How to cite this paper
Alhumaid, K. (2021). Developing an educational framework for using mobile learning during the era of COVID-19.International Journal of Data and Network Science, 5(3), 215-230.
Refrences
Aburayya, A., Alshurideh, M., Al Marzouqi, A., Al Diabat, O., Alfarsi, A., Suson, R., ... & Salloum, S. A. (2020). An empirical ex-amination of the effect of TQM practices on hospital service quality: an assessment study in UAE hospitals. Systematic Reviews in Pharmacy, 11(9), 347-362.
Aburayya, A., Alshurideh, M., Al Marzouqi, A., Al Diabat, O., Alfarsi, A., Suson, R., ... & Alzarouni, A. (2020). Critical Success Factors Affecting the Implementation of TQM in Public Hospitals: A Case Study in UAE Hospitals. Systematic Reviews in Phar-macy, 11(10), 230-242.
Aburayya, A., & Salloum, S. A. The Effects of Subjective Norm on the Intention to Use Social Media Networks: An Exploratory Study Using PLS-SEM and Machine Learning Approach.
Adapa, A., Nah, F. F. H., Hall, R. H., Siau, K., & Smith, S. N. (2018). Factors influencing the adoption of smart wearable devices. International Journal of Human–Computer Interaction, 34(5), 399-409.
Agha, K., Alzoubi, H. M., & Alshurideh, M. T. (2021, June). Measuring Reliability and Validity Instruments of Technologically Driven Cognitive Intrusion Towards Work-Life Balance. In The International Conference on Artificial Intelligence and Computer Vision (pp. 601-614). Springer, Cham.
Ahmed, A., Alshurideh, M., Al Kurdi, B. & Salloum, S.A. (2021). 1261 AISC Advances in Intelligent Systems and Computing Digi-tal Transformation and Organizational Operational Decision Making: A Systematic Review.
Ahmed, D., Salloum, S. A., & Shaalan, K. (2021). Knowledge Management in Startups and SMEs: A Systematic Review. Recent Advances in Technology Acceptance Models and Theories, 389-409.
Ahorsu, D. K., Lin, C. Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2020). The fear of COVID-19 scale: develop-ment and initial validation. International journal of mental health and addiction, 1-9.
Ajzen, I. (1991). The theory of planned behavior. Orgnizational Behavior and Human Decision Processes, 50(2), 179–211.
Akour, I., Alshurideh, M., Al Kurdi, B., Al Ali, A., & Salloum, S. (2021). Using machine learning algorithms to predict people’s in-tention to use mobile learning platforms during the COVID-19 pandemic: machine learning approach. JMIR Medical Education, 7(1), 1-17.
Al-Dhuhouri, F. S., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). Enhancing our understanding of the relation-ship between leadership, team characteristics, emotional intelligence and their effect on team performance: A Critical Review. In International Conference on Advanced Intelligent Systems and Informatics (pp. 644-655). Springer, Cham.
Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020). An empirical examination of continuous intention to use m-learning: An inte-grated model. Education and information technologies, 25(4), 2899-2918.
Al-Emran, M., & Salloum, S. A. (2017). Students’ Attitudes Towards the Use of Mobile Technologies in e-Evaluation. International Journal of Interactive Mobile Technologies (iJIM), 11(5), 195–202.
Al-Khayyal, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). Factors influencing electronic service quality on electronic loyalty in online shopping context: data analysis approach. In Enabling AI Applications in Data Science (pp. 367-378). Springer, Cham.
Al-Maroof, R. A., Arpaci, I., Al-Emran, M., Salloum, S. A., & Shaalan, K. (2021). Examining the acceptance of WhatsApp stickers through machine learning algorithms. In Recent advances in intelligent systems and smart applications (pp. 209-221). Springer, Cham.
Al-Maroof, R. S., Alfaisal, A. M., & Salloum, S. A. (2021). Google glass adoption in the educational environment: A case study in the Gulf area. Education and Information Technologies, 26(3), 2477-2500.
Al-Maroof, R. S., Salloum, S. A., Hassanien, A. E., & Shaalan, K. (2020). Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic. Interactive Learning Environments, 1-16.
Al-Maroof, R. A. S., & Al-Emran, M. (2018). Students Acceptance of Google Classroom: An Exploratory Study using PLS-SEM Ap-proach. International Journal of Emerging Technologies in Learning, 13(6).
Al-Maroof, R., Al-Qaysi, N., Salloum, S. A., & Al-Emran, M. (2021). Blended Learning Acceptance: A Systematic Review of Infor-mation Systems Models. Technology, Knowledge and Learning, 1-36.
Al-Maroof, R. S., Alshurideh, M. T., Salloum, S. A., AlHamad, A. Q. M., & Gaber, T. (2021, June). Acceptance of Google Meet dur-ing the Spread of Coronavirus by Arab University Students. Informatics 8(2), 24.
Al-Maroof, R. S., Alhumaid, K., Alhamad, A. Q., Aburayya, A., & Salloum, S. (2021). User acceptance of smart watch for medical purposes: an empirical study. Future Internet, 13(5), 127.
Al-Maroof, R. S., Alhumaid, K., Akour, I., & Salloum, S. (2021). Factors that affect e-learning platforms after the spread of COVID-19: post acceptance study. Data, 6(5), 49.
Al-Maroof, R. S., Salloum, S. A., AlHamadand, A. Q. M., & Shaalan, K. (2019, October). A unified model for the use and ac-ceptance of stickers in social media messaging. In International Conference on Advanced Intelligent Systems and Informatics (pp. 370-381). Springer, Cham.
Al-Maroof, R. S., Salloum, S. A., AlHamadand, A. Q. M., & Shaalan, K. (2020). Understanding an Extension Technology Ac-ceptance Model of Google Translation: A Multi-Cultural Study in United Arab Emirates. International Journal of Interactive Mo-bile Technologies, 14(03), 157–78.
Alameeri, K. A., Alshurideh, M.T., & Al Kurdi, B. (2021). The Effect of Covid-19 Pandemic on Business Systems’ Innovation and Entrepreneurship and How to Cope with It: A Theatrical View. The Effect of Coronavirus Disease (COVID-19) on Business Intel-ligence, 334, 275–88.
Alameeri, K., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The effect of work environment happiness on em-ployee leadership. In International Conference on Advanced Intelligent Systems and Informatics (pp. 668-680). Springer, Cham.
AlGhanem, H., Shanaa, M., Salloum, S., & Shaalan, K. (2020). The Role of KM in Enhancing AI Algorithms and Systems. Advanc-es in Science, Technology and Engineering Systems Journal, 5(4), 388-396.
Alghizzawi, M., Ghani, M. A., Som, A. P. M., Ahmad, M. F., Amin, A., Bakar, N. A., & Habes, M. (2018). The impact of smartphone adoption on marketing therapeutic tourist sites in Jordan. International Journal of Engineering & Technology, 7(4.34), 91-96.
Alhashmi, S. F., Salloum, S. A., & Abdallah, S. (2019, October). Critical success factors for implementing artificial intelligence (AI) projects in Dubai Government United Arab Emirates (UAE) health sector: applying the extended technology acceptance model (TAM). In International Conference on Advanced Intelligent Systems and Informatics (pp. 393-405). Springer, Cham.
