Search

The role of entrepreneurship in addressing the issue of educated unemployment is well acknowledged, while its specific implications for health professions students remain inadequately explored. This study's main objective is to investigate entrepreneurship education's effect on entrepreneurial intention by considering entrepreneurial self-efficacy as a mediator in students majoring in medical laboratory technology. This quantitative research uses an exploratory approach involving 300 respondents determined through simple random sampling techniques and analyzed using partial least square structural equation model (PLS-SEM). The analysis revealed that entrepreneurship education directly impacts self-efficacy and entrepreneurial intention. Furthermore, entrepreneurial self-efficacy was identified to exert a positive mediating effect between these variables. However, the effect size between the relationships of the research variables is low. Nevertheless, higher education offering health majors can optimize entrepreneurship education by implementing practical learning and field experience to increase confidence and intention in entrepreneurial activities.

The study delves into the behavioral shifts observed in "digital students" transitioning from distance to onsite learning during the Generation Z era, influenced significantly by the disruptive effects of the COVID-19 pandemic. Technological advancements have reshaped students' perspectives, rendering educational and organizational engagements more accessible via platforms like video conferencing. However, the return to onsite learning has prompted a notable culture shock, leading to heightened levels of stress and anxiety among digital students. This research aims to examine the psychological ramifications of stress and anxiety on post-pandemic student attitudes toward extracurricular organizational intention. Employing the depression anxiety stress scale (DASS-42) and conducting multiple linear regression analysis on a sample of 420 respondents, the study reveals a significant negative impact of stress level (-35.6%) on students' intentions to engage in organizational activities. Additionally, anxiety levels contribute to a variation of -6.8%. These findings underscore the intricate relationship between psychological factors and student participation, underscoring the imperative to address stress and anxiety to foster robust involvement in campus organizational endeavors.

How do teachers perceive and experience the impact of evaluation feedback across various domains of their work? This study investigates whether there are qualitatively distinct groups of teachers in the United States based on teacher perceived impact of evaluation feedback using the 2013 Teaching and Learning International Survey (TALIS 2013). Applying latent class analysis to the U.S. sample of lower-secondary school teachers (n=1,824), we find that there are four distinctive groups of teachers: Receptive (25%), Compliant (15%), Motivated (27%), and Indifferent (33%). Our analysis shows feedback sources and teacher beliefs about the evaluation's purpose are significant predictors of teacher class assignment. Finally, controlling for various individual and school-level characteristics, these teacher groups vary significantly in their intention to change school.

The global pandemic caused by the SARS-CoV-2 virus brought about a true revolution in the predominant teaching-learning processes (i.e., face-to-face environment) that had been implemented up to that point. In this regard, virtual teaching-learning environments (VTLEs) have gained unprecedented significance. The main objectives of our research were to define an explanatory theoretical model and to test a multiple serial mediation model with four variables in series (one independent variable plus three mediators) to relate perceived utility (independent variable) in the use of a VTLE and perceived learning (dependent or criterion variable) in such contexts, taking into account the mediation of subjective norm (mediator 1), ease of use (mediator 2), and intention to use behavior (mediator 3), and using the extended technology acceptance model as the theoretical framework. Additionally, we aimed to analyze the direct and indirect relationships and effects among the variables that constituted the proposed model. Methodologically, the research can be classified as a cross-sectional causal ex post facto design. A representative sample of students enrolled in higher education institutions in the Dominican Republic was used as the research population, and a standardized Likert scale was administered to measure the five dimensions of the proposed model. Finally, it is worth noting that the obtained results indicate that all direct and indirect effects considered in the model were statistically significant, except for the indirect effect, where the four predictor variables were arranged in series to verify their influence on the criterion variable: perceived learning.

In both the educational and business environments, two trends may be inarguable. The difference between the demand of technology positions as compared to the number of people majoring or interested in technology-based careers. Secondly, the education environment is radically changing in several aspects including a high number of undecided majors entering undergraduate institutions as well as the ability of skills development by higher education students entering the marketplace. The recent and historic attention in artificial intelligence and machine learning technology may have an impact on both a change in the demand for total positions and interest in technology-based careers. This research study will investigate the attitudes and perceptions of first-year college students over four academic years to determine changes. Six of the factors studied were found to have significant differences between the research period: attitude, job availability, personal image, social image, subjective norm and intent to major. The intent to major has remained consistently low for three of the four years. The implications from this research will provide insight to both business organizations for recruiting as well as all educational institutions.

The percentage of international faculty members at Korean universities peaked in 2013 and has been decreasing since, suggesting that Korean universities have a problem with international faculty member retention. This study investigates whether international faculty members' intention to leave is associated with their degree of acculturation. Results are based on analyses of data from 325 international faculty members with doctorates working at Korean universities nationwide. Regression analyses reveal that acculturation, work-related conditions (salary, workload, workplace climate) and mobility-related motivational factors (job market in home country, interest in Korea) explain international faculty members' intention to leave. A 'cultural advantage' (ethnically Korean or living with a Korean spouse) is not a significant predictor of intention to leave. Suggestions to support international faculty members, and to help bring about synergistic organizational change are ventured in the hopes of bolstering retention at Korean universities going forward.

Gamification can make learning more fun and engaging for students. Software engineering can utilize gamification to help students learn and improve their skills from the complexity of software engineering. This study used quantitative research to examines perceived ease of use, student satisfaction, and perceived usefulness to measure gamification quality, which can have an impact on software engineering intention, namely intention, loyalty, and participation in following and understanding software engineering materials. The data was collected based on an online questionnaire survey, 90 data were collected and then measured and analyzed using SmartPLS 3. The results showed that perceived ease of use, student satisfaction, and perceived usefulness have a significant influence on gamification quality, which also leads to a positive impact on software engineering intention. This research guides teachers and educational institutions that gamification is very successful as a learning medium to simplify complex information to be more interactive.

There are two difficulties associated with many previous evaluations of students' attitudes toward technology. First, most questionnaires focus on social and family environments, neglecting the schooling environment. Second, although some studies have considered the schooling environment, there has been no systematic review of these studies. To address this research gap, this study systematically identified articles from major education journals that have described students' attitudes toward technology. We reviewed these articles, evaluated the influence of the schooling environment, and created a valuable resource for future studies. Our review indicates that technological activities and advanced preparation by teachers can be beneficial in alleviating "boredom" as a key negative affective component of school environment. Equally important, our research indicates that technology classes, those that use modern technology as a basis for instruction, and those that stimulate higher-level thinking processes, can reduce the "difficulty" (a cognitive component of the schooling environment) of learning and improve students' conceptualizations of technology.

