Using the UTAUT model to understand students' usage of e-learning systems in developing countries

Behavioral intentions of university teachers and students toward the adoption of the hyb-blended learning method: Evidence from Bangladesh

Hyb-blended learning is a novel method that can serve as a substitute for conventional classroom-based learning activities, demonstrating effectiveness in both pandemics like COVID-19 and other crises, as well as in non-pandemic situations. The successful application of this method in the field of education depends on the users' intentions to adopt it. Therefore, this study aims to understand the behavioral intentions of teachers and students at Bangladeshi universities toward the adoption of the hyb-blended learning method. A correlational, cross-sectional, and sample survey-based research design was employed. Two structured questionnaires, one for teachers and one for students, were used to collect data from 171 teachers and 713 students from 11 public and 8 private universities in Bangladesh. The conceptual model of the study was developed on the theoretical underpinnings of the "Unified Theory of Acceptance and Use of Technology (UTAUT)." The study used a structural equation modeling technique to test the hypotheses. The results of the study revealed that the proposed learning method would increase teaching and learning opportunities for both teachers and students in Bangladeshi universities. They would adopt this method without relying on the experiences of others or what others think or say. Unlike teachers, the study also found that students would use it if they received support and influence from friends, fellow students, university authorities, and other external factors. However, their intentions toward adopting this method depend on the availability of resources and support for adopting it, as well as adequate and necessary understanding and talent to use it effectively. Results also revealed that they would adopt the method if it was found to be simple to use. The study has a notable practical implication, as it has proposed an alternative learning and teaching method that would be effective in Bangladeshi universities during the COVID-19 pandemic or other crises and in non-pandemic situations as well.

Social Robots for Meaningful Seated Activities: Acceptance & Use by Older Adults

Healthy aging requires the maintenance of good physical and cognitive activity. However, as they age, older adults often experience a decline in physical and cognitive activity, leading to a more sedentary lifestyle. Some older adults may not have a choice but to become increasingly sedentary as they age due to injury or deteriorated physicality. As such, they require assistive technologies to aid in their daily lives and activities to maintain healthy cognitive function. Social Robots are a newer form of assistive technology, specifically designed for social interactions and gameplay. As with other assistive technologies, compliance barriers to their acceptance and use for meaningful, seated activities among older adults are expected. To better explore this phenomenon, improve quality of life and understand what drives older adults to accept and use newer forms of technology like social robots, this conceptual paper conjoins two theoretical frameworks: The Activity Theory of Aging (ATA) and the Unified Theory of Acceptance and Use of Technology (UTAUT). As social robots hold great promise for improving the quality of life for older adults, exploring what driving factors could enable their greater acceptance and use is essential to furthering this field of study within Australia.

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

Background

While 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.

Aim

To investigate the associations between Emotional Intelligence (EI), chatbot utilization among undergraduate students.

Methods

A 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.

Results

of 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.

Conclusions

The 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.

AI in medical education: the moderating role of the chilling effect and STARA awareness

BACKGROUND

The rapid growth of artificial intelligence (AI) technologies has been driven by the latest advances in computing power. Although, there exists a dearth of research on the application of AI in medical education.

METHODS

this study is based on the TAM-ISSM-UTAUT model and introduces STARA awareness and chilling effect as moderating variables. A total of 657 valid questionnaires were collected from students of a medical university in Dalian, China, and data were statistically described using SPSS version 26, Amos 3.0 software was used to validate the research model, as well as moderated effects analysis using Process (3.3.1) software, and Origin (2021) software.

RESULTS

The findings reveal that both information quality and perceived usefulness are pivotal factors that positively influence the willingness to use AI products. It also uncovers the moderating influence of the chilling effect and STARA awareness.

CONCLUSIONS

This suggests that enhancing information quality can be a key strategy to encourage the widespread use of AI products. Furthermore, this investigation offers valuable insights into the intersection of medical education and AI use from the standpoint of medical students. This research may prove to be pertinent in shaping the promotion of Medical Education Intelligence in the future.

Factors affecting medical students' intention to use Rain Classroom: a cross-sectional survey

BACKGROUND

Rain Classroom was one of the most popular online learning platforms in Chinese higher education during the pandemic. However, there is little research on user intention under the guidance of technology acceptance and unified theory (UTAUT).

OBJECTIVE

This research aims to determine factors influencing students' behavioural intention to use Rain Classroom.

METHODS

In this cross-sectional and correlational investigation, 1138 medical students from five medical universities in Guangxi Province, China, made up the sample. This study added self-efficacy (SE), motivation (MO), stress (ST), and anxiety (AN) to the UTAUT framework. This study modified the framework by excluding actual usage variables and focusing only on intention determinants. SPSS-26 and AMOS-26 were used to analyze the data. The structural equation modelling technique was chosen to confirm the hypotheses.

RESULTS

Except for facilitating conditions (FC), all proposed factors, including performance expectancy (PE), effort expectancy (EE), social influence (SI), self-efficacy (SE), motivation (MO), anxiety (AN), and stress (ST), had a significant effect on students' behavioural intentions to use Rain Classroom.

CONCLUSIONS

The research revealed that the proposed model, which was based on the UTAUT, is excellent at identifying the variables that influence students' behavioural intentions in the Rain Classroom. Higher education institutions can plan and implement productive classrooms.

