Jul 2026· Asian Journal of Contemporary Education· 0 citations
TL;DR
First-year university students’ perceptions of generative AI in academic work are investigated, foregrounding student agency in a Global South context and offering pedagogical and policy implications for responsible AI adoption.
Abstract
Generative artificial intelligence (AI) tools are rapidly reshaping academic practices in higher education. While global debates focus on academic integrity, authorship, and assessment reform, empirical evidence from developing contexts remains limited. This study investigates first-year university students’ perceptions of generative AI in academic work, focusing on ethical awareness, learning adaptation, and expectations for institutional guidance. Using a cross-sectional survey design, data were collected from 213 undergraduate students across multiple disciplines. The instrument included demographic variables and Likert-scale items measuring attitudes toward AI collaboration, plagiarism awareness, and confidence in distinguishing AI-generated content, motivation to improve AI skills, and demand for university policy frameworks. Descriptive and comparative analyses reveal generally positive attitudes toward AI as a learning support tool, accompanied by high ethical concern and strong demand for institutional guidelines. Disciplinary variation suggests differing levels of comfort and adaptive engagement with AI tools. The findings indicate that students do not view AI solely as a shortcut mechanism but as an emerging academic partner requiring structured governance and literacy development. The study contributes to ongoing discussions on AI integration in higher education by foregrounding student agency in a Global South context and offering pedagogical and policy implications for responsible AI adoption.
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 study explores perceptions and practices of AI ethics among higher education students at Banaras Hindu University, using the AI and Ethics Perception Scale (AEPS) dimensions, including transparency, accountability, privacy, fairness, and human oversight, as a conceptual framework.
The rapid growth of generative Artificial Intelligence (AI) is reshaping how higher education conceptualizes learning, assessment, and pedagogy. Many institutions respond by relying on restrictive policies. Unfortunately, this approach often fails to support meaningful and sustainable education. The objective of this study is to reinterpret the Artificial Intelligence Assessment Scale (AIAS) (Perkins et al., 2024) as a developmental pedagogical framework that enables transparent, ethical, and reflective integration of AI into teaching and learning. Methodologically, the study applies the five-level AIAS model, ranging from AI prohibition to full AI collaboration, in FASH 137: Clothing, Society, and Culture, a General Education course examining the sociocultural meanings of dress. AI integration is scaffolded across multiple assignments, each explicitly aligned with a designated AIAS level. Data are drawn from assignment design, faculty observations, and structured student reflections documenting AI use and learning outcomes. Findings reveal three interrelated pedagogical themes. First, transparency as pedagogical integrity emerges through required “AI Use Notes,” which normalize disclosure and foster academic trust. Second, critical evaluation as human distinction is strengthened as students compare AI-generated insights with their own analyses, reinforcing judgment, creativity, and cultural interpretation. Third, AI as a structured learning partner supports exploration, critique, writing development, and identity reflection without replacing human authorship. The research outcomes demonstrate that AIAS functions effectively as a learning architecture, aligning academic integrity with instructional design. The framework offers a replicable model for fashion programs and other disciplines seeking responsible AI integration. Future research will expand empirical assessment across courses, disciplines, and institutions, examine longitudinal learning impacts, and refine discipline-specific AIAS applications to guide higher education in the AI-driven future.
D. Shen· PUPIL International Journal...· 0 citations
This study examined university students’ use of generative artificial intelligence (AI) in relation to engagement, confidence, ethical awareness, and perceived academic value. A descriptive-quantitative, cross-sectional design was employed, involving 380 students from 11 colleges of a Philippine state university. Data were collected using a structured questionnaire and analyzed using descriptive statistics. Students reported using AI-assisted applications primarily for research, summarization, writing, and editing, with ChatGPT, QuillBot, and Grammarly among the most frequently reported tools. Confidence in independent AI use was concentrated in the moderate and lower categories, while perceptions of AI-supported engagement were neutral overall. Ethical awareness was uneven: students showed stronger recognition of familiar concerns involving copyright and unethical academic use but greater uncertainty regarding the broader meaning of ethical AI use in education. Taken together, the findings indicate that access to and use of AI tools do not necessarily develop alongside confidence, meaningful engagement, and ethical understanding. The study highlights the need for AI literacy initiatives that combine practical skills with critical evaluation, appropriate disclosure, verification of generated information, and student accountability in AI-assisted academic work.
Daisy A. Mamaril, Lailani C. Banggawan· Journal of Intelligent Decis...· 0 citations
As artificial intelligence (AI) technologies increasingly permeate educational spaces, the need for structured and reflective faculty development becomes critical. This study presents a comprehensive case study of a six-week faculty institute designed to support higher education instructors in thoughtfully integrating AI into their pedagogical practices. Framed by Universal Design for Learning (UDL), Bloom’s Taxonomy, and design thinking methodologies, the institute explored the tensions between innovation and academic integrity while promoting inclusive, critical adoption of AI tools. Drawing on session materials, pre/post surveys, participant reflections, and capstone projects from ten interdisciplinary faculty members, this paper examines the experiences and evolving mindsets of educators navigating AI integration. The findings reveal a transformative journey from fear and resistance to collaborative innovation, demonstrating that AI integration, when scaffolded by inclusive design, ethical literacy, and practical application, can enhance faculty agency, curriculum responsiveness, and student engagement. The study identifies four key themes: shifting from fear to curiosity, the desire for ethical clarity, inclusive design as an equity amplifier, and the evolution of faculty from gatekeepers to guides. However, significant challenges persist around policy clarity, institutional support structures, and AI’s perceived legitimacy in teaching and learning. This case study contributes to emerging scholarship on faculty AI literacy and offers a replicable model for sustainable professional development design in a rapidly evolving technological landscape. The research provides practical implications for institutions seeking to bridge the divide between administrative enthusiasm and faculty skepticism, ultimately arguing that AI in higher education transcends fashion or fantasy to become a reality demanding thoughtful pedagogical engagement. Clinical trial number Not applicable.
John C. Chick, L. Morello, Stephanie Staffey· International Journal for Ed...· 0 citations
Despite the rapid adoption of Artificial Intelligence (AI) in higher education, limited research has explored how students in English for Specific Purposes (ESP) courses, particularly within non-English disciplines, perceive AI-assisted language learning and the pedagogical as well as ethical implications of its integration. This study aims to explore students’ perceptions of AI utilization in an ESP classroom as a means of scaffolding language learning. The study was conducted in the Environmental Science Study Program at an Islamic university in Surakarta, Indonesia. Employing a qualitative narrative inquiry design, data were collected through semi-structured interviews with nine second-semester students who had prior experience using AI tools for academic purposes. The findings indicate that students generally hold positive perceptions of AI integration in ESP learning, with ChatGPT, Gemini, and Grammarly identified as the most frequently used AI applications. Thematic analysis revealed five major themes: AI as a cognitive support tool, patterns of AI usage, perceived learning benefits, implementation challenges, and ethical-cultural considerations. Participants reported that AI enhanced writing quality, vocabulary development, reading comprehension, and content summarization while facilitating personalized learning, simplifying complex concepts, and increasing learning confidence and motivation. However, concerns were also raised regarding information inaccuracy, miscommunication, excessive dependency on AI, and the potential decline of critical thinking skills. The study highlights the importance of integrating AI into ESP instruction through pedagogically sound practices supported by ethical guidance and digital literacy. These findings contribute to the growing body of literature on AI-assisted language learning 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