Unified Theory Of Acceptance And Use Of Technology Research Articles

Exploring Technology Integration in Education: Lecturers Perspective on Outcomes-Based Education Platforms

Informatics education is evolving rapidly through the adoption of Outcome-Based Education (OBE), necessitating a rigorous investigation into the effectiveness of the implementation. This study was conducted using the advanced Unified Theory of Acceptance and Use of Technology (UTAUT)-3 model to assess the potential of OBE systems in enhancing teaching and learning processes. The study integrated a comprehensive set of nine variables to measure the acceptance level of OBE systems among lecturers at Maranatha Christian University Bandung and Universitas Muhammadiyah Malang. UTAUT-3 provides a more explicit understanding by incorporating Hedonic Motivation (H.M.), Habit (H), and Personal Innovativeness (P.I.). The Model also integrated the core constructs of Performance Expectancy (P.E.), Effort Expectancy (E.E.), Social Influence (S.I.), Facilitating Conditions (F.C.), Behavioral Intention (B.I.), and Users Behavior (U.B.). The result showed that B.I. was a central determinant of U.B., suggesting users' preparedness to engage with OBE systems.Furthermore, the routine use of technology as Habit (H) was closely related to Behavioral Intension (B.I.), showing that familiarity with technology facilitated the intention to adopt OBE systems. The result showed that UTAUT-3's comprehensive framework was superior in evaluating educational technology adoption due to its ability to account for users' engagement as Hedonic Motivation (H.M.), dispositional tendencies toward Personal Innovativeness (P.I.), and the critical role of established habits. Consumers' actual experiences and technological proficiency significantly influence adoption rather than individual characteristics. Therefore, UTAUT-3 was a more effective tool for predicting and understanding the Acceptance of OBE systems, guiding educational institutions toward successfully integrating information systems in learning environments.

Navigating Technology Adoption/Acceptance Models

The accelerated rate of technological progress has significantly altered how individuals and or-ganizations interact with technology. Understanding the process of technology adoption has be-come crucial for remaining competitive in a world that is becoming increasingly digital. This entry provides an overview of numerous technology adoption models, shedding light on the factors that influence the adoption of new technologies by individuals and organizations. This entry examines the Technology Acceptance Model (TAM) is examined, with an emphasis on perceived utility and usability. Focusing on performance expectation, effort expectation, social influence, and facilitat-ing conditions, the Unified Theory of Acceptance and Use of Technology (UTAUT) is presented. In addition, the Technology-Organization-Environment (TOE) Framework is discussed, taking in-to account the three factors that influence adoption decisions. The Innovation Adoption Lifecycle is investigated, with the characteristics and motivations of various adopter categories highlighted. Individual, organizational, and external factors that influence the adoption of technology are also examined. The entry concludes by addressing the challenges and limitations of existing models and highlighting the importance of technology adoption research in influencing the future of soci-ety and business.

Examining the association between emotional intelligence and chatbot utilization in education: A cross-sectional examination of undergraduate students in the UAE

BackgroundWhile Emotional Intelligence (EI) demonstrably affects academic success, literature lacks exploration of how implementing chatbot in education might influence both academic performance and students' emotional intelligence, despite the evident potential of such technology. AimTo investigate the associations between Emotional Intelligence (EI), chatbot utilization among undergraduate students. MethodsA cross-sectional approach was employed, utilizing a convenience sample of 529 undergraduate students recruited through online questionnaires. The participants completed the Trait Emotional Intelligence Questionnaire and modified and a modified versions of the unified theory of acceptance and use of technology (UTAUT) model. Resultsof the 529 participants, 83.6 % (n = 440) of participants regularly used chatbot for learning. Students demonstrated a moderate average EI score (129.60 ± 50.15) and an exceptionally high score (89.61 ± 20.70) for chatbot acceptance and usage. A statistically significant (p < 0.001) positive correlation was found between chatbot usage frequency and EI total score. Gender and major emerged as significant factors, with female students (p < 0.05) and health science students (p < 0.05) utilizing chatbot less compared to male and other major students, respectively. A negative correlation (r = −0.111, p = 0.011) was observed between study hours and chatbot usage, suggesting students with higher study hours relied less on chatbot. ConclusionsThe positive correlation between chatbot use and EI in this study sparks promising avenues for enhancing the learning experience. By investing in further research to understand this link and integrate AI tools thoughtfully, policymakers and educators can cultivate a learning environment that prioritizes both academic excellence and student well-being, reflecting the values and perspectives of UAE culture.

