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This study proposed a dynamic model of organizational technology adoption within a school institute culture. We described an implementation of a nonhomogeneous hidden Markov model based on a downscaling scheme that can project the cultural factors of the institute onto a teacher's implementation behavior. To reveal the dynamics of cultural evolution, we modeled the interactions within the institute's organization by incorporating extra dependencies and downscaling variables into the underlying process of cultural change. We applied an analysis scheme to the nine-semester e-textbook usage of a primary school and gain insight into teachers' technology adoption from a cultural perspective. We identified three states that represented the collective adoption contexts to examine how exogenous variables influence both the organization-scale context dynamics and the individual-scale implementation changes. The results showed that the effect of exogenous variables, especially external factors, varied between contexts and scales. The school's norm was shown to affect organizational adoption culture. Teachers were sensitive to the adopted context, as they are inclined to adjust their usage to meet preexisting norms. Interventions such as seminars initiated by the teachers' community were observed to cause a more long-term effect on the movement of the culture to an active context. Moreover, our research provided evidence that an organization can achieve more efficacy from teachers' involvement in a high degree of cooperation in in-class experiences.

Primary school teachers may lack the competencies to create and deliver lessons using ICT equipments. As a result, schools possess large quantities of rarely used educational ICT resources. The recording studio, a kind of ICT which is helpful in producing videos for teaching reflection, has recently been widely promoted and used in Chinese primary schools. This research aims to investigate teachers' intention regarding recording studios and other technologies to deliver instruction, so as to explain and decrease the widespread paradox between the high access and low use of ICT for Education (ICT4E). A triangle inquiry framework between using the status of ICT4E and its influencing factors was revealed, and the conceptual model of personal and environmental influencing factors on educators' behavioral intention was constructed. The model was validated by collecting data from 208 teachers in Chinese primary schools. Results indicated that compatibility, performance expectancy, and social influence directly influenced teachers' intention to use recording studios. External pressure and support included personal factors such as peer influence, which indirectly affected educators' intention. Finally, suggestions were made to administrators in primary schools on decreasing the existing paradox from the perspective of encouraging teachers' use of ICT.

Student satisfaction is of great significance in online learning, but few studies have explored its determinants in emerging countries. This study investigated the determinants of university students' satisfaction with online learning platforms in China through applying the Technology Satisfaction Model during the COVID-19 pandemic, when an unprecedented amount of learning began to take place online due to the closure of educational institutions. A total of 928 students from five universities in four Chinese provinces or municipalities were surveyed through a purposive sampling technique and analyzed through structural equation modeling and the Rasch model. Findings show that Chinese university students' satisfaction with online learning platforms is directly and indirectly impacted by their computer self-efficacy and the perceived ease of use and usefulness of the platforms. Findings also show that regional differences moderate the associations among these components. The current study adds to theoretical, methodical and practical understanding of university students' satisfaction with using online learning platforms, which have been recognized as irreplaceable emergency educational tools.

This study explores how entrepreneurship education and government policies influence the entrepreneurial intention of students receiving higher vocational education. It employs an empirically-based model that tests the effects of perceived entrepreneurial education and perceived entrepreneurial policy on entrepreneurial self-efficacy and entrepreneurial intention. This study also analyzes the moderating effect of gender. The model was constructed based on the Theory of Reasoned Action. A total sample of 462 Chinese students from public and private higher vocational colleges were randomly selected to participate in this study, and their responses were analyzed using structural equation modeling. The results of the research model showed that perceived entrepreneurial education and policy had positive direct influences on entrepreneurial self-efficacy and intention, respectively. Subsequently, students' entrepreneurial self-efficacy had a direct influence on their entrepreneurial intention. On the other hand, perceived entrepreneurial education and policy had multiple indirect influences on entrepreneurial intention mediated by entrepreneurial self-efficacy in higher vocational education. The findings also showed that gender did not significantly moderate the above direct and indirect causal relationships among the dimensions of the research model. Some implications for building better entrepreneurial community are provided. These include enabling students to obtain knowledge that is closely related to practice and to perceive the value of entrepreneurship education by creating participatory projects and teaching methods, issuing policies that college students care most about, proactively informing students about policy content in a clear and concise way, and fully considering the side effects of government policies and the compatibility among different kinds of policies.

