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Kole Norberg; Husni Almoubayyed; Stephen Fancsali – International Educational Data Mining Society, 2025
Solving a math word problem (MWP) requires understanding the mathematical components of the problem and an ability to decode the text. For some students, lower reading comprehension skills may make engagement with the mathematical content more difficult. Readability formulas (e.g., Flesch Reading Ease) are frequently used to assess reading…
Descriptors: Mathematics Instruction, Word Problems (Mathematics), Problem Solving, Reading Skills
Wan-Chong Choi; Chan-Tong Lam; António José Mendes – International Educational Data Mining Society, 2025
Missing data presents a significant challenge in Educational Data Mining (EDM). Imputation techniques aim to reconstruct missing data while preserving critical information in datasets for more accurate analysis. Although imputation techniques have gained attention in various fields in recent years, their use for addressing missing data in…
Descriptors: Research Problems, Data Analysis, Research Methodology, Models
Bogdan Yamkovenko; Charlie A. R. Hogg; Maya Miller-Vedam; Phillip Grimaldi; Walt Wells – International Educational Data Mining Society, 2025
Knowledge tracing (KT) models predict how students will perform on future interactions, given a sequence of prior responses. Modern approaches to KT leverage "deep learning" techniques to produce more accurate predictions, potentially making personalized learning paths more efficacious for learners. Many papers on the topic of KT focus…
Descriptors: Algorithms, Artificial Intelligence, Models, Prediction
Juan D. Pinto; Luc Paquette – International Educational Data Mining Society, 2025
The increasing use of complex machine learning models in education has led to concerns about their interpretability, which in turn has spurred interest in developing explainability techniques that are both faithful to the model's inner workings and intelligible to human end-users. In this paper, we describe a novel approach to creating a…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Behavior, Models
Seehee Park; Danielle Shariff; Mohammad Amin Samadi; Nia Nixon; Sidney D’Mello – International Educational Data Mining Society, 2025
Collaborative Problem Solving (CPS) is a vital 21st-century skill that integrates social and cognitive processes to achieve shared goals. Despite its importance, understanding how communication dynamics shape individual learning outcomes in CPS tasks remains a challenge, particularly in virtual settings. To address this gap, this study analyzes…
Descriptors: Group Dynamics, Problem Solving, Teamwork, Undergraduate Students
Pranjli Khanna; Kaleb Mathieu; Kole Norberg; Husni Almoubayyed; Stephen E. Fancsali – International Educational Data Mining Society, 2025
Recent research on more comprehensive models of student learning in adaptive math learning software used an indicator of student reading ability to predict students' tendencies to engage in behaviors associated with so-called "gaming the system." Using data from Carnegie Learning's MATHia adaptive learning software, we replicate the…
Descriptors: Computer Software, Computer Uses in Education, Reading Difficulties, Reading Skills

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