Exploring AI-Driven Feedback as a Cultural Tool
A Cultural-Historical Perspective on Design of AI Environments to Support Students’ Writing Process
Bibliographic Data
| ID | 6071802 |
|---|---|
| Authors | Irina Engene (0000-0001-5948-4992, Østfold University of Applied Sciences, corresponding author), Siv M Gamlem (0000-0002-6523-0486, Volda University College) |
| Year | 2025 |
| Volume | 59 |
| Issue | 1 |
| Pages | 23-23 |
| Publication date | 2025-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Integrative Psychological and Behavioral Science (JOURNAL) |
| Journal identifiers | ISSN: 1932-4502 • E-ISSN: 1936-3567 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s12124-025-09894-8 |
| PMID | 39891855 |
| OpenAlex | W4407060439 |
| Language | EN |
| Citations received | 10 |
| References cited | 51 |
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
Cognitive science · Engineering ethics · Mathematics education · Perspective (graphical · Process (computing · Value (mathematics · Computer Science · Educational Assessment and Improvement · Engineering · Innovative Education and Learning Practices · Psychology · Student Assessment and Feedback · Artificial Intelligence
A sociocultural perspective on the role of AI in shaping intercultural communicative competence in L2 education
Integrating AI into Spherical Video-Based Virtual Reality for Teaching Applications in Elementary Chinese Writing Education
Leapfrogging effect hypothesis
Students' perceptions and outcome of teacher feedback
When AI only asks
Investigating AI Chatbots’ Role in Online Learning and Digital Agency Development
Agency in Digital Education
A Study of AI ‐Supported Cross‐Cultural Learning and Its Influence on Cross‐Cultural Understanding, Learning Behaviour and Writing Performance of Learners in Authentic Contexts
Development, Network Analysis, and Validation of the Ethical–Spiritual Algorithmic Trust Calibration Scale (ES-ATCS)
Trust, resistance, and transformation
Psychological Significance and Difference Between Tools Use by Humans and Animals
Handbook of Formative Assessment
Mind in Society
A systematic review of AI-based automated written feedback research
Using automated written corrective feedback in the writing classrooms
Developing the theory of formative assessment
The Development of Academic Self-Regulation
A typology of written corrective feedback types
Feedback and Self-Regulated Learning
Formative assessment and the design of instructional systems
The Collected Works of L. S. Vygotsky
Do we still need teachers? Navigating the paradigm shift of the teacher's role in the AI era
Same assignment—two different feedback contexts
Challenges and opportunities for classroom-based formative assessment and AI
Using automated corrective feedback tools in language learning
From Inquiry-Based Science Education to the Approach Based on Scientific Practices
Developing teachers’ digital identity
State of the art and practice in AI in education
Learning for the future
Tools and Signs in Massive Open Online Courses
The power of internal feedback
The development of student feedback literacy
Written corrective feedback from sociocultural theoretical perspectives
Investigating Self-Regulation and Motivation
The Power of Feedback
| Unique citing works | 10 |
|---|---|
| Citations per year | 10 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 9 |