Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)

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AI-Enabled Feedback Systems in Management Education: Advancing Pedagogical Innovation and Learning Outcomes

Authors
Veto Dey1, *, M. Thamizhselvi2, P. C. Libeesh3, Priyanka Joshi4
1Associate Professor, The Oxford College of Science, Arts, Commerce and Management, Bangalore, Karnataka, India
2Associate Professor, NSB Academy, Bangalore, Karnataka, India
3Assistant Professor, NSB World Business School, Bangalore, Karnataka, India
4Assistant Professor, The Oxford College of Science, Arts Commerce and Management, Bangalore, Karnataka, India
*Corresponding author. Email: drvetodeyoxford@gmail.com
Corresponding Author
Veto Dey
Available Online 19 April 2026.
DOI
10.2991/978-2-38476-559-1_9How to use a DOI?
Keywords
AI in education; feedback systems; MBA pedagogy; ChatGPT; Grammarly; Microsoft Copilot; academic writing
Abstract

The integration of Artificial Intelligence (AI) in higher education is reshaping formative feedback practices, particularly in academic writing. AI-enabled feedback systems—such as ChatGPT, Grammarly, and Microsoft Copilot—offer scalable, real-time assistance that enhances writing fluency, coherence, and revision efficiency. However, concerns around ethical use, academic integrity, and pedagogical alignment persist. This study investigates the adoption, perception, and effectiveness of AI-assisted feedback tools in postgraduate management education. Utilizing a mixed-methods approach, data were collected from 120 MBA students and 15 faculty members across three business schools. Quantitative analysis included descriptive statistics, One-Way ANOVA, Pearson correlation, and Exploratory Factor Analysis (EFA) to examine institutional variations and underlying dimensions of user perception. Qualitative insights from faculty interviews provided contextual depth. Findings reveal high student engagement with AI tools, particularly for surface-level corrections, while faculty remain cautious due to concerns about plagiarism and diminished critical thinking. EFA identified three core factors influencing AI adoption: Usability & Effectiveness (42.3%), Learning Outcomes (31.7%), and Ethical Concerns (26.0%). To address these challenges, the study proposes the RAIF Framework (Relevance, Awareness, Integration, Formative Use) to guide responsible and pedagogically aligned AI integration. This framework underscores the importance of embedding AI literacy and maintaining instructor involvement to ensure AI tools support, rather than replace, critical academic practices. The study offers timely insights for educators, curriculum designers, and policymakers aiming to foster ethical and effective AI adoption in management education.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
19 April 2026
ISBN
978-2-38476-559-1
ISSN
2352-5398
DOI
10.2991/978-2-38476-559-1_9How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Veto Dey
AU  - M. Thamizhselvi
AU  - P. C. Libeesh
AU  - Priyanka Joshi
PY  - 2026
DA  - 2026/04/19
TI  - AI-Enabled Feedback Systems in Management Education: Advancing Pedagogical Innovation and Learning Outcomes
BT  - Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)
PB  - Atlantis Press
SP  - 127
EP  - 142
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-559-1_9
DO  - 10.2991/978-2-38476-559-1_9
ID  - Dey2026
ER  -