Mining for Contextual Educational Recommendation and Evaluation Strategies, Tiffany Y. Tang and Gordon G. McCalla Link Recommendation in E-Learning Systems Based on Content-Based Student Profiles, Daniela Godoy and Analia Amandi Log-Based Assessment of Motivation in Online Learning, Arnon Hershkovitz and Rafi Nachmias Mining Student Discussions for Profiling Participation and Scaffolding Learning, Jihie Kim, Erin Shaw, and Sujith Ravi Analysis of Log Data from a Web-Based Learning Environment: A Case Study, Judy Sheard Bayesian Networks and Linear Regression Models of Students' Goals, Moods, and Emotions, Ivon Arroyo, David G. Cooper, Winslow Burleson, and Beverly P. Woolf Capturing and Analyzing Student Behavior in a Virtual Learning Environment: A Case Study on Usage of Library Resources, David Masip, Julia Minguillon, and Enric Mor Anticipating Student's Failure as soon as Possible, Claudia Antunes Using Decision Trees for Improving AEH Courses, Javier Bravo, Cesar Vialardi, and Alvaro Ortigosa Validation Issues in EDM: The Case of HTML-Tutor and iHelp, Mihaela Cocea and Stephan Weibelzahl Lessons from Project LISTEN's Session Browser, Jack Mostow, Joseph E. Beck, Andrew Cuneo, Evandro Gouvea, Cecily Heiner, and Octavio Juarez Using Fine-Grained Skill Models to Fit Student Performance with Bayesian Networks, Zachary A. Pardos, Neil T. Heffernan, Brigham S. Anderson, and Cristina L. Heffernan Mining for Patterns of Incorrect Response in Diagnostic Assessment Data, Tara M. Madhyastha and Earl Hunt Machine-Learning Assessment of Students' Behavior within Interactive Learning Environments, Manolis Mavrikis Learning Procedural Knowledge from User Solutions to Ill-Defined Tasks in a Simulated Robotic Manipulator, Philippe Fournier-Viger, Roger Nkambou, and Engelbert Mephu Nguifo Using Markov Decision Processes for Automatic Hint Generation, Tiffany Barnes, John Stamper, and Marvin Croy Data Mining Learning Objects, Manuel E. Prieto, Alfredo Zapata, and Victor H. Menendez An Adaptive Bayesian Student Model for Discovering the Student's Learning Style and Preferences, Cristina Carmona, Gladys Castillo, and Eva Millan Index

Subfields: Computer Science Applications

View Paper: https://www.semanticscholar.org/paper/121354c8a91d0e261a8e0c4cdc44d20f00d2c18d

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Citations in the corpus

A reference model for learning analytics (2012, background): “…several EDM workshops which have led to the establishment of an annual International Conference on Educational Data Mining in 2008 and the appearance of the Journal of Educational Data Mining (JEDM) and specific books on EDM, such as ‘The Handbook of Educational Data Mining’ (Romero et al., 2010a).”
Process mining techniques for analysing patterns and strategies in students’ self-regulated learning (2013, methodology): “Process mining (PM) refers to methods of data mining (Robero et al. 2010) that build on the notion of a process model.”
A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques (2021, background): “According to information provided in [1], the EDM discipline deals with exploring, researching, and implementing Data Mining (DM) methods.”