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.
Abstract
AI ethics has become an essential part of higher education today, reshaping traditional ideas about academic honesty for the digital age. It remains unclear how students interpret the ethics of AI use, experience ethical principles, and apply guidelines in their academic settings. To fill the gap, this study explores perceptions and practices of AI ethics among higher education students at Banaras Hindu University (BHU), using the AI and Ethics Perception Scale (AEPS) dimensions, including transparency, accountability, privacy, fairness, and human oversight, as a conceptual framework. An interpretative qualitative case study was conducted with 15 purposively selected students from seven departments at BHU. We analysed responses from their semi-structured interviews using thematic analysis. The study findings show that most students (N = 10) perceive AI as lacking transparency, particularly regarding its sources and accuracy, and acknowledge their accountability for AI-assisted work. Students (N = 15) expressed concern about privacy, particularly about avoiding the entry of personal, financial, or academic information into AI systems. The study also found that teacher review plays an important role in maintaining academic integrity. Students reported frequent use of AI in their own educational tasks, often without considering ethical implications. The use of AI has affected their study habits, time management, and learning strategies, while also reducing their stress levels. This study suggests that universities should develop their own ethical guidelines and frameworks for the use of AI. They should also conduct seminars and workshops to raise awareness among students and teachers about ethical AI use in academia.
This study, conducted using an explanatory sequential mixed-methods design, aims to examine the views of faculty members and students on ethical issues related to the use of artificial intelligence (AI) in higher education. In the quantitative phase, data were collected via a survey from 971 students and 135 faculty members, followed by semi-structured interviews with 23 students and 14 faculty members to obtain qualitative data. The findings show that both groups generally expressed supportive views regarding the ethical use of AI, but these views took different forms at the individual, technological, institutional, and societal levels. Faculty members emphasized the importance of ethical principles but pointed out the lack of institutional guidelines and support. Students, on the other hand, stated that AI tools were beneficial in their learning processes, but expressed uncertainty about the sharing of ethical responsibilities and the assessment of the ethical appropriateness of the processes. Qualitative findings showed that perspectives were shaped in six themes, revealing a multidimensional ethical structure in the use of AI in education. Participants emphasized that while AI facilitates learning, its excessive use can have negative effects on cognitive skills. The results indicate that, in order for AI to be used ethically in higher education, professional development support should be provided to faculty members, courses covering ethical dimensions should be added to curricula, clear ethical usage guidelines should be established at universities, and these guidelines should be updated through interdisciplinary collaboration.
Buket Bilgiç, Demet Sever· International Journal of Edu...· 0 citations
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.
Sharifuzzaman, M. Rahman· Asian Journal of Contemporar...· 0 citations
In the education sector, AI is reshaping the education landscape in numerous ways, such as in the way students learn, the way they are taught, the way grades are awarded, the way research is conducted and the way academic administration is managed. However, the effective use of AI will not only need to be technically available and useful, it will take moral readiness from faculty who utilize, evaluate and oversee these new and emerging technologies. The research seeks to examine faculty perceptions about the use of AI tools and their ethical preparedness for their application in higher education focusing on academic integrity, data privacy, transparency, bias, responsibility and the responsible use of AI-generated content. The research explores faculty attitudes and perceptions towards opportunities and challenges and the institutional, professional and ethical implications that shape faculty attitudes on the introduction of AI in higher education. Faculty perspectives have been included as teachers play a key role in setting boundaries on how AI can be used, and in educating students about responsible digital use. The study also looks at the impact of institutional policies; Faculty development; Professional ethics and institutional support, on faculty confidence and preparedness. The outcomes will likely offer suggestions on the significance of merging technological progress with human skills, academic principles and ethics. The study calls for a shift in the design, and in the use of AI, in the Higher Education sector from focusing on technology to a more holistic approach that prioritizes transparency, accountability, inclusiveness and human oversight. Continued training and training faculty in ethical literacy can help create a more trustworthy and sustainable academic environment with AI.
