Jul 2026· Education Innovations: Systems and Future Learning· 0 citations· 46 references
TL;DR
A seven-component Student-AI-Centered conceptual framework that integrates AI into curricula while emphasising ethical awareness, diverse assessment modalities and ongoing educator support is proposed, which bridges the gap between teacher-centered, student and AI-centered paradigms.
Abstract
This paper explores expert perspectives on the integration of artificial intelligence (AI) in higher education and proposes a preliminary Student-AI-Centered conceptual framework. While AI is increasingly deployed in teaching and learning contexts, the field currently lacks conceptual frameworks that intentionally balance student agency with AI-enabled support. This study addresses that gap by examining how educators and institutions can promote responsible, ethical and student-driven AI adoption.
A qualitative research design was employed, drawing on semi-structured interviews with educational technology experts selected through purposive sampling. Each participant had a minimum of five years of experience in AI-related practice within higher education. Data were analysed using Braun and Clarke’s (2006) six-phase thematic analysis framework, with trustworthiness strengthened through member checking, triangulation, peer debriefing and an audit trail.
Thematic analysis of expert interviews produced two overarching themes: (1) Potentials of AI in Higher Education, encompassing three sub-themes, personalised learning, inclusive education and enhanced learning participation and (2) Challenges of AI Integration, encompassing two sub-themes, unverified information and ethical compliance. Drawing on these themes, the study proposes a seven-component Student-AI-Centered conceptual framework that integrates AI into curricula while emphasising ethical awareness, diverse assessment modalities and ongoing educator support.
The exploratory nature of the study and the small, purposive sample limit the generalisability of the findings. Future research should validate the proposed conceptual framework through larger, cross-institutional studies and longitudinal designs that assess its applicability across diverse educational settings and cultural contexts.
The Student-AI-Centered conceptual framework offers educators and institutions practical guidance for integrating AI tools responsibly. Pedagogical integrity refers to maintaining the primacy of genuine learning outcomes by ensuring AI supplements rather than supplant critical reasoning, independent inquiry and authentic assessment. Promoting critical thinking means equipping students to interrogate, verify and evaluate AI-generated content rather than accepting it uncritically. Together, these principles, alongside fostering ethical awareness, aim to cultivate responsible, reflective AI users in higher education.
This paper contributes a novel conceptual framework that positions AI as a complementary agent within student-centered learning, rather than as a replacement for educators or a source of uncritical dependency. The Student-AI-Centered approach bridges the gap between teacher-centered, student and AI-centered paradigms.
The increasing integration of artificial intelligence (AI) into educational contexts has significantly transformed discussions surrounding teaching practices and teacher professional development. While existing research frequently focuses on technological implementation and institutional innovation, teachers’ lived experiences of engaging with AI remain underexplored, particularly within language education. This qualitative case study investigates one language teacher’s journey toward AI awareness and integration within professional development practices. Using purposeful sampling, the study focuses on a teacher who actively engages with AI-informed professional learning. Data were collected through semi-structured interviews and a reflective narrative, allowing for an in-depth exploration of the participant’s perceptions, experiences, and meaning-making processes related to AI. Thematic analysis revealed that the participant’s engagement with AI evolved from initial curiosity about technological functionality to a more reflective and pedagogically informed understanding of AI as a supportive professional resource. The findings further indicate that the participant viewed AI as a tool for enhancing creativity, lesson preparation, and pedagogical flexibility while simultaneously maintaining critical awareness regarding authenticity, ethical responsibility, and teacher autonomy. The study highlights the importance of positioning AI within reflective and human-centered approaches to teacher professional development rather than viewing it solely as a technical innovation. By foregrounding a teacher’s voice, this research contributes to current discussions on AI, teacher agency, and ethical professional learning in contemporary educational contexts.
