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This study aims to examine the effects of iPad distribution on all teachers in a university and its application in teaching and student learning at home via wireless network during the coronavirus (COVID-19) pandemic. The attitude towards the use of iPads, behavioural intentions and the impact on the quality of teaching were evaluated.

This study used the technology acceptance model to explore the use of iPad smart mobile devices in multimedia teaching applications by university teachers. Furthermore, it used the structural equation modelling (SEM) for data analysis to explore the causal relationship between model variables, and it aimed to examine the causal relationship between variables to verify the theory. The SEM analysis included the following two stages: measurement model analysis and structural model analysis.

The “Internet information environment” had a significant positive impact on “perceived usefulness” and “perceived ease of use”. Amongst them, perceived usefulness had a significant positive effect on the use attitude, and use attitude had a significant positive effect on behaviour intention.

The findings confirmed that a good information network environment will directly and positively affect the perceived usefulness and the ease of use of iPad smart devices, of which the perceived usefulness will further positively affect teachers' perception of iPad smart devices. The attitude and behaviour of using such devices will in turn positively affect the quality of teaching. The results of the quality performance evaluation can be referenced further by manufacturers and scholars regarding the use of iPad smart devices for work at home during the COVID-19 pandemic.

ChatGPT, an artificial intelligence (AI)-powered chatbot, has gained substantial attention in the academic world for its potential to transform the education industry. While ChatGPT offers numerous benefits, concerns have also been raised regarding its impact on the quality of education. This study aims to bridge the gap in research by exploring teachers' perspectives on the adoption of ChatGPT, with a focus on identifying factors that motivate and inhibit them to adopt ChatGPT for educational purposes.

This research has employed a interpretative phenomenological analysis (IPA) qualitative approach. Through in-depth interviews among the teachers, data will be collected to identify the motivating and inhibiting factors that impact teachers' willingness to adopt ChatGPT. The data was collected from 34 teachers working across 10 branches of the University of Technology and Applied Sciences (UTAS) in Oman.

The analysis revealed four themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purpose. These include Theme 1: Exploration of innovative education technologies, Theme 2: Personalization teaching and learning, Theme 3: Time-saving and Theme 4: Professional development. On the other hand, inhibiting factors includes five themes which includes Theme 1: Reliability and accuracy concerns, Theme 2: Reduced human interaction, Theme 3: Privacy and data security, Theme 4: lack of institutional support and Theme 5: Overreliance on ChatGPT.

This study contributes to the understanding of teachers' perspectives on the adoption of ChatGPT in education. By understanding teachers' perspectives, policymakers can design appropriate policies and service providers can customize their offerings to meet teachers' requirements. The study's findings will be valuable for higher education institutions (HEIs) in formulating policies to ensure the appropriate and effective utilization of ChatGPT. The study will provide suggestions to ChatGPT service providers, enabling them to focus on motivating factors and address inhibiting factors, thereby facilitating the seamless adoption of ChatGPT among teachers.

In comparison to previous studies, this study goes beyond merely discussing the possible benefits and limitations of ChatGPT in education. This research significantly contributes to the understanding of ChatGPT adoption among teachers by identifying specific motivating and inhibiting factors that influence teachers to adopt ChatGPT for educational purposes. The research enables to gain important new insights that were not previously found, giving a fresh dimension to the existing literature.

The main objective of this study is to investigate the factors that influence the adoption intention of cloud computing services among individual users using the extended theory of planned behavior.

A purposive sampling technique was used to collect a total of 339 data points, which were analyzed using SmartPLS to derive variance-based structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA).

The results obtained from PLS-SEM indicate that attitude towards cloud computing, subjective norms, perceived behavioral control, perceived security, cost-effectiveness, and performance expectancy all have a positive and significant impact on the adoption intention of cloud computing services among individual users. On the other hand, the findings from fsQCA provide a clear interpretation and deeper insights into the adoption intention of individual users of cloud computing services by revealing the complex relationships between multiple combinations of antecedents. This helps to understand the reasons for individual users' adoption intention in emerging countries.

This study offers valuable insights to cloud service providers and cyber entrepreneurs on how to promote cloud computing services to individual users in developing countries. It helps these organizations understand their priorities for encouraging cloud computing adoption among individual users from emerging countries. Additionally, policymakers can also understand their role in creating a comfortable and flexible cloud computing access environment for individual users.