Alhashmi, S. F., Salloum, S. A., & Mhamdi, C. (2019). Implementing artificial intelligence in the United Arab Emirates healthcare sector: an extended technology acceptance model. International Journal of Information Technology and Language Studies, 3(3), 27-42.
Alkitbi, S.S., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2021). AISC Advances in Intelligent Systems and Computing Factors Affect Customer Retention: A Systematic Review.
Almansoori, A., AlShamsi, M., Salloum, S. A., & Shaalan, K. (2021). Critical Review of Knowledge Management in Healthcare. Re-cent Advances in Intelligent Systems and Smart Applications, 99-119.
Almazrouei, F. A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). Social Media Impact on Business: A Systematic Review. In International Conference on Advanced Intelligent Systems and Informatics (pp. 697-707). Springer, Cham.
Alshamsi, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The influence of service quality on customer reten-tion: A systematic review in the higher education. In International Conference on Advanced Intelligent Systems and Informatics (pp. 404-416). Springer, Cham.
Alsharhan, A., Salloum, S., & Shaalan, K. (2021). The impact of eLearning as a knowledge management tool in organizational per-formance. Advances in Science, Technology and Engineering Systems Journal, 6(1), 928-936.
AlShehhi, H., Alshurideh, M., Kurdi, B.A., & Salloum, S.A. (2021). AISC Advances in Intelligent Systems and Computing The Im-pact of Ethical Leadership on Employees Performance: A Systematic Review.
Alshraideh, A. T. R., Al-Lozi, M., & Alshurideh, M. T. (2017). The impact of training strategy on organizational loyalty via the me-diating variables of organizational satisfaction and organizational performance: An empirical study on Jordanian agricultural credit corporation staff. Journal of Social Sciences (COES&RJ-JSS), 6(2), 383-394.
Alshurideh, M., Salloum, S. A., Al Kurdi, B., Monem, A. A., & Shaalan, K. (2019). Understanding the Quality Determinants that Influence the Intention to Use the Mobile Learning Platforms: A Practical Study. International Journal of Interactive Mobile Technologies, 13(11).
Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2019, October). Examining the main mobile learning system drivers’ effects: A mix empirical examination of both the Expectation-Confirmation Model (ECM) and the Technology Acceptance Model (TAM). In In-ternational Conference on Advanced Intelligent Systems and Informatics (pp. 406-417). Springer, Cham.
Alshurideh, M., Salloum, S. A., Al Kurdi, B., & Al-Emran, M. (2019, February). Factors affecting the social networks acceptance: an empirical study using PLS-SEM approach. In Proceedings of the 2019 8th International Conference on Software and Computer Applications (pp. 414-418).
Alshurideh, M., Bataineh, A., Alkurdi, B., & Alasmr, N. (2015). Factors affect mobile phone brand choices–Studying the case of Jordan universities students. International Business Research, 8(3), 141-155.
Alshurideh, M., Al Kurdi, B., Abumari, A., & Salloum, S. (2018). Pharmaceutical Promotion Tools Effect on Physician’s Adoption of Medicine Prescribing: Evidence from Jordan. Modern Applied Science, 12(11), 210-222.
———. 2020. Predicting the Actual Use of M-Learning Systems: A Comparative Approach Using PLS-SEM and Machine Learning Algorithms. Interactive Learning Environments, 1–15.
Alshurideh, M. T., Kurdi, B. A., AlHamad, A. Q., Salloum, S. A., Alkurdi, S., Dehghan, A., ... & Masa’deh, R. E. (2021, June). Fac-tors affecting the use of smart mobile examination platforms by universities’ postgraduate students during the COVID 19 pan-demic: an empirical study. In Informatics (Vol. 8, No. 2, p. 32). Multidisciplinary Digital Publishing Institute.
Alshurideh, M. T., Al Kurdi, B., & Salloum, S. A. (2021). The moderation effect of gender on accepting electronic payment tech-nology: a study on United Arab Emirates consumers. Review of International Business and Strategy.
Alsuwaidi, M., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). Performance appraisal on employees’ motivation: A comprehensive analysis. In International Conference on Advanced Intelligent Systems and Informatics (pp. 681-693). Springer, Cham.
AlSuwaidi, S. R., Alshurideh, M., Al Kurdi, B., & Aburayya, A. (2021, June). The Main Catalysts for Collaborative R&D Projects in Dubai Industrial Sector. In The International Conference on Artificial Intelligence and Computer Vision (pp. 795-806). Springer, Cham.
Alt, D., & Boniel-Nissim, M. (2018). Links between adolescents' deep and surface learning approaches, problematic Internet use, and fear of missing out (FOMO). Internet interventions, 13, 30-39.
Alyammahi, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The impacts of communication ethics on work-place decision making and productivity. In International Conference on Advanced Intelligent Systems and Informatics (pp. 488-500). Springer, Cham.
Alzoubi, H. M., Alshurideh, M., & Ghazal, T. M. (2021, June). Integrating BLE Beacon Technology with Intelligent Information Systems IIS for Operations’ Performance: A Managerial Perspective. In The International Conference on Artificial Intelligence and Computer Vision (pp. 527-538). Springer, Cham.
Amarneh, B. M., Alshurideh, M. T., Al Kurdi, B. H., & Obeidat, Z. (2021, June). The Impact of COVID-19 on E-learning: Ad-vantages and Challenges. In The International Conference on Artificial Intelligence and Computer Vision (pp. 75-89). Springer, Cham.
Appavoo, P. (2021). Acceptance of technology in the classroom: A qualitative analysis of mathematics teachers’ perceptions. In In-telligent System Design (pp. 1-10). Springer, Singapore.
Bailey, A. A., Pentina, I., Mishra, A. S., & Ben Mimoun, M. S. (2020). Exploring factors influencing US millennial consumers’ use of tap-and-go payment technology. The International Review of Retail, Distribution and Consumer Research, 30(2), 143-163.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption ans use as an Illustration.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588.
Bettayeb, H., Alshurideh, M. T., & Al Kurdi, B. (2020). The effectiveness of Mobile Learning in UAE Universities: A systematic re-view of Motivation, Self-efficacy, Usability and Usefulness. International Journal of Control and Automation, 13(2), 1558-1579.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS quarterly, 25(3), 351-370.
Bhattacherjee, A., & Hikmet, N. (2007). Physicians' resistance toward healthcare information technology: a theoretical model and empirical test. European Journal of Information Systems, 16(6), 725-737.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorpo-rating household life cycle. MIS quarterly, 29(3), 399-426.
Mac Callum, K., & Jeffrey, L. (2014). Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Computers in Human Behavior, 39, 8-19.
Chen, E., & Li, Z. (2011, July). On the application of multimedia technology in foreign language teaching and learning in China's colleges: Challenges, problems and implications. In 2011 International Conference on Multimedia Technology (pp. 595-597). IEEE.
Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & education, 59(3), 1054-1064.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of applied social psychology, 22(14), 1111-1132.
Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computa-tional Statistics & Data Analysis, 81, 10-23.
Distler, V., Lallemand, C., & Koenig, V. (2020). How acceptable is this? How user experience factors can broaden our understanding of the acceptance of privacy trade-offs. Computers in Human Behavior, 106, 106227.
Doll, W. J., Hendrickson, A., & Deng, X. (1998). Using Davis's perceived usefulness and ease‐of‐use instruments for decision mak-ing: a confirmatory and multigroup invariance analysis. Decision Sciences, 29(4), 839-869.
El-Gayar, O., Moran, M., & Hawkes, M. (2011). Students' acceptance of tablet PCs and implications for educational institutions. Journal of Educational Technology & Society, 14(2), 58-70.
Elbasir, M., Elareshi, M., Habas, M., Jeljeli, R., & Salloum, S. A. (2021, June). Media and Non-media Students’ Feedback and Im-provement of University Teaching and the Learning Environment. In The International Conference on Artificial Intelligence and Computer Vision (pp. 754-765). Springer, Cham.
Ellahi, A. (2017, December). Fear of using technology: Investigating impact of using social networking sites in business education. In 2017 IEEE 15th student Conference on research and development (SCOReD) (pp. 234-237). IEEE.
Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gaid, M. L., & Salloum, S. A. (2021, June). Explore the Relationship Between COVID-19 Testing Rates with the Number of Cases. In The International Conference on Artificial Intelligence and Computer Vision (pp. 33-45). Springer, Cham.
Gasaymeh, A. M. M., & Waswas, D. M. (2019). The use of TAM to investigate university students' acceptance of the formal use of smartphones for learning: a qualitative approach. International Journal of Technology Enhanced Learning, 11(2), 136-156.
Gerhold, L. (2020). COVID-19: Risk Perception and Coping Strategies.
Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have advantages for small sample size or non-normal data?. MIS quarterly, 36(3), 981-1001.
Gresham, J. (2020). Manufacturing trends in automated inspection equipment: Linking technology with business change management using the technology acceptance model (Doctoral dissertation, Northcentral University).
Habes, M., Salloum, S. A., Elareshi, M., Ganji, S. F. G., Ziani, A. K., & Elbasir, M. (2020, December). The Influence of YouTube Videos on ELA During the COVID-19 Outbreaks in Jordan. In 2020 Sixth International Conference on e-Learning (econf) (pp. 133-138). IEEE.
Habes, M., Salloum, S. A., Alghizzawi, M., & Mhamdi, C. (2019, October). The relation between social media and students’ aca-demic performance in Jordan: YouTube perspective. In International Conference on Advanced Intelligent Systems and Informatics (pp. 382-392). Springer, Cham.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in in-formation systems research. Industrial Management & Data Systems, 117(3): 442–58.
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
Hantoobi, S., Wahdan, A., Salloum, S.A., & Shaalan, K. (2021). Integration of Knowledge Management in a Virtual Learning Envi-ronment: A Systematic Review. Recent Advances in Technology Acceptance Models and Theories, 247–72.
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., ... & Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational research methods, 17(2), 182-209.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing, 20, 277-319.
Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecifi-cation. Psychological methods, 3(4), 424.
Huang, F., Teo, T., & Zhou, M. (2020). Chinese students’ intentions to use the Internet-based technology for learning. Educational Technology Research and Development, 68(1), 575-591.
Johnston, A. C., & Warkentin, M. (2010). Fear appeals and information security behaviors: An empirical study. MIS quarterly, 34(3), 549-566.
Joo, Y. J., Kim, N., & Kim, N. H. (2016). Factors predicting online university students’ use of a mobile learning management sys-tem (m-LMS). Educational Technology Research and Development, 64(4), 611-630.
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology ac-ceptance model (TAM). Technology in Society, 60, 101212.
Karjaluoto, H., Mattila, M., & Pento, T. (2002). Factors underlying attitude formation towards online banking in Finland. Interna-tional journal of bank marketing, 20(6), 261–72.
Khanh, N. T. V., & Gim, G. (2014). Factors Influencing Mobile-Learning Adoption Intention: An Empirical Investigation in High Education. Journal of Social Sciences, 10(2), 51–62.
Al Khasawneh, M., Abuhashesh, M., Ahmad, A., Masa’deh, R., & Alshurideh, M. T. (2021). Customers Online Engagement with Social Media Influencers’ Content Related to COVID 19. The Effect of Coronavirus Disease (COVID-19) on Business Intelligence, 334, 385.
Kim, B. (2010). An empirical investigation of mobile data service continuance: Incorporating the theory of planned behavior into the expectation–confirmation model. Expert systems with applications, 37(10), 7033-7039.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measure-ment, 30(3), 607-610.
Al Kurdi, B., Alshurideh, M., Salloum, S., Obeidat, Z., & Al-dweeri, R. (2020). An empirical investigation into examination of fac-tors influencing university students’ behavior towards elearning acceptance using SEM approach. International Journal of Inter-active Mobile Technologies (iJIM) 14(02), 19–41.
———. (2021). The Effects of Subjective Norm on the Intention to Use Social Media Networks: An Exploratory Study Using PLS-SEM and Machine Learning Approach. In Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021, Springer International Publishing, 581–92.
Al Kurdi, B., Alshurideh, M., & Salloum, S. A. (2020). Investigating a theoretical framework for e-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6484-6496.
Le, T. T., Pham, H. M., Chu, N. H., Nguyen, D. K., & Ngo, H. M. (2020). Factors affecting users’ continuance intention towards mobile banking In Vietnam. American Journal of Multidisciplinary Research & Development (AJMRD), 2(4), 42-51.
Leo, S., Alsharari, N. M., Abbas, J., & Alshurideh, M. T. (2021). From Offline to Online Learning: A Qualitative Study of Challeng-es and Opportunities as a Response to the COVID-19 Pandemic in the UAE Higher Education Context. The Effect of Coronavirus Disease (COVID-19) on Business Intelligence, 334, 203.
Li, L., Chen, Y., Li, Z., Li, D., Li, F., & Huang, H. (2018, August). Online virtual experiment teaching platform for database tech-nology and application. In 2018 13th International Conference on Computer Science & Education (ICCSE) (pp. 1-5). IEEE.
Liang, Y., Zheng, T., & Wang, M. (2011, July). English audio-visual teaching mode and its teaching environment construction—Henan institute of science and technology as the example. In 2011 International Conference on Multimedia Technology (pp. 3050-3053). IEEE.
Lin, C. Y. (2020). Social reaction toward the 2019 novel coronavirus (COVID-19). Social Health and Behavior, 3(1), 1.
Liu, C. Z., Au, Y. A., & Choi, H. S. (2014). Effects of freemium strategy in the mobile app market: An empirical study of google play. Journal of Management Information Systems, 31(3), 326-354.
Liu, Q., Geertshuis, S., & Grainger, R. (2020). Understanding academics' adoption of learning technologies: A systematic review. Computers & Education, 151, 103857.
Liu, S. H., Liao, H. L., & Peng, C. J. (2005). Applying the technology acceptance model and flow theory to online e-learning users’ acceptance behavior. E-learning, 4(H6), H8.
