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Denis Shchepakin; Sreecharan Sankaranarayanan; Dawn Zimmaro – International Educational Data Mining Society, 2024
Bayesian Knowledge Tracing (BKT) is a probabilistic model of a learner's state of mastery for a knowledge component. The learner's state is a "hidden" binary variable updated based on the correctness of the learner's responses to questions corresponding to that knowledge component. The parameters used for this update are inferred/learned…
Descriptors: Algorithms, Bayesian Statistics, Probability, Artificial Intelligence
Wang, Ling Ling; Jian, Sun Xiao; Liu, Yan Lou; Xin, Tao – Applied Measurement in Education, 2023
Cognitive diagnostic assessment based on Bayesian networks (BN) is developed in this paper to evaluate student understanding of the physical concept of buoyancy. we propose a three-order granular-hierarchy BN model which accounts for both fine-grained attributes and high-level proficiencies. Conditional independence in the BN structure is tested…
Descriptors: Bayesian Statistics, Networks, Cognitive Measurement, Diagnostic Tests
Min Qi; Xinyang Hu; Hualin Bi – Journal of Baltic Science Education, 2024
The redox reaction is a core concept of upper-secondary school chemistry curriculum. Accurate diagnosis of students' conceptual understanding of the redox reaction from a cognitive structure perspective is critical for enhancing their understanding of chemical concepts. This study utilized Bayesian networks to investigate the cognitive structures…
Descriptors: Bayesian Statistics, Cognitive Measurement, Diagnostic Tests, Cognitive Structures
Kang, Jina; Baker, Ryan; Feng, Zhang; Na, Chungsoo; Granville, Peter; Feldon, David F. – Instructional Science: An International Journal of the Learning Sciences, 2022
Threshold concepts are transformative elements of domain knowledge that enable those who attain them to engage domain tasks in a more sophisticated way. Existing research tends to focus on the identification of threshold concepts within undergraduate curricula as challenging concepts that prevent attainment of subsequent content until mastered.…
Descriptors: Fundamental Concepts, Bayesian Statistics, Learning Processes, Research Skills
Abu-Ghazalah, Rashid M.; Dubins, David N.; Poon, Gregory M. K. – Applied Measurement in Education, 2023
Multiple choice results are inherently probabilistic outcomes, as correct responses reflect a combination of knowledge and guessing, while incorrect responses additionally reflect blunder, a confidently committed mistake. To objectively resolve knowledge from responses in an MC test structure, we evaluated probabilistic models that explicitly…
Descriptors: Guessing (Tests), Multiple Choice Tests, Probability, Models
Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
Sarah Bichler; Michael Sailer; Elisabeth Bauer; Jan Kiesewetter; Hanna Härtl; Martin R. Fischer; Frank Fischer – European Journal of Psychology of Education, 2024
Teachers routinely observe and interpret student behavior to make judgements about whether and how to support their students' learning. Simulated cases can help pre-service teachers to gain this skill of diagnostic reasoning. With 118 pre-service teachers, we tested whether participants rate simulated cases presented in a serial-cue case format as…
Descriptors: Clinical Diagnosis, Abstract Reasoning, Simulation, Case Method (Teaching Technique)

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