This article presents an investigation into the value-based affordances of volition as an integral philosophical component of technology education, specifically in relation to design methodology. As the central aspect of technology education, design has a prominent position in curricula all over the world, not just in subjects named Design and Technology, but also in most technology and engineering subjects in schools. In philosophy, it has been asserted that design "volition" (axiology) has a strong relationship with and in many ways forms the basis of design as a methodological stance. The primary philosophical frameworks used as the foundation for the philosophical analysis presented in this article are the ones introduced by Carl Mitcham in his "Thinking through Technology" (1994) and Andrew Feenberg's critical theory of technology. We perform a narrative review of relevant literature. Based on this review, we attempt a clearer definition of the lucid concept of volition/axiology in the literature, as well as explicate the relationship between axiology and methodology. In particular, we investigate this relationship in terms of values, intentionality, and sustainability in design. We review design as a societal and value-laden phenomenon, prone to strong and weak intentionality where expert and lay designers converge or diverge on sustainable values depending on the amount of interpretative flexibility. Concerning implications, school teaching needs to be founded on design volition which does not reduce technology education to technical education. Technology teachers and students need to be explicit about the values involved at all levels of technology and to clarify, justify, and debate their choices. Students must also be exposed to the way in which "sustainable values" might decrease interpretative flexibility and increase the opportunities for a technology to be sustainable in the medium to long term.

Occupational therapy practitioners (OTPs) do not receive additional training on the physiological, emotional, mental, and physical effects of music on the body or how to improve and increase its use in occupational therapy (OT) practice. Additionally, the specific effects of the use of music within OT practice have not been fully explored. This workshop was created to develop skills related to appropriately using music as supported by the American Occupational Therapy Association's Occupational Therapy Practice Framework-IV, and to address gaps in knowledge regarding how to use music intentionally, effectively, and safely in OT practice. This study's purpose was to evaluate the effectiveness of a continuing education workshop on increasing OTPs' confidence of facilitating intentional uses of music in OT practice. The free four-hour workshop was implemented as a continuing education course for currently practicing OTPs. Participants (N=13) completed Pre- and Post-Course Surveys and results indicated an increase in confidence levels for all twelve survey items. The One-Month Follow-Up Survey (N=6) measured the carryover of learned material and gathered additional information to inform revisions of workshop content for future implementation. Qualitative themes emerged indicating the workshop was effective for increasing understanding of how music impacts the brain and body and confidence in clinical application of music in OT practice. Results indicate the need to increase educational opportunities for OTPs regarding using music in practice.

Background/purpose: Widespread adoption of e-learning was triggered worldwide during the COVID-19 pandemic and modern higher education institutions dedicated significant resources to the use of diverse e-learning systems. However, to maximize the benefits of these investments, it is crucial that the degree to which end-users accept and continue using these systems is evaluated. Employing an integrative theoretical framework based on the extended Technology Acceptance Model (TAM) and Expectation Confirmation Model (ECM), this study aimed to scrutinize factors affecting students' continuance intention to use an e-learning platforms following the pandemic. Materials/methods: The research employed a cross-sectional design, and 343 university students were surveyed. Partial least squares structural equation modeling (PLS-SEM) was employed in the data analysis. Results: The findings indicate perceived usefulness and satisfaction to be direct predictors of e-learning system usage, whilst confirmation of expectation, perceived usefulness, perceived ease of use, and system interactivity were shown as indirect predictors. Conclusion: Discussed along with the literature, the study's results revealed satisfaction to be the most vital indicator of continuance intention. Some suggestions are put forward, aimed towards helping both instructors and system designers.

Massive Open Online Courses (MOOCs) have received significant global attention but face substantial criticism due to their low completion rates on mainstream platforms. The purpose of this study is to compare MOOC completion rates based on three different perspectives using four MOOCs provided by BilgeIs MOOC Portal. The completion rates based on traditional completion rates, active learners, and learner intentions revealed striking disparities in favor of the completion rates based on learner intentions. Specifically, completion rates based on learner intentions significantly exceeded both the traditional calculation and the active learner assessment for four MOOCs. This outcome underscores the critical importance of contextualizing MOOC completion data. By offering a more holistic perspective, this study contributes significantly to our understanding of the progress of MOOC success, particularly in developing countries. It is worth noting that, even when analyzed from different perspectives, regardless of culture and socio-economic factors, this study also underscored that MOOC dropout remains a prevalent issue in developing countries, lending support to the existing criticisms of completion rates. Nevertheless, it suggests that the issue may not be as severe as portrayed by studies relying solely on traditional completion metrics, as alternative viewpoints reveal completion rates that are notably higher.

This study examined pre-service teachers' perspectives on integrating generative AI (GenAI) tools into their own learning and teaching practices. Discussion posts from asynchronous online courses on ChatGPT were analyzed using the Diffusion of Innovations framework to explore awareness, willingness to apply ChatGPT to instruction, and potential benefits, challenges, and concerns about using GenAI in teaching and learning. The course discussions significantly increased pre-service teachers' awareness and foundational knowledge while reducing anxiety towards AI technologies. However, despite exposure to ChatGPT, only a few confirmed intentions to adopt AI tools in their teaching practices, potentially reflecting lingering uncertainties evidenced by emotional responses, such as worry and concern. Professional development in AI literacy can address these uncertainties and enhance teachers' understanding about using GenAI in class. The study offers insights into responsible GenAI adoption in education and how higher education can leverage ChatGPT to enhance pre-service teacher learning.

