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Building Information Modeling (BIM) competitions are a beneficial approach to enhance BIM education, offering students practical experience in BIM application, including mastering workflows and technical tools. However, research exploring the individual perceptions influencing participation intentions and behaviors in BIM competitions is limited. Therefore, this study aims to investigate the factors affecting university students' behavioral intention and behavior in BIM competitions, providing theoretical support for BIM competitions and educational reform.

This study employs the Structural Equation Modeling (SEM) based on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to analyze the factors influencing BIM competition participation among 970 Architecture, Engineering, and Construction (AEC) university students.

The results of the study show that social influence, attitude, and self-efficacy play critical roles in shaping students' intentions to participate in BIM competitions. Furthermore, self-efficacy, facilitating conditions, and behavioral intention significantly influence students' actual engagement in such competitions. Surprisingly, effort expectancy negatively influences intentions, as less challenging tasks can lead students to perceive their participation as less impactful on their skills and learning, reducing their behavioral intention to participate.

This research provides valuable insights into the effectiveness of BIM competitions in enhancing BIM education for AEC students. Extending the UTAUT model to include self-efficacy and attitude, provides a novel perspective for understanding students' intentions and behaviors regarding BIM competitions. The study’s theoretical support proposes incorporating BIM competitions to augment BIM teaching methods and offers suggestions for advancing the efficacy of students' involvement in BIM competitions within higher education, thus contributing to educational reform in the AEC sector.

The purpose of this study is to assess the correlations between the e-entrepreneurial intentions, attitude toward e-entrepreneurship, subjective norms, perceived behavior control, attitude toward risk and entrepreneurial knowledge of Jordanian business students to start an online business and the e-entrepreneurial intention.

A sample of 392 undergraduate business students from different Jordanian public and private universities participated in the study. Data were collected using an online survey-based questionnaire (i.e. Google Forms) using emails and social media platforms (i.e. WhatsApp, Facebook, etc.); reliability and validity tests were ensured. This study employs a 50-item questionnaire (distributed online via Google Forms and in two languages) to collect data, utilizing 5-point Likert scales; correlation analysis, linear regression analysis, and structural equation modeling are used to analyze the data.

The results showed that the e-entrepreneurship intentions of Jordanian business students are significantly predicted by their attitude toward e-entrepreneurship, subjective norms, perceived behavioral control, and entrepreneurial knowledge. One’s attitude toward risk does not influence the ambition to launch an Internet company much. Furthermore, their affiliation does not significantly impact the students' plans to pursue e-entrepreneurship.

The study has important real-world implications, particularly for Jordan. The country could create more jobs and boost the economy by encouraging students to start online businesses and helping small businesses grow. This is especially important in Jordan, where many people, particularly young adults, struggle to find work. Therefore, true need for interventions to foster e-entrepreneurship among business students in emerging economies like Jordan.

The goal of this research is to examine Jordanian business students' aspirations to launch Internet businesses in developing nations throughout the digital age. The results offer valuable information on the elements influencing the e-entrepreneurial intents of Jordanian business students. This information may be utilized to create programs and policies that effectively encourage e-entrepreneurship in Jordan.

This study aims to provide insights into the drivers of student engagement in food waste reduction strategies in educational institutions. The proposed research model integrates social media celebrities' attractiveness, expertise and trustworthiness with the value belief norm (VBN) theory to explore their influence on students' behaviour towards food waste reduction.

The data were collected from 417 students enrolled in public and private universities in the Riyadh and Macca regions of Saudi Arabia to evaluate the proposed model. The partial least squares-structural equation modelling (PLS-SEM) was employed to analyse the responses.

The results showed that VBN theory's components, such as values (biospheric, altruistic and egoistic), beliefs (new ecological paradigm, awareness of consequences and aspirations of responsibility) and norms significantly and positively influence food waste reduction behavioural intentions. It was also discovered from the results that social media celebrities' attractiveness, expertise and trustworthiness influence food waste reduction behavioural intentions.

This study contributes significantly to the literature by identifying factors influencing student engagement in food waste reduction strategies in educational institutions where limited research exists. It fills this research gap by developing a novel theoretical framework integrating social media celebrities' attributes with the VBN theory to explain these factors.

