Editorial Acknowledgment


This issue features seven articles that will be presented at the 17th  International Conference on Educational Data Mining (EDM 2024) in the JEDM Journal Track at EDM 2024 that will take place in Atlanta, USA, July 14-17, 2024. This issue features as well three regular articles and three articles selected by the program chairs of the 16th  International Conference on Educational Data Mining (EDM 2023); these articles are extended versions of papers presented at EDM 2022, and that could not be published in the corresponding special section of the December Issue of JEDM in 2023.


For the tenth time, EDM 2024 will hold a Journal track allowing papers submitted to JEDM to be presented at the conference. The JEDM Track at EDM 2024 received 17 submissions, among which seven made it to the final stage in time for publication in this issue. We are pleased to publish the following works.


Yang Shi, Robin Schmucker, Keith Tran, John Bacher, Kenneth Koedinger, Thomas Price, Min Chi, and Tiffany Barnes address the knowledge component (KC) attribution problem among computer programming students. This refers to the difficulty in attributing student errors to specific KCs, as programming requires students to practice several KCs at the same time. Their supervised code2vec model trained on expert-defined KCs achieved AUCs of 75% or higher. Subsequent experiments showed how the inclusion of submission correctness and learning curves into the model can help with KC attribution.


The paper Automated Evaluation of Classroom Instructional Support with LLMs and BoWs: Connecting Global Predictions to Specific Feedback by Jacob Whitehill and Jennifer LoCasale-Crouch compares the use of Large Language Models (LLMs) and Bag of Words (BoW) models to analyze the presence of Instructional Support in teachers’ speech and estimate a global CLassroom Assessment Scoring System (CLASS) score. One finding is that “LLMs generally yield slightly greater accuracy than BoW, though the best models often combined features extracted from both LLM and BoW”.


In the paper, An Approach to Improve k-Anonymization Practices in Educational Data Mining Frank Stinar, Zihan Xiong, and Nigel Bosch propose a framework to k-anonymize students' data while preserving the utility of the dataset for data mining tasks. Their evaluation shows that the downstream machine learning accuracy is improved by 30.59% when using their framework over baseline data anonymization. 


The paper Exploring the Impact of Symbol Spacing and Problem Sequencing on Arithmetic

Performance: An Educational Data Mining Approach by Avery Harrison Closser, Anthony F. Botelho and Jenny Yun-Chen Chan revisit an earlier study on manipulating the spacing between symbols in arithmetic expressions and its effect on students’ performance.  They find that problem composition and problem order may have caused unintended effects in the earlier study and draw methodological implications for educational researchers.

Kirk Vanacore, Ashish Gurung, Adam Sales, and Neil Heffernan build on previous research to test various ways of proactively discouraging students from gaming the system. In this study they compare the effects delaying hint access to the effects of gamification (not to be confused with gaming the system). Specifically, they combine established methods in a novel way, using a fully latent principal stratification for causal inference to examine detectors of gaming the system.


John Stamper, Steven Moore, Carolyn P. Rose, Philip I. Pavlik, Jr., and Kenneth Koedinger present LearnSphere, a web-based data infrastructure that integrates previously siloed educational data and analytic resources, one of which is DataShop. In an atmosphere that is increasingly concerned about AI ethics, LearnSphere’s structure and in so doing shows how this tool contributes to model transparency and explainability by enabling reproducibility and replicability of experiments.


Md Akib Zabed Khan and Agoritsa Polyzou discuss a recommendation system that helps students manage their academic load. The system suggests courses from the upcoming semester that are best suited to be taken together. The authors use information from past students about co-taken courses as basis for establishing the relationship between courses and their compatibility. The authors found that this session-based method for arriving at recommendations outperforms existing approaches based on course popularity, association, similarity, and others.



Maria Mercedes T. Rodrigo (Chair JEDM@EDM2024), Ateneo de Manila University, PHILIPPINES

Agathe Merceron (Chair JEDM@EDM2024), Berlin University of Applied Sciences, GERMANY

Jaclyn Ocumpaugh (Chair JEDM@EDM2024), University of Pennsylvania, USA


The Editor and Associate Editors would like to warmly thank the editorial board and colleagues who kindly served as reviewers in 2023. Their professionalism and support are much appreciated.


Editorial Board

Tiffany Barnes, North Carolina State University, USA
François Bouchet, Université Pierre et Marie Curie, FRANCE

Michel Desmarais, Polytechnique Montréal, CANADA
Stephen E. Fancsali, Carnegie Learning, Inc., USA
Dragan Gasevic, Monash University, AUSTRALIA

Neil Heffernan, Worcester Polytechnic Institute, USA
Jelena Jovanovic, University of Belgrade, SERBIA
Kenneth R. Koedinger, Carnegie Mellon University, USA
Irena Koprinska, University of Sydney, AUSTRALIA
Andrew Lan, University of Massachusetts at Amherst, USA
Collin F. Lynch, North Carolina State University, USA
Bruce M. McLaren, Carnegie Mellon University, USA