Liu, Y., & Chen, N.S. (2008). An Adoption Model for Mobile Learning. In Proceeding for the IADIS International Conference E-Commerce, 251–56.
Lohmöller, J. B. (2013). Latent variable path modeling with partial least squares. Springer Science & Business Media.
Machů, E., & Morysová, D. (2016). Analysis of the emotion of fear in gifted children and its use in teaching practice. Procedia-Social and Behavioral Sciences, 217, 222-228.
Makttoofa, N., Khalidb, H., & Abdullahc, I. (2020). The effect of individual factors on the adoption of mobile banking within banks in Iraq. International Journal of Innovation, Creativity and Change, 11(9), 73-90.
McIlroy, S., Ali, N., & Hassan, A. E. (2016). Fresh apps: an empirical study of frequently-updated mobile apps in the Google play store. Empirical Software Engineering, 21(3), 1346-1370.
Al Mehrez, A. A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). Internal Factors Affect Knowledge Management and Firm Performance: A Systematic Review. In International Conference on Advanced Intelligent Systems and Informatics (pp. 632-643). Springer, Cham.
Meng, F., Guo, X., Zhang, X., Peng, Z., & Lai, K. H. (2020, January). Examining the role of technology anxiety and health anxiety on elderly users’ continuance intention for mobile health services use. In Proceedings of the 53rd Hawaii International Confer-ence on System Sciences.
Mhamdi, C., Al-Emran, M., & Salloum, S. A. (2018). Text mining and analytics: A case study from news channels posts on Face-book. In Intelligent Natural Language Processing: Trends and Applications (pp. 399-415). Springer, Cham.
Alsharari, N. M., & Alshurideh, M. T. (2020). Student retention in higher education: the role of creativity, emotional intelligence and learner autonomy. International Journal of Educational Management,
35(1), 233–47. https://doi.org/10.1108/IJEM-12-2019-0421.
Mohammadi, H. (2015). Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49, 191-207.
MORCHID, N. The Current State of Technology Acceptance: A Comparative Study.
MOUZAEK, E., ALAALI, N., A SALLOUM, S. A. I. D., & ABURAYYA, A. (2021). An Empirical Investigation of the Impact of Service Quality Dimensions on Guests Satisfaction: A Case Study of Dubai Hotels. Journal of Contemporary Issues in Business and Government, 27(3), 1186-1199.
Mtebe, J., & Raisamo, R. (2014). Investigating students’ behavioural intention to adopt and use mobile learning in higher education in East Africa. International Journal of Education and Development using ICT, 10(3).
Naqvi, R., Soomro, T. R., Alzoubi, H. M., Ghazal, T. M., & Alshurideh, M. T. (2021, June). The Nexus Between Big Data and Deci-sion-Making: A Study of Big Data Techniques and Technologies. In The International Conference on Artificial Intelligence and Computer Vision (pp. 838-853). Springer, Cham, 838–53.
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches?. Jour-nal of Retailing and Consumer Services, 43, 157-169.
Nchunge, D. M., Sakwa, M., & Mwangi, W. (2012). User’s perception on ICT adoption for education support in schools: a survey of secondary school teacher’s in Thika district Kenya. International Journal of Humanities and Social Science, 2(10), 17-29.
Nunnally, J. C. (1994). Psychometric theory 3E. Tata McGraw-hill education.
Nunnally, J. C. (1978). Psychometric theory (2nd edit.). New York.
Nuseir, M. T., Al Kurdi, B.H., Alshurideh, M.T., & Alzoubi, H.M. (2021). Gender Discrimination at Workplace: Do Artificial Intel-ligence (AI) and Machine Learning (ML) Have Opinions About It. In The International Conference on Artificial Intelligence and Computer Vision, Springer, 301–16.
Pappas, G., Kiriaze, I. J., Giannakis, P., & Falagas, M. E. (2009). Psychosocial consequences of infectious diseases. Clinical microbi-ology and infection, 15(8), 743-747.
Park, S. Y., Nam, M. W., & Cha, S. B. (2012). University students' behavioral intention to use mobile learning: Evaluating the tech-nology acceptance model. British journal of educational technology, 43(4), 592-605.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), 879.
Prieto, J. C. S., Migueláñez, S. O., & García-Peñalvo, F. J. (2014, October). Mobile learning adoption from informal into formal: an extended TAM model to measure mobile acceptance among teachers. In Proceedings of the Second International Conference on Technological Ecosystems for Enhancing Multiculturality (pp. 595-602).
Raza, S. A., Qazi, W., Khan, K. A., & Salam, J. (2021). Social isolation and acceptance of the learning management system (LMS) in the time of COVID-19 pandemic: an expansion of the UTAUT model. Journal of Educational Computing Research, 59(2), 183-208.
Ringle, C. M., Wende, S., & Becker, J.M.. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
Salloum, S. A., Al-Emran, M., Khalaf, R., Habes, M., & Shaalan, K. (2019). An Innovative Study of E-Payment Systems Adoption in Higher Education: Theoretical Constructs and Empirical Analysis. International Journal of Interactive Mobile Technologies, 13(6).
Salloum, S. A., Al-Emran, M., Abdallah, S., & Shaalan, K. (2017, September). Analyzing the Arab gulf newspapers using text min-ing techniques. In International Conference on Advanced Intelligent Systems and Informatics (pp. 396-405). Springer, Cham.
Salloum, S. A., Al-Emran, M., & Shaalan, K. (2016). A survey of lexical functional grammar in the Arabic context. International Journal of Computing and Network Technology, 4(03).
Salloum, S. A., Maqableh, W., Mhamdi, C., Al Kurdi, B., & Shaalan, K. (2018). Studying the social media adoption by university students in the United Arab Emirates. International Journal of Information Technology and Language Studies, 2(3), 83-95.
Salloum, S. A., Al-Emran, M., Habes, M., Alghizzawi, M., Ghani, M. A., & Shaalan, K. (2021). What Impacts the Acceptance of E-learning Through Social Media? An Empirical Study. Recent Advances in Technology Acceptance Models and Theories, 419-431.
———. (2021). Predicting the Intention to Use Social Media Sites: A Hybrid SEM-Machine Learning Approach. Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021: 324.
Salloum, S. A., & Al-Emran, M. (2018). Factors affecting the adoption of E-payment systems by university students: Extending the TAM with trust. International Journal of Electronic Business, 14(4), 371-390.
Salloum, S. A., Alshurideh, M., Elnagar, A., & Shaalan, K. (2020, April). Machine learning and deep learning techniques for cyber-security: a review. In Joint European-US Workshop on Applications of Invariance in Computer Vision (pp. 50-57). Springer, Cham, 50–57.
Salloum, S. A., Mhamdi, C., Al Kurdi, B., & Shaalan, K. (2018). Factors affecting the adoption and meaningful use of social media: a structural equation modeling approach. International Journal of Information Technology and Language Studies, 2(3), 96-109.
Sami Alkalha, Ziad et al. (2012). European Journal of Economics, Finance and Administrative Sciences Investigating the Effects of Human Resource Policies on Organizational Performance: An Empirical Study on Commercial Banks Operating in Jordan.