Higher education institutions (HEIs) play a pivotal role in fostering economic development by cultivating skilled workforce and generating knowledge and innovation. However, HEIs may pose a potential risk to sustainable economic development due to the generation of food waste inside their campus canteens. Therefore, this study aims to examine the influence of attitude, subjective norm (SN), perceived behavior control (PBC), religiosity and pro-social behavior among State Islamic Religious College (SIRC) students on their intention to avoid food waste behavior. This study also focused on the mediating role of the three original theory of planned behavior (TPB) variables and pro-social behavior in the relationship between religiosity and the intention to reduce food waste.

Questionnaires were used to collect data from 443 students at SIRC. The collected data were processed and analyzed using structural equation modelling to test direct, indirect and mediating effects.

The empirical results indicated that the eagerness of students at SIRC to reduce their behavior of leaving food behind can be driven by their negative attitudes or views toward food waste, the practice of religious teachings in their lives, the belief that they can avoid food waste and their concern for the environment. The empirical results reveal that even though religiosity influences SN, it is unable to strengthen the relationship between religiosity and the desire to be anti-food waste.

In addition to contributing to the food waste literature in the context of eating behavior, the results of this study have theoretical and practical implications.

To assess SIRC students’ behavioral intentions to avoid food waste behavior, this study used a contemporary setting to measure attitude, SN, PBC, religiosity and pro-social behavior, so strengthening the TPB’s empirical underpinning.

The use of social media for sustainable information is important since it has the potential to influence people’s intentions and behaviour towards sustainability. As previous studies on social media and sustainable development have primarily focussed on Western viewpoints, this study presents a comprehensive Asian perspective by investigating the impact of social media on sustainable intention and behaviour amongst Malaysian and Indonesian undergraduate university students.

A campus-wide online survey was conducted with 953 students from Malaysia and Indonesia. The researchers collected data through an online questionnaire and a two-week quantitative survey of undergraduate students in Malaysia and Indonesia. Quantitative data were analysed by SmartPLS software and comparative studies were conducted.

The result of the survey indicated that Facebook and Instagram were mainly used by Malaysian students to obtain and communicate about sustainability information, whilst Instagram was mainly used by Indonesian students. The findings also discovered that social media usage and social media effectiveness and usefulness are statistically significant predictors of sustainable intention amongst the students in Malaysia and Indonesia. Sustainable intention is also a statistically significant predictor of sustainable behaviour amongst the students. Additionally, this study also found that Malaysian students appeared to have a high level of the effect of sustainable intention on sustainable behaviour and the effect of the effectiveness and usefulness of social media to sustainable intention compared to Indonesian students. On the contrary, their use of social media related to sustainable behaviour was relatively low compared to Indonesian students.

Overall, the findings can contribute to the presently scant empirical works that focus on social media’s influence on sustainability and sustainable development. Furthermore, the findings contribute to the growing body of knowledge related to sustainability communication and sustainable education, particularly in terms of the use of social media in the learning and teaching process. Future research could focus on studying postgraduate students and university students from other Asian countries. Moreover, using qualitative methods like in-depth interviews or focus group discussion and applying other theories might unveil further results.

Although many universities have begun to provide artificial intelligence (AI)-related courses for students, the influence of the course on students' intention to participate in the development of AI-related products/services needs to be verified. In order to explore the factors that influence students' participation in AI services and system development, this study uses self-efficacy, AI literacy, and the theory of planned behaviour (TPB) to investigate students' intention to engage in AI software development.

The questionnaire was distributed online to collect university students' responses in central Taiwan. The research model and eleven hypotheses are tested using 151 responses. The testing process adopted SmartPLS 3.3 and SPSS 26 software.

AI programming self-efficacy, AI literacy, and course satisfaction directly affected the intention to participate in AI software development. Moreover, course playfulness significantly affected course satisfaction and AI literacy. However, course usefulness positively affected course satisfaction but did not significantly affect AI literacy and AI programming self-efficacy.

