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Generative AI in education: Process-aware pedagogy, assessment integrity, and institutional governance.
Nora Pireci Sejdiu1, Simone Grassini2, Sejdi Sejdiu3
1Department of Mathematics, University of Prishtina 'Hasan Prishtina', Prishtina, Prishtina, Kosovo (Serbia and Montenegro).
Open Research Europe
|June 22, 2026
Summary
Generative artificial intelligence (GenAI) is transforming higher education, presenting challenges to academic integrity and institutional readiness. A new augmented pedagogy framework suggests using GenAI as a learning scaffold, not a replacement, to ensure responsible integration.
Area of Science:
- Higher Education Research
- Educational Technology
- Artificial Intelligence in Education
Background:
- Generative artificial intelligence (GenAI), including large language models like ChatGPT, is significantly altering knowledge production and assessment in higher education.
- While offering benefits for learning and efficiency, GenAI introduces substantial concerns about academic integrity, governance, and ethical sustainability.
Purpose of the Study:
- To review and synthesize current research on the integration of GenAI in higher education.
- To identify key challenges and tensions arising from GenAI adoption in academic settings.
- To propose a pedagogical framework for responsible GenAI integration.
Main Methods:
- A qualitative thematic literature review of research published between 2020 and 2025.
- Thematic synthesis of scholarly articles, institutional reports, and policy discussions.
- Analysis focused on GenAI's rise, academic integrity, institutional responses, and ethical/environmental impacts.
Main Results:
- Identified four key tensions: student adoption vs. institutional readiness, authorship/assessment ambiguity, fragmented policy responses, and overlooked ethical/environmental costs.
- Observed that these critical issues are often addressed in isolation, lacking a holistic perspective.
- Highlighted the gap between rapid GenAI advancements and comprehensive institutional strategies.
Conclusions:
- Advocates for an 'augmented pedagogy' framework that treats GenAI as a cognitive scaffold for learning.
- Emphasizes the need for transparency in AI use, process-oriented assessments, and robust institutional governance.
- Argues that responsible AI integration can enhance, not detract from, the core educational mission of universities.
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