AI in medical education: medical student perception, curriculum recommendations and design suggestions

Medical AI has transformed modern medicine and created a new environment for future doctors. However, medical education has failed to keep pace with these advances, and it is essential to provide systematic education on medical AI to current medical undergraduate and postgraduate students. To address this issue, our study utilized the Unified Theory of Acceptance and Use of Technology model to identify key factors that influence the acceptance and intention to use medical AI. We collected data from 1,243 undergraduate and postgraduate students from 13 universities and 33 hospitals, and 54.3% reported prior experience using medical AI. Our findings indicated that medical postgraduate students have a higher level of awareness in using medical AI than undergraduate students. The intention to use medical AI is positively associated with factors such as performance expectancy, habit, hedonic motivation, and trust. Therefore, future medical education should prioritize promoting students' performance in training, and courses should be designed to be both easy to learn and engaging, ensuring that students are equipped with the necessary skills to succeed in their future medical careers.

A study on factors influencing Chinese undergraduate EFL learners' self-directed use of mobile English learning resources

This study aimed to examine the factors that potentially impact the self-directed use of mobile English learning resources (MELR). The participants were 206 Chinese undergraduate EFL learners at Yangzhou University in Mainland China. Applying and modifying the Unified Theory of Acceptance and Use of Technology (UTAUT), this study involved six constructs, including students' performance expectancy, effort expectancy, social influence, facilitating conditions, perceived playfulness, and behavioral intention to use MELR. The structural equation modeling (SEM) technique was adopted to analyze the data collected from the questionnaire. The findings showed that facilitating conditions acted as the most significant predictor of behavioral intention to adopt MELR, followed by effort expectancy, perceived playfulness, and performance expectancy. However, social influence did not have significant effects on students' use of MELR. Pedagogical implications for teachers and students were also presented in the end.

Gravitating towards Fintech: A study on Undergraduates using extended UTAUT model

One of the most pressing issues affecting people worldwide is the accessibility of financial services in the wake of the COVID-19 outbreak. While peoples' adoption of technological advancements has spiraled over time, the acceptance of Fintech services edged up for instilling resilience during the pandemic. Hence, the study aims at exhuming the Fintech adoption for sustainable financial inclusion among young undergraduate users through the Unified Theory of Acceptance and Use of Technology (UTAUT) model. To test the model, the researchers obtained data from 375 undergrads. The study adopted the Structural Equation Modelling (SEM) approach in AMOS software to examine the determinants that affect the users to embrace Fintech services. The findings revealed that performance expectancy, effort expectancy, and facilitating conditions significantly influence the students' intention to use Fintech, whereas, the users' facilitating condition and behavioral purposes positively influence them to use the financial technology. Interestingly, the social influence and personal innovativeness did not affect their intention to accept and adopt Fintech. Therefore, the study results will help explore the expectations, preferences, and actual level of use of Fintech among undergraduates and contribute to the escalation of Fintech use, leading to sustainable financial inclusion.

Understanding student intentions to take online courses: A theory-driven examination of adoption factors and prior experience

Online education options have expanded rapidly, yet empirical knowledge of students' adoption choices remains relatively limited. Within higher education, it is important for both instructors and administrators to understand what students value in online courses in order to provide a quality learning experience and manage enrollment demands. The current work applies and expands on the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine factors involved in course modality choices. Study 1 (N = 257) uses a single discipline to validate measures of online course perceptions and provide initial predictive evidence. Study 2 (N = 1257) examines adoption intentions among students in a wide range of disciplines. Performance expectancies, hedonic motivation, and flexibility emerged as the most substantial factors in student decisions about course modality. The results also reveal shifts in online course perceptions over time, including larger shifts for students with no prior online course experience. These findings expand current understanding of why students choose to take (or avoid) online courses, particularly concerning the role of flexibility in enrollment decisions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10639-023-11823-4.

Willingness of university students to continue using e-Learning platforms after compelled adoption of technology: Test of an extended UTAUT model

The COVID-19 pandemic has prompted the adoption of an e-Learning pedagogy. This forced teachers and students to shift to online learning and thus was compelled to adopt online educational technology. Educational institutes have been facing challenges like insufficient infrastructure and a shortage of quality teachers. Online learning can help to address these challenges as online classes can accommodate more students. However, before implementing e-Learning technology management of institutes wants to be sure whether students will adopt new technology. Therefore, the purpose of this study was to unveil which factors are important to adopt new technology if implemented mandatorily. We tested the most popular technology acceptance model the UTAUT to understand students' intentions to continue using the e-Learning system in a mandatory environment. The study used a quantitative approach of research. The participants for this study were selected from a private university in India. The questionnaire for the study was adapted from previous studies. The survey was conducted by sharing an online link while students were attending classes online during the pandemic. Thus, the study utilized a convenience sampling technique. The data were analyzed using structural equation modelling. The findings revealed that the UTAUT model can partially explain the forceful adoption of technology. The study found 'Performance expectancy' and the 'availability of resources' as significant indicators of 'intention for continued usage'. This study recommends educational institutes should ensure students attain academic goals by using e-Learning platforms and ensuring the availability of essential resources to use the e-Learning technology.

