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Conrad Borchers; Paulo F. Carvalho; Meng Xia; Pinyang Liu; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2023
In numerous studies, intelligent tutoring systems (ITSs) have proven effective in helping students learn mathematics. Prior work posits that their effectiveness derives from efficiently providing eventually-correct practice opportunities. Yet, there is little empirical evidence on how learning processes with ITSs compare to other forms of…
Descriptors: Problem Solving, Intelligent Tutoring Systems, Mathematics Education, Learning Processes
Eglington, Luke G.; Pavlik, Philip I., Jr. – Grantee Submission, 2022
An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Processes, Individual Differences
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Automated scoring of student language is a complex task that requires systems to emulate complex and multi-faceted human evaluation criteria. Summary scoring brings an additional layer of complexity to automated scoring because it involves two texts of differing lengths that must be compared. In this study, we present our approach to automate…
Descriptors: Automation, Scoring, Documentation, Likert Scales
Metcalfe, Janet; Huelser, Barbie J. – Grantee Submission, 2020
Many recent studies have shown that memory for correct answers is enhanced when an error is committed and then corrected, as compared to when the correct answer is provided without intervening error commission. The fact that the kind of errors that produced such a benefit, in past research, were those that were semantically related to the correct…
Descriptors: Recall (Psychology), Memory, Learning Processes, Error Patterns
Metcalfe, Janet; Schwartz, Bennett L.; Bloom, Paul A. – Grantee Submission, 2017
Theories of study time allocation and of curiosity suggest that people are most engaged with and want to devote their time to materials that are not completely mastered but also are not so difficult that they might be impossible. Their curiosity is thought to be triggered by items that are almost known, or are in what is sometimes called theregion…
Descriptors: Recall (Psychology), Metacognition, Personality Traits, Response Style (Tests)
Metcalfe, Janet – Grantee Submission, 2017
Although error avoidance during learning appears to be the rule in American classrooms, laboratory studies suggest that it may be a counterproductive strategy, at least for neurologically typical students. Experimental investigations indicate that errorful learning followed by corrective feedback is beneficial to learning. Interestingly, the…
Descriptors: Error Patterns, Error Correction, Feedback (Response), Educational Benefits
Hershkovitz, Arnon; Baker, Ryan S. J. d.; Gobert, Janice; Wixon, Michael; Sao Pedro, Michael – Grantee Submission, 2013
In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…
Descriptors: Learning Analytics, Models, Learning Processes, Case Studies