CausalEDM: Linking Innovations in Instructional Design and the Complex Behaviors that Underlie Learning Processes and Outcomes

Causal inference is becoming a critical focus within the field of Educational Data Mining (EDM), providing insights into how instructional innovations influence learning behaviors and outcomes. The CausalEDM workshop at EDM 2025 aims to synthesize past research, showcase ongoing work, and explore future directions in causal inference methodologies. This workshop will feature a retrospective on causal research in EDM, highlighting advancements in experimental design, effect heterogeneity, and quasi-experimental approaches. Discussions will include the methods for estimating the impact of Generative AI on student engagement, the integration of machine learning in causal modeling, and emerging methodological challenges. The event will include expert panels, paper presentations, and lightning talks, fostering collaboration between causal inference specialists and the broader EDM community. Through these discussions, the workshop seeks to explore causal methodologies, expand their applications, and address key research gaps in understanding the interplay between instructional design and learning processes.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-12
DOI
https://doi.org/10.5281/zenodo.15870314
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

CausalEDM: Linking Innovations in Instructional Design and the Complex Behaviors that Underlie Learning Processes and Outcomes

Zenodo (CERN European Organization for Nuclear Research)
Online Learning and Analytics
article

CausalEDM: Linking Innovations in Instructional Design and the Complex Behaviors that Underlie Learning Processes and Outcomes

article en

Abstract

Causal inference is becoming a critical focus within the field of Educational Data Mining (EDM), providing insights into how instructional innovations influence learning behaviors and outcomes. The CausalEDM workshop at EDM 2025 aims to synthesize past research, showcase ongoing work, and explore future directions in causal inference methodologies. This workshop will feature a retrospective on causal research in EDM, highlighting advancements in experimental design, effect heterogeneity, and quasi-experimental approaches. Discussions will include the methods for estimating the impact of Generative AI on student engagement, the integration of machine learning in causal modeling, and emerging methodological challenges. The event will include expert panels, paper presentations, and lightning talks, fostering collaboration between causal inference specialists and the broader EDM community. Through these discussions, the workshop seeks to explore causal methodologies, expand their applications, and address key research gaps in understanding the interplay between instructional design and learning processes.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 46%
Online Learning and Analytics
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