Mobile Technology in Higher Education: An Extended Technology Acceptance Perspective

There is a lack of research that provides institutions with information on educators’ acceptance of mobile technology in higher education within the United States. This study utilized the Chen et al. (2013) extended technology acceptance model, that extended the original Davis (1989) TAM. In this research study, Chen et al. (2013) survey instrument provided the necessary tool to collect data from educators in higher education within the United States before COVID-19. The results showed statistical significance exists in relationships across the assessed factors of perceived usefulness, perceived ease of use, perceived attitude toward use, and behavioral intention, which contribute to the acceptance of mobile technology in higher education. The study implies that institutions face a challenging task to understand the technology acceptance of educators as they incorporate the use of mobile technology to support their work and improve instructional practices

Behavioral Intention and Use Behavior of University Students in Chengdu in Using Virtual Reality Technology for Learning

The purpose of this study is to investigate the factors that influence the usage of virtual reality (VR) technology in learning among university students in Chengdu, China. Scholars created a virtual reality teaching game based on Unreal Engine 4 software that was utilized to instruct a videography course at the Design College of Sichuan University of Media and Communications in Chengdu, China, with 1160 university students participating in a two-year pedagogical reform project. The researchers employed a quantitative research approach with a sample size of 50 participants, as well as a face-to-face questionnaire survey of the target respondents. The data was gathered via stratified random sampling. The Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) were applied to analyze the data (SEM). The findings indicate that all factors have a substantial influence on students' utilization of virtual reality (VR) technology in learning, with behavioral intention having the biggest impact on actual usage, and that satisfaction has a considerable impact on actual usage. As a result, academic institutions that promote virtual reality (VR) technology as a teaching tool may be able to examine the factors that influence students' usage of VR technology in their learning, thereby boosting students' enthusiasm for learning and performance

Predicting the intention to use social media among medical students in the United Arab Emirates: A machine learning approach

Aim: The volume of research being conducted on the acceptance of social media platforms is rising. But the factors influencing the acceptance for academic reasons are still not properly identified. This study's goal is two-fold. Initially, by including Technology Acceptance Model (TAM) and external variables, analyze the students' intention to use social media networks. Secondly, to employ Machine Learning (ML) algorithms and Partial Least Squares-Structural Equation Modeling (PLS-SEM) to verify the proposed theoretical model. Methods: The focus of this research is to create a conceptual model by supplementing TAM with a subjective norm to assess students' adoption of social media in the classroom. Students currently at one private university in the United Arab Emirates (UAE) provided a sum of 627 acceptable questionnaire surveys out of 700 distributed corresponding to 89.6%. The collected data were evaluated using ML and PLS-SEM. Results: According to the research findings, students' intention to utilize social media networks for learning is significantly predicted by “subjective norms, perceived usefulness, and perceived ease of use”. These findings illustrated how crucial it is for students to feel capable and secure using social networks in their academic work. For validation using machine learning classifiers, the results showed that J48 (a decision tree) typically outperformed other classifiers. Conclusion: According to the empirical findings, "subjective norm," "perceived usefulness and ease of use" all significantly increase students' intention to use social networks for learning. These results were in line with earlier research on social network acceptability. Lawmakers and managers of social media platforms in education must therefore concentrate on those factors that are crucial to promoting education and enhancing students' capacity for developing and implementing successful social media applications. Conflicts of interest: None declared

Predicting the intention to use social media among medical students in the United Arab Emirates: A machine learning approach

Aim: The volume of research being conducted on the acceptance of social media platforms is rising. But the factors influencing the acceptance for academic reasons are still not properly identified. This study's goal is two-fold. Initially, by including Technology Acceptance Model (TAM) and external variables, analyze the students' intention to use social media networks. Secondly, to employ Machine Learning (ML) algorithms and Partial Least Squares-Structural Equation Modeling (PLS-SEM) to verify the proposed theoretical model. Methods: The focus of this research is to create a conceptual model by supplementing TAM with a subjective norm to assess students' adoption of social media in the classroom. Students currently at one private university in the United Arab Emirates (UAE) provided a sum of 627 acceptable questionnaire surveys out of 700 distributed corresponding to 89.6%. The collected data were evaluated using ML and PLS-SEM. Results: According to the research findings, students' intention to utilize social media networks for learning is significantly predicted by “subjective norms, perceived usefulness, and perceived ease of use”. These findings illustrated how crucial it is for students to feel capable and secure using social networks in their academic work. For validation using machine learning classifiers, the results showed that J48 (a decision tree) typically outperformed other classifiers. Conclusion: According to the empirical findings, "subjective norm," "perceived usefulness and ease of use" all significantly increase students' intention to use social networks for learning. These results were in line with earlier research on social network acceptability. Lawmakers and managers of social media platforms in education must therefore concentrate on those factors that are crucial to promoting education and enhancing students' capacity for developing and implementing successful social media applications

The behavioural intention to use Facebook among Malaysian public universities as technology alternative tool for e-learning: the mediating role of end user satisfaction

Nowadays, Facebook is one of the most popular Social Networking Sites (SNS) among the tertiary education students. This site is seen to be used as technology alternative to support the main Learning Management System (LMS) that is provided by the university. However, the real situation nowadays, the students prefer to use Facebook compares to LMS as their e-Learning tool for communicating and sharing knowledge among them. Two well-known models are integrated in this study which is Unified Theory of Acceptance and Use of Technology (UTAUT) and End User Computing Satisfaction (EUCS) for better understanding the vital factors that stimulate students' Behavioural Intention (BI) in using Facebook as e-Learning tool. The sample size comprised of 472 students in Malaysia's Public Universities taken through the quota sampling technique. Thus, the total of 411 usable questionnaires was used for further analysis. Based on data analysis by utilizing PLS SEM method, the results supported the hypothesized of direct effects relationship between all four core factors of UTAUT (Performance Expectancy, Effort Expectancy, Social Influence and Facilitating Conditions) and EUCS on BI. Meanwhile, EUCS mediated the relationship between all four core factors of UTAUT on BI. These findings also supported the view that the integration between satisfaction and acceptance models increases the exploratory power on the users' behaviour of interest in using information technology. Lastly, theoretical, methodological and practical implications are discussed