Digital Adherence Technologies Linked to Mobile Money Incentives for Medication Adherence Among People Living With Tuberculosis: Mixed Methods Feasibility and Acceptability Study.

Complementing digital adherence technologies (DATs) with mobile money incentives may improve their utility in supporting tuberculosis medication adherence, yet the feasibility and acceptability of this integrated approach remain unclear. This study aims to describe the feasibility and acceptability of a novel DAT intervention called My Mobile Wallet composed of real-time adherence monitoring, SMS text message reminders, and mobile money incentives for tuberculosis medication adherence in a low-income setting. We purposively recruited people living with tuberculosis from the Mbarara Regional Referral Hospital in Mbarara, Uganda, who (1) were starting tuberculosis treatment at enrollment or within the past 4 weeks, (2) owned a mobile phone, (3) were able to use SMS test messaging, (4) were aged ≥18 years, and (5) were living in Mbarara district. At study exit (month 6), we used interviews and questionnaires informed by the unified theory of acceptance and use of technology (UTAUT) to collect feasibility and acceptability data, reflecting patients' experiences of using each component of My Mobile Wallet. Feasibility also included tracking the functionality of the adherence monitor (ie, an electronic pillbox) as well as SMS text message and mobile money delivery. We used a content analytical approach to inductively analyze qualitative data and Stata (version 13; StataCorp LLC) to analyze quantitative data. All 39 participants reported that the intervention was feasible because it was easy for them to use (eg, access and read SMS text messages) and worked as expected. Almost all SMS text messages (6880/7064, 97.4%) were sent as planned. The transmission of adherence data from the monitor worked well, with 98.37% (5682/5776) of the data transmitted as planned. All participants additionally reported that the intervention was acceptable because it helped them take their tuberculosis medication as prescribed; the mobile money incentives relieved them of tuberculosis-related financial burdens; SMS text message reminders and electronic pillbox-based alarms reminded them to take their medication on time; and participants perceived real-time adherence monitoring as "being watched" while taking their medication, which encouraged them to take their medication on time to demonstrate their commitment. The intervention was perceived as a sign of care, which eventually created emotional support and a sense of connectedness to health care. Participants preferred daily SMS text message reminders (32/39, 82%) to reminders linked to missed doses (7/39, 18%), citing the fact that tuberculosis medication is taken daily. The use of real-time adherence monitoring linked to SMS text message reminders and mobile money incentives for tuberculosis medication adherence was feasible and acceptable in a low-resource setting where poverty-based structural barriers heavily constrain tuberculosis treatment and care.

Mixed-methods approach to investigating the diffusion of FinTech services: enriching the applicability of TOE and UTAUT models

PurposeThe rapid global use of Financial Technology (FinTech), an innovative and advanced technology, is leading to the replacement of traditional financial services. Despite this, consumers in the United Arab Emirates are still not accepting FinTech services as anticipated. This study aims to investigate the barriers preventing consumers from using FinTech services in the banking industry based on the technology-organisation-environment (TOE) framework and anchored by the unified theory of acceptance and use of technology (UTAUT).Design/methodology/approachThe current study used an exploratory sequential mixed-method design. A purposive sample was used to conduct preliminary semi-structured interviews with ten banking practitioners. These interviews aimed to explore the obstacles that hinder consumers from adopting FinTech services. To provide further empirical validation, the conceptual model has been systematically examined through a quantitative cross-sectional online survey encompassing a sample of 332 bank customers.FindingsThe qualitative investigation highlighted six new barriers to the usage of FinTech based on TOE’s model attributes. Through quantitative data analysis, the preliminary qualitative findings were primarily verified. It was discovered that self-efficacy, electronic word-of-mouth, system quality and bank image substantially influence consumers to use FinTech services, in addition to performance expectancy and facilitating conditions. Meanwhile, IT features and governmental support were found to have insignificant effects. Yet, government support was found to have a positive moderating role in strengthening social influence and system quality towards customer use of FinTech. Thus, the research supports the UTAUT and TOE models’ fitness for explaining FinTech usage with high predictive relevance.Originality/valueThis study is the authors’ pioneering effort to propose a comprehensive research framework that integrates the UTAUT and TOE models to tackle the limited adoption of FinTech services among consumers. Moreover, the study specifically examined the moderating influence of government support to propose an integrated model. Remarkably, this study is one of the initial attempts to investigate the adoption of FinTech using a mixed-methodology approach by incorporating quantitative and qualitative methods within a single inquiry to yield more comprehensive and insightful findings than research that relies on a single method.