Caitlin Mills, University of Minnesota, USA
Tanja Mitrovic, University of Canterbury, NEW ZEALAND
Jack Mostow, Carnegie Mellon University, USA
Zachary A. Pardos, University of California at Berkeley, USA
Philip Irvin Pavlik Jr., University of Memphis, USA
Niels Pinkwart, Humboldt-Universität zu Berlin, GERMANY
Kaśka Porayska-Pomsta, University College London, UNITED KINGDOM
Carolyn Penstein-Rosé, Carnegie Mellon University, USA

Maria Mercedes T. Rodrigo, Ateneo de Manila University, PHILIPPINES

Cristobal Romero, University of Cordoba, SPAIN
Elizabeth Rowe, TERC, USA

Amal Zouaq, Polytechnique Montréal, CANADA


Special Reviewers

Deepak Agarwal, Khan Academy, INDIA

Juan Miguel Andres-Bray, McGraw Hill Education, USA

Michelle Banawan, Asian Institute of Management, PHILIPPINES

Johannes Berens, University of Wuppertal, GERMANY

Anthony Botelho, University of Florida, USA

Javier Bravo Agapito, Universidad Complutense de Madrid, SPAIN

Carrie Demans Epp, University of Alberta, CANADA

Luke Eglington, Amplify Education Inc., USA

Lief Esbenshade, Google, LLC, USA


April Galyardt, University of Georgia, USA

Josh Gardner, University of Washington, USA

Ilya Goldin, Phenom People, USA

Qiwei He, Georgetown University, USA

Martin Hlosta, Fernfachhochschule, SWITZERLAND

Paul Hur, University of Illinois Urbana–Champaign, USA

Stephen Hutt, University of Denver, USA

Paul Inventado, California State University Fullerton, USA

Qinjin Jia, North Carolina State University, USA

Weijie Jiang, University of California,  Berkeley, USA

Song Ju, North Carolina State University, USA

Mohammad Khajah, Kuwait Institute for Scientific Research, KUWAIT

Sebastien Lalle, Sorbonne University, FRANCE

Renza Campagni, University of Florence, ITALY

Amar Lalwani, IIIT-Bangalore, INDIA

Morgan Lee, Worcester Polytechnic Institute, USA

Qi Liu, University of Science and Technology of China, CHINA

Xuesong Lu, East China Normal University, CHINA

Christopher J. MacLellan, Georgia Institute of Technology, USA

Varun Mandalapu, University of Maryland Baltimore County, USA

Rubén Manrique, Universidad de los Andes, COLOMBIA

Roberto Martinez-Maldonado, University of Melbourne, AUSTRALIA

Mirko Marras, University of Cagliari, ITALY

Tanya Nazaretsky, EPFL, SWITZERLAND

Jaclyn Ocumpaugh, University of Pennsylvania, USA

Benjamin Paassen, University Bielefeld, GERMANY

Shalini Pandey, Facebook, USA

Seyed Parsa Neshaei, EPFL, SWITZERLAND

Philip Irvin Pavlik Jr., University of Memphis, USA

Radek Pelanek, Masaryk University Brno, CZECH REPUBLIC

Juan Pinto, University of Illinois Urbana–Champaign, USA

Agoritsa Polyzou, Florida International University, USA


Eloi Puertas, Universidad de Barcelona, SPAIN

Emanuel Queiroga, Instituto Federal Sul-rio-grandense, BRASIL


Adam C. Sales, Worcester Polytechnic Institute, USA

Alexander Scarlatos, University of Massachusetts - Amherst, USA

Sabine Seufert, University St. Gallen, SWITZERLAND

Yang Shi, North Carolina State University, USA

Antonette Shibani, "University of Technology,  Sydney", AUSTRALIA

Heiner Stuckenschmidt, University of Mannheim, GERMANY

S Supraja, Nanyang Technological University, SINGAPORE


Ange Tato, École de Technologie Supérieure, CANADA

Stefan Trausan-Matu, University Politehnica of Bucharest and Institute of Artificial Intelligence of the Romanian Academy, ROMANIA

Maomi Ueno, University of Electro-Communications,  Chofugaoka, JAPAN

Kirk Vanacore, Worcester Polytechnic Institute, USA

Kerstin Wagner, Berlin University of Applied Sciences, GERMANY

Tianqi Wang, University at Buffalo, USA

Jacob Whitehill, Worcester Polytechnic Institute, USA

Renzhe Yu, Columbia University, USA

Jifan Yu, Tsinghua University, CHINA

Amelia Zafra Gómez, University of Córdoba, SPAIN

Guojing Zhou, University of Colorado Boulder, USA

Jia Zhu, "Zhejiang Normal University,  Jinhua,  China", CHINA


Agathe Merceron (Editor), Berlin University of Applied Sciences, GERMANY

Ryan S. Baker (Associate Editor), University of Pennsylvania, USA

Min Chi (Associate Editor), North Carolina State University, USA

Andrew M. Olney (Associate Editor and Editor 2017-2021), University of Memphis, USA

Luc Paquette (Associate Editor), University of Illinois at Urbana-Champaign, USA

Anna Rafferty (Associate Editor), Carleton College, USA

Olga C. Santos (Associate Editor), Universidad Nacional de Educación a Distancia, SPAIN

Kalina Yacef (Associate Editor and Founding Editor, 2009-2013), University of Sydney, AUSTRALIA