Song, Y., & Kong, S. C. (2017). Investigating students’ acceptance of a statistics learning platform using technology acceptance model. Journal of Educational Computing Research, 55(6), 865-897.
Suleman, M., Soomro, T. R., Ghazal, T. M., & Alshurideh, M. (2021, June). Combating Against Potentially Harmful Mobile Apps. In The International Conference on Artificial Intelligence and Computer Vision (pp. 154-173). Springer, Cham.
Sultan, R. A., Alqallaf, A. K., Alzarooni, S. A., Alrahma, N. H., AlAli, M. A., & Alshurideh, M. T. (2021, June). How Students In-fluence Faculty Satisfaction with Online Courses and Do the Age of Faculty Matter. In The International Conference on Artificial Intelligence and Computer Vision (pp. 823-837). Springer, Cham.
Al Suwaidi, F., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The impact of innovation management in SMEs performance: A systematic review. In International Conference on Advanced Intelligent Systems and Informatics (pp. 720-730). Springer, Cham.
Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1), 243-257.
Tarhini, A., Hone, K., & Liu, X. (2015). A cross‐cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between B ritish and L ebanese university students. British Journal of Educational Tech-nology, 46(4), 739-755.
Teo, T. (2012). Examining the intention to use technology among pre-service teachers: An integration of the technology acceptance model and theory of planned behavior. Interactive Learning Environments, 20(1), 3-18.
Thatcher, J. B., & Perrewe, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and com-puter self-efficacy. MIS quarterly, 26(4), 381-396.
Trial, D. “Model Fit.” https://www.smartpls.com/documentation/algorithms-and-techniques/model-fit.
Tsai, T. H., Lin, W. Y., Chang, Y. S., Chang, P. C., & Lee, M. Y. (2020). Technology anxiety and resistance to change behavioral study of a wearable cardiac warming system using an extended TAM for older adults. PloS one, 15(1), e0227270.
Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Jour-nal of Information technology theory and application, 11(2), 5-40.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
Wong, K. T., Teo, T., & Russo, S. (2012). Influence of gender and computer teaching efficacy on computer acceptance among Ma-laysian student teachers: An extended technology acceptance model. Australasian Journal of Educational Technology, 28(7).
Zhang, S. X., Wang, Y., Rauch, A., & Wei, F. (2020). Unprecedented disruption of lives and work: Health, distress and life satisfac-tion of working adults in China one month into the COVID-19 outbreak. Psychiatry research, 288, 112958.
Aburayya, A., Alshurideh, M., Al Marzouqi, A., Al Diabat, O., Alfarsi, A., Suson, R., ... & Alzarouni, A. (2020). Critical Success Factors Affecting the Implementation of TQM in Public Hospitals: A Case Study in UAE Hospitals. Systematic Reviews in Phar-macy, 11(10), 230-242.
Aburayya, A., & Salloum, S. A. The Effects of Subjective Norm on the Intention to Use Social Media Networks: An Exploratory Study Using PLS-SEM and Machine Learning Approach.
Adapa, A., Nah, F. F. H., Hall, R. H., Siau, K., & Smith, S. N. (2018). Factors influencing the adoption of smart wearable devices. International Journal of Human–Computer Interaction, 34(5), 399-409.
Agha, K., Alzoubi, H. M., & Alshurideh, M. T. (2021, June). Measuring Reliability and Validity Instruments of Technologically Driven Cognitive Intrusion Towards Work-Life Balance. In The International Conference on Artificial Intelligence and Computer Vision (pp. 601-614). Springer, Cham.
Ahmed, A., Alshurideh, M., Al Kurdi, B. & Salloum, S.A. (2021). 1261 AISC Advances in Intelligent Systems and Computing Digi-tal Transformation and Organizational Operational Decision Making: A Systematic Review.
Ahmed, D., Salloum, S. A., & Shaalan, K. (2021). Knowledge Management in Startups and SMEs: A Systematic Review. Recent Advances in Technology Acceptance Models and Theories, 389-409.
Ahorsu, D. K., Lin, C. Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2020). The fear of COVID-19 scale: develop-ment and initial validation. International journal of mental health and addiction, 1-9.
Ajzen, I. (1991). The theory of planned behavior. Orgnizational Behavior and Human Decision Processes, 50(2), 179–211.
Akour, I., Alshurideh, M., Al Kurdi, B., Al Ali, A., & Salloum, S. (2021). Using machine learning algorithms to predict people’s in-tention to use mobile learning platforms during the COVID-19 pandemic: machine learning approach. JMIR Medical Education, 7(1), 1-17.
Al-Dhuhouri, F. S., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). Enhancing our understanding of the relation-ship between leadership, team characteristics, emotional intelligence and their effect on team performance: A Critical Review. In International Conference on Advanced Intelligent Systems and Informatics (pp. 644-655). Springer, Cham.
Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020). An empirical examination of continuous intention to use m-learning: An inte-grated model. Education and information technologies, 25(4), 2899-2918.
Al-Emran, M., & Salloum, S. A. (2017). Students’ Attitudes Towards the Use of Mobile Technologies in e-Evaluation. International Journal of Interactive Mobile Technologies (iJIM), 11(5), 195–202.
Al-Khayyal, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). Factors influencing electronic service quality on electronic loyalty in online shopping context: data analysis approach. In Enabling AI Applications in Data Science (pp. 367-378). Springer, Cham.
Al-Maroof, R. A., Arpaci, I., Al-Emran, M., Salloum, S. A., & Shaalan, K. (2021). Examining the acceptance of WhatsApp stickers through machine learning algorithms. In Recent advances in intelligent systems and smart applications (pp. 209-221). Springer, Cham.
Al-Maroof, R. S., Alfaisal, A. M., & Salloum, S. A. (2021). Google glass adoption in the educational environment: A case study in the Gulf area. Education and Information Technologies, 26(3), 2477-2500.
Al-Maroof, R. S., Salloum, S. A., Hassanien, A. E., & Shaalan, K. (2020). Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic. Interactive Learning Environments, 1-16.
Al-Maroof, R. A. S., & Al-Emran, M. (2018). Students Acceptance of Google Classroom: An Exploratory Study using PLS-SEM Ap-proach. International Journal of Emerging Technologies in Learning, 13(6).
Al-Maroof, R., Al-Qaysi, N., Salloum, S. A., & Al-Emran, M. (2021). Blended Learning Acceptance: A Systematic Review of Infor-mation Systems Models. Technology, Knowledge and Learning, 1-36.
Al-Maroof, R. S., Alshurideh, M. T., Salloum, S. A., AlHamad, A. Q. M., & Gaber, T. (2021, June). Acceptance of Google Meet dur-ing the Spread of Coronavirus by Arab University Students. Informatics 8(2), 24.
Al-Maroof, R. S., Alhumaid, K., Alhamad, A. Q., Aburayya, A., & Salloum, S. (2021). User acceptance of smart watch for medical purposes: an empirical study. Future Internet, 13(5), 127.