The objective of this study is to determine the impact of entrepreneurship and digital literacy on the inclination of college students to initiate their own business ventures. Furthermore, the study aims to examine the role of business attitude and self-efficacy as mediators and moderators. The data utilized in this investigation was sourced from a sample of 536 authentic individuals and only pertains to Indonesia. The acquired data is analyzed using partial least squares structural equation modeling to evaluate the research model. The findings indicate that possessing a creative mentality, receiving formal education in entrepreneurship, and demonstrating proficiency in technology can significantly enhance an individual's inclination to embark on an entrepreneurial endeavor. Moreover, the entrepreneurial mindset serves as a bridge between the acquisition of business knowledge with the desire to become an entrepreneur. The results indicate that self-efficacy has a positive impact on the relationship between the aspiration to become an entrepreneur and having an entrepreneurial mindset. The unexpected finding revealed that self-efficacy diminishes the link between acquiring knowledge about entrepreneurship and the inclination to establish a business. Moreover, the results suggest that self-efficacy does not modify the correlation between digital knowledge and the inclination to start one's own business. The findings of the study have important implications for both the theoretical comprehension and practical execution of establishing and achieving company objectives.

The evolving Metaverse in Higher Education (HE) in Mexico can enrich pedagogy, facilitate skills development, and improve students' learning experience. This research aimed to identify the factors guiding the adoption of the Metaverse in a Business School in Mexico. A survey analysis was conducted to gauge insights from stakeholders on the Metaverse in HE. A total of 117 respondents, comprising students, professors, and staff members, completed the 21-item questionnaire. To determine the relationship between data, a quantitative analysis was performed using a structural equation model (SEM), and a path analysis was computed to illustrate the relationship among the adoption components of the UTAUT model. The study found no correlation between age, gender, and previous experience toward adopting the Metaverse. On the other hand, performance expectancy, effort expectancy, social influence, and facilitating conditions significantly impact the stakeholders' attitudes toward adopting this technology. The research reveals that a practical learning exercise in the Metaverse improved student knowledge acquisition. Implementing this model is to be at the service of concerned HE authorities to create an adequate environment for adopting the Metaverse in Universities in Mexico.

Indigenous people are often hesitant to participate in research projects because they lack trust in researcher intentions. In this article, we explore the critical role that Indigenous boundary spanners play in research conducted with Indigenous communities through our research on oceans and human health. Our analysis centers around five principles where Indigenous boundary spanners significantly influence the research process. Centering work around 'ohana (family), being intentional around where to collect data, approaching the work with humility knowing that the community are the experts, cultivating team members' knowledge of community through conversations, and challenging assumptions within the institution are all aspects of research that must be considered when working with Indigenous communities. Including Indigenous community members and Indigenous scholars as part of teams can improve these aspects of research and begin the process of (re)building trust with Indigenous communities.

This study aims to predict accounting students' inclination toward a career in accounting in Indonesia by integrating the Social Cognitive Career Theory (SCCT) and the Theory of Reasoned Action (TRA). The research relies on primary data obtained through an online, closed-ended questionnaire. We employ Structural Equation Modeling (SEM) for the analysis, utilizing statistical tools like SPSS 24.0 and AMOS 24.0 software. Findings from the survey conducted among final-year accounting students in three Indonesian tertiary institutions reveal that self-efficacy impacts the behavioral intention to pursue an accounting career, mediated by outcome expectations, subjective norms, and attitudes. The study identifies both direct and indirect influences of self-efficacy on the behavioral intention. The study innovatively combines the TRA and SCCT models, utilizing a questionnaire to assess the effects of the Association of Southeast Asian Nations (ASEAN) Economic Community on graduates opting for accounting careers within the TRA and SCCT frameworks. Based on the results, integrated career choices must be considered when choosing a career in accounting or other professions. Intervention in an accounting course will help increase the final-year accounting student's understanding of the accounting profession, including relevant work experience and professional accounting membership.

This paper focuses on a study conducted in two historically disadvantaged schools (deep-rural and semi-urban) in South Africa where the rising access to mobile technology implies that the long-standing promise of mobile learning is becoming accessible despite the lack of recent research. This research aims to investigate the relationship between the type of school and various aspects of mobile phone use as well as differences in behavioural intention constructs to use mobile phones for learning. After a literature review, several hypotheses were developed. Using non-probability sampling techniques and the survey method, data was obtained from 128 participants, 79 from the deep-rural school and 49 from the semi-urban school. The semi-urban school exhibited slightly higher percentages in all aspects of cell phone use. Outside of mobile phone ownership and Internet access, all associations were significant. Significant differences were reported in favour of the semi-urban school for all constructs regarding the behavioural intention to use mobile phones for learning. However, the future of m-learning appears to be more promising than reported in earlier research by reporting positive behaviour from students in both schools. Critical stakeholders in education should take note and move from the goals of improving broad access to explicit objectives to implement m-learning in rural schools.

This study employs Structural Equation Modeling (SEM) and the Technology Acceptance Model (TAM) framework to explore the factors influencing Massive Open Online Courses (MOOCs) usage among college students in Southwest China. Using probability sampling, data were collected from 602 participants through an online survey distributed over a period of ten days, yielding a robust sample for analysis. The survey, divided into 7 sections, focused on various dimensions of user interaction with MOOCs, including perceived ease of use, usefulness, and value. The findings indicate that perceived usefulness significantly impacts user engagement, with attitude serving as a critical mediator. The study's theoretical contributions include extending TAM by emphasizing cultural and regional specifics in MOOC adoption. Practically, the results suggest targeted strategies to enhance user engagement and highlight the importance of designing MOOC platforms that cater to the educational expectations and preferences of students in diverse socio-economic settings.

The potential for vocational students to achieve success in entrepreneurship is considerable, especially since they have acquired specific skills that are in line with their area of specialization since the beginning of their vocational schooling. However, schools cannot be alone in promoting entrepreneurial careers among vocational students. This study aims to measure the role of three educational centers, in influencing self-efficacy, entrepreneurial intention and career choice as an entrepreneur. This study was approached with a quantitative approach using structural equation modeling (SEM), the sample in the study was 354 vocational students. Data analysis through four stages, namely exploratory factor analysis, normality and outlier tests, confirmatory factor analysis and hypotheses testing (structural model). The results showed that the three education centers significantly influence self-efficacy and entrepreneurial intention which in turn can encourage students to choose a career as an entrepreneur. This research contributes to the understanding of how the three education centers can be an important catalyst in shaping a generation of resilient and innovative entrepreneurs.

