ArticleIntegrative psychological & behavioral science2025
Exploring AI-Driven Feedback as a Cultural Tool: A Cultural-Historical Perspective on Design of AI Environments to Support Students' Writing Process.
Article in Integrative psychological & behavioral science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth.Frontiers in psychology · 2026Pooled it
- Mind Mapping in Orthodontic Education: A Two-Cohort Action-Research Study Exploring the Impact of Feedback on Student Learning and Perception.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Article
- Development, Network Analysis, and Validation of the Ethical-Spiritual Algorithmic Trust Calibration Scale (ES-ATCS): Exploring Teachers' Ethical and Spiritual Trust in AI Integration Within Jordanian Secondary Education.Journal of religion and health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.