A Framework for Explaining Teachers’ Diagnostic Judgements by Cognitive Modeling (DiaCoM)

By Katharina Loibl, Timo Leuders, T. Dörfler. 2020

121 citations recorded by the source corpus.

Abstract Research on diagnostic competencies of teachers nowadays raises the question which person or situational characteristics moderate judgement accuracy. Beside this correlational approach, a stronger interest in understanding the cognitive processes involved in the genesis of diagnostic judgements has emerged. To address the theoretical gap regarding cognitive processes underlying diagnostic judgements, we propose a framework, called DiaCoM (Explaining Teachers’ Diagnostic Judgements by Cognitive Modeling). It aims at supporting (existing or envisioned) research that strives to test cognitively oriented explanations for processes and products of diagnostic judgements of teachers.

Subfields: Artificial Intelligence, Developmental and Educational Psychology, Education

View Paper: https://www.semanticscholar.org/paper/c04d7009ceeab864eab789209c924666f2c0dd09

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. K. Schnitzler
2. Doris Holzberger
3. Tina Seidel

In Developmental and Educational Psychology

1. Doris Holzberger
2. Tina Seidel

In Education

1. Doris Holzberger
2. K. Schnitzler
3. Tina Seidel
4. J. Scheerens

Citations in the corpus

• All better than being disengaged: Student engagement patterns and their relations to academic self-concept and achievement (2020, background): “Thereby, teachers rely on the interpretation of observable information cues such as student participation (Loibl et al. 2020; Seidel et al. 2020).”