This study aims to discover the factors that influence the acceptance of electronic learning media and its effect on the effectiveness of digital instruction. The study involved a learning management system and online tutorials using management system (MS) teams from various faculties at the Universitas Terbuka. These include the Faculty of Economics and Business, the Faculty of Teacher Training and Education, the Faculty of Science and Technology, and the Faculty of Law, Social Sciences, and Political Sciences. also conducted in three regional offices in Ambon, Gorontalo and Makassar, which were selected through purposive sampling. Primary data sources include participant questionnaires and interviews. Analytical methods include correlation and multiple regression analysis, with descriptive statistics used to summarize the dataset. Variable selection involves reliability and validity tests and classical assumption tests like multicollinearity. The F-test demonstrates a statistically significant and beneficial influence of utilizing e-learning media and individual ability, training, and intention to use it for digital learning success. The results of t-tests and regression models provide empirical evidence supporting the significant effect of e-learning media and intention to use on the effectiveness of digital learning. However, variables related to training and ability do not show any significant influence.

Artificial intelligence (AI) offers new possibilities for English as a foreign language (EFL) learners to enhance their learning outcomes, provided that they have access to AI applications. However, little is written about the factors that influence their intention to use AI in distributed EFL learning contexts. This mixed-methods study, based on the technology acceptance model (TAM), examined the determinants of behavioral intention to use AI among 464 Chinese EFL college learners. As to quantitative data, a structural equation modelling (SEM) approach using IBM SPSS Amos (Version 24) produced some important findings. First, it was revealed that perceived ease of use significantly and positively predicts perceived usefulness and attitude toward AI. Second, attitude toward AI significantly and positively predicts behavioral intention to use AI. However, contrary to the TAM assumptions, perceived usefulness does not significantly predict either attitude toward AI or behavioral intention to use AI. Third, mediation analyses suggest that perceived ease of use has a significant and positive impact on students' behavioral intention to use AI through their attitude toward AI, rather than through perceived usefulness. As to qualitative data, semi-structured interviews with 15 learners, analyzed by the software MAXQDA 2022, provide a nuanced understanding of the statistical patterns. This study also discusses the theoretical and pedagogical implications and suggests directions for future research.

This study proposes a hypothetical model combining the unified theory of acceptance and use of technology (UTAUT) with self-determination theory (SDT) to explore design professionals' behavioral intentions to use artificial intelligence (AI) tools. Moreover, it incorporates job replacement (JR) as a moderating role. Chinese-speaking design professionals in regions influenced by Confucian culture were surveyed. An analysis of 565 valid cases with AMOS (Analysis of Moment Structures) supported the structural model hypothesis. The model explains 52.1% of the variance in behavioral intention to use (BIU), proving its effectiveness in explaining these variances. The results further validate the importance of performance expectancy (PE) over effort expectancy (EE) in influencing BIU. Additionally, it has been shown that the impact on intrinsic motivation (IM) and extrinsic motivation (EM) can be either amplified or diminished by anxiety about JR. For individuals experiencing higher levels of JR anxiety, there is a marked increase in IM. They may perceive adopting AI tools as an opportunity to enhance their skills and job security. Conversely, this anxiety also significantly boosts EM, as the potential for improved efficiency and productivity with AI use becomes a compelling incentive. These findings suggest new paths for academic researchers to explore the psychological impacts of AI on design professionals' roles. For practitioners, especially in human resources and organizational development, understanding these dynamics can guide the creation of training programs that address job replacement anxiety.

Artificial intelligence (AI) has undergone considerable advancement in the contemporary period and represents an emerging technology in higher education. Cultural contexts significantly shape individuals' perceptions, attitudes, and behaviors, particularly in the realm of technology acceptance. By adopting a cross-cultural lens, this research explores the potential variations across Chinese and international students from diverse countries in terms of attitudes and their behavioral intentions toward AI use. With a technology acceptance model (TAM) framework, the research used a survey approach, employing questionnaires as the primary means of data collection. The data were then analyzed through structural equation modeling and descriptive statistics. A substantial discrepancy was found in the prevalence, attitudes, and behavioral intentions toward AI use between Chinese and international students. Findings further revealed a stronger effect of perceived ease of use on both attitudes and behavioral intentions among international students compared with their Chinese counterparts. Findings suggest that cultural backgrounds and prior technological exposure play intricate roles in shaping perceptions of AI technology. The study emphasizes the need for tailored educational strategies to regulate diverse cultural perspectives, provide language-specific support, and ensure user-friendly interfaces. These insights contribute to the evolving discourse on technology acceptance in higher education and offer practical implications for educators and institutions toward optimizing AI integration in pedagogical practices.

The objective of this study was to ascertain the efficacy of music therapy in alleviating anxiety among university students. This is achieved by employing the theory of planned behaviour. A survey comprising 350 participants was disseminated to evaluate their subjective norms, perceived behavioural control, attitudes, intentions to engage, and actual involvement in music therapy, as well as their degrees of anxiety. The information gathered was examined using structural equation modelling. The findings validated that favorable attitudes, robust subjective standards, and elevated perceived behavioral control fostered students' inclination to engage in music therapy. In addition, it is unsurprising that students who intended to participate ultimately followed through and carried out the task. The structural equation modelling analysis ultimately demonstrated that engaging in these sessions significantly decreased students' levels of anxiety. While effective in the examined context, the research acknowledges geographic and demographic limitations, suggesting the need for broader investigations. This study adds to the growing evidence supporting the integration of music therapy into mental health services, particularly for university students facing academic stressors.

Disability and chronic disease can have a profound effect on individuals' sexuality and sexual health, resulting in decreased quality of life for many. While sexuality and sexual health are identified within the domain of occupational therapy (OT), this topic is not routinely addressed in clinical practice. This qualitative phenomenological study explored the perceived needs, facilitators, and barriers to addressing sexuality in clinical practice by 10 graduate OT students recruited from one Western New York (WNY) university. Semi-structured virtual interviews were conducted utilizing a researcher developed interview guide. The Theoretical Domains Framework (TDF) was used as the conceptual framework for the study. Data were analyzed inductively using thematic analysis, followed by mapping the identified themes deductively to the established domains of the TDF. Ten domains were identified as likely to influence whether or not sexuality is addressed in clinical practice, including knowledge, skills, social/professional role and identity, beliefs about capabilities and consequences, intentions, environmental context and resources, social influences, emotions, and behavior regulation. The results highlight the barriers, facilitators, and action steps, as perceived by OT students, that are needed in order to effectively address sexuality in clinical practice, including increasing sexual health curriculum within OT education, providing opportunities for practice and experience, and integrating sexual content into routine practice.