Consistent with their goal of becoming a centre for educational excellence in teaching, learning and research, the authorities of Chinese higher education introduced their academic database system as one of their e-library services. However, the existing literature exhibits inadequate empirical measurements of academic databases in all aspects of higher education throughout the world during the COVID-19 pandemic. To address this gap, this study aims to validate the technology satisfaction model (TSM) for measuring students' satisfaction in using academic databases for their learning and research purposes. This study also analysed local and international academic databases to explore whether these databases could play a moderating role in shaping learners' satisfaction. The data were collected through a survey of 500 respondents studying at a research university in Shanghai. The results, which were analysed by structural equation modelling and the Rasch model, showed that students' satisfaction is determined by three valid predictors: computer self-efficacy, perceived usefulness and ease of use, and causal direct and indirect relationships among these variables in the use of local and international academic databases. Our new findings on the moderating effect of local (i.e. Chinese) and international (e.g. English) academic databases highlighted that the TSM has successfully estimated dual databases and produced insignificant, dissimilar results. This study could aid local and international educators, researchers, information science professionals and others in measuring the perception of academic databases for learning and research. This research could also serve as a guideline for researchers and psychometricians in measuring innovative learning technologies using structural equation modelling and the Rasch model. This is the unique contribution of this study, which concludes that local and international academic databases are almost equally important for postgraduate students at a research university in China. Moreover, these students are satisfied in using these academic databases to learn and do research. [ABSTRACT FROM AUTHOR]

The problem motivating this research is the rapid introduction of educational technologies and the strong push to use new technologies in technical and vocational training in China coupled with varied responses and uneven adoption of new tools on the part of practitioners. This study investigated the factors that influence technical and vocational college teachers' adoption and appreciation of information and communication technology (ICT) in China using the technology adoption and gratification (TAG) model. At total of 535 teachers from public technical and vocational colleges were surveyed using a purposive sampling procedure. The survey data were analyzed through structural equation modeling. Findings suggest that the use of ICT had three primary determinants: teaching purpose, research purpose and academic purpose. Technical and vocational college teachers' technology adoption and gratification was directly and indirectly predicted by their computer self-efficacy, intention to use, perceived ease of use and usefulness of ICT. Most importantly, the TAG model accounted for 77% of the variance in teachers' gratification using those predictive variables. This research successfully applied the TAG model and it further fosters recommendations for future investigations. This study contributes to theoretical, methodical and practical understandings of the use of ICT in technical and vocational education, which has been much less explored than in K-12 education and university settings.

Research databases are a significant contributing aspect of modern technology, and, as such, innovation has enhanced learning and research outputs using online databases introduced by authorities in charge of higher education. However, databases have been rarely investigated from the perspective of psychological assessment. Therefore, this research examined databases using structural equation modelling and the Rasch model to explore contributing factors of learning and research in higher education. To measure databases, this research adapted the online database adoption and satisfaction (ODAS) model and analysed the responses of 300 postgraduate students, from a double first class university in Shanghai, collected using a stratified random sample technique. The results of the ODAS model showed that the postgraduate students' perceived usefulness and ease of use of databases played mediating roles in establishing connections between their computer self-efficacy and intention to use and satisfaction with databases for research and learning. However, the ODAS model also showed that the students' satisfaction was indirectly explained by their perceived usefulness of databases through ease of use and intention to use. The results of our investigation contribute to a better understanding of the ODAS model and suggest assessment strategies for learning and research through databases for researchers, academicians, and librarians.

Assessment studies using structural equation modeling and Rasch Model have long been prominent in all areas of educational psychology. Their emphases have covered, but have not been limited to, the improvement of quality in teaching, learning, and research as well as the pursuit of research productivity. However, such methodological approaches have rarely taken place in the arena of information and communication technology (ICT) in tertiary education. As such, this study assesses Chinese lecturers' expression of ICT satisfaction through the technology satisfaction model (TSM). Data from 196 Chinese lecturers were collected using stratified random sampling and analyzed applying structural equation modeling and the Rasch model. The findings suggested that Chinese lecturers' satisfaction around ICT use was explored by the three underlying antecedents of computer self-efficacy, perceived usefulness, and ease of use. Computer self-efficacy was evidently a powerful exogenous variable in assessing direct and indirect causal associations among the dimensions of TSM. In future research, it is recommended that assessment of Chinese lecturers' ICT use for teaching and research purposes should be considered through structural equation modeling and the Rasch model. This would support future researchers, academicians, and practitioners in performing technological measurements in all the arenas of tertiary education.