Exploring Sustainable Learning Intentions of Employees Using Online Learning Modules of Office Apps Based on User Experience Factors: Using the Adapted UTAUT Model

Research on the information module has identified a range of factors in the adoption model that determine their intention to learn sustainably. This research investigates the determinants of employees’ intentions to use an online learning module within an office application, utilizing a modified Unified Theory of Acceptance and Use of Technology (UTAUT) model. Data were collected from 564 employees in different organizations and analyzed using structural equation modeling. The research examines correlations between four key determinants—performance expectancy, effort expectancy, social influence, and facilitating conditions—and eight user experience motivational factors, including career development, business needs, self-management, learning experience, company atmosphere, external pressure, company support, and course quality. The findings indicate that all four UTAUT determinants significantly support employees’ use of the online learning module for continuous learning. Performance expectancy is positively influenced by career development and business needs, effort expectancy by self-management, social influence by external pressure, and facilitating conditions by company support and course quality. The learning experience and company atmosphere showed no significant correlation. The study offers valuable insights for managers, investors, and developers to enhance the adoption of online learning modules, promoting sustainable learning and employee development.

Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial.

Mental health problems are prevalent among people with diabetes, yet often under-diagnosed. Smart sensing, utilizing passively collected digital markers through digital devices, is an innovative diagnostic approach that can support mental health screening and intervention. However, the acceptance of this technology remains unclear. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study aimed to investigate (1) the acceptance of smart sensing in a diabetes sample, (2) the determinants of acceptance, and (3) the effectiveness of an acceptance facilitating intervention (AFI). A total of N = 132 participants with diabetes were randomized to an intervention group (IG) or a control group (CG). The IG received a video-based AFI on smart sensing and the CG received an educational video on mindfulness. Acceptance and its potential determinants were assessed through an online questionnaire as a single post-measurement. The self-reported behavioral intention, interest in using a smart sensing application and installation of a smart sensing application were assessed as outcomes. The data were analyzed using latent structural equation modeling and t-tests. The acceptance of smart sensing at baseline was average (M = 12.64, SD = 4.24) with 27.8% showing low, 40.3% moderate, and 31.9% high acceptance. Performance expectancy (γ = 0.64, p < 0.001), social influence (γ = 0.23, p = .032) and trust (γ = 0.27, p = .040) were identified as potential determinants of acceptance, explaining 84% of the variance. SEM model fit was acceptable (RMSEA = 0.073, SRMR = 0.059). The intervention did not significantly impact acceptance (γ = 0.25, 95%-CI: -0.16-0.65, p = .233), interest (OR = 0.76, 95% CI: 0.38-1.52, p = .445) or app installation rates (OR = 1.13, 95% CI: 0.47-2.73, p = .777). The high variance in acceptance supports a need for acceptance facilitating procedures. The analyzed model supported performance expectancy, social influence, and trust as potential determinants of smart sensing acceptance; perceived benefit was the most influential factor towards acceptance. The AFI was not significant. Future research should further explore factors contributing to smart sensing acceptance and address implementation barriers.