Metaverse, an amalgamation of diverse information technologies, is seen as the future of the internet and holds promise for transforming education. Leveraging metaverse media for immersive learning has the potential to reshape education practices. Despite being a novel concept, metaverse-based education has the capacity to enrich online learning experiences. The study utilized the Unified Theory of Acceptance and Use of Technology (UTAUT) model alongside the factor of personal innovativeness in IT, conducting a comprehensive survey involving 244 students from Federal University Wukari, Nigeria. Employing STATA 14, a popular variance-based structural equation modeling technique in social sciences and management, the study analyzed the structural model and conceptual measures, confirming the discriminant validity, dependability, and content of the data. The research findings highlight the importance of personal innovativeness in IT as a direct and indirect predictor of adoption intention among Generation Z students in making decisions about integrating metaverse technologies into higher education. Students demonstrating a high level of innovativeness in IT exhibit a greater willingness to engage with metaverse-based learning incorporating artificial intelligence. The results demonstrate a strong association between the identified characteristics and students' intentions to utilize educational platforms utilizing metaverse technology, contributing valuable insights to the use of technology in educational settings.

Using the pull-and-push model as a main theoretical framework, this qualitative interview-based study explores the changes in STEM students' intentions to pursue international mobility in the context of the Russia-Ukraine war and the factors related to students' mobility decisions in the context of geopolitical tensions. The findings suggest that in situations with military conflict, STEM students are 'pulled' and 'pushed' to make decisions under the influence of the factors located both on the receiving and domestic sides, and the decisions of whether to pursue international mobility were primarily driven by safety, financial, and social tension concerns. The study's findings offer some theoretical and practical implications of the changes in student mobility in the context of war conflict for higher education institutions internationally.

Several studies have been conducted on e-learning acceptance among university students. Most of these studies examined various factors and individual characteristics as predictors of actual use and behavioral intention for e-learning systems. However, latent profile analysis was used in the present study, adopting a person-centered approach. Accordingly, the study's primary purpose was to define LMS acceptance profiles by grouping university students based on gender according to four main UTAUT predictor variables. The secondary purpose was to examine the extent to which LMS acceptance profiles had a relationship with the students' online self-regulation and engagement in online learning environments. The participants in the study were 397 students from a state university in Turkey who continued their distance education. Student Engagements Scale, Online Self-regulation Questionnaire, and Learning Management System Acceptance Scale were used to collect data. The obtained data were analyzed using latent profile analysis. The results obtained in the study revealed that there were three different student profiles: "very low LMS acceptance", "low LMS acceptance", and "high LMS acceptance". According to another result, it was seen that low online self-regulation and engagement had a relationship with a student profile with very low LMS acceptance and that high online self-regulation and engagement had a relationship with a student profile with high LMS acceptance. Based on the findings, various implications were made about increasing students' LMS acceptance.

The 4-H program is America's largest youth development organization (National 4-H Council, 2019). The 4-H program is part of the Cooperative Extension system, which provides unbiased, research-based educational programming to communities through the land grant university system (USDA, 2019). Volunteers play a major role in the delivery and functioning of Cooperative Extension's 4-H Youth Development program. 4-H volunteer leaders serve in various capacities (Radhakrishna & Ewing, 2011), including leading 4-H clubs, organizing educational clinics for youth members on various topics, and assisting with educational events and camps. Around ten thousand volunteers currently serve the Pennsylvania 4-H program. 1, 2018). In the 4-H program, volunteers often spend more time with youth and families than 4-H Extension educators and paid program staff, as they are the adults teaching and working with the youth. This can lead to volunteers having a closer relationship with 4-H members than 4-H staff. Despite volunteers' integral role in maintaining the 4-H program, Penn State Extension has not recently examined 4-H volunteer leaders' satisfaction (Dr. Josh Rice, , October 1, 2018 personal communication), reasons for volunteering, and turnover intention. Ensuring volunteers are satisfied and provided with conditions to thrive and grow through their work is vital to 4-H and the Cooperative Extension system. 4-H educators must understand volunteer service motivators (Cleveland & Thompson, 2007) to recruit and maintain dedicated and fulfilled volunteers. Therefore, the authors examined Pennsylvania 4-H Extension volunteers' experience with volunteering in a twenty-first century context. Results will help improve Pennsylvania Extension's 4-H program's service for volunteers, enhance volunteers' effectiveness in the Pennsylvania 4-H program, and improve clientele satisfaction. Services for volunteers include training and recognition programs. If volunteer feedback data support volunteer programming, they will likely make volunteers feel more satisfied with their experience (Pascuet et al., 2012).

This study investigates the reasons behind pre-service and in-service teachers' decisions to use digital literacy tools in their teaching following the COVID-19 pandemic. The objective is to understand the factors influencing their choices and to identify areas where support and training are needed. Semi-structured interviews were conducted with eight teachers from a university demonstration school in Thailand, evenly divided between pre-service and in-service teachers. The Technology Acceptance Model (TAM) framework guided the creation and adaptation of the interview questions. The findings indicate that pre-service teachers prefer digital tools that are easy to use, accessible, and affordable, with features such as templates, multimedia, and engaging functionalities. In contrast, in-service teachers prioritize familiar tools that save time and enhance the quality of teaching materials. Both groups value tools that facilitate collaboration and ensure privacy. The study highlights the significant generational differences in technology adoption, with younger teachers showing a greater inclination towards exploring a variety of digital tools, while more experienced teachers tending to stick with familiar technologies due to time constraints and comfort levels. These insights underscore the necessity for ongoing, tailored professional development programs that address the specific needs of both pre-service and in-service teachers. Such programs should focus on enhancing digital literacy, providing practical examples of new tools' benefits, and fostering a supportive community for technology integration. By understanding these differences, educational institutions can better support teachers in integrating digital literacy tools effectively, thereby improving teaching practices and professional development opportunities. The implications of this study suggest that a one-size-fits-all approach to technology training may not be effective, and differentiated support is essential to cater to the diverse needs of educators.

