Where experience makes a difference: teachers' judgment accuracy and diagnostic reasoning regarding student learning characteristics

Front Psychol. 2024 Mar 7:15:1278472. doi: 10.3389/fpsyg.2024.1278472. eCollection 2024.

Abstract

The concept of teacher professional vision suggests that experienced teachers, compared to novice teachers, might be better at making accurate judgments of students' learning characteristics, which can be explained by their advanced reasoning in diagnostic situations. This study examines experienced and novice teachers' diagnoses of different student characteristic profiles: three inconsistent profiles (overestimating, uninterested, and underestimating) and two consistent profiles (strong and struggling). We examined both experienced (n = 19 in-service mathematics teachers) and novice teachers (n = 24 pre-service mathematics teachers) to determine the extent of differences in their judgment accuracy and their diagnostic reasoning about observable cues when diagnosing student profiles while watching a lesson video. ANOVA results indicate that experienced teachers generally achieved a higher judgment accuracy in diagnosing student profiles compared to novice teachers. Moreover, epistemic network analysis of observable cues in experienced and novice teachers' diagnostic reasoning showed that, compared to novice teachers, experienced teachers make more relations between a broader spectrum of both surface cues (e.g., a student's hand-raising behavior) and deep cues (e.g., a student being interested in the subject). Experienced teachers thereby construct more comprehensive and robust reasoning compared to novice teachers. The findings highlight how professional experience shapes teachers' professional skills, such as diagnosing, and suggest strategies for enhancing teacher training.

Keywords: expert-novice comparison; judgment accuracy; noticing; professional vision; reasoning; student characteristics.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The present research project was funded by the Deutsche Forschungsgemeinschaft (German Research Foundation, grant no. SE1397/7-3). The funders had no role in the study’s design, data collection and analysis, the decision to publish, or the preparation of the manuscript. The ENA online tool used in this study is funded by the National Science Foundation (DRL-2100320, DRL-2201723, DRL-2225240), the Wisconsin Alumni Research Foundation, and the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison. The presented opinions, findings, and conclusions do not reflect the views of the funding agencies, cooperating institutions, or other individuals.