University Students’ Beliefs about Generative AI -Mediated Academic Reading and Writing Practices: Development and Validation of a Multidimensional Questionnaire
The findings indicate that the questionnaire constitutes a psychometrically robust and analytically sensitive instrument for examining how students interpret, evaluate, and regulate the use of GAI in academic practices, offering a valuable tool for both educational research and the design of training interventions in higher education.
As generative artificial intelligence (GenAI) becomes increasingly integrated into university contexts, it is essential to understand students' perspectives of the competencies needed to apply its tools for academic writing. This study conceptualized critical GenAI literacy and developed a quantitative survey from theoretical and expert sources.
The survey was then administered to undergraduate students, whose responses were randomly divided into two independent subsamples for exploratory (
n
= 214) and confirmatory (
n
= 273) factor analyses.
Based on the initial validation results, the final self-report instrument comprised four dimensions: Functional Literacy, Agency and Autonomy, Ethical and Responsible Use, and Reflective Use. The final 23-item instrument captured both applied and critical dimensions of GenAI use in academic writing and demonstrated preliminary structural validity and acceptable internal consistency within a single institutional context.
This study provides a foundation for future research on GenAI literacy and supports the development of pedagogical interventions that align with students' critical GenAI literacy levels.
Youmen Chaaban, Hiba Naccache, S. Qadhi· Frontiers in Education· 0 citations
The rapid integration of generative artificial intelligence (GenAI) into higher education has transformed academic writing practices while creating new challenges in aspects of academic integrity, authorship, and ethical technology use. This study examines the level of generative AI literacy among university students in Bangladesh along with their level of responsible academic writing practices. Additionally, it explores the relationship between GenAI literacy and responsible writing behaviour and also aims to identify whether these practices differ across academic disciplines. The research was conducted by employing a quantitative cross-sectional survey, and 250 valid responses were collected from undergraduate students enrolled in different higher education institutions in Bangladesh through an anonymous online questionnaire. The survey instrument consisted of three sections: demographic information, generative AI literacy, and responsible academic writing practices. To analyze the data, descriptive and inferential statistical analyses were used with a view to examining students’ AI literacy levels, writing practices, relationships between variables, and disciplinary differences. The study findings indicate that generative AI has become a common component of students’ academic activities, with more than 71% of participants reporting frequent use of AI tools for purposes such as brainstorming, language improvement, summarization, and writing assistance. The research also revealed considerable awareness of AI capabilities, limitations, hallucinations, and ethical concerns. However, the results revealed that while most students engage in responsible AI-assisted writing practices, including fact verification, source checking, rewriting AI-generated content, and maintaining personal authorship, some students reported a need for clearer institutional guidelines and formal AI literacy training. Moreover, the findings also suggest a positive association between generative AI literacy and responsible academic writing practices, which is consistent with the relevance of Long and Magerko’s (2020) AI literacy framework for understanding ethical AI engagement. The study concludes by recommending that universities in Bangladesh should consider formal approaches and develop curriculum models for GenAI literacy to support critical evaluation, ethical AI use, and responsible academic writing practices.
Rabeya Akter, Pabitra Chandra Shuva· International journal of res...· 0 citations
This study investigates English as a Foreign Language (EFL) teachers’ perceptions of ethical artificial intelligence (AI) use in teaching, learning, and assessment within an Omani higher education context. Despite rapid AI adoption in education, institutional governance frameworks remain critically underdeveloped, particularly in EFL contexts — creating an urgent need for empirical, locally grounded research. Using a convergent mixed-methods design, quantitative data were collected from 52 EFL faculty members through a structured 52-item Likert-scale questionnaire, complemented by focus group discussions with nine purposively selected teachers drawn from the same participant pool. Analysis across five constructs revealed high levels of AI literacy and ethical awareness (M = 4.09), ethical responsibility and academic integrity (M = 4.19), and positive pedagogical engagement (M = 4.11). The most critical finding was a significant institutional policy deficit reflected in the lowest construct mean (M = 3.25), with the majority of participants reporting an absence of clear guidelines, consequences, or detection tools. Future orientation and framework acceptance recorded the highest mean (M = 4.30), with 98.1% of participants endorsing formal adoption of an Ethical AI Responsibility (E.A.R.) framework. Qualitative findings corroborated a persistent awareness–practice gap, student over-reliance on AI, and inadequate institutional scaffolding. The study recommends urgent development of context-specific, human-centered AI governance frameworks that bridge individual ethical awareness and institutional policy action, with particular relevance to Omani and comparable EFL higher education contexts.