The use of language in digital discourse for marketing has rapidly developed through mass media. This paper elucidates how advertisers employ various pragmatic strategies to persuade the recipient to act (behavior) by purchasing specific products. This study utilized different theoretical and conceptual frameworks (Theory of Reasoned Action and Aristotle's Models of Persuasion) to address the shortcomings of the social cognitive approach in studying persuasion, to investigate how language of advertisements can influence the recipient's thinking of a product from a psychological perspective. Guided by the principles of TRA, the present study argues that persuasion in advertisements is structured by three dimensions: attraction (through language features and appeals), evaluation (through beliefs, attitudes, and intention), and behavior (social acceptance or reluctance). This study revealed eight persuasion techniques employed by advertisers including demonstrating distinction, honoring commitment, expressing authority, hyperbolizing, glorification, providing proofs, expressing solidarity, and proving success. Showing distinction and Honoring commitment were the most frequently used strategies. Additionally, the study found that strategies of persuasion involved ethical, logical, and emotional appeals for their large effect on the recipient as they contribute to the recipient's positive evaluations. Appealing to reasoning (logic) is the most common one in slogans.

This study investigates the factors influencing the adoption of Generative-AI tools amongst Thai university students, employing the Technology Acceptance Model (TAM) as a theoretical framework. Data from 911 higher education students from 10 different Thai Universities Health Sciences, Sciences and Technology, Social Sciences and Humanities, and Vocational Fields were analysed via Structural Equation Modelling (SEM). The instrument used in collecting the data was a questionnaire. Results indicated that Expected Benefits, Perceived Usefulness, Attitude Toward Technology, and Behavioural Intention all significantly impacted student adoption of Generative AI. Intriguingly, Perceived Ease of Use was negatively correlated with Perceived Usefulness, challenging conventional TAM assumptions. This study underscores the need to address language barriers, foster a culture of innovation, and establish ethical guidelines to promote responsible AI use within education. Despite inherent limitations, this research contributes to our understanding of AI adoption in educational settings and helps inform strategies for equitable access and responsible innovation. The result demonstrated that the easier a tool was to use, the less value leaners seemed to see in it for their learning process. It can be implied that as Generative AI get more intuitive, learners think they're less helpful. These finding challenges a few of those assumptions we usually make within the TAM model. It also points out the characteristic of learners which affects their learning preferences and expectation. Another finding showed the impact of language barrier on non-native English speaker that obstruct the user experience in AI services. Moreover, the role of universities in fostering both AI integration for learning for and the ethical implementation of Generative AI. By providing a supportive environment that encourages AI experimentation, redesign learning, empowering learners and faculty instructors to investigate how Generative AI can be applied across disciplines, and developing guidelines for ethical use, universities play a critical role in shaping the effective and responsible integration of AI into the next educational landscape.

Finding a way out for new business creation has been a global issue, and the Indonesian government has responded to this issue by promoting entrepreneurship programs for students. For this matter, understanding the role of the entrepreneurial ecosystem can be used to design and promote business for university students. This study employed structural equation modeling with partial least squares to raise understanding among variables. This study involved an entrepreneurial ecosystem to explain the intention of Indonesian university students to do business. The findings indicate that the entrepreneurial ecosystem robustly links with students' entrepreneurial intention and new business creation. This study confirms that access to finance, government programs, support, access to physical infrastructure factors, education, and training factors are crucial for determining Indonesian university students' business. The theoretical and practical implications were provided in this research.

The aim of this study is to examine the variables that influence the learners' intention of using online learning platforms and usage behavior continuity to evaluate relationships between variables with a model proposal and to determine the predictive power of the model. Accordingly, a sustained technology acceptance model (STAM) was developed to identify the factors that influence learners' intention and usage behavior of online learning. The sample of this study consisted of learners registered in the Anadolu University Open Education System. As a result of the factor analyses, a 42-item measurement tool consisting of eleven factors was developed. Structural equation modeling revealed that the eleven-structured model explained 49.8% of perceived usefulness, 30.3% of perceived ease of use, 39.4% of usage intention, and 52.4% of usage behavior continuity, and all 12 proposed hypotheses were supported. The analysis to determine the predictive power of the model revealed that it has a strong predictive power. The developed model is believed to be efficient in determining learners' expectations, supporting their adaptation to the online learning environment, and ensuring their continued usage.

Adapting the Technology Acceptance Model (TAM) framework, this study investigates English teachers' perspectives on the intention to adopt and integrate ChatGPT in their classrooms. This study utilizes quantitative cross-sectional research with 114 respondents answering the online questionnaire. The Structural Equation Modeling (SEM) statistical analysis through SmartPLS 3.0 was employed to analyze the collected data. The result indicates that the proposed TAM model in this study can predict ChatGPT acceptance in English language teaching. Additionally, the structural model showed that perceived usefulness, ease of use, and attitude toward using significantly and positively influenced behavioral intention. Furthermore, attitude toward using and behavioral intention significantly and positively impacted actual system use. Teachers' perspectives on ChatGPT uptake and integration into English language learning are critical to technological innovation. This paper could assist teachers in Indonesia and comparable regions in understanding and adopting ChatGPT in English language teaching.

This paper provides a thorough examination of the role of Artificial Intelligence (AI), particularly ChatGPT and other AI language models, in the realm of education. Drawing insights from existing literature and a novel study on educator perspectives, the paper delves into the potential advantages, ethical dilemmas, and factors shaping educators' attitudes towards AI integration in education. AI language models have the potential to revolutionize educational content creation, personalize learning experiences, and streamline assessment and feedback processes. These capabilities hold the potential to enhance teaching and learning outcomes while catering to the diverse needs of students. However, ethical concerns loom large in the adoption of AI in education. Bias in generated content is a chief concern, as it can perpetuate societal biases and lead to unfair treatment or the dissemination of inaccurate information. The solution lies in rigorous data curation to ensure equitable educational experiences for all students. Moreover, the potential for generating inappropriate or misleading content poses a significant ethical challenge, impacting students' well-being, civic understanding, and social interactions. Safeguards must be implemented to detect and rectify biased or inappropriate content, fostering inclusive and unbiased learning environments. Transparency emerges as a crucial ethical consideration. The opacity of AI models like ChatGPT makes it difficult to comprehend their decision-making processes. Enhancing model interpretability and explainability is vital for accountability and addressing embedded ethical issues. Privacy concerns related to data collection and usage are emphasized in the literature. Clear policies and guidelines must govern data collection, use, and protection, ensuring data is solely employed for educational purposes and maintaining robust data security measures. Our study expands upon these insights by exploring socio-demographic factors, motivations, and social influences affecting educators' AI adoption in higher education. These findings inform institutions on tailoring AI integration strategies, emphasizing responsible usage through training, and assessing the impact on learning outcomes. As educational institutions increasingly embrace AI, including advanced models like GPT-4, a cautious and thoughtful approach is vital. Balancing potential benefits with ethical challenges ensures that AI enhances teaching and learning while upholding fairness, equity, and accountability. In summary, this paper illuminates the potential of AI in education, accentuates ethical concerns, and highlights the significance of understanding educators' perspectives. Collaboration between educators and policymakers is essential to navigate the complexities of AI integration, ensuring that education remains a realm of equitable, efficient, and accountable learning experiences.