Determinants of internet of things (IoT) smart home technology (SHT) adoption behavior of consumers: Empirical evidence from a least developed country (LDC)

Though millions of users in developed countries utilize IoT smart home technology, its applicability in underdeveloped countries is limited. This study addresses this gap by unveiling the determinants of IoT smart home technology adoption behavior among consumers in the least developed country. The study has extended the unified theory of acceptance and use of technology (UTAUT) by including perceived hedonism, lifestyle, and well-being constructs in the research framework. Data from 355 IoT smart home users were analyzed using structural equation modeling (SEM). The findings reveal that performance expectancy, facilitating conditions, perceived hedonism, and lifestyle positively affect behavioral intention. Moreover, behavioral intention positively affects use behavior. In the post-adoption stage, use behavior positively affects multifaceted user well-being. However, effort expectancy and social influence did not affect behavioral intention. The study has a novel theoretical contribution to the extant literature and significantly contributes to technology designers, marketers, elderly users, and government agencies.

A Unified Theory of Acceptance and Use of Technology Assessment in Learning Resources Management and Development System

The platform for Learning Resource Management and Development System (LRMDS) has the potential to be helpful for learning. Teachers find support and resources from the learning portal of the Department of Education. This study focused on determining the acceptance of the Learning Resources Management Development System (LRMDS) as a learning resource portal using the Unified Theory of Acceptance and Use of Technology (UTAUT) model among EPP/TLE/TVL teachers in the Division of Iligan City. For the sample selection based on structures and items, Soper's (2024) a-priori sample size calculator for structural modeling was utilized. This calculator calculates the minimum need to identify desired effects for a structural equation model inquiry by considering variables, effect size, and power levels. The study was based on quantitative and qualitative research designs via demographic questionnaire based on the UTAUT theory model and the perception questions. Findings indicate that the effort expectancy and social influence have positive effects on behavior intentions and facilitating conditions; behavioral intentions also have positive effects on use behavior. However, Performance expectancy is not significant. Additionally, qualitative findings suggest that teachers believe the LRMDS can greatly improve teaching effectiveness when viewed as valuable and dependable, resulting in its effective use. Teachers generally consider the content provided by LRMDS to be relevant and sufficient. However, a significant issue is that some resources, particularly in TLE (Technology and Livelihood Education), are outdated, likely due to limited access to ready-made resources and sufficient learning materials. The findings of this study also suggest that enhancing LRMDS integration, communication and outreach efforts are recommended, including a training guide matrix to raise awareness of LRMDS benefits and address misconceptions through targeted campaigns, workshops, and peer sharing. Recommendations include improving knowledge management, simplifying user interfaces, informing teachers about support conditions, and implementing the training guide matrix in public schools to highlight the advantages of the LRMDS portal.

Generating customer wealth by mobile-based agricultural extension services: BOP farmers in the emerging markets

Purpose This research was motivated by the recognition that the use of mobile-based agricultural extension services (AES) applications has become increasingly popular among the bottom of the pyramid segment in recent years. However, users’ adoption is determined not only by their perception of the technology but also by its perceived wealth. In other words, even though a technology may be perceived as advanced, if it does not fit users’ wealth perception benefits, they may not adopt it. Using an extended unified theory of acceptance and use of technology (UTAUT) perspective, this study aims to explore potential predictors of behavioral intention toward AES such as effort expectancy, performance expectancy, customer wealth (CW), social influence and perceived characteristics of innovation. Design/methodology/approach Potential causal connections between key UTAUT factors and users’ intentions to use the services are hypothesized. An integrated theoretical model was developed and tested against the empirical data collected from 336 AES users. A measurement model and structural equation model were tested using AMOS 22.0 and confirmed all 14 hypothesized relationships. Findings The results were consistent with the recent literature on mobile technology acceptance, confirming an unmoderated relationship between CW and the adoption of mobile-based AES. This research proposes a mobile AES user adoption model by integrating CW with the unified theory of acceptance and usage of technology (UTAUT). Originality/value This study establishes CW as an outcome of various relationships.