Al-Maroof, R. S., Alhumaid, K., Akour, I., & Salloum, S. (2021). Factors that affect e-learning platforms after the spread of COVID-19: post acceptance study. Data, 6(5), 49.
Al-Maroof, R. S., Salloum, S. A., AlHamadand, A. Q. M., & Shaalan, K. (2019, October). A unified model for the use and ac-ceptance of stickers in social media messaging. In International Conference on Advanced Intelligent Systems and Informatics (pp. 370-381). Springer, Cham.
Al-Maroof, R. S., Salloum, S. A., AlHamadand, A. Q. M., & Shaalan, K. (2020). Understanding an Extension Technology Ac-ceptance Model of Google Translation: A Multi-Cultural Study in United Arab Emirates. International Journal of Interactive Mo-bile Technologies, 14(03), 157–78.
Alameeri, K. A., Alshurideh, M.T., & Al Kurdi, B. (2021). The Effect of Covid-19 Pandemic on Business Systems’ Innovation and Entrepreneurship and How to Cope with It: A Theatrical View. The Effect of Coronavirus Disease (COVID-19) on Business Intel-ligence, 334, 275–88.
Alameeri, K., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The effect of work environment happiness on em-ployee leadership. In International Conference on Advanced Intelligent Systems and Informatics (pp. 668-680). Springer, Cham.
AlGhanem, H., Shanaa, M., Salloum, S., & Shaalan, K. (2020). The Role of KM in Enhancing AI Algorithms and Systems. Advanc-es in Science, Technology and Engineering Systems Journal, 5(4), 388-396.
Alghizzawi, M., Ghani, M. A., Som, A. P. M., Ahmad, M. F., Amin, A., Bakar, N. A., & Habes, M. (2018). The impact of smartphone adoption on marketing therapeutic tourist sites in Jordan. International Journal of Engineering & Technology, 7(4.34), 91-96.
Alhashmi, S. F., Salloum, S. A., & Abdallah, S. (2019, October). Critical success factors for implementing artificial intelligence (AI) projects in Dubai Government United Arab Emirates (UAE) health sector: applying the extended technology acceptance model (TAM). In International Conference on Advanced Intelligent Systems and Informatics (pp. 393-405). Springer, Cham.
Alhashmi, S. F., Salloum, S. A., & Mhamdi, C. (2019). Implementing artificial intelligence in the United Arab Emirates healthcare sector: an extended technology acceptance model. International Journal of Information Technology and Language Studies, 3(3), 27-42.
Alkitbi, S.S., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2021). AISC Advances in Intelligent Systems and Computing Factors Affect Customer Retention: A Systematic Review.
Almansoori, A., AlShamsi, M., Salloum, S. A., & Shaalan, K. (2021). Critical Review of Knowledge Management in Healthcare. Re-cent Advances in Intelligent Systems and Smart Applications, 99-119.
Almazrouei, F. A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). Social Media Impact on Business: A Systematic Review. In International Conference on Advanced Intelligent Systems and Informatics (pp. 697-707). Springer, Cham.
Alshamsi, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The influence of service quality on customer reten-tion: A systematic review in the higher education. In International Conference on Advanced Intelligent Systems and Informatics (pp. 404-416). Springer, Cham.
Alsharhan, A., Salloum, S., & Shaalan, K. (2021). The impact of eLearning as a knowledge management tool in organizational per-formance. Advances in Science, Technology and Engineering Systems Journal, 6(1), 928-936.
AlShehhi, H., Alshurideh, M., Kurdi, B.A., & Salloum, S.A. (2021). AISC Advances in Intelligent Systems and Computing The Im-pact of Ethical Leadership on Employees Performance: A Systematic Review.
Alshraideh, A. T. R., Al-Lozi, M., & Alshurideh, M. T. (2017). The impact of training strategy on organizational loyalty via the me-diating variables of organizational satisfaction and organizational performance: An empirical study on Jordanian agricultural credit corporation staff. Journal of Social Sciences (COES&RJ-JSS), 6(2), 383-394.
Alshurideh, M., Salloum, S. A., Al Kurdi, B., Monem, A. A., & Shaalan, K. (2019). Understanding the Quality Determinants that Influence the Intention to Use the Mobile Learning Platforms: A Practical Study. International Journal of Interactive Mobile Technologies, 13(11).
Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2019, October). Examining the main mobile learning system drivers’ effects: A mix empirical examination of both the Expectation-Confirmation Model (ECM) and the Technology Acceptance Model (TAM). In In-ternational Conference on Advanced Intelligent Systems and Informatics (pp. 406-417). Springer, Cham.
Alshurideh, M., Salloum, S. A., Al Kurdi, B., & Al-Emran, M. (2019, February). Factors affecting the social networks acceptance: an empirical study using PLS-SEM approach. In Proceedings of the 2019 8th International Conference on Software and Computer Applications (pp. 414-418).
Alshurideh, M., Bataineh, A., Alkurdi, B., & Alasmr, N. (2015). Factors affect mobile phone brand choices–Studying the case of Jordan universities students. International Business Research, 8(3), 141-155.
Alshurideh, M., Al Kurdi, B., Abumari, A., & Salloum, S. (2018). Pharmaceutical Promotion Tools Effect on Physician’s Adoption of Medicine Prescribing: Evidence from Jordan. Modern Applied Science, 12(11), 210-222.
———. 2020. Predicting the Actual Use of M-Learning Systems: A Comparative Approach Using PLS-SEM and Machine Learning Algorithms. Interactive Learning Environments, 1–15.
Alshurideh, M. T., Kurdi, B. A., AlHamad, A. Q., Salloum, S. A., Alkurdi, S., Dehghan, A., ... & Masa’deh, R. E. (2021, June). Fac-tors affecting the use of smart mobile examination platforms by universities’ postgraduate students during the COVID 19 pan-demic: an empirical study. In Informatics (Vol. 8, No. 2, p. 32). Multidisciplinary Digital Publishing Institute.
Alshurideh, M. T., Al Kurdi, B., & Salloum, S. A. (2021). The moderation effect of gender on accepting electronic payment tech-nology: a study on United Arab Emirates consumers. Review of International Business and Strategy.
Alsuwaidi, M., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). Performance appraisal on employees’ motivation: A comprehensive analysis. In International Conference on Advanced Intelligent Systems and Informatics (pp. 681-693). Springer, Cham.
AlSuwaidi, S. R., Alshurideh, M., Al Kurdi, B., & Aburayya, A. (2021, June). The Main Catalysts for Collaborative R&D Projects in Dubai Industrial Sector. In The International Conference on Artificial Intelligence and Computer Vision (pp. 795-806). Springer, Cham.
Alt, D., & Boniel-Nissim, M. (2018). Links between adolescents' deep and surface learning approaches, problematic Internet use, and fear of missing out (FOMO). Internet interventions, 13, 30-39.
Alyammahi, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The impacts of communication ethics on work-place decision making and productivity. In International Conference on Advanced Intelligent Systems and Informatics (pp. 488-500). Springer, Cham.
