Artificial Intelligence and Academic Integrity in Virtual Higher Education: A Descriptive-Comparative Study of Student and Faculty Perceptions in Ecuador
Jul 2026· Trends in Higher Education· Vol 5, pp. 67· 0 citations· 45 references
TL;DR
Both groups report limitations in current virtual assessment, suggesting the need for AI-resilient assessment design, explicit disclosure rules, faculty development, student AI literacy, and proportional use of proctoring.
Abstract
The rapid adoption of generative artificial intelligence (GenAI) has created a practical problem for virtual higher education: universities must distinguish legitimate AI-supported learning from undisclosed delegation of academic work, while maintaining valid, fair, and privacy-sensitive assessment. This study compared student and faculty perceptions of AI use and academic integrity at the Technical University of Machala, Ecuador. A descriptive-comparative cross-sectional survey was administered to 1660 students and 34 faculty members during the second academic semester of 2024. The student questionnaire examined AI-use frequency, perceived academic benefit, readiness for non-assisted assessment, observation of dishonest online practices, perceived efficacy of virtual assessment, and attitudes toward proctoring. The faculty questionnaire examined suspected AI-generated submissions, responses to suspected use, perceived assessment efficacy, training, control tools, ethical judgments and proctoring. Findings indicate a transitional integrity landscape: students view AI mainly as a useful academic support, whereas faculty interpret it primarily through authorship, evidence and assessment-security concerns. Both groups report limitations in current virtual assessment, suggesting the need for AI-resilient assessment design, explicit disclosure rules, faculty development, student AI literacy, and proportional use of proctoring. The article argues against both blanket prohibition and permissive ambiguity, proposing a governance model grounded in transparent policy, authentic assessment, due process and human-centered AI literacy.
The increasing accessibility of generative artificial intelligence (GenAI) tools is transforming academic practices in higher education. This study investigates the adoption of generative AI among undergraduate students in Malaysia, with particular attention to usage patterns, perceived academic benefits, and perceptions of academic integrity. A quantitative survey was conducted with 166 respondents, and the data were analysed using descriptive statistics, analysis of variance (ANOVA), and independent t-tests. The findings indicate a high level of generative AI adoption, with 97.6% of students reporting using AI tools for academic purposes. ChatGPT and Canva emerged as the most frequently used tools. Respondents generally perceived generative AI as beneficial for completing academic tasks, understanding course content, solving study-related problems, and enhancing the quality of academic work. At the same time, concerns were reported about plagiarism, overreliance on AI, and the need to disclose AI-assisted work in academic submissions. Inferential results further suggest that, although selected demographic differences exist in the use of certain tools and in some usage-related perceptions, perceptions of academic integrity are broadly consistent across age, gender, and level of study. These findings underscore the growing role of generative AI in higher education and the need for institutional policies that promote ethical, transparent, and responsible use.
A. A. Sharip, U. M. A. Jalil, R. M. Saidi et al.· International journal of res...· 0 citations
This study explores the perceptions of college students toward the integration of Artificial Intelligence (AI) in education, with a focus on its general use, role in learning processes and outputs, and associated ethical concerns such as transparency, fairness, privacy, and data security. A total of 293 students from the Nueva Ecija University of Science and Technology – Gabaldon Campus participated in the study, representing various programs including Agriculture, Education, Information Technology, and Hospitality Management. A validated researcher-made questionnaire was used, comprising 25 items distributed across five constructs. Data were analyzed using descriptive statistics, mean and standard deviation, to determine levels of agreement, while Principal Components Analysis (PCA) was employed to examine communalities and ensure construct validity. The findings revealed a general agreement among students regarding the positive role of AI in enhancing learning experiences, increasing assignment efficiency, and developing skills relevant to future careers. However, lower mean scores in areas such as reliance on AI for research and collaboration suggest a need for further support and training. Notably, students expressed high confidence in the ethical management of their data, with strong agreement on institutional safeguards and transparency in data usage. Communality values ranging from 0.459 to 0.889 indicated that most items were well-represented within their respective constructs. The results highlight both the benefits and challenges of AI integration in education. The study recommends that institutions enhance AI-related communication, training, and ethical safeguards to support students in maximizing the potential of AI tools in their academic and professional development.
