ACADEMIC INTEGRITY IN THE ERA OF GENERATIVE AI: AUTHORSHIP, AUTHENTICITY AND FORMATIVE EXPERIENCE IN HIGHER EDUCATION

From production to verification: generative AI, doctoral formation, and the leadership of digital education

Generative artificial intelligence is often framed in higher education as a problem of academic integrity, assessment security, or technology adoption. This framing is necessary but insufficient for doctoral education, where writing, reading, coding, synthesizing literature, and interpreting evidence are not merely academic tasks but formative practices through which students become scholars. Based on qualitative interviews with twenty-one doctoral students at a large research university in the United States, this study examines how doctoral students understand and negotiate generative AI in their scholarly work. The study began with students in education and was extended through purposive and snowball recruitment to include students across a range of other disciplines, so that the account would reflect more than one scholarly context; interviews were semi-structured. The findings show that AI functions as an access infrastructure, lowering linguistic barriers for some students and technical barriers for others depending on the demands of their scholarly work. At the same time, students engage in careful boundary work between assistance and authorship, distinguishing grammar support, translation, coding help, and conceptual orientation from intellectual substitution. The analysis further suggests that, among these participants, generative AI is shifting doctoral labor from production toward verification: students' distinctive responsibility increasingly lies in judging the accuracy, legitimacy, ownership, and defensibility of machine-assisted work. Under conditions of policy ambiguity, doctoral students also become primary governors of their own AI use, managing disclosure, caution, verification, and risk. The article argues that the leadership of digital education should move beyond broad AI policies toward context-sensitive guidance, verification literacy, transparent disclosure norms, and process-based assessment, including the culminating site of doctoral assessment, the dissertation defense. These claims are offered as analytic propositions grounded in a single-site interpretive study rather than as generalizable findings. Generative AI has not made doctoral education less necessary; it has made its purposes more urgent.

The Polemics of Ethical AI Usage in Higher Education: A Case Study Investigating the Axiological Expectations Mismatch

It is argued that AI-related integrity disputes are better understood as conflicts between competing values than as individual moral failings, and implications for policy design, assessment reform, and faculty development are discussed.

From diffusion to negotiation: generative AI and academic integrity in higher education assessment

Beyond AI-Generated Text: Strengthening Academic Integrity and Critical Thinking in Higher Education

Empirical evidence is contributed from educational action research showing that structured pedagogical interventions can promote the critical, ethical, and responsible use of Generative Artificial Intelligence in education.

Empowering the AI-Literate Learners: Evaluating the Intersection of Digital Governance and Academic Integrity

It is concluded that in order for undergraduate education to continue to be relevant in a society where AI is pervasive, governance must change toward process-oriented evaluation and relational originality.

Re-Imagining the Imago Dei in the Digital Age: Artificial Intelligence and the Formation of Student Identity in Higher Education

This study re-examines the theological concept of the Imago Dei (Image of God), particularly its biblical grounding in Genesis 1:26–27, as an interpretive framework for understanding these transformations. The study employs a qualitative, interpretive, literature-based methodology that brings theological anthropology into conversation with philosophy of technology and contemporary higher education scholarship. Sources were identified through a structured search and selection process, examined against explicit relevance criteria, and synthesised through thematic analysis. Four themes emerged from the interdisciplinary literature: human agency and dignity, cognitive formation and externalisation, digitally mediated identity and authorship, and ethical-relational formation. The findings indicate that AI can augment learning and creativity but may also encourage cognitive dependence, blur conventional understandings of authorship, and intensify the tendency to evaluate students through measurable digital outputs. Contemporary higher education scholarship similarly emphasises the importance of human agency, critical engagement, ethical governance, and responsible AI literacy. The study argues that the Imago Dei provides a constructive theological framework to ensure that AI remains a means of supporting, rather than replacing, human intellectual, moral, relational, and spiritual formation. The paper proposes a human-centred model of AI integration in higher education grounded in dignity, agency, discernment, relationality, and holistic formation.