Alzoubi, H. M., Alshurideh, M., & Ghazal, T. M. (2021, June). Integrating BLE Beacon Technology with Intelligent Information Systems IIS for Operations’ Performance: A Managerial Perspective. In The International Conference on Artificial Intelligence and Computer Vision (pp. 527-538). Springer, Cham.
Amarneh, B. M., Alshurideh, M. T., Al Kurdi, B. H., & Obeidat, Z. (2021, June). The Impact of COVID-19 on E-learning: Ad-vantages and Challenges. In The International Conference on Artificial Intelligence and Computer Vision (pp. 75-89). Springer, Cham.
Appavoo, P. (2021). Acceptance of technology in the classroom: A qualitative analysis of mathematics teachers’ perceptions. In In-telligent System Design (pp. 1-10). Springer, Singapore.
Bailey, A. A., Pentina, I., Mishra, A. S., & Ben Mimoun, M. S. (2020). Exploring factors influencing US millennial consumers’ use of tap-and-go payment technology. The International Review of Retail, Distribution and Consumer Research, 30(2), 143-163.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption ans use as an Illustration.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588.
Bettayeb, H., Alshurideh, M. T., & Al Kurdi, B. (2020). The effectiveness of Mobile Learning in UAE Universities: A systematic re-view of Motivation, Self-efficacy, Usability and Usefulness. International Journal of Control and Automation, 13(2), 1558-1579.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS quarterly, 25(3), 351-370.
Bhattacherjee, A., & Hikmet, N. (2007). Physicians' resistance toward healthcare information technology: a theoretical model and empirical test. European Journal of Information Systems, 16(6), 725-737.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorpo-rating household life cycle. MIS quarterly, 29(3), 399-426.
Mac Callum, K., & Jeffrey, L. (2014). Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Computers in Human Behavior, 39, 8-19.
Chen, E., & Li, Z. (2011, July). On the application of multimedia technology in foreign language teaching and learning in China's colleges: Challenges, problems and implications. In 2011 International Conference on Multimedia Technology (pp. 595-597). IEEE.
Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & education, 59(3), 1054-1064.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of applied social psychology, 22(14), 1111-1132.
Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computa-tional Statistics & Data Analysis, 81, 10-23.
Distler, V., Lallemand, C., & Koenig, V. (2020). How acceptable is this? How user experience factors can broaden our understanding of the acceptance of privacy trade-offs. Computers in Human Behavior, 106, 106227.
Doll, W. J., Hendrickson, A., & Deng, X. (1998). Using Davis's perceived usefulness and ease‐of‐use instruments for decision mak-ing: a confirmatory and multigroup invariance analysis. Decision Sciences, 29(4), 839-869.
El-Gayar, O., Moran, M., & Hawkes, M. (2011). Students' acceptance of tablet PCs and implications for educational institutions. Journal of Educational Technology & Society, 14(2), 58-70.
Elbasir, M., Elareshi, M., Habas, M., Jeljeli, R., & Salloum, S. A. (2021, June). Media and Non-media Students’ Feedback and Im-provement of University Teaching and the Learning Environment. In The International Conference on Artificial Intelligence and Computer Vision (pp. 754-765). Springer, Cham.
Ellahi, A. (2017, December). Fear of using technology: Investigating impact of using social networking sites in business education. In 2017 IEEE 15th student Conference on research and development (SCOReD) (pp. 234-237). IEEE.
Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gaid, M. L., & Salloum, S. A. (2021, June). Explore the Relationship Between COVID-19 Testing Rates with the Number of Cases. In The International Conference on Artificial Intelligence and Computer Vision (pp. 33-45). Springer, Cham.
Gasaymeh, A. M. M., & Waswas, D. M. (2019). The use of TAM to investigate university students' acceptance of the formal use of smartphones for learning: a qualitative approach. International Journal of Technology Enhanced Learning, 11(2), 136-156.
Gerhold, L. (2020). COVID-19: Risk Perception and Coping Strategies.
Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have advantages for small sample size or non-normal data?. MIS quarterly, 36(3), 981-1001.
Gresham, J. (2020). Manufacturing trends in automated inspection equipment: Linking technology with business change management using the technology acceptance model (Doctoral dissertation, Northcentral University).
Habes, M., Salloum, S. A., Elareshi, M., Ganji, S. F. G., Ziani, A. K., & Elbasir, M. (2020, December). The Influence of YouTube Videos on ELA During the COVID-19 Outbreaks in Jordan. In 2020 Sixth International Conference on e-Learning (econf) (pp. 133-138). IEEE.
Habes, M., Salloum, S. A., Alghizzawi, M., & Mhamdi, C. (2019, October). The relation between social media and students’ aca-demic performance in Jordan: YouTube perspective. In International Conference on Advanced Intelligent Systems and Informatics (pp. 382-392). Springer, Cham.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in in-formation systems research. Industrial Management & Data Systems, 117(3): 442–58.
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
Hantoobi, S., Wahdan, A., Salloum, S.A., & Shaalan, K. (2021). Integration of Knowledge Management in a Virtual Learning Envi-ronment: A Systematic Review. Recent Advances in Technology Acceptance Models and Theories, 247–72.
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., ... & Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational research methods, 17(2), 182-209.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing, 20, 277-319.
Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecifi-cation. Psychological methods, 3(4), 424.
Huang, F., Teo, T., & Zhou, M. (2020). Chinese students’ intentions to use the Internet-based technology for learning. Educational Technology Research and Development, 68(1), 575-591.
Johnston, A. C., & Warkentin, M. (2010). Fear appeals and information security behaviors: An empirical study. MIS quarterly, 34(3), 549-566.
Joo, Y. J., Kim, N., & Kim, N. H. (2016). Factors predicting online university students’ use of a mobile learning management sys-tem (m-LMS). Educational Technology Research and Development, 64(4), 611-630.
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology ac-ceptance model (TAM). Technology in Society, 60, 101212.
Karjaluoto, H., Mattila, M., & Pento, T. (2002). Factors underlying attitude formation towards online banking in Finland. Interna-tional journal of bank marketing, 20(6), 261–72.
Khanh, N. T. V., & Gim, G. (2014). Factors Influencing Mobile-Learning Adoption Intention: An Empirical Investigation in High Education. Journal of Social Sciences, 10(2), 51–62.
Al Khasawneh, M., Abuhashesh, M., Ahmad, A., Masa’deh, R., & Alshurideh, M. T. (2021). Customers Online Engagement with Social Media Influencers’ Content Related to COVID 19. The Effect of Coronavirus Disease (COVID-19) on Business Intelligence, 334, 385.
Kim, B. (2010). An empirical investigation of mobile data service continuance: Incorporating the theory of planned behavior into the expectation–confirmation model. Expert systems with applications, 37(10), 7033-7039.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measure-ment, 30(3), 607-610.
Al Kurdi, B., Alshurideh, M., Salloum, S., Obeidat, Z., & Al-dweeri, R. (2020). An empirical investigation into examination of fac-tors influencing university students’ behavior towards elearning acceptance using SEM approach. International Journal of Inter-active Mobile Technologies (iJIM) 14(02), 19–41.
———. (2021). The Effects of Subjective Norm on the Intention to Use Social Media Networks: An Exploratory Study Using PLS-SEM and Machine Learning Approach. In Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021, Springer International Publishing, 581–92.
