Aug 2026· Sustainability· 0 citations· 12 references
Abstract
The study explores the paradigm shift in education brought about by the introduction of generative artificial intelligence (AI) tools, focusing on educational stakeholders’ self-reported perceptions rather than observed changes in teaching or learning outcomes. We consider stakeholders’ views on AI-based technologies within the teaching–learning process. The current study uses a cross-sectional empirical survey design with a sample of N = 917 respondents, including teachers, students, administrators, and management. It examines the use of advanced AI technologies such as ChatGPT, Gemini, DeepSeek, and Grok, and stakeholders’ perceived connection between digital skills and classroom performance, student motivation, and critical thinking. We also discuss the ethical dilemmas and structural challenges that accompany this digital change. Inferential statistics, such as One-Way ANOVA and the Pearson Chi-Square test, show statistically significant differences in perceptions and regulatory expectations across organizational responsibilities. The findings contribute to understanding how advanced digitalization is perceived to reshape traditional academic roles, offering practical insights for creating effective, responsible, and sustainable teaching practices.
This proposed research work will be evaluated using real-time data collected from various university students via a research study to provide insight into how GAI has impacted the creative quotient of students who prefer to utilize modern tools over the traditional teaching-learning methodology.
Renuka Devi D, Midhun Chakkaravarthy· International Journal of Ele...· 0 citations
A ten-step teaching framework for AI-supported creative interactive content design is proposed, aimed at fostering pedagogical innovation while preserving critical thinking, creativity, and student authorship.
Belén Mainer, Ana Pérez-Escoda· Education sciences· 0 citations
This study explored how a higher education educator experienced and made sense of generative artificial intelligence (GenAI) within teaching, peer collaboration, and assessment practices. Using an Interpretative Phenomenological Analysis (IPA) research design, the study focused on a single participant, who is a curriculum leader and instructor at a private European university undergoing rapid shifts in GenAI policy and practice. Data were collected through a semi-structured interview and participant pre-account and analyzed using IPA’s idiographic and interpretative procedures. Findings identified three superordinate themes, including divergent peer adoption of GenAI, pedagogical adaptation and uncertainty, and assessment ambiguity. These illustrate GenAI as an ongoing disruption that reshapes collegial dynamics, teaching approaches, and conceptions of learning and authorship. While GenAI supports accessibility and content simplification, it also raises concerns about student dependency and academic integrity, prompting a shift toward evaluating students’ critical engagement with AI outputs. Interpreted through Mezirow’s transformative learning theory, GenAI emerges as a sustained disorienting dilemma, producing gradual, relational, and ongoing perspective transformation in higher education practice. Future research should extend this work beyond a single-case design to include comparative and longitudinal studies across disciplines and institutions, further examine GenAI-informed assessment models, and the extent to which existing theoretical frameworks capture the relational and evolving nature of AI-mediated educational change.
Karen K. Fujii, N. Perez· IAFOR Journal of Education· 0 citations
Aim/Purpose: This study examines lecturers’ perceptions of Generative Artificial Intelligence (GenAI) in higher education and how these perceptions vary with demographic characteristics, namely gender, age and teaching experience. It further investigates how such perceptions relate to lecturers’ frequency of GenAI use and stage of adoption, identifying the opportunities and challenges lecturers associate with the integration of GenAI in educational practice.
Background: The rapid emergence of GenAI has introduced new possibilities and challenges for higher education, yet empirical research examining lecturers’ perspectives, particularly within diverse contexts, remains limited. While existing studies have largely focused on students’ use of GenAI or technical adoption models, less attention has been given to lecturers’ perceptions, demographic influences, and the ethical and pedagogical implications of GenAI integration
Methodology: A mixed-methods research design was employed. Quantitative data were collected through an online survey administered to 98 lecturers from different higher education institutions spanning a range of disciplines (55% male, 45% female; 44% aged 25-45, 30% aged 46-55, 26% aged 56+). Qualitative data were gathered through semi-structured interviews with a purposive subsample of ten lecturers. Quantitative analyses included independent-samples t-tests, one-way ANOVA, and Spearman rank-order correlations, while qualitative data were analyzed using Braun and Clarke’s six-phase thematic analysis.
