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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.

Education for sustainable development (ESD) is a developing educational concept that aims to achieve economic, social and environmental sustainability through education. Cultural sustainability education aims to cultivate awareness and protection of cultural assets, promote sustainable development and foster environmental responsibility. This study establishes a cyber-physical metaverse of cultural sustainability learning to cultivate students' motivation, multicultural identity, critical thinking and sustainability thinking.

In this study, virtual reality (VR) and 3D printing technologies were utilized to create a cyber-physical metaverse learning environment. This learning environment is designed to allow elementary school children to learn about indigenous cultures and the architecture of slate houses, as well as socio-architectural issues. Learners will be able to experience first-hand the plight of the indigenous tribal areas and the exploration of related cultural knowledge.

The study collected pre- and post-test data through questionnaires, using covariates to analyze learners' perceptions of learning. The results of this study showed that cyber-physical metaverse learning environment had a significant impact on learning motivation, multicultural identity and sustainability thinking for culturally sustainable education. However, this study’s impact on critical thinking skills in students remains to be confirmed.

This is a quasi-experimental study of a single country’s elementary school children in the indigenous area, so its findings cannot be extrapolated to other areas or to learners of different ages.

This study introduces a framework for incorporating both virtual and real cultures to promote sustainable learning. The cyber-physical metaverse learning is used to supplement teaching activities to enhance learners' motivation in learning multicultural knowledge. Students were able to recognize and protect cultural assets, as well as emphasize the importance of sustainable development.

The purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis (SNA) and analyze its knowledge base such as research authors, research countries, document type, keyword analysis and subject areas.

Bibliometric analysis is used and furthermore, Lotka’s and Bradford’s law is applied to perform author productivity analyses in this field during 1999 and 2018, respectively, in turn, discovering historical vein and research tendency in the future.

It appears that the research on SNA has been very popular and still in the highly mature period. So far, the USA takes the lead among the published paper. The top 2 subject areas are “Computer Science” and “Business Economics.” The primary journal that SNA articles were published is Computers in Human Behavior. SNA has been related to many research areas, such as “Social network analysis,” “Computer-mediated communication,” “Online learning,” “Social Network” and “Community of inquiry.” Finally, Kolmogorov–Smirnov (K-S) test proved that the frequency indexes of author productivity distribution certainly followed Lotka’s law.

First, the productivity distribution may inform researchers and scholars of current issues and development of SNA. Second, the study proposed a theoretical model, based on Lotka’s law, for author productivity analysis of SNA, which can serve as reference for different areas of study in the evaluation of author productivity models. Also, in order to allow researchers to gain in-depth insights, this study aimed to report the most published institutions and keep track of the growth and trend of author productivity, by which scholars in related fields are provided with more opportunities for academic communication and technological cooperation.

This research on the productivity distribution of SNA may inform researchers and scholars of current issues and development of SNA. The findings report the major publication outlets and related discussion issues about SNA. Such information would be valuable for related authors, who are writing the manuscript on SNA, and also for practitioners, who may be interested in applying the theory or ideas of SNA.