Exploring AI-driven feedback as a cultural tool: a cultural-historical perspective on design of AI environments to support students' writing process
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This study draws on the cultural-historical perspectives of Vygotsky and Galperin to examine the role of AI-generated feedback within the Assessment for Learning (AfL) process in fostering students’ development as learners. By leveraging Galperin’s concept of cultural tools and the developmental role of human activity, elaborated in his dissertation written almost a hundred years ago, this study elucidates how this theoretical framework can enhance our understanding of the pedagogical value of individually tailored feedback from AI, ultimately contributing to human development and inspire the Design Principles (DPs) of AI-based educational technologies. Essay Assessment Technology (EAT), designed according to the suggested DPs, is presented to illustrate the application of AfL strategies in schools, highlighting its potential to enhance students’ learning and their development as learners.
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Emerging frameworks emphasize process-oriented assessment that documents iterative revision, reflective decision-making, and AI integration strategies rather than solely evaluating final products.
“Emerging frameworks emphasize process-oriented assessment that documents iterative revision, reflective decision-making, and AI integration strategies rather than solely evaluating final products (Engeness and Gamlem, 2025; Tseng and Lin, 2024; Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Engeness and Gamlem, 2025
The Role of Feedback in the Writing Process (page unavailable) calls for attention to revision and how students respond to feedback. The Empirical Snapshot and Concluding Reflections (pages unavailable) describe successive drafts, reflection on AI feedback, and guidance during writing rather than feedback only on completed work. The paper does not, however, describe an assessment framework that documents students’ reflective decisions or AI-integration strategies. (LLM, conf=0.84)
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Cited by
Sorted by citations
Abdellatif, M. S., Alshehri, M. A., Lamouchi, A., Rahmath, M., & Nemt-allah, M. A. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1809174
“Emerging frameworks emphasize process-oriented assessment that documents iterative revision, reflective decision-making, and AI integration strategies rather than solely evaluating final products (Engeness and Gamlem, 2025; Tseng and Lin, 2024; Wang, 2024).”
- Authors
- Engeness, I., & Gamlem, S. M.
- Affiliations
- Østfold University of Applied Sciences (NO)
- Volda University College (NO)
- Corresponding author
- Engeness, Irina
- Venue
- Integrative Psychological and Behavioral Science
- Published
- 2025-02-01
- Volume
- 59
- Issue
- 1
- Pages
- 23-23
- ISSN
- 1932-4502 (ISSN-L)
- 1936-3567
- PMC
- PMC11787257
- OpenAlex
- W4407060439
- Cited by
- 26
- References
- 14
- Citations by year
- 2026: 15 · 2025: 11
- FWCI
- 80.45
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Integrative Psychological and Behavioral Science (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Ostfold University College
- Topics
- Social Sciences › Education › Student Assessment and Feedback
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- AI-generated feedback, assessment for learning, cultural tools, Galperin, Vygotsky, historical-cultural theory, writing process, essay scoring, student development, personalized feedback
- MeSH terms
- Artificial Intelligence, Culture, Feedback, Humans, Learning, Students, Writing, Educational Technology
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