Investigating the intention of purchasing private pension scheme based on an integrated FBM-UTAUT model: The case of China

The newly established private pension scheme in China has received great attention as it would be an important supplement to China’s social safety net and corporate annuity amid an aging population. It provides a way of helping to address the challenge of ensuring adequate retirement income, and the scheme is expected to grow significantly in the coming years. This study investigates factors affecting the intention of purchasing the private pension scheme using a conceptual model based on the integration of Fogg Behavioral Model (FBM) and Unified Theory of Acceptance and Use of Technology (UTAUT) model. The questionnaire-based data from a sample of 462 respondents had been analyzed. Both exploratory factor analysis and confirmatory factor analysis were used to assess validity. The hypothesized relationships in the integrated FBM-UTAUT model were tested using structural equation modeling. The research findings indicate that anticipation, social influence, effort expectancy, performance expectancy, side benefits and facilitating conditions have significant positive impacts on intention to purchase. According to the exploratory factor analysis, the integrated FBM-UTAUT model can explain more than 70% of the total variance. Meanwhile, effort expectancy can be affected by time effort, thought effort and physical effort collectively, while performance expectancy can be affected by risk and trust. It is revealed that the integrated FBM-UTAUT model can be effective in explaining purchase intentions in a private pension scheme context, and this study is expected to offer helpful advice on the design of pension products and the reform of pension policies.

A modified UTAUT framework to predict students' intention to adopt online learning: moderating role of openness to change

Purpose

The current study employs a modified framework of the unified theory of acceptance and use of technology (UTAUT) to predict students' intention to adopt online learning in India. The moderating role of openness to change in influencing the proposed relationships is also assessed.

Design/methodology/approach

A structured questionnaire was emailed to 650 students enrolled in various courses in public and private universities in India. In total 424 responses were considered for analysis using structural equation modeling (SEM). Moderation analysis was carried out with multi-group SEM and chi-square difference tests.

Findings

The results reveal that there is a significant impact of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FS) and perceived security (PS) on students' intention to adopt online learning. Further, openness to change moderates the impact of PE, FS and PS on intention of students to opt for online learning.

Originality/value

This study is one of the initial efforts to examine the factors affecting students' intention to adopt online learning at the onset of third wave of coronavirus disease 2019 (COVID-19) pandemic in India. Besides the factors of the UTAUT model, this study highlights the importance of PS and openness to change in influencing students' intention to opt for online learning.

Self-archiving of Scholarly Publications for improved access to local content in Tanzania: A study of Open Access Institutional Repositories in Universities in Tanzania

This study sought to investigate how the self-archiving of scholarly publications in Open Access Institutional Repositories can be strengthened for improved access to local content. Specifically, the study sought to investigate factors that influence self-archiving of scholarly publications in OAIRs, examine the implementation of OAIRs policies on self-archiving of scholarly publications in OAIRs and determine challenges that hinder self-archiving of scholarly publications in OAIRs. The population of the study consisted of 2894 faculty members and 413 sample size, obtained through a systematic random sampling technique. Data were collected using questionnaires and interviews with eight key informants. Key findings indicated that there are factors that influenced self-archiving of scholarly publications in OAIRs among faculty members such motivating factors, availability of technical support, supervisors/peers/colleagues and supporting services. Moreover, the study found challenges that hindered self-archiving as low level of awareness and inadequate advocacy for a self-archiving, lack of personal benefit such as rewards and promotions, fear of the plagiarism, lack of enough facilities like ICT and internet connectivity. The study also found that there was a need to implement OAIR policies in self-archiving of scholarly publications in the OAIRs. In order to strengthen self-archiving, the study recommends providing support services, technical supports, encouraging supervisors/peers/colleagues, creating awareness, providing personal benefits, provide education and give more time, effort and implement OAIR policies to enhance the process of self-archiving scholarly publications in OAIRs. The findings of this study shall contribute new knowledge to the existing research outputs that have been conducted in this field.

The impact of e-government information quality (EGIQ) dimensions on the adoption of electronic government services

E-government's capacity to reform public service delivery is hinged on critical factors from the demand side of e-government. The demand side of e-government is the element that drives users’ behaviors to adopt e-government services and understanding these factors is fundamental to driving the realization of e-government targets. This study thus examined the extent to which e-government information quality dimensions can stimulate the acceptance and utilization of e-government services. The Unified Theory of Acceptance and Use of Technology (UTAUT) was used as the theoretical basis for this paper and the data congregated was evaluated with Analysis of Moment Structures (AMOS) statistical software using the structural equation modeling (SEM) approach. The results have revealed that both effort expectancy and facilitating conditions significantly drive the intention to use and recommend the adoption of e-government services. Also, e-government information quality dimensions such as availability, objectivity, utility, confidentiality, and integrity were all found to positively drive the intention to use e-government services. Additionally, people's intention to use e-government was significant in driving the recommendation behavior of e-government services to others. The practical and research repercussions of these discoveries on the development and deployment of e-government-empowered services are deliberated.

Moderating Role of Perceived Trust and Perceived Service Quality on Consumers’ Use Behavior of Alipay e-wallet System: The Perspectives of Technology Acceptance Model and Theory of Planned Behavior

The advancement of e-wallet systems, including Alipay, has led consumers to embrace digital payment with financial technologies. Yet, limited research focused on the usage of e-wallets in the context of emerging economies. This research is aimed at investigating the predictors of consumers’ use behavior of the Alipay e-wallet system in an emerging market and moderating role of perceived trust and perceived service quality on this relationship. The technology acceptance model (TAM) and the theory of planned behavior (TPB) were applied as the guiding principle. Data gathered via online surveys among 378 Malaysian Alipay users were analyzed using the partial least square-structural equation modeling (PLS-SEM) approach. The results reveal that all hypotheses were significant towards consumers’ intention to use Alipay in an emerging market except for the moderating role of perceived trust. Perceived usefulness was the strongest predictor factor towards consumers’ intention to use Alipay in an emerging market. This is followed by perceived ease of use. They heavily emphasize the superiorities of Alipay over other e-wallet systems such as efficiency and convenience for conducting financial activities. This study contributes to the existing literature by proposing a comprehensive integrated research model. The research outcome can serve as a guideline for service providers towards enhancing consumers’ adoption of e-wallets for digital payment with financial technologies.