Contribution: Theoretically, the study extends technology-adoption research by integrating the Technology Acceptance Model with an interpretive technology-in-practice perspective, suggesting that lecturers’ perceptions of GenAI are socially situated and systematically shaped by gender, age, and teaching experience, and that these perceptions in turn are strongly associated with frequency of use and depth of adoption. Practically, the findings highlight the need for differentiated professional development, updated ethical guidelines, and redesigned assessment practices that foster critical AI literacy, supporting responsible and sustainable GenAI integration in higher education.
Findings: Quantitative findings revealed significant demographic differences in lecturers’ perceptions. Female lecturers reported more positive perceptions than male lecturers on several pedagogical dimensions. A clear age-related gradient emerged, with lecturers aged 25-45 expressing the most favorable perceptions and those aged 56+ the least. Strong positive correlations were observed between perceptions and frequency of GenAI use, between perceptions and stage of adoption (rs = 0.67, p< 0.01) and between frequency of use and stage of adoption (rs= 0.74, p<0.01). Also, the thematic analysis of interview data identified three opportunity themes. These included: empowering lecturers in teaching and time management, enhancing pedagogical practices and student learning and improving accessibility to information and knowledge creation, alongside three challenging themes involving ethical and academic integrity concerns, technological limitations and dependency and threats to professional identity.
Recommendations for Practitioners: Institutions should implement differentiated professional development and update ethical governance frameworks, with particular emphasis on redesigning assessment to foster critical GenAI literacy and authentic engagement.
Recommendation for Researchers: Further studies should investigate how GenAI evolves from a technological tool into a sustained technology-in-practice within higher education systems.
Impact on Society: The study underscores the importance of responsible GenAI integration to safeguard educational quality, equity, and human-centered academic values.
Future Research: Future research should incorporate a larger, cross-cultural sample to explore how differing institutional, national, and policy environments moderate GenAI acceptance. Furthermore, while this investigation indicates an association between positive perceptions and the frequency of GenAI use, a step for subsequent studies is to empirically validate the longitudinal relationship between initial positive attitudes and the deep, sustained integration of GenAI into core curricula and assessment practices.
Abeer Mahmoud Watted, Michelle Attard Tonna, P. Camilleri· Journal of Information Techn...· 0 citations
Research background: The rapid development of generative artificial intelligence (AI) and ongoing digital transformation are reshaping higher education and increasing demand for more flexible and competence-oriented educational approaches. Recent studies indicate that students tend to associate educational innovation less with technological novelty itself and more with flexibility, practical learning outcomes, and career relevance.
Purpose of the article: This article aims to identify the key educational and digital factors that positively influence students’ perceptions of innovative educational approaches that support critical thinking and personal development in higher education.
Methods: The quantitative research was conducted using a sample of 925 students from a partner university participating in a V4 research project. Students’ attitudes were collected through an online questionnaire administered in October 2025. The research hypotheses were tested using correlation analysis and linear regression modelling. The data were analysed using IBM SPSS Statistics.
Findings & Value added: The findings indicate that students place greater value on educational approaches that support practical skills development, flexibility, and preparation for future careers than on technological novelty itself. The strongest positive effects were identified for approaches supporting the development of future career skills and flexible educational systems. By contrast, several variables related to AI and digital resources exhibited weaker or statistically non-significant effects. This may indicate that students increasingly perceive digital technologies as a standard component of higher education rather than as a distinct indicator of educational innovation. The study contributes to current debates on AI and educational innovation by demonstrating that students associate innovation more strongly with competence development and flexibility than with technological novelty alone.
Anikó Csepregi, Andrej Rajský· Journal of Business Sectors· 0 citations
This systematic literature review investigates how instructors and students perceive and experience the implementation of AI-supported teaching and learning approaches in TVET settings and provides insights into emerging opportunities, challenges, and implications for policy and practice.
Iron G. Morales, John Hillard Mansueto, Russel M. Dela Torre· International journal of res...· 0 citations
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