Surya Subrahmanyam Vellanki, Asiya T Tabassum· Arab World English Journal· 0 citations
The study concludes that successful AI integration in education required more than mere access to technology; it requires fostering AI literacy, self-efficacy, motivation, and ethical awareness through dedicated pedagogical support.
Basanta Prasad Adhikari, Suyantiningsih, Ariyawan Agung Nugroho et al.· OCEM Journal of Management,...· 0 citations
Although a growing body of research has examined students’ attitudes toward generative artificial intelligence (GenAI) in higher education, few studies have compared perceptions across contrasting institutional contexts or explored how students’ reported uses of GenAI relate to broader learning practices. This study addresses that gap by examining university students’ perceptions, self-reported competence, and use of GenAI at two Swedish universities with different academic profiles: a technology-oriented institution and a broader multidisciplinary institution. The study is based on an exploratory questionnaire survey administered to all enrolled students at both universities, yielding 1,097 responses (University A response rate: 11.27%, University B response rate: 14.06%) from students across diverse disciplines, including engineering, nursing, and criminology. Quantitative data were analyzed using reliability analysis, exploratory factor analysis, and non-parametric group comparisons, supplemented by thematic analysis of qualitative responses. The analysis identified three reliable constructs: perceived learning benefit, perceived institutional support and integration, and self-reported technical knowledge and competence. Across both institutions, students reported generally positive attitudes toward GenAI and described using it primarily for information retrieval, text refinement, and text analysis, but also as a discussion partner or personal tutor in ways that suggest both surface-level and more dialogic forms of engagement. Comparisons between the two universities showed broad similarity across most measures, with the only statistically significant difference relating to perceived institutional support and integration, which was rated higher by students at the technology-oriented university. Students at both institutions also viewed GenAI primarily as a complement to, rather than a replacement for, traditional teaching, while reporting only moderate trust in AI-generated outputs. These findings suggest that GenAI is already embedded in students’ study practices, but that its use is largely self-directed rather than strongly shaped by institutional context. The study thus contributes comparative empirical evidence on student engagement with GenAI across contrasting higher education settings and highlights the need for pedagogical and institutional strategies that support critical, reflective, and responsible use.
Å. Nygren, Anna-Li Eriksson, Jeanette Sjöberg et al.· Education and Information Te...· 0 citations
The rapid proliferation of Artificial Intelligence (AI)-based writing tools including ChatGPT, Grammarly, QuillBot, and Microsoft Copilot has introduced both transformative opportunities and profound ethical challenges in higher education globally. In Nigeria, the growing adoption of these tools among undergraduate students raises urgent questions about their net effects on academic achievement, ethical conduct, and skills development, particularly in discipline like Social Studies Education. A descriptive survey research design was adopted. The study population comprised all Social Studies undergraduate students at the Department of Social Studies Education, AFUED. A purposive sample of 200 students was drawn, consisting of 50 students from each of the four levels: 100 Level, 200 Level, 300 Level, and 400 Level. Data were collected using a validated, researcher-developed instrument titled the AI-Based Writing Tools in Education Questionnaire (AIBWTEQ), comprising 40 items across four subscales. Content validity was confirmed by three experts, and Cronbach’s Alpha reliability coefficient was r = 0.87. Data were analysed using descriptive statistics (means and standard deviations), one-way Analysis of Variance (ANOVA), and Pearson Product-Moment Correlation Coefficient (PPMCC). Findings revealed that: (i) AI-based writing tools had a moderate positive effect on students’ academic achievement (grand mean = 2.89); (ii) significant ethical concerns including plagiarism, academic dishonesty, and over-reliance were prevalent, with 400 Level students exhibiting greater ethical awareness than 100 Level students; (iii) AI tools moderately enhanced specific skills such as grammar correction and information retrieval but demonstrated a negative relationship with critical thinking and original writing development; and (iv) there was a statistically significant difference in students’ perceptions of AI effects across academic levels [F(3, 196) = 6.43, p = .000]. The study recommended the development of clear institutional AI usage policies, integration of AI literacy modules into the Social Studies curriculum, and a balanced pedagogical approach that harnesses AI capabilities while safeguarding original intellectual development.
