Jul 2026· OCEM Journal of Management, Technology & Social Sciences· 0 citations· 1 references
TL;DR
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.
Abstract
This study used a convergent parallel mixed-methods design to examine at how generative Artificial Intelligence (AI) is reshaping educational practices, however there is limited evidence regarding its impact on students’ learning outcomes, especially in developing countries. This study further examined the relationships among AI-related skills, perceived usefulness, self-efficacy, motivation, and academic performance, as well as students’ experiences with generative AI in learning environments. Applying a survey design, this research collected survey data from two hundred ninety-nine ( N = 299) students in Nepal, Indonesia, and Brazil. This study also conducted semi-structured interviews with fourteen ( N = 14) interviewees. Quantitative results indicated low levels of AI literacy, self-efficacy, perceived usefulness, and motivation, all averaging means below midpoint scores of five point Likert scale of survey variables. Regression analyses revealed weak correlations between those independent variables and reported academic enhancement, suggesting that students often lack the confidence and skills required to integrate AI tools effectively into their learning activities.
Conversely, qualitative results highlighted significant advantages of generative AI, such as improved learning efficiency, enhanced communication, and greater problem-solving capabilities. Interviewees noted that AI tools simplified complex concepts and saved time, despite receiving limited formal training. The integration of quantitative and qualitative results exposed a perception practice gap: while students benefited from generative AI, they generally underestimated their abilities and lacked structured guidance. 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.
Generative AI tools are increasingly embedded in university study practices, yet institution-level evidence remains limited, particularly in underrepresented regions. This study examined the frequency and patterns of AI use among undergraduates at Maaref University of Applied Sciences in northern Syria and explored its relationship with perceived understanding, academic performance, attitudes, and concerns. An online questionnaire was completed by 58 students from seven faculties, and data were analyzed using descriptive statistics, correlations, t-tests, ANOVA, and multiple regression. Most respondents (81.0%) used AI daily or several times weekly, with ChatGPT the most commonly reported tool. AI use was positively associated with perceived understanding (r = .677, p < .001) and academic performance (r = .765, p < .001). The regression model explained 72.1% of the variance in perceived academic performance. Although causal conclusions cannot be drawn, the findings support structured AI-literacy training, verification practices, and clear institutional guidance for responsible academic use.
Bashar Abdulkareem Alali, Mohamad Rami Al Jundi, Salahaldin Arour et al.· Research Journal of Maaref U...· 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 development of Artificial Intelligence (AI) has significantly reshaped English as a Foreign Language (EFL) education. This study investigates Indonesian EFL students' perceptions of artificial intelligence (AI) use in their language learning, focusing on a gender-based perspective to identify local patterns in gender dynamics in AI-enabled language learning. Using a mixed-methods design, quantitative and qualitative data were collected from 40 undergraduate EFL students (24 females, 16 males) via a structured questionnaire comprising scaled and open-ended items. Quantitative findings revealed a moderate level of self-reported AI dependency, with females showing a slightly higher dependency score (M = 5.50/10, SD = 1.77) than male students (M = 5.13/10, SD = 1.86), though the difference was not statistically significant (p = 0.652). Qualitative thematic analysis revealed more noticeable gender differences in concerns and usage habits: female students expressed greater concerns regarding AI inaccuracies (+27% compared to male students) and greater awareness of access limitations (+25%), while also reporting higher engagement in proofreading and independent verification practices (+25%) to lessen AI errors. Conversely, convenience and speed were primary motivations for both genders. This study suggests that while AI tools offer significant educational benefits, pedagogical interventions should be personalized to address gender-specific usage patterns and concerns, ensuring equitable access and fostering critical thinking to avoid over-reliance.
A ten-step teaching framework for AI-supported creative interactive content design is proposed, aimed at fostering pedagogical innovation while preserving critical thinking, creativity, and student authorship.
Belén Mainer, Ana Pérez-Escoda· Education sciences· 0 citations
Artificial intelligence (AI) educational tools are increasingly incorporated into higher education, making students’ awareness, attitudes, satisfaction and continued-use intentions important for understanding their educational adoption. This study examined these dimensions among students at Government College Madappally, Kerala. A descriptive research design was adopted, and primary data were collected from 185 students through a structured questionnaire using stratified sampling. Frequencies, percentages and weighted mean scores were used for descriptive analysis. One-way ANOVA assessed differences in awareness across Commerce, Science and Arts streams, while independent-samples t-tests examined gender differences in attitude and satisfaction. Students demonstrated high awareness of AI educational tools, with an overall mean awareness score of 3.94, and awareness of AI mistakes and limitations also remained high at 3.70. Attitudes were positive, with the highest mean score recorded for the statement that AI makes the learning process easier (4.07). Satisfaction was high for accuracy and effectiveness (4.04) and for feedback and guidance (3.90). Seventy-one per cent of respondents agreed or strongly agreed that they intended to continue using AI tools for their studies. Awareness differed significantly across academic courses (F = 8.07, p = 0.000438), whereas gender differences in attitude (p = 0.17) and satisfaction (p = 0.14) were not statistically significant. The findings indicate positive student acceptance alongside persistent technical and feedback-related challenges, highlighting the importance of AI literacy, responsible use and institutional support.
M. Praveen, C. Anwaya, T. Vineethan· Journal of global research i...· 0 citations
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
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