Unlocking the power of AI in education: students’ intentions and AI tool use driving learning success in an emerging economy

This study examines the factors influencing the adoption and use of artificial intelligence (AI) tools to enhance writing skills among English as a Foreign Language (EFL) learners in Oman, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT). The objectives were to assess the impact of performance expectancy, effort expectancy, social influence, and facilitating conditions on students’ behavioral intention and actual AI usage, and to test the moderating role of prior AI experience. A cross-sectional quantitative design was employed, with data collected from 255 undergraduate female EFL students through a validated questionnaire. Structural equation modeling (SEM) and confirmatory factor analysis were used to validate the measurement model and test hypothesized relationships. Findings indicate that behavioral intention and facilitating conditions significantly predicted actual AI tool use, while performance expectancy, effort expectancy, and social influence strongly shaped behavioral intention. Mediation tests confirmed that behavioral intention served as a key pathway linking UTAUT constructs to actual adoption, and moderation analysis showed that prior AI experience strengthened the intention–usage relationship. This research contributes to a context-specific, evidence-based framework for AI adoption in EFL writing, offering novel insights for educators, institutions, and technology designers to integrate AI ethically and effectively in language learning.

This study investigates the determinants of artificial intelligence (AI) tool adoption among professional designers using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) as the guiding theoretical framework. As AI increasingly reshapes creative industries, understanding the factors that drive designers’ intention to adopt and actual use of AI tools has become both theoretically and managerially relevant. Data were collected through a cross-sectional survey administered to 170 professional designers, including graphic, UI/UX, and product designers. The proposed research model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that performance expectancy, effort expectancy, social influence, hedonic motivation, and price value have significant positive effects on designers’ behavioral intention to adopt AI tools. In contrast, facilitating conditions do not significantly influence behavioral intention but exert a strong positive effect on actual use behavior. Habit and behavioral intention also significantly predict use behavior, with habit emerging as the strongest determinant of sustained usage. The model explains a substantial proportion of variance in both behavioral intention and use behavior, confirming the strong predictive power of the UTAUT2 model in a creative professional context. This study contributes to the growing literature on AI adoption by extending UTAUT2 to the design industry and highlighting the joint role of utilitarian, hedonic, and habitual factors. Managerially, the findings provide actionable insights for AI tool developers and design organizations seeking to foster effective and sustained AI adoption. Keywords: Artificial Intelligence, UTAUT2, Technology Adoption, Designers, Use Behavior

Students’ use of Artificial Intelligence tools to complete assignments spawns issues in academic integrity. The purpose of this study was to explore students’ and faculty’s perspectives on the benefits and challenges of using ChatGPT and assistive Artificial intelligence (AI) tools to complete assignments. This descriptive phenomenological qualitative methodology study encompassed interviews with eight students who used Large Language Models (LLMs) AI tools to complete their assignments and nine students who did not. It also contains interviews with six Faculty and their perspectives on students’ use of Large Language Models (LLMs) AI tools to complete their assignments and their thoughts on the benefits and challenges. The participants were purposively selected. The data were coded based on Braun and Clarke’s (2013) six steps in thematic analysis. Descriptive, in vivo, and evaluative coding were used. Additionally, data were examined semantically and latently using reductionist analysis to determine the final themes. Five components of the Unified Theory of Acceptance and Use of Technology (UTTAUT) were applied to the data collected and provided the framework for the study. Behavioural intention served as the foundation. Effort and Performance Expectancies, and facilitating conditions were exemplified in participants’ responses about the use of ChatGPT, Grammarly, and other AI assistive tools, plagiarism/academic integrity, and social influence were indicated when participants (both Students and Faculty) suggested the need for the development of policies and procedures toward the appropriate use of AI tools. Effort and performance expectancies and habits were found in the data collected in the form of consideration of the pros of using AI tools such as ChatGPT and assistive tools. These include the time saved by generating information, examples for both students and Faculty, and help in the teaching/learning process, and one participant found that it motivated her. The cons cited were students’ lack of creativity and the inability to think critically, the cost of the AI assistive tools (related to the component Price), the bandwidth needed to use them, the digital divide, and the false information generated. This study has significance for the use of ChatGPT and assistive AI tools in education and the ethical implications. It is recommended that specific policies be established and enacted to ensure the appropriate use of assistive and Artificial Intelligence (LLMs) tools.

ChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants' socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34-50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

ChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants' socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34-50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

Background ChatGPT is an open-source large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. Methods We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants’ socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. Results We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34–50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). Conclusion The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

ChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants' sociodemographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34-50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for nonacademic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

BackgroundChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda.MethodsWe conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants’ sociodemographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0.ResultsWe recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34–50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for nonacademic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]).ConclusionsThe use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

This survey study aims to understand how college students use and perceive artificial intelligence (AI) tools in the United Arab Emirates (UAE). It reports students’ use, perceived motivations, and ethical concerns and how these variables are interrelated. Responses (n = 822) were collected from seven universities in five UAE emirates. The findings show widespread use of AI tools (79.6%), with various factors affecting students’ perceptions about AI tools. Students also raised concerns about the lack of guidance on using AI tools. Furthermore, mediation analyses revealed the underlining psychological mechanisms pertaining to AI tool adoption: perceived benefits fully mediated the relationship between AI knowledge and usefulness perceptions, peer pressure mediated the relationship between academic stress and AI adoption intent, and ethical concerns fully mediated the relationship between ethical perceptions and support for institutional AI regulations. The findings of this study provide implications for the opportunities and challenges posed by AI tools in higher education. This study is one of the first to provide empirical insights into UAE college students’ use of AI tools, examining mediation models to explore the complexity of their motivations, ethical concerns, and institutional guidance. Ultimately, this study offers empirical data to higher education institutions and policymakers on student perspectives of AI tools in the UAE.