Adoption of online mathematics learning in Ugandan government universities during the COVID-19 pandemic: pre-service teachers' behavioural intention and challenges

In the wake of COVID-19, higher education institutions worldwide were forced to continue teaching and learning through online means. However, it was only during the pandemic that institutions in Uganda, such as Kabale University, embraced online learning. Against this background, one could not predict how students drastically adapted to the new normal, especially in mathematics, which requires a lot of practice. Thus, this study sought to establish the relationship between behavioural intention to use technology and the adoption of online mathematics learning among pre-service teachers at Kabale University. We conceptualized behavioural intention to use technology according to the Unified Theory of Acceptance and Use of Technology (UTAUT) as comprising four factors: performance expectancy, effort expectancy, facilitating conditions, and social influence. This mixed methods study followed a cross-sectional correlational survey and hermeneutic phenomenological research designs. We collected data from 140 pre-service mathematics teachers, who were sampled using stratified and simple random sampling techniques, through a self-administered questionnaire. Also, we collected qualitative data through nine face-to-face interviews of pre-service mathematics teachers using criterion sampling, where the most prominent criterion was the participant's experience with the phenomenon under study. Using Pearson's linear correlation, results showed that all UTAUT constructs were related to the adoption of online learning. Simple linear regression revealed that facilitating conditions were the strongest predictor. Furthermore, the narrative analysis indicated that, among others, a lack of technological knowledge hindered learners' effective participation in online mathematics lectures. Therefore they barely benefited from online learning. Thus, we recommend government universities enhance teachers' and learners' technological knowledge, among other facilitating conditions such as establishing strong on-campus Wi-Fi connections as online learning continues.

Adoption of social media-based knowledge-sharing behaviour and authentic leadership development: evidence from the educational sector of Pakistan during COVID-19

Purpose

This research paper aims to explore the influence of social media–based knowledge-sharing intentions (SMKI) on prospective authentic leadership development (ALD) to deal with the future crisis. In the existing literature, to the best of the authors’ knowledge, there is no significant empirical evidence to test the relationship between SMKI and ALD. Thus, this study contributes to the growing literature regarding the role of SMKIs, ALD, social media–based knowledge-sharing behavior (SMKB) and facilitating conditions (FCs). However, in this study, the authors developed a conceptual framework based on technology adoption and leadership theory. It was used to identify preservice educational leaders’ SMKIs and their effect on ALD to deal with an educational crisis during the COVID-19 pandemic. Furthermore, SMKIs are strengthening ALD, directly and indirectly, using SMKB and FCs.

Design/methodology/approach

In this study, the higher education students are considered preservice leaders who were enrolled in educational leadership and management programs. However, this study’s target population and sample are students enrolled in educational leadership and management programs. Therefore, higher education students are considered preservice educational leaders. Therefore, a multilevel questionnaire survey approach was adopted to collect data from preservice educational leaders (n = 451 at Time 1 and n = 398 at Time 2) enrolled in education departments in the selected universities in Pakistan. A total of 398 survey questionnaires were finalized with a return ratio of 89%. The partial least square structural equation modeling with SmartPLS 3.2.8 was used for the data analysis.

Findings

This research found that SMKIs are positively and significantly connected with ALD. This study also confirms that SMKB significantly and positively mediates the relationship between SMKIs and ALD. Therefore, this study concludes that preservice educational leaders were ready to adopt SMKB.

Practical implications

Social media–based knowledge sharing can be helpful to develop authentic leadership among preservice educational leaders during a crisis. Preservice educational leaders as authentic leaders can prove to be an asset in dealing with the COVID-19 pandemic crisis.

Originality/value

This research integrated the technology adoption model and leadership theory to provide empirical evidence of SMKIs’ direct and indirect influence on ALD through social media–based knowledge-sharing actual use behavior by preservice educational leaders during the COVID-19 pandemic. Moreover, the moderated mediating effect of the FCs was also studied in the relationship between SMKIs and actual user behavior as well as ALD.

Factors influencing microgame adoption among secondary school mathematics teachers supported by structural equation modelling-based research

Microgames are rapidly gaining increased attention and are highly being considered because of the technology-based media that enhances students’ learning interests and educational activities. Therefore, this study aims to develop a new construct through confirmatory factor analysis, to comprehensively understand the factors influencing the use of microgames in mathematics class. Participants of the study were the secondary school teachers in West Java, Indonesia, which had a 1-year training in microgames development. We applied a quantitative approach to collect the data via online questionnaires through google form. Structural Equation Modelling (SEM) with AMOS software was used to analyze the proposed model. Empirical results confirmed the perceived easy to use and subjective norm influence (PEU and SN) relationship with teachers’ microgame usage behaviors and intentions. In this condition, SN was found to have the initial significant influence on behavioral intention (BI), as attitude, BI, and facilitating conditions also correlated with the actual use of microgames. Furthermore, the largest influential factor was BI, with the results subsequently showing that TPACK had no significant influence on the actual use of microgames. This report is expected to help bridge the gap across several previous studies, as well as contribute to the explanation and prediction of the factors influencing the teachers’ mathematical utilization of the study’s program. Besides this, it also helps to increase the use of microgames in teaching and learning activities.