Mobile learning has been introduced for quite some time now at Taif University. However, there is no research conducted to measure the readiness of mobile learning within its context. As such, the aim of this study is to assess the lecturers' readiness for mobile learning in higher education in terms of perceived usefulness and perceived ease of use. A total of 140 lecturers were collected from the faculty of education using online survey. A five-point Likert scale that demonstrated degrees of agreement (from strongly disagree to strongly agree) was applied to capture the lecturers' perceptions on their readiness for mobile learning. The instrument validity was conducted using factor analysis. A multiple regression model demonstrated that all predictors accounted for 60.9% of the variation. The findings showed that perceived ease of use and perceived usefulness are the valid predictors of assessing lecturers' readiness for mobile learning in higher education. Therefore, it was concluded that perceived usefulness and perceived ease of use have a significant impact on readiness for mobile learning.

This study focuses on visual creativity and how it can be supported with computer technologies and thereby be used to support learning and instruction. However, studies related to computer-enabled visual creativity have not been frequently explored. As such, the current research proposes a model consisting of four major factors: (a) computer-aided visual art self-efficacy, (b) computer self-efficacy, (c) general creative self-efficacy, and (d) visual creativity. The aim is to explore the causal relationships among these factors so that they can then be used to support creativity, especially in the context of learning and instruction. To test the proposed model, this study firstly collected a total of 736 responses from an American public university to construct a scale using exploratory factor analyses and confirmatory factor analyses for three factors: (a) computer self-efficacy, (b) computer-aided visual art self-efficacy, and (c) general creative self-efficacy. Later, 164 responses were collected to analyze those hypothesized predictors of visual creativity and their relationships using structural equation modeling with M"plus." The results of the study indicate that computer self-efficacy was a significant predictor of computer-aided visual art self-efficacy, which in turn was a significant predictor of general creative self-efficacy. General creative self-efficacy, in turn, was a significant predictor of visual creativity. Finally, the study yielded a significant indirect effect of computer-aided visual art self-efficacy on visual creativity as mediated by general creative self-efficacy. Implications for learning and instruction are discussed as well as future studies to further research to develop relevant models of visual creativity in support of learning.

The problem motivating this study is the fact that almost 19.70 million university students in China have been required to engage in e-learning under the government's initiative of "Classes are Suspended, yet Learning is still Ongoing" during the COVID-19 epidemic, coupled with varied responses, uneven adoption of e-learning platforms and varying degrees of satisfaction toward them. Using the online database adoption and satisfaction (ODAS) model, this study examines the determinants which impact university students' adoption of and satisfaction with e-learning platforms at this particular time in China. The ODAS model was also cross-validated using gender as a moderating variable. A purposive sampling procedure was used to survey a total of 1,136 students from six universities in five provinces or municipalities of China. The data for this survey were estimated using the Rasch model and structural equation modeling. Results exhibit that students' adoption of and satisfaction with e-learning platforms were significantly measured by their computer self-efficacy, their intention to use e-learning platforms, and their perceived ease of use and perceived usefulness of these platforms, while the relationships among these components were moderated by gender differences. This empirically-based cross-validation of the ODAS provides recommendations for future studies, including practical implications for e-learning. This current study contributes to the body of knowledge in evaluating e-learning platforms during the COVID-19 epidemic.

