This study investigates how engineering students’ personality traits, perceived team roles, and AI literacy influence their perceptions of generative Artificial Intelligence (Gen-AI) tools in university education. Building on previous frameworks that link psychological and behavioral variables to technology adoption, a longitudinal design was adopted across two academic years (2023–24 and 2024–25) at the University of Udine. The same validated questionnaire was administered to undergraduate and graduate engineering students, combining the Big Five personality inventory, perceived team-role selection, and five multi-item scales measuring Attitude, Trust, Social Influence, Fairness & Ethics, and Usefulness toward Gen-AI. Descriptive and inferential analyses showed stable perceptions over time, with small yet meaningful increases in Attitude and AI Literacy (p < .05). The mediation analysis indicated that AI literacy acts as a mediator between Openness and perceived Usefulness, although the effect was small and non-significant. The results suggest that continued exposure to Gen-AI fosters both greater confidence and more critical awareness among engineering students. The study provides evidence of the structural reliability of the proposed Excel-based framework and offers practical guidance for integrating AI literacy modules into design-oriented engineering curricula.
Artificial intelligence (AI) is reshaping the landscape of higher education, yet empirical understanding of how university instructors perceive, engage with, and evaluate AI in their teaching contexts remains limited. This study examines university instructors' general perceptions, institutional AI engagement, student experience impact, concerns about AI, and future expectations regarding artificial intelligence in higher education, and investigates whether these dimensions differ by demographic and professional characteristics and which factors predict institutional AI engagement. A quantitative cross-sectional survey design was employed. Data were collected from N = 229 university instructors across five academic schools using the QUIA instrument with five subscales of five items each — General Perceptions (GPI), Current AI Use (UAI), Student Experience Impact (ISE), Concerns About AI (CAU), and Future Expectations (EAI) — scored on a five-point Likert scale. Instructors expressed positive agreement across all five dimensions. Future Expectations (EAI) were highest and Current AI Use (UAI) lowest, revealing an attitude-engagement gap. Concern about AI replacing teachers was the only item below the neutral midpoint. Female instructors reported significantly higher Concerns About AI (CAU) than male colleagues. School of Education instructors reported the highest institutional AI engagement. Student Experience Impact (ISE) and General Perceptions (GPI) were the primary psychological predictors of institutional AI engagement, while gender and School of Education affiliation were the significant demographic predictors. Institutions seeking to increase responsible AI adoption should prioritize structured, discipline-specific professional development that enables instructors to experience AI's pedagogical benefits directly.
Fatima Khalifeh, Raúl Santiago, Ramon Palau· International journal of res...· 0 citations
As generative artificial intelligence becomes more integrated into educational environments, comprehending the psychological traits influencing users’ engagement with these technologies is crucial. This study investigated the influence of personality traits on the self-reported use of ChatGPT and the mediating role of trust in this relationship by drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework as a theoretical reference. Employing a quantitative research design, data were collected through structured questionnaires administered to a sample of 330 university students in North Cyprus using purposive/judgmental technique. The data were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The findings show that extraversion and conscientiousness did not significantly influence perceived trust, whereas agreeableness, neuroticism, and openness are significant predictors of trust. In addition, perceived trust has a significant positive effect on ChatGPT use, highlighting its pivotal role as a cognitive evaluation linking dispositional traits to behavior. These results underscore how individual differences contribute to technology adoption and offer practical insights for educators and platform developers seeking to foster trustworthy Artificial Intelligence (AI) experiences. In an era of rising technological awareness, understanding the psychological antecedents of trust can help higher education institutions design interventions that encourage responsible and effective use of generative AI tools.
Damla Karagozlu· International Journal of Inf...· 0 citations
This study examined GenAI acceptance among private vocational teachers in Thailand by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) with three AI-specific constructs: AI Literacy, Trust, and Perceived AI Risk and tested Behavioral Intention as an antecedent of Digital Competency.
This study examined the attitudes and utilization of generative artificial intelligence (AI) as a learning tool among pre-service mathematics teachers. Employing a descriptive-correlational research design, data were collected from 71 respondents through a structured survey instrument to determine their perceptions of generative AI and the frequency of its use in learning mathematics. Findings revealed that respondents demonstrated a moderately positive attitude toward generative AI across cognitive, affective, and behavioral dimensions. In terms of utilization, participants commonly used generative AI tools for step-by-step explanations, clarification of mathematical concepts, and assistance in solving mathematical problems. However, integration of these tools into regular study routines remained limited. Correlation analysis showed a significant moderate positive relationship between attitudes and frequency of use, indicating that more favorable perceptions are associated with higher levels of engagement with generative AI in academic tasks. Respondents also perceived the curriculum as moderately supportive in developing competencies for effective AI utilization, particularly in enhancing problem-solving skills, critical thinking, and conceptual understanding. Nevertheless, some hesitation was noted in encouraging peer use, reflecting concerns about appropriate and responsible application. In general, the study highlights the need for structured integration of generative AI in mathematics education. It is recommended that teacher education institutions provide targeted training, clear guidelines, and pedagogical strategies to strengthen technological competence, critical thinking, and ethical use of AI. Future research may further examine its long-term effects on learning outcomes and professional readiness.
Nora V. Marasigan, Ericka A. Onte, Althea P. Matanguihan et al.· Community and Social Develop...· 0 citations
Artificial intelligence literacy is often assumed to be a uniform antecedent of its adoption, without empirically contrasting the relative weight of its distinct dimensions on behavioral intention to use. This study examined, through partial least squares structural equation modeling (PLS-SEM), the relationships between AI awareness, critical evaluation, ethical perception, self-efficacy, and prior experience, and behavioral intention to use artificial intelligence tools, in a sample of 300 Ecuadorian university students. The measurement model showed adequate reliability and validity across the six constructs assessed (AVE between 0.560 and 0.757; maximum HTMT of 0.634). The structural model explained 45.3 percent of the variance in behavioral intention, with eleven of the twelve hypothesized paths reaching statistical significance. The central finding of the study is that ethical perception toward artificial intelligence did not significantly predict behavioral intention to use it (beta = 0.042; p = 0.365), unlike awareness, critical evaluation, self-efficacy, and prior experience, all of which did. This result evidences a disconnect between ethical sensitization and declared technological behavior, with relevant implications for the design of training strategies on responsible artificial intelligence use in higher education.
Gabriel Estuardo, Cevallos Uve, G. Adolfo et al.· Journal of Intelligent Decis...· 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
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