Gamification and e-learning adoption: a sequential mediation analysis of flow and engagement

Purpose

The purpose of this paper is to examine the effect of gamification on students’ e-learning adoption. In addition, this paper examines the effect of two mediations, that is, flow and engagement between gamification and e-learning adoption by using sequential mediation analysis.

Design/methodology/approach

The authors used the online survey method to collect the 570 responses through convenience sampling procedure. Sequential mediation analysis technique was used to test the mediation hypothesis.

Findings

The findings of this paper revealed that gamification elements are an important feature of flow, engagement in e-learning adoption process. Also, the paper found that engagement in the learning process is a key element for students to adopt e-learning.

Research limitations/implications

This paper makes its contribution to the literature related to gamification and e-learning adoption. The paper signifies the importance of gamification as an educational application in e-learning environment and its contribution in designing an interactive learning environment.

Originality/value

Empirically, to the best of the authors’ knowledge, it is the first paper to examine the sequential mediation model of gamification in the education sector in a developing nation like India. Furthermore, this paper also extends engagement and flow theory related to e-learning process by showing how students’ engagement and flow impact the e-learning adoption in the gamified environment.

Accentuating technology acceptance among academicians: A conservation of resource perspective in the Malaysian context

Although recent research looked at the unified theory of acceptance and use of technology (UTAUT) model among academicians, there is still lacking an adequate account for their technology adoption intentions and behaviors in the face of the COVID-19 virus. This study applies the conservation of resource (COR) theory to ground the statistical results investigating the moderation and moderated mediation effects of COVID-19 anxiety in relation to the UTAUT model. According to the COR theory, anxiety linked with the COVID-19 pandemic endangers resources such as human connections (death of friends and relatives), job security and finances, as well as physical health and psychological well-being. Since resource loss is more salient according to COR theory, academicians are more willing to employ technologies like Zoom, MS Teams, and Google Classroom since the COVID-19 threat is existential and the resource loss is eminent. To test the theory, data was collected through an anonymous survey during the months of December 2020 and January 2021. The resultant data from 215 academicians was analyzed using Hayes Process Macro in SPSS. COVID-19 Anxiety positive moderates both the direct effects of Performance Expectance-Behavior Intention and the mediating Performance Expectance-Behavior Intension-Usage relationships. Similar results were seen for other predictors, albeit the moderated mediations for Effort Expectancy and Facilitating Conditions were not significant. These findings overwhelmingly corroborate the claims that COR theory more comprehensively explains the effects of COVID-19 anxiety among academicians in relation to the UTAUT model.

Building Information Modeling Learning Behavior of AEC Undergraduate Students in China

With the popularization and application of Building Information Modeling (BIM), the demand for BIM technical talents in the construction industry is increasing. Exploring college students’ BIM technical learning behavior is of great practical significance to improve education activities. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), this research adds learning attitude variables to construct a theoretical model of influencing factors of college students’ BIM technology learning behavior. Chinese undergraduate students were asked to complete online questionnaires through peer-to-peer contact with sample colleges and universities. Finally, 1090 valid questionnaires were obtained. The students were sampled from research-oriented, applied research-oriented, application-oriented, and private research-oriented universities in seven regions of China: northeast, north, east, south, central, northwest, and southwest. The structural equation model was used to analyze the sampling data. The results indicate that college students’ BIM learning attitude, performance expectations, and social influence positively and directly impact their learning intention, which indirectly impacts their learning behavior. At the same time, promoting factors and learning intention demonstrate a significant positive and direct impact on learning behavior. Therefore, the following suggestions have been put forward to enhance college students’ learning motivation for BIM technology: increase the popularization of BIM technology in colleges and universities and improve the operation level of full-time BIM teachers. The latter enables colleges and universities to continuously and stably export qualified BIM technical talents to society and the market, resulting in a continuous industry development cycle.

Digitalisation of Schools from the Perspective of Teachers’ Opinions and Experiences: The Frequency of ICT Use in Education, Attitudes towards New Media, and Support from Management

The digitalisation of education has become an irreversible process, and Poland is no exception. However, the issue of ICT usage in education raises many concerns and controversies, posing numerous methodological challenges at the same time. In the interpretation of our research, one of the most frequently used and validated models in empirical research—the Unified Theory of Technology Acceptance and Use (UTAUT) model—was used. The aim of the research was to show the frequency of use of popular hardware, software and websites among teachers from Poland (in the Silesia Province) and finding answers to the questions pertaining to the main determinants of digital teaching aids. The frequency of ICT use in education was juxtaposed with the attitudes towards new media in the school environment as well as with the support of managers in that area. Quantitative research was conducted on a sample of N = 258 in 2020. A questionnaire in the form of a digital diagnostic survey was used to collect data. Based on the data collected, it was noted that: (1) Teachers use virtual systems (eRegisters) and interactive whiteboards most often, while educational podcasts and software for learning foreign languages are used least often; (2) approximately 40% of teachers use ICT often or very often in their school teaching; (3) in public schools, digital teaching aids are used slightly more often than in non-public institutions; (4) teachers are consistent in their use of digital teaching aids, so the individuals experimenting with and implementing ICT at school do so regardless of the type of software and hardware; (5) active support from school head teachers strengthens the frequency of ICT use in education; and (6) in schools where the use of smartphones by students is prohibited, the frequency of ICT use in education is at a lower level.