Do in-service teachers accept artificial intelligence-driven technology? The mediating role of school support and resources

This study investigates the acceptance and utilization of artificial intelligence (AI) among in-service teachers in Lesotho, focusing on the mediating role of school support and resources (SSR). In Lesotho's educational landscape, which is characterized by a growing interest in technology integration, this study fills an essential gap in the existing literature by exploring in-service teachers' perspectives on AI adoption and the mediating influence of SSR. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, the study adopts a cross-sectional design, collecting data from a sample of 315 in-service teachers through online surveys. The data was analyzed using maximum likelihood estimation. The results reveal a substantial positive relationship between perceived usefulness, perceived ease of use, and a positive attitude towards AI, with SSR playing a pivotal role as a complementary mediator in these connections. However, the study identifies a non-significant relationship between technical proficiency and behavioral intention, suggesting a need for further investigation into the technical skills essential for effective AI integration. The results highlight the critical role of SSR in shaping in-service teachers' intentions to use AI in their teaching practices. As a result, the study recommends tailored continuous professional development programs and collaborative learning communities to enhance teachers' skills. Additionally, it emphasizes the importance of advocating for policies that support AI integration in education and underscores the ethical considerations related to AI use. We discuss the implications of our results concerning integrating AI into teachers' teaching practices in schools and outline future directions.

Psychological factors influencing online booking intentions among resort tourism service users

PurposeThis study examines the psychological factors that directly influence individuals’ intentions to book or arrange reservations through resort hotel websites within the context of the Unified Theory of Acceptance and Use of Technology (UTAUT). Specifically, this study focused on identifying and understanding the key drivers of online purchase intentions, including performance expectancy, effort expectancy, social influence and facilitating conditions within the UTAUT model.Design/methodology/approachThis study used the UTAUT as a theoretical framework. A quantitative research approach was adopted and data were collected through surveys using a five-point Likert scale. The sample consisted of 270 participants, selected through purposive sampling. Data analysis was performed using Smart PLS software.FindingsThe results indicate that performance and effort expectancy significantly influence online purchase intentions. However, social influence did not significantly affect online purchase intention. By contrast, facilitating conditions significantly and positively influence online purchase intention.Practical implicationsThese findings have practical implications for hotel managers and marketers. Emphasizing performance, effort expectations and facilitating conditions can improve customer perceptions of website usefulness and directly increase their intention to book. The limited impact of social influence suggests the need to focus less on social recommendations or endorsements in online marketing efforts and prioritize individual factors and objective information.Originality/valueThis study contributes to the field of technology and tourism by examining the psychological factors that directly influence users’ intention to purchase from resort hotel websites. This extends the understanding of online purchase intentions in the context of resort tourism and highlights the importance of facilitating conditions. This study also partially confirms the applicability of the UTAUT model in this domain and provides insights for future research on online purchase intentions in resort tourism.

Adoption of e-learning by pre-university students following the COVID-19 pandemic: An analysis based on the unified theory of acceptance and use of technology (UTAUT)

Adoption of e-learning by pre-university students following the COVID-19 pandemic: An analysis based on the unified theory of acceptance and use of technology (UTAUT)

Factors influencing the purchase intention toward electric vehicles; a nonuser perspective

PurposeThe demand for electric vehicles (EVs) has significantly increased in recent years, though some countries like Sri Lanka have reported the opposite direction compared to the global trend. Hence, this study focused on identifying factors affecting EV purchase intention and barriers to the widespread adoption of EVs in a developing country context. Also, this study presents an overview of the theoretical perspectives utilized for understanding consumer intentions and adoption behavior toward alternative fuel vehicles (AFVs).Design/methodology/approachThe questionnaire method was employed, and 394 individuals who lived in Colombo City, Sri Lanka, with valid driving licenses and a hybrid or conventional vehicle were the study sample. The partial least squares structural equation modeling (PLS-SEM) was used to test the research hypothesis.FindingsThe findings confirmed that the three relationships between the unified theory of acceptance and use of technology (UTAUT) variables and EV purchase intention are significant, and there is no significant moderator effect from the consumer’s perceived risk.Originality/valueThese results offer useful information for governments and EV companies to better understand consumer behavior toward purchasing EVs.