Factors Influencing Students’ Choice of an Institution of Higher Education

This study examined the following research question: What factors influence student college selection process? The study sought to fill an existing gap in the literature by examining what role technology and other relevant factors have on students’ decision-making as related to college choice. By identifying influencers of college choice, the study’s findings can add to the body of knowledge that admission counselors might use as they develop an appropriate recruiting mix of strategies best suited for today’s college applicants . As the theoretical framework, this research drew on the previous work of Hamrick & Hossler (1996) which combined constructs of both economic and sociologic perspectives with college choice. Additionally, an adaptation of the Unified Theory of Acceptance and Use of Technology (UTAUT) model (Venkatesh, Morris, & Davis, 2003) was created with key constructs such as Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. In addition, the adapted model incorporated two sets of moderators (University Attributes and Individual Attributes) that were hypothesized to influence university or college choice. Socio-demographic information was also collected to better understand how students are being recruited and what methods they perceive as most effective. A convenience sample of students from the freshman class at a major research university in the Southeast were surveyed. Approximately 750 students were selected to receive the main survey, selected with the help of university advisement personnel and university faculty in identifying possible classes to participate. The survey was distributed by e-mail. Over the course of a two-month period, 427 students responded, with 341 surveys completed. Usable surveys were analyzed using the SPSS 25 statistical package. From the data analyzed via multiple regression, Performance Expectancy and Facilitating Conditions were found to be statistically significant whereas Effort Expectancy and Social Influence were found to be insignificant. Individual Attributes as a moderating factor within the model was found to be insignificant. University attributes as a moderating factor within the model was found to be partially confirmed, as only the relationship between social influence (SI) and school of choice behavior (B) was significant, whereas the other hypothesized paths were insignificant. Socio-demographic information from the survey suggested that students were being recruited via email most often, with mail and brochure usage also noted. Social media platforms such as Instagram and Facebook were found to be highly used by students but were not effective recruiting tools. The results suggest that performance expectancy and facilitating conditions such as classrooms, athletic facilities, and academic reputation have a significant and positive relationship with behavior (school choice). Conversely, effort expectancy and social influence did not have a significant direct relationship with school of choice behavior. As technology continues to evolve and become a more pervasive influence on students, colleges need to explore if social media might be a useful recruitment tool. The data from this study adds to the body of literature on economic and status-based factors related to school of choice by including the role of technology

WHEN PRIVACY PROCLIVITY MEET COVID-19: NO LONGER CONCERNS OF TODAY’S M-COMMERCE USERS?

This is continuous research of our previous publication (Thomas et al., 2021). A new two by two study (Before and After COVID 19) X (China and the US culture) was designed to test the moderated mediation effect of the COVID pandemic on M-commerce user’s privacy proclivity, trust, and M-commerce intention! A new sample was collected from two countries in different time periods (Before and after COVID pandemic) to investigate whether M-commerce users’ concern about privacy proclivity has changed after COVID-19. Built on top of our 2021 publication, this study discovered that privacy proclivity no longer has a significant direct impact on consumers’ M-commerce intentions after COVID, as consumers’ desires for convenience outweigh their privacy risk concerns. However, privacy proclivity still has significant influence on consumers’ M-commerce Trust, therefore, it has an indirect impact on M-commerce intentions, but the impact is limited. Finally, the results from Hayes’ PROCESS replicated our previous study findings that culture plays a moderating role in the relationship between privacy proclivity and m-commerce trust after COVID-19 outbreak (Thomas et al., 2021). The impact of privacy proclivity is stronger on M-commerce Trust in China than in the US

Factors influencing the behavioral intention to listen to IIUM.FM among non-listeners

This study is part of a longitudinal study done on the audience reception of IIUM.FM, a campus radio the first study or phase 1 was done in 2011 and the second phase was done in 2016. This study specifically compares the non-listeners in Phase 1 (2011) and Phase 2 (2016) in terms of demographic characteristics, academic-related information and computer-related information. In addition, both internal and external factors that may intensify the listening to IIUM.FM are explored and so that the barriers and challenges facing the listeners are eliminated in the near future as IIUM.FM will remain as the only campus radio in IIUM. The same survey questionnaire is used in the data collection at both phases of the study. In addition to the comparison between both phases using t-test and ONEWAY ANOVA, a simple-multiple regression is conducted to determine the predictors of behavioral intention to listen to IIUM.FM. If the predictor is considered a barrier then it should be eliminated so that the listening habit of the students can be improved especially now that the radio can be listened to via multiple sources such as the app, webstream and social media. If the barriers are the reasons that prevent listening to IIUM.FM are removed, then there is a possibility that IIUM.FM are listened by many more students not only among IIUM students but also others worldwide

Factors of using e-learning in higher education and its impact on student learning

This research was conducted to evaluate the adoption of e-learning in higher education and its impact on students. The quantitative research design was used in this study, and the technology acceptance model (TAM) was used with two external variables perceived enjoyment (PEN) and perceived self-efficacy (PSE), to analyze the validity and reliability of items and to test the hypotheses. This study was conducted among 592 undergraduate students who were selected using a random sampling technique. The findings of this study have successfully proven all ten hypotheses. It was evident that the students enjoyed e-learning’s adoption, which had succeeded in increasing students’ motivation to learn, increasing students’ confidence, and expanding students’ knowledge