This study has contributed to the increasingly growing empirical literature on cloud computing adoption and demonstrates the effectiveness of the proposed theoretical framework in identifying the potential reasons for the slow growth of cloud computing services adoption in the developing world.

This study aims to investigate the relationship between talent management, organizational commitment and turnover intention. The moderating role of gender and experience in relationships was explored.

A conceptual model was developed, and relationships were studied by collecting data from 392 faculty members working in higher educational institutions (HEIs) in southern India. After checking the instrument’s psychometric properties using the LISREL package of structural equation modeling, data were analyzed using Hayes’s PROCESS macros.

The results revealed that talent recruitment strategies positively predict organizational commitment and negatively predict turnover intention; organizational commitment mediates the relationship between talent management and turnover intention. Further, the results documented that experience (first moderator) and gender of faculty members (second moderator) influenced the relationship between talent management and organizational commitment and organizational commitment and turnover intention.

The outcomes of this research are helpful for the administrators of HEIs to strategize to attract and retain talented faculty to maintain sustained competitive advantage. This research also helps to understand gender differences that exist in talent management and retention and organizational commitment in HEIs.

The three-way interactions between talent management, gender and experience in influencing organizational commitment and turnover intentions is a novel idea that contributes to the talent management literature – the relationship between talent recruitment strategies and talent engagement. The implications for talent management theory and practice are discussed.

The study assesses pre-service teachers' attitudes, confidence in research and intentions to use research by comparing the effectiveness of practical versus theoretical training in research methods courses.

This natural experiment examines the impact of the adaptations made to a research methods course for 848 pre-service teachers, due to the COVID-19 pandemic. The participants were naturally divided into two cohorts, each attending either the applied version, which required the completion of a whole research study, or the theoretical version, which did not require data collection and analyses. The data were collected through three questionnaires measuring attitudes, confidence and intentions toward research.

Inferential statistics revealed that pre-service teachers in the theoretical course (1) had more positive attitudes toward research and less anxiety, (2) had more intentions to integrate research in their daily practice and (3) had more confidence in engaging in educational research, compared to the pre-service teachers who completed the applied version of the course.

This study uniquely capitalizes on course adaptations, imposed due to the pandemic, to compare attitudes toward research. This is an ideal comparison because comparing attitudes of participants from different contexts involves many confounding variables. The study’s significance is amplified as, it not only elucidates the variances in attitudes, but also underscores the intricate relationship these attitudes share with the design of research courses. The insights yielded by this study offer substantial potential for reshaping pedagogical strategies in research methods instruction, thereby serving as a cornerstone for future educational innovations.

In collaboration with their home cities, universities increasingly develop courses in which students investigate urban sustainability challenges. This paper aims to understand how far-reaching the collaboration with urban stakeholders in these courses is and what students are meant to learn from the transdisciplinary pedagogies.

This research is designed as a qualitative multiple-case study into the intentions of transdisciplinary courses in which universities collaborate with their home cities: Delft University of Technology in Delft and Amsterdam Institute for Advanced Metropolitan Solutions in Amsterdam. The study compares the written intentions of eight courses in course descriptions with the ideal intentions that teachers describe in interviews.

First, seven of the eight investigated courses were designed for urban stakeholders to participate at a distance or as a client but rarely was a course intended to lead to a collaborative partnership between the city and students. Second, the metacognitive learning objectives, such as learning to deal with biases and values of others or getting to know one’s strengths and weaknesses in collaboration, were often absent in the course descriptions. Learning objectives relating to metacognition are at the heart of transdisciplinary work, yet when they remain implicit in the learning objectives, they are difficult to teach.

This paper presents insight into the levels of participation intended in transdisciplinary courses. Furthermore, it shows the (mis)alignment between intended learning objectives in course descriptions and teachers’ ideals. Understanding both the current state of transdisciplinarity in sustainability courses and what teachers envision is vital for the next steps in the development of transdisciplinary education.

The purpose of this study is to identify the factors that influence the willingness of Saudi Arabian students from four universities in Saudi Arabia, to adopt learning management systems (LMSs). This will be accomplished by using two popular technology acceptance models unified theory of acceptance and use of technology (UTAUT) and theory of planned behavior (TPB).

In total, 445 undergraduates from four Saudi educational institutions participate in filling out the study questionnaire. To investigate the correlations between the variables, the study used structural equation modeling for data analysis.