The (Un)Knowledgeable, the (Un)Skilled? Undertaking Chat-GPT Users’ Benefit-Risk-Coping Paradox in Higher Education Focusing on an Integrated, UTAUT and PMT

The advent of Chat-GPT, an AI-driven technology, is reshaping various sectors, particularly higher education. This study, merging the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Protection Motivation Theory (PMT), explores the relationship between technology adoption and protection motivation in higher education, addressing the concept of “the (un)knowledgeable, the (un)skilled.” Through Structural Equation Modeling, findings from Indonesian participants (N = 445), including students and lecturers, reveal that perceived benefits such as task efficiency, hedonic motivation, performance expectancy, and effort expectancy predominantly motivate Chat-GPT use. Risk perception leans more on perceived vulnerability than severity, with insignificant impact from response cost. Response efficacy and self-efficacy significantly determine intention. Insight from moderating effect of educational level suggest that doctoral-level users demonstrate increased Chat-GPT usage, and gender plays a role in response efficacy and task efficiency. Both educational level and gender actively influence users’ intentions and actual usage behavior. These insights guide educators, policymakers, and institutions in ethically integrating AI, managing evolving risk perceptions, and empowering users in the dynamic AI landscape of higher education. Policymakers (e.g., university boards) are urged to dexterity an ethical framework and authorize in user efficacy to ensure equitable access and benefits from Chat-GPT in education.

ACCEPTANCE OF m-HEALTH AND ITS COMPLEXITY FOR THE PROVISION OF QUALITY HEALTHCARE SERVICES

Objectives: To identify the factors affecting the adoption of mobile health, assess the perception of the role of mobile health in health care service, and compare the technology acceptability and complexity trend among Community Health Workers. Materials and methods: A cross-sectional quantitative study was done using a two-stage sampling technique to collect the required sample from 308 Community Health Workers (CHWs) comprising 258 Lady health workers (LHW), 21 Community midwives (CMWs), 18 Lady health visitors (LHVs) and 11 Family welfare workers /councilors (FWWs/FWCs) of district Peshawar. Data was analyzed using SPSS version 22. Results: The majority of CHWs agree that mobile phones are useful in communication with fellow health professionals, diagnostic and treatment support, and medical data collection. The majority of CHWs were, willing to adopt mHealth technology. CHWs believed that mHealth adoption could make their job easier and improve access to healthcare services. mHealth can also enhance disease prevention and awareness. Affordability, result orientation, and easy usage are the significant factors in the adoption of mHealth. Conclusion: mHealth usefulness and acceptance role for awareness, and disease prevention are the most agreed factors in the view of community health workers. Highest PCA score recordings for “m-health make it more accessible, affordable for the general population". Key Words: Community Health Workers, Unified Theory of Acceptance and use of technology (UTAUT), mHealth.

Acceptance and use of ChatGPT in the academic community

AbstractSince OpenAI released ChatGPT, the discussion on its usage in education has been conducted by students and teachers of every education level. Also, many studies have been performed on the tool’s possibilities and the threats related to its usage, such as incomplete or inaccurate information obtained or even plagiarism. Many universities worldwide have introduced specific regulations on ChatGPT usage in academic work. Furthermore, research on using ChatGPT by students and their attitudes towards it has appeared. However, a research gap exists in higher education teachers’ acceptance of AI solutions. The goal of this research was to explore the level of acceptance of the usage of ChatGPT by academics in Poland, as well as point out factors influencing their intention to use this tool. The study motivation was related to an ongoing academic discussion mainly focusing on the disadvantages of AI solutions used in scientific work and the willingness to fill the gap by showing teachers’ attitudes toward AI. The data was collected online by inviting academic teachers from Polish public universities to complete the prepared survey. The survey was prepared using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model extended with Personal Innovativeness. It revealed the acceptance level of ChatGPT usage in Polish universities by teachers and researchers and the antecedents influencing willingness to use this technology in academic work. The paper contributes to the theory of AI usage by structuring the studies regarding ChatGPT application for teaching and research, and provides practical recommendations on ChatGPT adoption in the work of academics.