AbstractChatGPT, as the pioneer of advanced generative AI tools, has triggered scholarly discussions about the potential use of such AI technologies in interdisciplinary fields. With a focus on the surge of AI-related preprints since the introduction of ChatGPT by OpenAI, the study investigated what the surge implies for AI literature, particularly in terms of credibility and quality. A scoping review was initially conducted to study the characteristics of the AI-related preprints in the Web of Science (WoS) database and also in five (5) preprint platforms (ArXiv, MedRxiv, SocArxiv, SSRN, and Research Square). The publication date range was set at January 01, 2023 to September 08, 2023. This was followed up by an interpretive phenomenological analysis (IPA) of the perceptions of experts in the AI field about the preprints. Employing a scoping review of AI-related preprints across six databases and a qualitative analysis of 15 AI experts’ opinions, our study reveals concerns about the research accuracy, quality, and credibility of preprints, and advocates for a robust evaluation and high-quality assurance process to promote open science objectives during their dissemination. Specifically, 45,918 AI-related preprints were found in the six preprint databases or repositories across different fields. The nine themes from the IPA showed that preprints can be of value. However, experts advocated for the safe and responsible use of AI-related preprints, involving such tenets as maintaining ethical integrity and high-quality work on the part of authors and establishing sound AI-content guidelines from publishers and editors. Future studies are recommended to investigate the impact of preprints on decision-making processes in educational research and practice. [ABSTRACT FROM AUTHOR]

This study extended the Expectancy Confirmation model (ECM) to examine the factors that influence online learning stickiness. The structural equation modeling was used to reveal the relationships among the factors through a survey of 395 online consumers. The findings indicate that learning stickiness was significantly impacted by switching cost and satisfaction. Learners' perceived usefulness, perceived interactivity, and expectation confirmation have a significant effect on their satisfaction. Furthermore, learners' perceived usefulness was significantly influenced by their perceived interactivity and expectation confirmation. The results of this research also provide sustainable development directions for online platforms, such as the quality of curriculum design and the level of interaction between curriculum platforms.

Computational thinking (CT) is vital for success in numerous domains. However, the nature, definition, and scope of CT are ill‐defined, and research on how best to develop CT is very limited. This study focused on how thinking styles and STEM attitudes have effects on computational thinking. Using a proportionate stratified random sampling procedure, 1195 students from two universities were surveyed. A structural equation modeling analysis showed that students' thinking styles and STEM attitudes directly predicted their computational thinking skills and that thinking styles mediated the relationship between STEM attitudes and computational thinking skills. Thinking styles and STEM attitudes are strong predictors of CT skills. Based on the results, we recommended that the conceptualization of CT be broadened to reflect its trans‐disciplinary nature within the context of STEM education. This study adds to the limited theoretical understanding of CT and CT‐predictors in higher education, which has been studied much less than in K‐12 education. [ABSTRACT FROM AUTHOR]

The concept of big data has been extensively considered as a technological modernisation in organisations and educational institutes. Thus, the purpose of this study is to determine whether the modified technology acceptance model (MTAM) is viable for evaluating the performance of librarians in the use of big data analytics in academic libraries. This study used an empirical research method for collecting data from 211 librarians working in Pakistan's universities. On the basis of the findings of the MTAM analysis by structural equation modelling, the performances of the academic libraries were comprehended through the process of big data. The main influential components of the performance analysis in this study were the big data analytics capabilities, perceived ease of access and the usefulness of big data practices in academic libraries. Subsequently, the utilisation of big data was significantly affected by skills, perceived ease of access and the usefulness of academic libraries. The results also suggested that the various components of the academic libraries lead to effective organisational performance when linked to big data analytics. [ABSTRACT FROM AUTHOR]

In today's technology-enriched environment, online research databases have become an indispensable tool in learning and research activities. Libraries worldwide have incorporated them as an integral part of their current service delivery. This study intends to determine whether the technology satisfaction model (TSM) validly measures postgraduate students' satisfaction of using online research databases in an academic library. It further explores the relationships among antecedents within the model. To measure the components of the TSM, the stratified random sampling strategy was used to conduct a survey with 300 postgraduate students from six faculties of COMSATS University Islamabad (CUI) in Pakistan. The data were statistically analysed using the Rasch model and structural equation modelling (SEM). The results of the study illustrate direct and indirect associations among the exogenous, endogenous and mediating variables of the TSM, with the studied postgraduate students' computer self-efficacy playing a crucial role in influencing their satisfaction. The TSM shows that 69% of the variance in the postgraduate students' satisfaction can be explained by perceived usefulness, computer self-efficacy and perceived ease of use, which confirm that the TSM has a strong predictive power and is viable for measuring endogenous variable. The findings also make a significant contribution to the testing of databases for academics, service providers and researchers in higher education. [ABSTRACT FROM AUTHOR]