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Picones, Gio; PaaBen, Benjamin; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2022
In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…
Descriptors: Prediction, Academic Achievement, Learning Analytics, Concept Mapping
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Slater, Stefan; Baker, Ryan – Distance Education, 2019
Considerable attention has been given to methods for knowledge estimation, a category of methods for automatic assessment of a student's degree of skill mastery or knowledge at a specific time. Knowledge estimation is frequently used to make decisions about when a student has reached mastery and is ready to advance to new material, but there has…
Descriptors: Prediction, Mastery Learning, Academic Achievement, Bayesian Statistics
Kristina K. Wong – ProQuest LLC, 2021
An acquisition criterion, more commonly known as "mastery criterion" is an instructor-established standard of performance that may signal the acquisition of a novel skill or the conclusion of a phase of intervention. When teaching new behaviors, researchers and practitioners in the field of Applied Behavior Analysis (ABA) apply some type…
Descriptors: Mastery Learning, Skill Development, Academic Achievement, Evaluation Criteria
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Amukune, Stephen; Calchei, Marcela; Józsa, Krisztián – Electronic Journal of Research in Educational Psychology, 2021
Introduction: The current focus of empirical studies demonstrates the significance of mastery motivation in child development, academic achievement and school success. Consequently, it is critical to have reliable and valid tools to measure this important variable accurately. The Preschool version of the Dimensions of Mastery Questionnaire (DMQ)…
Descriptors: Mastery Learning, Child Development, Academic Achievement, Accuracy
Rollinson, Joseph; Brunskill, Emma – International Educational Data Mining Society, 2015
At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…
Descriptors: Prediction, Models, Educational Policy, Intelligent Tutoring Systems