Jul 2026· International journal of computer information systems and industrial management applications· 0 citations
TL;DR
The study highlights the need for ethical training, policies, and clear guidelines to ensure responsible use of GAI, promoting innovation while safeguarding academic values.
Abstract
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.
The increasing use of Generative Artificial Intelligence (GenAI) in higher education has changed the academic writing practices of students, presenting both opportunities to improve learning and challenges to academic integrity. The study explored the relationship between the GenAI use profile, academic integrity awareness, ethical judgment and decision-making, and responsible GenAI use practices in academic writing of fourth-year students of North Eastern Mindanao State University (NEMSU). It examined students’ awareness of risks to academic integrity associated with GenAI, ethical judgment and decision-making in GenAI-assisted writing, and responsible AI-use practices. The study also explored the lived experiences and perceptions of students on ethical use of GenAI in academic writing. A descriptive correlational design was employed. The quantitative data were collected from 303 fourth-year students selected using simple random sampling. Descriptive statistics and Pearson Product-Moment Correlation were used to analyze the data. The findings revealed that respondents were generally moderately aware of GenAI-related academic integrity risks, exhibited moderately manifested ethical judgment and decision-making, and demonstrated moderately practiced responsible GenAI use behaviors. Significant relationships were found between GenAI use profile and academic integrity awareness, academic integrity awareness and ethical judgment and decision-making, and ethical judgment and decision-making and responsible GenAI use practices. These findings suggest that while students possess foundational knowledge and ethical awareness regarding GenAI use, gaps remain in translating awareness into consistently responsible practices. The study underscores the need for comprehensive AI literacy programs, explicit institutional guidelines, and ethics-focused educational interventions that promote transparency, accountability, critical evaluation, and responsible human oversight in AI-assisted academic writing.
Christianne Mae R. Rivas, Mardie E. Bucjan· International journal of res...· 0 citations
It is concluded that AI-related academic misconduct is often a rational behavioral choice driven by perceived institutional unpreparedness rather than ignorance, and calls for a transition toward adaptive academic integrity frameworks that prioritize ethical awareness and transparent academic policy communications to students.
Ignatius Ogbaga, U. Onwudebelu, Nathaniel Akwuma et al.· Systems and Computing· 0 citations
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.
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.
Joe Mutebi, Brian Mugisha, Ibrahim Adabara et al.· F1000Research· 0 citations
The
rapid adoption of Gen-AI tools such as ChatGPT and Gemini in science education
has created unprecedented opportunities for learning, while simultaneously
threatening core ethical scientific attitudes. This conceptual paper examines
how honesty and integrity, as foundational values in science, are being tested
in an AI-mediated educational environment. The paper argues that the ease of
fabricating data, generating lab reports, and obscuring AI use necessitates a
rethinking of how ethical scientific attitudes are taught, assessed and
modelled in science education research. Based on literature in science ethics
and educational technology, a three-dimensional ‘‘AI Disclosure-Accountability
Model’’ is proposed emphasizing truthfulness in reporting, transparency in AI
use, and responsibility for verifying AI outputs. The paper further discusses
pedagogical strategies, assessment redesigns, and institutional policies needed
to foster honesty and integrity among students and researchers. It concludes
that intentional cultivation of ethical attitudes is essential to preserve the
credibility and integrity of science education in the age of Gen-AI
Geoffrey Aondolumun Ayua, Tertsea Caleb Kwagh· Journal of Studies in Scienc...· 0 citations
Tunisian higher education is operating in something close to a policy vacuum on AI-assisted writing, and 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