Development and Acceptability of Web-based Module in Cookery

This study delves into the development and acceptance of a web-based cookery module, aiming to enhance culinary education, particularly in the face of challenges such as the pandemic. These modules offer promising avenues for effective learning experiences and the promotion of self-regulated learning among students. Employing a mixed-method approach utilizing the Input-Process-Output design model, the study involves the validation of the developed module by eight expert practitioners in cookery. Subsequently, its acceptability will be assessed among Senior High School (SHS) Technical-Vocational-Livelihood (TVL) students enrolled in cookery subjects during the academic year 2023-2024. Evaluation of the module by teacher experts utilizes a four-point rating scale, drawing from the Guidelines and Processes for Learning Resource Management and Development System (LRMDS) Assessment &amp; Evaluation – Evaluation Rating Sheet for Non-Print Materials (DepEd, 2009), focusing on content quality, instructional quality, technical quality, and other pertinent factors. Similarly, student feedback is gathered through a five-point scale adapted from Venkatesh et al. (2003) and modified by Namoco, S. (2021) to align with the Unified Theory of Acceptance and Use of Technology (UTAUT) model, offering both rating scale responses and descriptive interpretations. Both teacher experts and student users are purposefully selected for their insights. Initial findings from the expert evaluation indicate a high recommendation for implementing the web-based module in cookery education. However, ongoing data collection and analysis are underway to gauge student-user acceptability comprehensively. This study underscores the significance of well-designed interactive learning modules in fostering self-regulated learning and enhancing student performance in cookery subjects, notwithstanding the challenges posed by the pandemic and economic constraints.

Use of ChatGPT for education by engineering students in developing countries: a mixed-methods study

ABSTRACT Developing countries face challenges in AI integration into learning initiatives. With the widespread use of ChatGPT, many concerns were expressed. Thus, it is crucial to investigate students' attitudes toward ChatGPT and the factors influencing their decision to continue using it in the future. We used a mixed-methods triangulation design based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and collected data based on convenience sampling from N = 195 engineering students in developing countries through semi-structured surveys with open-ended questions. Quantitative analysis included descriptive statistics and logistic regression, while thematic analysis was used for the qualitative part. Most students (89.69%) use ChatGPT, with all the elements of the UTAUT framework being strong predictors of their intention to continue. Most have continuous internet access and feel comfortable using technology. High-frequency usage, perceived benefits, and peer encouragement positively influence students' intention to continue using ChatGPT. However, concerns about accuracy, privacy, and laziness negatively correlate with usage intention. Address personal, institutional, and governmental concerns to integrate ChatGPT safely in educational systems, ensuring equitable access and preparing for future e-learning initiatives.

Explaining primary school teachers’ intention to use digital learning platforms for students’ individualized practice: comparison of the standard UTAUT and an extended model

IntroductionThough technologies for individualization appear to benefit primary school students’ learning, studies suggest that their integration remains sparse. Technology acceptance research has largely focused on exploring teachers’ general acceptance of educational technologies, although factors might predict usage intentions differently depending on the specific usage purpose of an educational technology. Digital learning platforms for individualized practice are comparably challenging and complex to use and so far, predictors of primary school teachers’ intention to integrate such technologies into lessons are largely unknown. Meanwhile, research on teachers’ technology acceptance generally lacks comparability due to the absence of a shared theoretical model and usage purpose specification.MethodsIn a sample of 272 German primary school teachers, this study aims to identify predictors of teachers’ acceptance of digital learning platforms for students’ individualized practice in consideration of the unified theory of acceptance and use of technology (UTAUT). To ensure a shared understanding, teachers were provided with a video which specified the addressed usage purpose. Regarding teachers’ usage intention, the explanatory power of the standard UTAUT predictors was investigated and compared with an extended UTAUT model accounting for seven additional context-specific predictors.ResultsThe standard UTAUT significantly explained teachers’ usage intention, with performance expectancy, effort expectancy, and the availability of the necessary technical infrastructure showing significant associations with intention. However, neither a significant nor meaningful increase in explained variance was observed for the extended UTAUT model.DiscussionResults suggest that the standard UTAUT model is sufficient in explaining teachers’ usage intention and that its extension by context-specific predictors provides no added value. Acceptance facilitating interventions should therefore target performance and effort expectancy as well as the availability of technical infrastructure. Thus, underlining that successful implementation of complex educational technologies should consider both, individual and structural factors.