The model improves our comprehension of the influence of AI literacy and AI programming self-efficacy on the intention. Moreover, the effects of AI course usefulness and playfulness on literacy and self-efficacy were verified. The findings and insights can help design the AI-related course and encourage university students to participate in AI software development. The study concludes with suggestions for course design for AI course instructors or related educators.

This paper aims to explore students’ intention to use and actual use of the artificial intelligence (AI)-based chatbot such as ChatGPT or Google Bird in the field of higher education in an emerging economic context like Bangladesh.

The present study uses convenience sampling techniques to collect data from the respondents. It applies partial least squares structural equation modeling (PLS-SEM) for analyzing a total of 413 responses to examine the study’s measurement and structural model.

The results explore that perceived ease of use (PEOU) negatively affects intention to adopt AI-powered chatbots (IA), whereas university students’ perceived usefulness (PU) influences their IA positively but insignificantly. Furthermore, time-saving feature (TSF), academic self-efficacy (ASE) and electronic word-of-mouth (EWOM) have a positive and direct impact on their IA. The finding also reveals that students' IA positively and significantly affects their actual use of AI-based chatbot (AU). Precisely, out of the five constructs, the TSF has the strongest impact on students’ intentions to use chatbots.

Students who are not aware of the chatbot usage benefits might ignore these AI-powered language models. On the other hand, developers of chatbots may not be conscious of the crucial drawbacks of their product as per the perceptions of their multiple users. However, the findings transmit a clear message about advantages to users and drawbacks to developers. Therefore, the results will enhance the chatbots’ functionality and usage.

The findings of the study alert the teachers, students and policymakers of higher educational institutions to understand the positive outcomes and to accept AI-powered chatbots such as OpenAI’s ChatGPT. Outcomes also notify the AI-product developers to boost the chatbot’s quality in terms of timeliness, user-friendliness, accuracy and trustworthiness.

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.

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.

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.

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.

This study intends to extend the unified theory of acceptance and use of technology (UTAUT) model by integrating perceived enjoyment as an intrinsic motivation so as to investigate factors influencing Chinese undergraduate English as a Foreign Language (EFL) students' intention to use ChatGPT for English learning.

A cross-sectional quantitative survey method research design was used in this study. Data were collected from 432 undergraduate students at two Chinese universities. The data analysis was carried out using SmartPLS 4, a computer software that employs the partial least squares structural equation modelling (PLS-SEM) technique. The analysis of the model was performed in two stages, including the assessment of reflective measurement model and structural model. The PLS predict was utilized to assess the model’s predicting power.

Findings showed that effort expectancy, performance expectancy, social influence and perceived enjoyment were positively related to Chinese undergraduate EFL learners' intention to use ChatGPT for English learning. Perceived enjoyment mediated the relationships between effort expectancy, performance expectancy, social influence and intention to use ChatGPT for English learning respectively.

Through incorporating the perceived enjoyment as an intrinsic motivation into the UTAUT model to explore factors that impact Chinese undergraduate EFL learners' intention to use ChatGPT for English learning, this study has extended the applicability of the UTAUT model and provide insights into factors affecting students' intention to utilize ChatGPT or other AI-based technologies for English learning.

The current study aims to explore the determinants of user intentions towards fitness YouTube channels, employing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Uses and Gratifications Theory (UGT) as theoretical frameworks.

Symmetric and asymmetric analyses were employed for data analysis, utilizing partial least squares-structural equation modeling (PLS-SEM) for symmetric analysis and fuzzy-set qualitative comparative analysis (fsQCA) for asymmetric analysis.

The study revealed significant impacts of most UTAUT2 determinants and all UGT determinants on user intentions. Additionally, the fsQCA results supported the concept of equifinality, indicating that various configurations of causal combinations can predict a high level of behavioral intention. These findings underscore the significance of comprehending user motivations and factors related to technology and social media in the context of maintaining or increasing followership and viewership for fitness content providers.

The findings suggest that individuals with high expectations and facilitating conditions, as per UTAUT, and heightened hedonic and socializing motivations, in line with UGT, are more inclined to follow fitness YouTube channels. This study offers valuable insights for fitness content creators and marketers navigating the complexities of the digital age.