Investigation of open educational resources adoption in higher education using Rogers' diffusion of innovation theory

Open Educational Resources (OER) are teaching, and research resources provided under the Creative Commons (CC) licenses and can be freely used, shared, and modified. However, OER adoption is not widespread, and various barriers remain in the way of its growing emphasis. This article is aimed to investigate OER adoption in higher institutions by using Rogers' Diffusion of Innovation (DOI) theory. 422 responses to an online survey from faculty are gathered and analyzed, where adaptive attributes of DOI are adopted. The results of the descriptive method confirmed that relative advantage has a positive impact on faculty OER adoption. Indeed, positive impacts of observability and complexity are also shown. Ultimately, the findings from the structural model used, indicated that there is a positive correlation between trialability and respectively complexity and compatibility. Whereas relative advantage of OER impacts positively complexity and negatively compatibility. This study showed that it is not enough that faculty agree on OER benefits for teaching and research, the OER adoption rate must increase. Decision-makers in higher institutions are asked to perform additional OER initiatives to overcome challenges related to OER trialability, complexity, and compatibility.

Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory

Artificial intelligence (AI) technology has been widely applied in many fields. AI-assisted learning environments have been implemented in classrooms to facilitate the innovation of pedagogical models. However, college students' willingness to accept (WTA) AI-assisted learning environments has been ignored. Exploring the factors that influence college students' willingness to use AI can promote AI technology application in higher education. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and the theory of perceived risk, this study identified six factors that influence students' willingness to use AI to analyze their relationships with WTA AI-assisted learning environments. A model including six hypotheses was constructed to test the factors affecting students' WTA. The results indicated that college students showed "weak rejection" of the construction of AI-assisted learning environments. Effort expectancy (EE), performance expectancy (PE), and social influence (SI) were all positively related to college students' WTA AI-assisted learning environments. Psychological risk (PR) significantly negatively influenced students' WTA. The findings of this study will be helpful for carrying out risk communication, which can promote the construction of AI-assisted learning environments.

Establishing novel experimental operation teaching by a click-and-mortar environment

Purpose

This study aims to focus on the Artificial Intelligence of Things (AIoT) course. As AIoT has many theoretical theories and students usually have little interest in learning the protocols, the experiments can help stimulate their curiosity. Due to the environmental factor, the teaching requires assistive videos and Problem-Based Learning (PBL) to understand students' learning conditions.

Design/methodology/approach

The experimental design generally follows the course theories going from easy to complex, and students can extend the acquired concepts to other project development, yet, without in-depth knowledge about the experiment, resulting in limited creativity.

Findings

The assessment analysis can reveal whether students have grown from the teaching. The final analysis at the end of the term can show learners' conditions; meanwhile, students can deliver their level of satisfaction. The click-and-mortar teaching environment provided in this research can improve learning setting and quality, solidifying learners' proficiency.

Originality/value

The research result has proved the feasibility of the proposed method. Apart from showing the experimental steps, the video also explains the corresponding theories, helping students reinforce experimental knowledge and boost learning willingness.

Determinants of Behavioral Intention and Use of Interactive Whiteboard by K-12 Teachers in Remote and Rural Areas

Interactive Whiteboard (IWB) has recently been used to replace the TWB (traditional whiteboard), with many of its features being observed to help teachers in educational activities. This is based on effectively and efficiently increasing the teacher-student interaction. Therefore, this study aims to analyze the determinants of Behavioral Intention (BI) and the use of interactive whiteboards by K-12 teachers, in remote and rural Chinese areas. The Modified-Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was used in this analysis, as a learning medium to deliver the subject matter to students. The sample and population were also the teachers in the Guangxi Zhuang Autonomous Region, China, where 171 voluntary respondents participated in this study. Furthermore, the obtained data were processed using a Structural Equation Model (SEM) approach, through the Smart-PLS software. The results showed that Habit and Hedonic Motivation had a significant influence on the Behavioral Intention (BI) of teachers, toward the utilization of IWB in remote and rural areas. Besides this, Facilitating Conditions (FCs) and BI also had a significant positive effect on Usage Behavior. Based on these results, important information was provided to school principals, local governments, and teachers for education quality improvement, regarding the patterns of increasing IWB utilization in remote and rural areas.

Factors Affecting the Use of Digital Mathematics Textbooks in Indonesia

Digital mathematics textbooks differ from traditional printed textbooks in, among other things, their dynamic structural elements, representing a potential that traditional textbooks cannot fulfil. Notably, dynamic structural elements, i.e., multimodal representations of mathematics, could be of particular importance for learning, which is why the scientific interest in digital mathematics textbooks has increased in recent years and many digital textbooks have been developed. However, research related to predicting teacher usage behavior of digital textbooks is still limited. Therefore, this research aims to analyze the predictors that may influence the intentions of mathematics teachers and the actual usage of digital textbooks by applying the Unified Theory of Acceptance and Use of Technology (UTAUT). Data were collected from 277 teachers in West Java Province, Indonesia, and analyzed using structural equation modeling (SEM). The results indicated that Performance Expectancy (PE) is the biggest significant factor, followed by Social Influence (SI), that influences the Behavioral Intention (BI) of mathematics teachers to use digital textbooks in Indonesia. Effort Expectancy (EE) does not affect the intention to use a digital textbook. In turn, BI has the largest and most significant effect on teachers’ actual usage of digital textbooks. This result contributes to the understanding of the predictors that can increase the use of digital textbooks by mathematics teachers.