Jaouhara Elmzandi, Soukaina Laayadi, Kamal Barbara et al.· British Journal of Teacher E...· 0 citations
Generative artificial intelligence (GenAI) can improve efficiency in academic work. However, it also raises a central psychological question: when AI helps produce a task, why do some learners still experience the final work as their own, whereas others experience it as polished but psychologically distant? This study examines psychological ownership and competency anxiety in AI-assisted learning, distinguishing between dependent AI outsourcing and reflective human–AI collaboration. An exploratory qualitative interview-based design with supplementary background information was used. The background form was used only for sample description and interview preparation, followed by in-depth interviews with 50 undergraduate and postgraduate students from five Chinese universities, interviews with 10 faculty members and administrators, and 128 student critical incident records. Data were analyzed through a hybrid deductive–inductive thematic analysis, with NVivo 14 used as a supporting tool for code management and matrix comparison. In participants’ accounts, dependent AI outsourcing was associated with weaker psychological ownership, described in terms of reduced cognitive and authorial presence during planning, reasoning, and revision. This weakened sense of ownership was, in turn, linked to shallow memory, difficulty explaining an individual’s work, reduced meaning-making, and stronger competency anxiety. Reflective human–AI collaboration, by contrast, was associated with retained ownership when students planned before using GenAI, evaluated AI output, revised it in their own voice, and could explain their final decisions. Perceived educational support, including feedback, clear AI-use guidance, and psychologically safe learning environments, was described as helping students treat AI use as a learnable practice rather than a hidden shortcut. Faculty and administrators also framed these patterns as issues of assessment feasibility, workload, policy clarity, and curriculum design, rather than solely as student choice. Because the data were collected at five Chinese universities, the proposed model is presented as context-sensitive: the observed dynamics may be amplified where assessment is strongly product-oriented, formative feedback is constrained, and AI use is difficult to discuss openly. This study contributes to psychological ownership theory by extending it to human–AI interaction and proposing that, in this setting, ownership depends on cognitive and authorial presence rather than solely on task completion.
This qualitative study examines the perspectives of in-service teachers regarding the integration of Artificial Intelligence (AI) into educational settings. A purposive sampling framework combining criterion and snowball sampling strategies was employed, semi-structured interviews were conducted with 23 in-service teachers. Data were analyzed through content analysis. The analysis revealed three themes: teachers’ current digital practices, AI acceptance and integration of AI. The findings showed that teachers currently use digital technologies for various pedagogical purposes and have also begun using AI technologies in educational settings. Also, teachers perceived AI as useful because of easier access to information, time efficiency, decision-making support, personalized feedback, and professional development. However, they also expressed pedagogical and ethical concerns regarding student overreliance, academic dishonesty, the potential misuse of AI, data security, and the digital divide. The results indicate that, given the multifaceted nature of AI technologies successful AI integration requires specific teacher competencies, particularly critical AI literacy and ethical awareness competencies. Findings also suggest that successful integration requires practical, subject-specific training for both in-service and pre-service teachers, training for students, family engagement, and financial support. This study provides insights into how teachers use AI technologies, their perceptions of required competencies, the challenges and concerns they perceive. Limitations and suggestions for future research are also discussed.
Feray Uğur Erdoğmuş· Participatory Educational Re...· 0 citations
The study highlights the importance of integrating AI into ESP instruction through pedagogically sound practices supported by ethical guidance and digital literacy by providing context-specific insights that can inform the design of responsible, effective, and ethically grounded AI-enhanced ESP instruction.
D. Zulaiha, Yunika Triana· Journal of Educational Manag...· 0 citations
Generative artificial intelligence (GenAI) tools are becoming increasingly visible in instructional design education, yet little is known about how emerging designers learn to reason with these tools during authentic design work. This phenomenological study examines graduate students’ lived experiences using GenAI as a thinking partner in a fully online master’s-level instructional design course at a regional public university in Florida. Guided by Situated Learning Theory and informed by Van Manen’s interpretive phenomenology, the study draws on structured reflections, peer exchanges, design artifacts, and end‑of‑course letters from nine students. Three themes describe how students engaged with GenAI across the ADDIE framework: AI as amplifier and challenger, negotiating voice and authorship, and developing trust, judgment, and critical engagement. Findings illustrate a shift from early reliance on GenAI toward more discerning use grounded in professional judgment. The study contributes to instructional design education by highlighting how GenAI mediates reflection, authorship, and learning in authentic design environments.
M. Stork, Krista Bixler· Florida Journal of Education...· 0 citations
This case study examines how students were positioned as experts in shaping artificial intelligence (AI) literacy curricula at a United Kingdom university, and contributes to the current discourse on fostering critical, responsible AI literacies in HE through the lens of students as partners.
Nurun Nahar, David Howard, Kater Akeren et al.· Compass: Journal of Learning...· 0 citations
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