Divyabharathi M, N. Madhumithaa· International journal of com...· 0 citations
Background: GenAI systems are now an integral element of academic life, although guidelines for research ethics are mostly based on the experiences of the NorthAmerican and European countries. There is not much information available about the ethical issues related to AI that researchers face in Tunisia as well as whether their institutions have adapted to the developments.
Objective: to record the way faculty members, postgraduate students and editors in Tunisia comprehend and handle the ethical issues related to AI-created academic materials and to investigate whether the current institutional policy provides significant assistance.
Methods: eighteen participants across three institutions (ISET Kasserine, FLSH Sousse, University of Sfax) took part in semi-structured interviews, supplemented by analysis of institutional documents and observation of five research-methods and writing seminars, coded thematically using Braun and Clarke's (2006) six-phase approach.
Results: awareness of AI ethics was uneven, with only about a third of participants describing solid understanding and a fifth reporting minimal awareness; institutional documents were largely silent on AI, with the great majority of integrity codes making no mention of it; and the concern raised most often was the absence of structured training, followed by uncertainty over authorship attribution.
Conclusion: Tunisian higher education is operating in something close to a policy vacuum on AI-assisted writing. To remedy this situation, it is essential to formulate codes of ethics that incorporate the notion of so-called AI literacy into the educational process of teaching research methods and academic writing.
Mongi Aloui· Review of Artificial Intelli...· 0 citations
Objectives: The perspective on the use of Generative AI (GAI)in higher education at King Abdulaziz University is balanced yet cautious. Professors recognize GAI's potential for education but are concerned about originality, academic integrity, and ethics. Faculty believe GAI can enhance analysis and clarity in research writing, but maintaining ethical compliance and oversight is crucial to uphold originality and scholarly standards. The study aims to explore ethical concerns and their impact on the quality of graduate students' academic submissions. It seeks to promote responsible use of GAI, thereby strengthening academic integrity and fostering innovation in graduate research. The research emphasizes the importance of ethical training, clear institutional policies, and transparent guidelines to responsibly incorporate GAI into research and teaching. Increasing awareness and developing robust ethical frameworks are essential to ensure GAI serves as a tool for innovation, not academic compromise.Methods: A quantitative approach was used, with a questionnaire to collect data on professors' assessments of graduate students' research quality and their adherence to GAI ethics. 29 participants, including full professors, associate professors, assistant professors, and lecturers. Purposive sampling was used, with significant experience in evaluating research integrating GAI tools, to ensure participants are well-versed in assessing GAI-augmented academic research.Results: The findings show a cautious yet balanced view of Generative AI in higher education. Professors at the Department of Information Science at King Abdulaziz University see GAI's benefits but worry about its impact on originality, integrity, and ethics. Faculty view GAI as a helpful research tool but emphasize ethical compliance and supervision to maintain standards.Conclusions: The study highlights the need for ethical training, policies, and clear guidelines to ensure responsible use of GAI, promoting innovation while safeguarding academic values.
H. Albadi· International journal of com...· 0 citations
This study explores how digital literacy shapes research integrity among final-year Library and Information Science students at the University of Ilorin, Nigeria, within AI-mediated academic environments. Using a qualitative phenomenological approach, data were collected from thirty participants through interviews and focus groups and analysed thematically to capture students’ experiences of digital research and ethical decision making. The findings show that although students display strong ethical awareness linked to their professional identity, this does not always translate into practice. Digital competence supports source evaluation and reference management, but also enables uncritical copying, use of rewriting tools, and uncertain engagement with artificial intelligence, especially under academic pressure. Behaviour is further influenced by inconsistent supervision, unclear institutional guidance, and peer norms. The study reframes digital literacy as an ethical competence rather than a purely technical skill, showing that its role in research integrity depends on intention and context. It contributes evidence from an underexplored African setting and highlights the need for clearer, discipline-sensitive policies on AI use, alongside stronger supervision and integrity education.
A. Dunmade· IQRO Journal of Islamic Educ...· 0 citations