Factors predicting University students' behavioral intention to use eLearning platforms in the post-pandemic normal: an UTAUT2 approach with 'Learning Value'

The use of eLearning platforms has made it possible to continue the learning process in universities, and other educational institutions, during the Covid pandemic. Students' acceptance of eLearning is important because it is associated with their engagement in the online teaching-learning environment. This study used the Unified Theory of Acceptance and Use of Technology (UTAUT2: Venkatesh et al., 2012) to determine the factors predicting the behavioral intention of university students' to use eLearning platforms in the post-pandemic era. UTAUT2 was extended to include the constructs 'Learning Value' and 'Empowerment in Learning'. 314 students from different universities across Greece participated by completing an online questionnaire. Performance Expectancy, Social Influence, Hedonic Motivation, Learning Value and Habit had a significant impact on students' intention to use eLearning platforms to learn, while Facilitating Conditions and Learning Value had a direct impact on actual use. The findings enhance the research applying the UTAUT2 model, with the Learning Value, for the investigation of students' intention to use eLearning platforms in the post-Covid era. We suggest for Learning Value to be included in future research in an educational context.

What critical factors forecast student-teachers utilization of online learning system in the University of Education, Ghana during the Covid19 pandemic?

The shutdown of schools due to the Covid19 epidemic has generated a move towards online education. The operation of an electronic instructional system in many higher learning institutions was a major challenge. Online instructional system namely Moodle possesses some characteristics that are important for its operation in the era of the covid19 epidemic. Nevertheless, the effective implementation of the electronic instructional system depends on grasping the determinants that confront the modern electronic instructional system. Therefore, this inquiry aims to examine the determinants that influence learners' operation of the instructional learning system in the period of covid19. This inquiry adopted a quantitative research design. A convenient sampling approach was employed to choose a sample size of 276 students. The result of the inquiry found that all the nine determinants elucidated 53.8% of the change in utilization of the online learning system. Of the nine determinants, social influence and system quality contributed substantially to learners' utilization of online learning system. Implications for the study were also discussed.

Factors influencing graduate students' behavioral intention to use Google Classroom: Case study-mixed methods research

Blended learning combines face-to-face instruction and online learning experiences. It capitalizes on online learning management systems, one of which is Google Classroom (GC). Nevertheless, empirical investigations have mirrored literature gaps in understanding how the GC platform affects students' behavioral intention to harness it for web-based learning. Therefore, this case study applied a modified version of the extended unified theory of acceptance and use of technology (UTAUT2) as a theoretical underpinning to examine factors influencing graduate students' behavioral intention to utilize the GC platform. Employing mixed methods explanatory sequential design, the study first analyzed survey data from 23 EFL graduate students implementing partial least squares structural equation modeling (PLS-SEM). Subsequently, it conducted a qualitative stage carrying out semi-structured interviews for data collection and thematic analysis for its evaluation. The study through PLS-SEM results revealed that the most crucial determinant of students' behavioral intention toward the GC platform was habit, which hung on facilitating conditions and hedonic motivation. Besides, it evinced facilitating conditions as the most important performing interaction factor in determining graduate students' behavioral intention. Nonetheless, it indicated that performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation had no direct effect on behavioral intention. The follow-up qualitative findings explained that since the students mainly used the GC platform off-campus, the GC App on their smartphones and the interesting content on the GC platform sustained their habitual tendencies toward employing the GC platform. Accordingly, the study explicates implications and recommendations for theory, policy, and practice.

Educational Technology Adoption: A systematic review

During the past decades a respectable number and variety of theoretical perspectives and practical approaches have been advanced for studying determinants for prediction and explanation of user's behavior towards acceptance and adoption of educational technology. Aiming to identify the most prominent factors affecting and reliably predicting successful educational technology adoption, this systematic review offers succinct account of technology adoption and acceptance theories and models related to and widely applied in educational research. Recognised journals of the Web of Science (WoS) database were searched with no time frame limit, and a total of 47 studies published between 2003 and 2021 were critically analysed. The key research findings revealed that in educational context a vast majority of selected studies explore the validity of Technology Acceptance Model (TAM) and its many different extensions (N=37), along with TAM's integrations with other contributing theories and models (N=5). It was exposed that among numerous predictors, thematically grouped into user aspects, task & technology aspects, and social aspects, self-efficacy, subjective norm, (perceived) enjoyment, facilitating conditions, (computer) anxiety, system accessibility, and (technological) complexity were the most frequent predictive factors (i.e. antecedents) affecting educational technology adoption. Considering types of technologies, e-learning was found to be the most common validated mode of delivery, followed by m-learning, Learning Management Systems (LMSs), and social media services. The results also revealed that the majority of analysed studies were conducted in higher education environments. New directions of research along with potential challenges in educational technology acceptance, adoption, and actual use are discussed as well.