J. L. Galang, A. T. Capinding, Rosalie A. Pineda· TEM Journal· 0 citations
It is concluded that academic institutions must use clear ethical practices and AI-aware assessment designs to ensure that technology is used as an assisting tool that improves users' learning while ensuring the fundamental values of education.
Sugandha Nandedkar, Prachi N. Waghmare, Ashwini Swami et al.· International Scientific Jou...· 0 citations
This study explores university EFL students’ perceptions of Artificial Intelligence (AI) in higher education learning environments, particularly within Faculty of Teacher Training and Education in Indonesia. Employing a qualitative phenomenological design, data were collected through semi-structured interviews with nine students from the Faculty of Teacher Training and Education who actively use AI-assisted tools in their academic activities. The findings reveal that EFL students demonstrate high familiarity with AI applications, especially for language learning, doing tasks, and perceive AI as a supportive learning assistant that enhances efficiency, autonomy, and confidence. AI tools are widely valued for providing immediate feedback, facilitating comprehension, and reducing learning anxiety through flexible and interactive learning experiences. However, the study also identifies critical concerns related to accuracy, ethical integrity, and dependency, as excessive reliance on AI may hinder critical thinking and academic responsibility. These findings highlight the dual role of AI as both an empowering pedagogical resource and a potential challenge when used uncritically. The study underscores the importance of developing deeper AI literacy and institutional guidance to ensure responsible, ethical, and cognitively meaningful AI integration in higher education.
Suratman Dahlan, A. Usman, Awaludin Rizal et al.· Journal of Language Teaching...· 0 citations
Generative artificial intelligence (GenAI) is transforming assessment practices in higher education, offering opportunities for efficiency and personalization while raising concerns related to academic integrity, fairness, and responsible use. Understanding how different users perceive and engage with GenAI is essential, particularly within rapidly advancing digital contexts such as the United Arab Emirates (UAE).
This study investigates students' and instructors' perceptions of GenAI integration in assessment and examines the relationships among perceived usefulness, perceived ease of use, perceived risk, attitudes, and responsible use, including the moderating role of user type.
An explanatory sequential mixed‐methods design was employed. Quantitative data were collected from 193 participants (163 students and 30 instructors) using a validated survey instrument. Correlation, regression, mediation, and moderation analyses were conducted, complemented by qualitative thematic analysis of open‐ended responses.
Findings revealed significant positive relationships among all constructs. Perceived usefulness and ease of use were combined into a higher‐order Technology Acceptance Model construct that strongly predicted attitudes. Perceived risk significantly influenced both attitudes and responsible use, emerging as the strongest predictor of responsible behaviour. Attitude partially mediated the relationship between technology acceptance and responsible use. User role significantly moderated this relationship, with a stronger effect observed among instructors. Qualitative findings indicated generally positive but cautious attitudes, highlighting concerns about over‐reliance, accuracy, and academic integrity, alongside a continued intention to use GenAI.
GenAI adoption in assessment is shaped by a balance between perceived benefits and risk awareness. The findings highlight the importance of promoting responsible use through clear policies, training, and assessment design, offering practical implications for integrating GenAI within higher education systems.
Fatima Salem Al Mohsen, Areej Elsayary· Journal of Computer Assisted...· 0 citations
The rapid integration of Artificial Intelligence (AI) in higher education has changed teaching and assessment practices and has introduced new risks for faculty well-being. This study, conducted in 10 public and private universities in Dhaka, Bangladesh, examines faculty burnout associated with AI adoption and academic integrity enforcement. Semi-structured interviews were conducted with 37 full-time faculty members, each with more than 5 years of teaching experience. Reflexive thematic analysis identified 5 domains of burnout: workload intensification through invisible labor, technostress driven by rapid technological change, an investigative burden that moves the faculty role from pedagogy toward surveillance, ethical strain within a policy vacuum, and disruption of professional identity. Participants described AI integration as a structural intensifier of academic labor rather than a labor-saving tool. In the absence of clear governance, faculty members absorbed the cognitive, emotional, and administrative costs of institutional transitions. The findings support the need for written institutional AI policies, formal recognition of assessment redesign labor, fair and reliable misconduct procedures, and sustained professional development so that integrity enforcement does not rest on individual instructors alone. The results carry implications for university governance, national regulatory bodies, and occupational health in academic workplaces.
Ridwan Islam Sifat, Mohaimenul Islam Jowarder, Rafiul Azim Jowarder et al.· New solutions : a journal of...· 0 citations
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