The purpose of this study was to evaluate the factors that influence behavioural intention (BI) to use the Online Summary-with Automated Feedback (OSAF) in a MOOCs platform. Task-Technology Fit (TTF) was the main framework used to analyse the match between task requirements and technology characteristics, predictng the utilisation of the technology. The relationships between TTF and BI was moderated by students' performance. This TTF provides an illustration of the extent to which the suitability of technology support for tasks will affect the performance and utilization of technology. There were 9 hypotheses examined in this study. The participants consisted of 151 students at a public university in East Java, Indonesia. In order to analyse the collected data, PLS-SEM (partial least squares -- structural equation modeling) was employed, using SmartPLS 3.0. In this study, several points can be concluded, namely: (1) task characteristics and technology characteristics were not positively and significantly effected by TTF, while students' characteristics had a positive and significant effect on TTF; (2) TTF and utilization which are influenced by social influence, have a positive effect on performance impact. In this case the performance impact is constructed from 3 dimensions, namely: learning performance, personal integrity, self-confidence, except TTF were not postitive and were significantly affected by self-confidence. (3) TTF and performance impact positively influence behavioural intention, except in the dimension of performance impact, personal integrity was not postively and significantly effected by behavioural intention.

Social distancing policies during the COVID-19 period have opened a space for interventions in the use of digital technology that was previously rejected by the public. Currently, most of the community activities have been carried out online, including those related to education, such as hosting virtual exhibitions with an educational purpose. Virtual exhibitions (VE) are online exhibitions that display information on specific topics. However, to the best of our knowledge, research on VE in the educational context is still lacking. This study aims to identify the variables that affect users' intentions to attend the virtual exhibition frequently. The channel expansion theory, flow theory, technology acceptance model, and expectation confirmation theory serve as the foundation for the research model that is constructed. The model was tested using data from 321 respondents who had visited VE, then analyzed using Structural Equation Modeling (SEM) with the aid of the SmartPLS application version 3.3.3. The findings show that 11 factors significantly influence the intention to continue using VE, while the other 2 factors have no significant influence. Thus, perceived usefulness has a significant effect on satisfaction and continued use intention to use VE, but not on perceived enjoyment. Furthermore, the perceived ease of use of VE has a significant impact on perceived usefulness and perceived enjoyment. However, media richness does not significantly affect perceived enjoyment. It's just that media richness influences perceived ease of use significantly. Confirmation also has a significant impact on perceived enjoyment, perceived usefulness, and satisfaction. Perceived enjoyment has a significant effect on satisfaction and continued use intention, and satisfaction has a significant effect on continued use intention to use VE. The findings are useful for VE providers and developers in developing a transformation strategy to increase the intention to use VE in every educational exhibition. [The publication year on the PDF is incorrect. The correct year is 2024.]

Research shows that videoconferencing tools can be used for delivering high-quality instruction in real-time to a large number of students simultaneously during and even in the aftermath of the pandemic. However, there is a lack of data on how favourable it is among students, particularly in the Philippine setting, in the field of Physical Education (PE). In this regard, this study aimed at inspecting exogenous factors linked to students' acceptance of a video-conferencing platform in learning knowledge- and skill-based concepts in Physical Education through the adaptation of the Technology Acceptance Model. After performing the Partial Least Square-Structural Equation Modelling from a purposively selected sample of 250 teacher education students, the results showed that perceived ease of use (PEOU) positively affected perceived usefulness (PU). It was also found that PEOU and PU impacted behavioural intention. Lastly, behavioural intention (BI) positively leverages actual use of the Zoom platform. It can be inferred that students can benefit greatly from using the video-conferencing platform to learn various PE concepts. Moreover, another surprising discovery was that students could use the platform to efficiently learn, thus capitalising on the university's educational system, even in the New Normal.

This study aims to identify factors that can influence students when using the learning management system (LMS) in learning educational pedagogy. The LMS that we mean in this study is Pedagogi.id Platform. The design model in the study uses the UTAUT model. Questionnaires with five UTAUT variables, namely performance expectancy, effort expectancy, social influence, facilitating condition, behavioral intention, and use behavior, were distributed to students at one of the universities in Bandung. Hypothesis testing or data analysis of this study using the Structural Equation Model (SEM) approach with the help of the SmartPLS application. The results showed that the entire hypothesis was accepted or had a significant influence between variables. The most potent factors shown based on the results of the magnitude of influence are the variables facilitating conditions on student usage behavior and performance expectancy on student behavior intention. Therefore, this study recommends learning by utilizing technology, especially in universities, to improve students' knowledge and skills, one of which is using the Pedagogi.id Platform.

The study aims to improve the existing unified theory of acceptance and use of technology (UTAUT) framework to understand the adoption of e-learning platforms in developing countries and to understand the relevance of the quality of study life among students. The constructs for the UTAUT model were chosen based on the e-learning study context and expanded with the variable study-life quality. The expanded model was tested with empirical data collected from graduate and post-graduate students of higher education institutes. The hypotheses testing and adequacy of the expanded model were analysed using structural equation modeling using SmartPLS v 3.2.8. The study's findings indicate that nine out of the twelve hypothesized paths significantly influenced students' engagement with e-learning platforms, and a total of six significant variables explained a variance of 65.8% of the dependent variable behavioral intention. The variable study-life quality had the highest [beta] coefficient value of 0.380, indicating that it is the most significant factor for e-learning adoption in this study setting. The study adds to the publication on adoption theories by providing an expanded UTAUT framework that is empirically tested.