The perceptions of social media users of digital detox apps considering personality traits

The purpose of this study was to investigate the perceptions of users about using digital detox applications and to display relationships among personality traits and technology-related variables. This study was designed using survey approach and employed Generalized Structured Component Analysis (GSCA). As such, 11 hypotheses were constructed and tested. The study recruited 263 participants who utilize detox applications to avoid social media distractions. Data were collected through Google Form and analyzed using GSCA Pro 1.1 to better understand whether the proposed conceptual model fits the data. The results of the study indicated that behavioral intention predicted usage behavior significantly; performance expectancy, effort expectancy, and social influence positively affected behavioral intention; in turn, agreeableness and extroversion positively influenced performance expectancy, and extroversion affected effort expectancy; finally, neuroticism had a statistically significant and negatively associated with effort expectancy of using social media detox apps. The significant exceptions were that facilitating conditions were not predictive of behavioral intention, openness to experience did not influence performance expectancy, and conscientiousness was not linked to effort expectancy. The proposed conceptual model explained 56.68% of the amount of variation, indicating that instructors, policy makers and software designers should consider personal factors for preparing practical intervention approaches to mitigate learning issues related to social media distraction.

Analyzing student aspirations factors affecting e-learning system success using a structural equation model

E-learning system success factors identification is of major interest in higher education. Understanding the role of students' aspirations factor affecting the success of the e-learning system is a challenge for most educational institutions. The present study aims to analyze the effects of students' aspirations factors in ensuring the success of the e-learning system through a developed research model extended from the integrated updated Unified Theory of Acceptance and Use of Technology and the DeLone and McLean Information System Success Model. The study participants who made up the model data sample were collected from 379 students engaged in the e-learning system at universities across the Kingdom of Saudi Arabia. Students' aspirations are resumed in Motivation, Expectation, and Enjoyment factors. The structural equation model was used to analyze the main causes and effects that would guide students towards the use and success of the e-learning system. The study results showed the strong relationship between the students' aspirations factors (Motivation, Expectation, and Enjoyment) and the adoption factors (Intention to Use and Perceived Usefulness) that lead to increased students' confidence that e-learning adds value to their educational experience. In addition, results revealed the determining role of the effect of the Enjoyment factor on the benefits expected from the e-learning system process. Therefore, higher education institutions that aspire to benefit the most from the e-learning system should pay close attention to the aspirations of their students and enhance their enjoyment, and then redefine the "e" in e-learning as enjoy rather than simply electronic.

Applying the UTAUT Model to Understand Factors Affecting Micro-Lecture Usage by Mathematics Teachers in China

In the last decade, micro-lectures have been widely used to teach mathematics, but only a few studies have examined the factors affecting teachers’ intentions of using micro-lectures. As teachers are key to integrating modern technologies such as micro-lectures into students’ learning processes, knowledge about teachers’ intentions in this regard could be of particular importance. This study aimed to analyze the behavioral intention (BI) of mathematics teachers in using micro-lectures in mathematics in China, and identify the most influential factors involved, for the very first time. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used as a design model to investigate teachers’ BIs concerning the use of micro-lectures, and we used an online questionnaire to collect quantitative data. The participants in our research were 174 mathematics teachers from China, 166 of whom provided us with evaluable questionnaire data. Furthermore, partial least squares (PLS) regression was used, and hypothesis testing was performed with the Smart-PLS software. From the results, BI was positively affected by Performance Expectancy (PE), Effort Expectancy (EE), and Social Influence (SI). BI and facility conditions also had positive effects on user behavior; in contrast to other studies, SI had the most significant positive effect on BIs in our study. Our findings could provide insights into both future strategies for successful technology integration in mathematics classes and into mathematics teachers’ intentions towards integrating technologies into mathematics teaching.

To “D” or Not to “D”?

Although digital learning has been used by the public universities to teach students for some time, the relatively new established universities still didn't fully adopt the digital learning practices. Therefore, this research aims to understand the factors that influence instructors' intentions to adopt digital learning during and post COVID-19 time period. For this, the paper proposed a model based on the unified theory of acceptance and use of technology extended with additional construct such as self-efficacy and moderators such as staff IT-training and institutional support. The workable data were collected from 274 instructors across 10 public universities that have implemented digital learning in their curriculum relatively lately after 2010, and they are still experimenting its implementation using their resources. The data were analysed using PLS SEM. The results supported the influence of antecedents on instructors' intentions to adopt digital learning, and moderators were also found to support the relationships significantly.

Factors Affecting the Acceptance of Online Learning among the Urban Poor: A Case Study of Malaysia

Education is an avenue of gaining knowledge and skills that will, in turn, support economic growth. Therefore, as online learning platforms are abundantly available in Malaysia, the urban poor in the Klang Valley have a means of improving their knowledge and skills to generate more income. However, online learning requires technical readiness. As such, this study examined the factors affecting the acceptance of online learning among the urban poor in Malaysia. An acceptance model was developed by integrating the constructs of the unified theory of acceptance and use of technology (UTAUT) with factors that influence the perceived value of online learning among the urban poor. To assess the reliability of these factors, 293 respondents participated in an online survey. SmartPLS 3.0 was then used to analyse the collected data. We found that performance expectancy (PE), facilitating conditions (FC), and perceived value (PV) positively influenced the behavioural intention to use (BI) online learning. Therefore, the findings of this study provide an understanding of the value and vital factors that impact the acceptance of online learning among the urban poor in the Klang Valley.