Promoting Reflection Skills of Pre-Service Teachers—The Power of AI-Generated Feedback

Reflection skills are a key but challenging element in teacher training. Feedback on reflective writing assignments can improve reflection skills, but it is affected by challenges (high variability in judgments and time investment). AI-generated feedback offers many options. Therefore, the aim of this study was to examine the potential of AI-generated feedback compared to that provided by lecturers for developing reflective skills. A total of 93 randomly selected pre-service teachers (70% female) in a course at a German university wrote two reflections and received feedback from either lecturers or ChatGPT 4.0 based on the same prompts. Pre-service teachers’ written reflections were assessed, and an online questionnaire based on standard instruments was applied. Control variables included metacognitive learning strategies and reflection-related dispositions. Based on a linear mixed model, the main effects on reflective skills were identified for time (β^ = 0.41, p = 0.003) and feedback condition (β^ = −0.42, p = 0.032). Both forms of feedback similarly fostered reflective skills over time, with academic self-efficacy emerging as a pertinent disposition (β^ = 0.25, p = 0.014). The limitations of this study and implications for teacher training are discussed.

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Publication Details

Journal
Education Sciences
Published
2025-10-03
DOI
https://doi.org/10.3390/educsci15101315
Citations
2
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
4.96

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article

Promoting Reflection Skills of Pre-Service Teachers—The Power of AI-Generated Feedback

F. Hofmann, Michaela Gläser‐Zikuda, Lea Plößl, Tina-Myrica Daunicht
2 citations
Education Sciences
Educational Technology and Pedagogy
4.96
article

Promoting Reflection Skills of Pre-Service Teachers—The Power of AI-Generated Feedback

F. Hofmann, Michaela Gläser‐Zikuda, Lea Plößl, Tina-Myrica Daunicht
article en
2 citations

Abstract

Reflection skills are a key but challenging element in teacher training. Feedback on reflective writing assignments can improve reflection skills, but it is affected by challenges (high variability in judgments and time investment). AI-generated feedback offers many options. Therefore, the aim of this study was to examine the potential of AI-generated feedback compared to that provided by lecturers for developing reflective skills. A total of 93 randomly selected pre-service teachers (70% female) in a course at a German university wrote two reflections and received feedback from either lecturers or ChatGPT 4.0 based on the same prompts. Pre-service teachers’ written reflections were assessed, and an online questionnaire based on standard instruments was applied. Control variables included metacognitive learning strategies and reflection-related dispositions. Based on a linear mixed model, the main effects on reflective skills were identified for time (β^ = 0.41, p = 0.003) and feedback condition (β^ = −0.42, p = 0.032). Both forms of feedback similarly fostered reflective skills over time, with academic self-efficacy emerging as a pertinent disposition (β^ = 0.25, p = 0.014). The limitations of this study and implications for teacher training are discussed.

Education SciencesVol. 15(10)
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 5%
Educational Technology and Pedagogy
4.96
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Promoting Reflection Skills of Pre-Service Teachers—The Power of AI-Generated Feedback — F. Hofmann, Michaela Gläser‐Zikuda, et al. · Education Sciences (2025) | TGRS Research Map | TGRS