The results of the study show that effort expectancy (EE), subjective norm (SN), attitude toward behavior (ATB) and perceived behavioral control (PBC) are found to be substantially connected with their intentions to use (ITU) LMSs. The findings also show that there is a strong relationship between students’ intentions and their actual use of LMSs.

Like many studies, this research has some limitations. The primary limitation is that the findings of the study cannot be extrapolated to other settings since the report’s analysis and investigation were limited to four Saudi universities. Therefore, to generalize the study’s findings, similar research needs to be conducted in other Gulf and similar cultural universities.

The integrated model identifies key factors that influence the intent of Saudi Arabian students to use LMS, including EEs, social influence, ATB and PBC. This model can help develop solutions for the obstacles that prevent students from using LMS. The findings can be used to provide assistance to increase the likelihood of LMS acceptance as part of the educational experience. The model may also inspire further research on this topic in the Gulf nations, particularly in Saudi Arabia.

As none of the relevant studies conducted previously in Saudi Arabia has integrated the two models to study the students’ ITU LMSs, this study combines two major theories, TPB and UTAUT, in the context of Saudi Arabia, contributing to the field of technology use in education by expanding empirical research and providing a thorough understanding of the challenges associated with the use of LMS in Saudi universities. This study should be viewed as filling a crucial gap in the field. Moreover, this integrated model, using more than one theoretical perspective, brings a thorough comprehension of the barriers that hinder students’ adoption of LMSs in the academic context in Saudi Arabia and thus assists in making effective decisions and reaching viable solutions.

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 study aims to improve the Unified Theory of Acceptance and Use of Technology (UTAUT) model by examining technological anxiety and other influential factors on international students' adoption of mobile learning (m-learning) during COVID-19 emergency remote teaching (ERT).

This study utilized the modified UTAUT framework to test hypotheses through a cross-sectional survey method. Participants were university students studying Chinese as a foreign language who were selected using a convenience sampling approach. An online questionnaire was then administered. The data collected from the surveys were analyzed using the partial least squares method with SmartPLS 4 software.

The study examined 16 hypotheses and found support for six of them. The results confirmed that performance expectancy (PE) is a significant predictor of behavioral intention (BI), and anxiety influences both PE and effort expectancy. The negative effect of social influence on anxiety was found to be significant, while facilitating conditions had a negative impact on learners' self-efficacy. The model fit indices indicated a good overall fit for the model.

This study presents a valuable contribution to the literature on m-learning in emergency education by incorporating technological anxiety into the enhanced UTAUT model. Examining the relationships between the key factors of the model provides a better understanding of learners' intentions and can inspire researchers to establish new theoretical foundations to evaluate the roles of these factors in diverse educational settings.

The study found that performance expectations are linked to learners' intentions, and anxiety indirectly affects BIs to use mobile learning platforms. Thus, these platforms should be designed to meet learners' expectations with minimum effort and eliminate anxiety triggers to facilitate ease of use. Language curriculum developers and policymakers should incorporate mobile learning applications to support diverse language skills, address students' needs and encourage their use through professional development opportunities for instructors.

Social factors have been found to significantly influence anxiety levels among learners. Therefore, it is crucial for teachers and family members to play an essential role in mitigating anxiety's adverse effects. Discussing related issues can enhance the quality of mobile learning and stimulate social initiative by providers, ultimately improving the learning experience for all learners, regardless of their location or circumstances. This can also contribute to the growth and development of society.

This study contributes to the originality of m-learning development by proposing an enhanced UTAUT model that considers anxiety and emphasizes the critical role of foreign learners' BIs. It provides fundamental guidelines for designing and evaluating m-learning in ERT contexts.

This study explores how one novice teacher navigated his first-year teaching sixth-grade social studies.

One-sixth grade novice teacher was observed during his unit on the Islamic Empire. The teacher was interviewed before the unit began to understand his approach to combating Islamophobia and interviewed again after the unit so he could reflect on the unit and discuss if he believed he had accomplished his original goal. Classroom artifacts (handouts, slide decks, etc.) were collected.

The findings highlight the various forces that impacted the decisions the teacher made in the classroom. Lack of support from administration and various colleagues left the teacher feeling overwhelmed and unable to accomplish his goals. While the teacher started the unit with a clear purpose for teaching against Islamophobia, he ultimately taught a unit where students memorized discrete pieces of information.

This study adds to previous research on the need for providing administrative support for novice teachers to be able to teach in ambitious ways by highlighting the numerous shortcomings.