Modeling Teachers’ Diagnostic Judgments by Bayesian Reasoning and Approximative Heuristics

• Published in: Research in Subject-matter Teaching and Learning (RISTAL) Vol. 4; no. 1; pp. 88 - 108
• Main Authors: Loibl, Katharina, Leuders, Timo
• Format: Journal Article
• Language: English
• Published: Vienna Sciendo 01.12.2021; De Gruyter Poland
• Subjects: Bayesian reasoning; computational simulation; diagnostic judgment; heuristic
• ISSN: 2616-7697
• DOI: 10.23770/rt1844

The diagnostic judgments teachers make can be regarded as inferences from manifest observable evidence on students’ behavior (e.g., responses to a task) to their latent traits (e.g., misconceptions). The judgment process can be modeled by Bayesian reasoning. We use this framework to analyze the situ...