This study investigates the use of artificial intelligence (AI) tools for improving teachers' pedagogical skills at the secondary level. The purpose of the study was to examine how AI-driven applications become increasingly integrated into education, offering new opportunities for improving lesson planning, assessment practices, differentiated instruction, and classroom management. The study's objectives were to identify the level of awareness and understanding of AI tools and to determine the extent to which teachers utilise AI tools for pedagogical enhancement at the secondary level. In order to achieve the objectives, research questions were used to check the association between the use of artificial intelligence (AI) tools for enhancing teachers' pedagogical skills at the secondary level. The population includes female school teachers from the district of Mardan. The study sample consists of 320 female (primary, middle and secondary) school teachers, who were selected randomly. For the conduction of the study, a positivist research paradigm was used, and the research design was descriptive. A closed-ended questionnaire with a five-point Likert scale was used for data collection. The data was analysed to identify the level of awareness and understanding of AI tools, and to what extent teachers utilise AI tools for pedagogical enhancement. Data was scrutinised using SPSS: descriptive statistics (mean, standard deviation, frequency, and percentage) and inferential statistics (p<0.05) to determine the significance of AI use and pedagogical skills. The study findings underlined the need for professional training, Government support, and policy guidelines to ensure accountable AI integration in pedagogy.

Purpose: This analysis aims to propose guidelines for artificial intelligence (AI) research ethics in scientific publications, intending to inform publishers and academic institutional policies in order to guide them toward a coherent and consistent approach to AI research ethics.Methods: A literature-based thematic analysis was conducted. The study reviewed the publication policies of the top 10 journal publishers addressing the use of AI in scholarly publications as of October 2024. Thematic analysis using Atlas.ti identified themes and subthemes across the documents, which were consolidated into proposed research ethics guidelines for using generative AI and AI-assisted tools in scholarly publications.Results: The analysis revealed inconsistencies among publishers’ policies on AI use in research and publications. AI-assisted tools for grammar and formatting are generally accepted, but positions vary regarding generative AI tools used in pre-writing and research methods. Key themes identified include author accountability, human oversight, recognized and unrecognized uses of AI tools, and the necessity for transparency in disclosing AI usage. All publishers agree that AI tools cannot be listed as authors. Concerns involve biases, quality and reliability issues, compliance with intellectual property rights, and limitations of AI detection tools.Conclusion: The article highlights the significant knowledge gap and inconsistencies in guidelines for AI use in scientific research. There is an urgent need for unified ethical standards, and guidelines are proposed for distinguishing between the accepted use of AI-assisted tools and the cautious use of generative AI tools.

The Value of Artificial Intelligence for Healthcare Decision Making—Lessons Learned

Technical English (TE) proficiency is crucial for the future careers of polytechnic students. While Artificial Intelligence (AI) tools offer significant potential to enhance language learning, their effectiveness relies on student acceptance and use. There is limited understanding of what drives polytechnic students to adopt these tools specifically for TE. This study aims to identify the key factors influencing polytechnic students' acceptance and use of AI tools in this context and employ a quantitative approach based on the Technology Acceptance Model (TAM) and Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data collected from 100 Polytechnic Kota Bharu (PKB) students enrolled in TE courses. The research investigates core antecedents, primarily perceived usefulness (PU) and perceived ease of use (PEOU), and their impact on students' behavioral intention (BI) to use AI tools. The potential influence of external factors such as social influence and lecturer support are examined. The study found PEOU was identified as a critical antecedent, which significantly positively affected PU and BI. The study reaffirmed the significant predictive power of BI on AU, indicating that students' stated intentions reliably translate into their subsequent usage behaviour. This research will offer practical recommendations for educators seeking to integrate AI tools effectively into TE instruction. Theoretically, this study contributes to understanding technology adoption within the specific domain of technical and vocational language education, providing valuable insights for leveraging AI to improve essential communication skills for aspiring technical professionals.

Objective: To explore the perception of university students on the use of Artificial Intelligence (AI) tools for the development of autonomous learning. Theoretical Framework: The research is based on Technological Acceptance Theory and Constructivism, focusing on the perception of AI in autonomous learning of university students. Method: Quantitative approach with a descriptive scope, the sample consisted of 665 students enrolled in the Faculty of Education Sciences and Languages (FCEI) of the Peninsula de Santa Elena State University (UPSE)-Ecuador; in the collection of information, the Questionnaire of Perception on the Use of Artificial Intelligence for Autonomous Learning was designed based on 4 dimensions of both variables, and the statistical program SPSS version 29 was used for data processing. Results and Discussion: The results indicate that students show a favorable perception towards the use of AI tools for the autonomous learning process, however, although AI is recognized as a potential tool in university environments, there are still challenges to be overcome. Research Implications: The study has practical implications for strengthening in students the digital competencies needed to effectively use AI tools in their autonomous learning. Originality/Value: The research provides data on the perception of AI tools among university students, offering a starting point for future technology integration strategies in universities.

Using artificial intelligence (AI) tools in education is a contemporary method that enhances the evaluation, transformation, and promotion of learning and teaching processes. Integrating AI tools into the learning process in STEM fields contributes to the development of students' metacognitive abilities. This study aims to learn and evaluate adolescents' opinions and insights regarding the use of AI tools in STEM fields. Our research examines students' attitudes, confidence, and perceptions towards using AI tools and their perspectives on current global issues. Their views on the use of digital AI tools to solve these problems are also explored. Face-to-face interviews were conducted with eight participants for the study. The collected data were analyzed using content analysis methods. A review of the relevant literature revealed no studies similar to the methodology of this study. In this regard, we believe that the results of our study will benefit researchers conducting studies on the use of AI tools in education especially towards STEM education.