This study examines the factors affecting the intention to use and actual use of YouTube in improving English-speaking skills in Indonesia. To meet the aims, we extended the theory of technology acceptance model (TAM); two external factors, subjective norms, and perceived enjoyment, to support the TAM variables (perceived ease of use, perceived usefulness, attitude, intention to use, and actual use). Data were collected through a survey with 526 measurable responses from Indonesian preservice English teachers in three Indonesian universities. The data were analyzed through partial least square structural equation modeling (PLS-SEM), measurement, and structural model. The findings informed that all hypothesized relationships were accepted and confirmed. The strongest relationship emerged between intention to use and actual use. Meanwhile, the weakest correlation was between subjective norms and perceived ease of use. The study facilitates recommendations for future researchers, language educators, and all related parties.

Massive open online courses (MOOCs) have gained popularity among sales professionals who use them for self-directed learning and upskilling. However, research related to their intentions to continue learning is scarce. Drawing from the social cognition theory, this research aimed to address this gap by investigating the role of task-technology fit, self-development, and social recognition in sales professionals' continued use of MOOCs. The study hinged on empirical research and used a survey to collect data from 366 sales professionals. The results suggest that task-technology fit, self-development, and social recognition play a significant role in sales professionals' continued use of MOOCs. The study has practical implications for organizations promoting employee learning and development. The findings provide valuable information for MOOC designers and providers to develop more effective courses that meet the needs of sales professionals.

Open universities have provided quality higher education through open and distance education to serve learners who could not attend traditional in-person universities. While open universities vary in terms of providing their services to learners at a distance, many have shifted to e-learning using cost-effective platforms. A common platform that is essential for online teaching and learning is the learning management system (LMS). While there are common processes observed among open universities in the way they use their LMS, there are also subtle differences caused by each institution's unique and special context. Their contextual challenges often drive them to develop technologies or techniques that may easily be adopted by others. Thus, benchmarking activities are often recommended for mutual improvement. In this regard, a comparative study of open universities in Indonesia, the Philippines, and Pakistan was conducted for decision-makers to understand how they could improve in providing quality education to their learners through Moodle, which is their primary LMS. The Delone and Mclean Model was used to systematically compare system, information, and service quality in e-learning delivered through their LMS. The authors hope that the results and recommendations from this study may help other educational institutions overcome similar challenges in their learning platforms.

This article presents an exploratory study that examines how 11 first-year writing instructors' conceptualizations of information literacy evolved over the course of their participation in an inquiry group co-developed and co-facilitated by the Libraries' teaching faculty and the Director of Composition & Rhetoric at a public university in the United States. The authors developed a coding schema to identify the presence of information literacy-related themes and practices in pre- and post-program course syllabi and in reflective pieces submitted by instructors. The findings revealed that instructors' use and applications of the ACRL Framework increased after the program, showing greater personal engagement as evidenced by more preferential application of frames most relevant to their learning goals. Moreover, instructors integrated those frames more fully into their instructional practices. The authors' analysis of instructor-created artifacts provides a unique lens into disciplinary instructors' conceptualizations of and approaches to information literacy while examining the impact of one path for collaboration and scalability of information literacy integration within a curriculum.

The COVID-19 pandemic has prompted significant changes in education, including a widespread transition from traditional, in-person instruction to online learning, which has also affected music conservatories. This study investigates the relationship between social outcome expectations and teacher satisfaction with remote education (SRE) among conservatory music professors during the pandemic. Rooted in the Social Cognitive Theory (SCT), the study examines whether technostress mediates this relationship and whether the intention to use information and communication technology (ICT) moderates it. A cross-sectional survey was conducted among 108 Italian conservatory teachers through an online self-report questionnaire. The results indicate a negative indirect effect of social outcome expectations on teacher satisfaction through technostress. However, surprisingly, the direct effect was positive and stronger. The study suggests that social expectations lead to technostress. Still, they also present an opportunity for music educators to embrace the challenge of remote education and increase their satisfaction with it.

The purpose of this paper is to analyze factors that affect the behavioral intentions of undergraduate students to use blended learning methods. The research uses the three-tier use model (3-TUM) to explore the influencing behavioral factors of students at the undergraduate level to use LMSs. "The research was carried out at a university and consisted of undergraduate students majoring in business-related fields. Students responded to online questionnaires administered at the end of the semester concerning their experience with the LMS." A customized Moodle platform was used to measure the user's perceived usefulness, perceived satisfaction, and perceived ease of use with the LMS. Results show that interactivity in portal and self-efficacy have a direct impact on all second-tier constructs, while multimedia instruction influences only perceived usefulness and perceived satisfaction. In addition, perceived usefulness impacts perceived satisfaction. Perceived usefulness and perceived ease of use significantly impact behavioral intention of students to use learning platforms, while the relation between perceived satisfaction and behavioral intention was unindicative. "The study confirms that the individual experience of users and the quality of the system affect the successful implementation of an LMS and its adoption by users."

The present study intends to investigate the determinants influencing students' behavioral intention and use of Google Classroom as an instrument for enhancing the learning experience in the domain of physical education. This investigation employed the Technology Acceptance Model (TAM) as a conceptual framework. The results revealed that perceived ease of use positively predicts perceived usefulness of the learning management system (LMS). Moreover, perceived ease of use and perceived usefulness positively influences behavioral intention and actual use. Lastly, behavioral intention to use leverages actual use of the educational platform. The results indicate that Google Classroom is a viable and efficient technology for facilitating online learning.

This study aimed to assess the readiness of Jordanian science teachers for integrating Artificial Intelligence (AI) in science education, focusing on their perceptions, challenges, and training needs. A quantitative survey methodology was employed, using a 35-item questionnaire distributed to 136 science teachers in urban Jordan. The questionnaire, developed and refined through expert peer review and a pilot study, encompassed demographics, attitudes towards AI, perceived benefits and challenges of AI in science teaching, self-efficacy in using AI, and behavioural intentions regarding its use. The results indicated varying teacher readiness levels, influenced by gender, educational background, and concerns over data privacy and security. While there was a general sense of optimism about the potential of AI, significant challenges related to limited resource access and insufficient professional development were identified. These results emphasized the need for targeted policy initiatives and training programs to enhance teachers' readiness for AI adoption. The study's insights contributed to understanding the facilitators and barriers to AI integration in science education, highlighting the critical role of teacher readiness in the effective utilization of AI in educational contexts.