Mohammed A. Alzubaidi is an Associate Professor of Economics of Education and Training at the Faculty of Education, King Abdulaziz University, Jeddah, Saudi Arabia. His qualifications include a Ph.D. in Economics of Education and M.Ed. in Leadership, Policy, and Change from Monash University, Australia.
The purpose of this study is to analyze the impact of overeducation on several job attitudes and outcomes. The study is based on cross-sectional survey data from 398 Saudis in the labor market. Drawing upon a person-job fit theory, two different self-assessments—direct self-assessment and indirect self-assessment—are used to examine how overeducation influences job satisfaction, organizational commitment, turnover intentions, and job performance. The results of the hierarchical regressions suggest that overeducation across the two measures is significantly negatively related to job satisfaction and organizational commitment, while significantly positively related to turnover intentions, even after controlling for different confounding variables. However, no significant impact was found for job performance. Furthermore, despite the slight differences in terms of the magnitudes of their effects, the two self-assessment measures of overeducation largely overlap and yield similar conclusions. These findings confirm that except for job performance, overeducation—as a form of person–job misfit—is an important predictor of job attitudes and outcomes. The current study extends the existing literature by providing comparative empirical evidence on the impact of overeducation in Saudi Arabia
The study explores the impact of artificial intelligence (AI) on graduate employability within transnational higher education (TNHE). The findings demonstrate significant improvements in employment rates, with institutions such as the University of Nottingham Malaysia and RMIT University Vietnam reporting higher employment rates among graduates who utilised AI-based career services compared to those who did not. AI-driven platforms have enhanced student satisfaction, with approximately 85% of students acknowledging that AI tools helped them develop industry-relevant skills, thereby increasing their job readiness. Furthermore, AI has played a crucial role in aligning TNE curricula with industry needs, as evidenced by the successful integration of AI tools at Singapore Management University and the American University of Sharjah to tailor programs that meet employer demands. Despite these benefits, challenges such as inclusivity and ethical considerations persist, emphasising the need for continuous evaluation and improvement of AI systems in educational settings.
The foreign scholarships awarded by Saudi public universities to their trainee academics are intended to provide substantial learning and capacity development opportunities for future faculty members, through education and training at well-established higher education institutions throughout the world. At the same time, such overseas study is intended to provide sponsoring universities with highly qualified domestic faculty members, who can help meet staffing needs and strengthen human and institutional capabilities. However, this investment can be successful for faculty members and universities alike only if faculty members are effectively utilised by their universities after they return from overseas, and given the opportunity to apply their acquired skills, knowledge, and experiences. <br> The purpose of this study was to examine the important but largely ignored issue of competence utilisation among foreign-trained faculty members in Saudi public universities. First, the study explored and assessed how the education, skills, abilities, and experiences of foreign-trained faculty members are fully and desirably utilised through the requirements and challenges of their work. Second, the study examined how patterns of competence utilisation systematically influence important job attitudes and outcomes. Third, the study explored the factors that influence competence utilisation among foreign-trained faculty members. <br> <br> This descriptive cross-sectional study was conducted using a concurrent mixed methods design. This design involved collecting both quantitative and qualitative data at approximately the same time, analysing data separately, and then interpreting the results to form the basis for the study discussion and conclusion. Quantitative data were collected, through a survey instrument, from a sample of 586 of foreign-trained faculty members in three major universities. Qualitative data were collected from semi-structured interviews with 21 foreign-trained faculty members who were drawn from one selected university. <br> <br> The findings of the study generally suggested that competence underutilisation might be a pervasive problem that has negative ramifications for foreign-trained faculty members and Saudi universities. Specifically, the quantitative results revealed that a substantial portion of foreign-trained faculty members in this study were not fully and adequately utilised by their universities. Expanding on the quantitative results, the qualitative findings provided more insights into how foreign-trained faculty members interpreted and evaluated the current realities of their competence utilisation. The perceptions of most interview participants indicated that their jobs failed to provide them with the opportunities they desired, and maybe felt they deserved, to fully utilise their acquired skills and qualifications, leading to a perceived deficit in the way they were utilised. <br> <br> Additionally, competence utilisation was found to be significantly positively related to job satisfaction, organisational commitment, and job performance, and significantly negatively related to turnover intentions, even after controlling for demographic variables. Moreover, analysis of the qualitative data revealed several key factors that have the potential to influence competence utilisation among foreign-trained faculty members, including facilities, resources, and infrastructure; clarity of work duties, tasks, and procedures; knowledge about available abilities and talents; bureaucracy; workload; regulations and policies; opportunities for developing existing skills and learning additional skills; work ethics, values, and customs; monitoring and evaluation; career path planning and competence management; and individual’s desire, motivation, and determination. The findings of the study have important implications for policy and practice on competence utilisation.
Education expansion has prompted an extensive body of literature on the issue of overeducation, particularly in developed countries. However, as is the case for many developing countries, little, if any, empirical evidence from Saudi Arabia has emerged on this topic. Using cross-sectional survey data, this study examined the prevalence and possible determinants of overeducation among Saudi graduates in the labour market on the basis of two different self-assessment measures. Results indicated that nearly 50% of Saudi graduates in the study were considered overeducated based on each measure, while about 41% were consistently considered overeducated based on both measures. Using logistic regression models, several individual and job characteristics were deemed as major determinants of the probability of being overeducated across both measures. Furthermore, the two measures largely overlapped and yielded somewhat similar conclusions in terms of both the estimates and determinants of overeducation among graduates. The plausible implications of the results for education and labour market policies are discussed.
Education expansion has prompted an extensive body of literature on the issue of overeducation, particularly in developed countries. However, as is the case for many developing countries, little, if any, empirical evidence from Saudi Arabia has emerged on this topic. Using cross-sectional survey data, this study examined the prevalence and possible determinants of overeducation among Saudi graduates in the labour market on the basis of two different self-assessment measures. Results indicated that nearly 50% of Saudi graduates in the study were considered overeducated based on each measure, while about 41% were consistently considered overeducated based on both measures. Using logistic regression models, several individual and job characteristics were deemed as major determinants of the probability of being overeducated across both measures. Furthermore, the two measures largely overlapped and yielded somewhat similar conclusions in terms of both the estimates and determinants of overeducation among graduates. The plausible implications of the results for education and labour market policies are discussed.
The aim of this study is to identify and empirically validate the factors that increase students' engagement in remote work-integrated learning (WIL). The technology interactivity model was considered an appropriate theoretical foundation for proposing the conceptual model in this study. Four factors i.e. interactivity, customisation, active control, and synchronicity were derived as key predictors of student's engagement. This was also extended by considering two factors from social identity theory: social identity and personal identity. The necessary data was collected using an online questionnaire with a purposive sample of students at different levels and from different educational backgrounds. Statistical findings largely approved the impact of social identity, interactivity, customisation, and active control on the students' engagement with remote WIL. Results supported the moderating effects of telepresence and social presence on the relationships between the key independent factors: interactivity, customisation, social identity and engagement.
I am open to research collaboration in the broad area of employability and labour-market outcomes, with particular interest in graduate emp…
I would like to conduct a multi-cultural study related to the implications of the use of AI tools in student retention and dropout rate in …
Seeking collaborators for a research project on AI and higher education, grounded in critical approaches. Topic and data are under develo…