Al Kurdi, B., Alshurideh, M., & Salloum, S. A. (2020). Investigating a theoretical framework for e-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6484-6496.
Le, T. T., Pham, H. M., Chu, N. H., Nguyen, D. K., & Ngo, H. M. (2020). Factors affecting users’ continuance intention towards mobile banking In Vietnam. American Journal of Multidisciplinary Research & Development (AJMRD), 2(4), 42-51.
Leo, S., Alsharari, N. M., Abbas, J., & Alshurideh, M. T. (2021). From Offline to Online Learning: A Qualitative Study of Challeng-es and Opportunities as a Response to the COVID-19 Pandemic in the UAE Higher Education Context. The Effect of Coronavirus Disease (COVID-19) on Business Intelligence, 334, 203.
Li, L., Chen, Y., Li, Z., Li, D., Li, F., & Huang, H. (2018, August). Online virtual experiment teaching platform for database tech-nology and application. In 2018 13th International Conference on Computer Science & Education (ICCSE) (pp. 1-5). IEEE.
Liang, Y., Zheng, T., & Wang, M. (2011, July). English audio-visual teaching mode and its teaching environment construction—Henan institute of science and technology as the example. In 2011 International Conference on Multimedia Technology (pp. 3050-3053). IEEE.
Lin, C. Y. (2020). Social reaction toward the 2019 novel coronavirus (COVID-19). Social Health and Behavior, 3(1), 1.
Liu, C. Z., Au, Y. A., & Choi, H. S. (2014). Effects of freemium strategy in the mobile app market: An empirical study of google play. Journal of Management Information Systems, 31(3), 326-354.
Liu, Q., Geertshuis, S., & Grainger, R. (2020). Understanding academics' adoption of learning technologies: A systematic review. Computers & Education, 151, 103857.
Liu, S. H., Liao, H. L., & Peng, C. J. (2005). Applying the technology acceptance model and flow theory to online e-learning users’ acceptance behavior. E-learning, 4(H6), H8.
Liu, Y., & Chen, N.S. (2008). An Adoption Model for Mobile Learning. In Proceeding for the IADIS International Conference E-Commerce, 251–56.
Lohmöller, J. B. (2013). Latent variable path modeling with partial least squares. Springer Science & Business Media.
Machů, E., & Morysová, D. (2016). Analysis of the emotion of fear in gifted children and its use in teaching practice. Procedia-Social and Behavioral Sciences, 217, 222-228.
Makttoofa, N., Khalidb, H., & Abdullahc, I. (2020). The effect of individual factors on the adoption of mobile banking within banks in Iraq. International Journal of Innovation, Creativity and Change, 11(9), 73-90.
McIlroy, S., Ali, N., & Hassan, A. E. (2016). Fresh apps: an empirical study of frequently-updated mobile apps in the Google play store. Empirical Software Engineering, 21(3), 1346-1370.
Al Mehrez, A. A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). Internal Factors Affect Knowledge Management and Firm Performance: A Systematic Review. In International Conference on Advanced Intelligent Systems and Informatics (pp. 632-643). Springer, Cham.
Meng, F., Guo, X., Zhang, X., Peng, Z., & Lai, K. H. (2020, January). Examining the role of technology anxiety and health anxiety on elderly users’ continuance intention for mobile health services use. In Proceedings of the 53rd Hawaii International Confer-ence on System Sciences.
Mhamdi, C., Al-Emran, M., & Salloum, S. A. (2018). Text mining and analytics: A case study from news channels posts on Face-book. In Intelligent Natural Language Processing: Trends and Applications (pp. 399-415). Springer, Cham.
Alsharari, N. M., & Alshurideh, M. T. (2020). Student retention in higher education: the role of creativity, emotional intelligence and learner autonomy. International Journal of Educational Management,
35(1), 233–47. https://doi.org/10.1108/IJEM-12-2019-0421.
Mohammadi, H. (2015). Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49, 191-207.
MORCHID, N. The Current State of Technology Acceptance: A Comparative Study.
MOUZAEK, E., ALAALI, N., A SALLOUM, S. A. I. D., & ABURAYYA, A. (2021). An Empirical Investigation of the Impact of Service Quality Dimensions on Guests Satisfaction: A Case Study of Dubai Hotels. Journal of Contemporary Issues in Business and Government, 27(3), 1186-1199.
Mtebe, J., & Raisamo, R. (2014). Investigating students’ behavioural intention to adopt and use mobile learning in higher education in East Africa. International Journal of Education and Development using ICT, 10(3).
Naqvi, R., Soomro, T. R., Alzoubi, H. M., Ghazal, T. M., & Alshurideh, M. T. (2021, June). The Nexus Between Big Data and Deci-sion-Making: A Study of Big Data Techniques and Technologies. In The International Conference on Artificial Intelligence and Computer Vision (pp. 838-853). Springer, Cham, 838–53.
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches?. Jour-nal of Retailing and Consumer Services, 43, 157-169.
Nchunge, D. M., Sakwa, M., & Mwangi, W. (2012). User’s perception on ICT adoption for education support in schools: a survey of secondary school teacher’s in Thika district Kenya. International Journal of Humanities and Social Science, 2(10), 17-29.
Nunnally, J. C. (1994). Psychometric theory 3E. Tata McGraw-hill education.
Nunnally, J. C. (1978). Psychometric theory (2nd edit.). New York.
Nuseir, M. T., Al Kurdi, B.H., Alshurideh, M.T., & Alzoubi, H.M. (2021). Gender Discrimination at Workplace: Do Artificial Intel-ligence (AI) and Machine Learning (ML) Have Opinions About It. In The International Conference on Artificial Intelligence and Computer Vision, Springer, 301–16.
Pappas, G., Kiriaze, I. J., Giannakis, P., & Falagas, M. E. (2009). Psychosocial consequences of infectious diseases. Clinical microbi-ology and infection, 15(8), 743-747.
Park, S. Y., Nam, M. W., & Cha, S. B. (2012). University students' behavioral intention to use mobile learning: Evaluating the tech-nology acceptance model. British journal of educational technology, 43(4), 592-605.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), 879.
Prieto, J. C. S., Migueláñez, S. O., & García-Peñalvo, F. J. (2014, October). Mobile learning adoption from informal into formal: an extended TAM model to measure mobile acceptance among teachers. In Proceedings of the Second International Conference on Technological Ecosystems for Enhancing Multiculturality (pp. 595-602).
Raza, S. A., Qazi, W., Khan, K. A., & Salam, J. (2021). Social isolation and acceptance of the learning management system (LMS) in the time of COVID-19 pandemic: an expansion of the UTAUT model. Journal of Educational Computing Research, 59(2), 183-208.
Ringle, C. M., Wende, S., & Becker, J.M.. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
Salloum, S. A., Al-Emran, M., Khalaf, R., Habes, M., & Shaalan, K. (2019). An Innovative Study of E-Payment Systems Adoption in Higher Education: Theoretical Constructs and Empirical Analysis. International Journal of Interactive Mobile Technologies, 13(6).
Salloum, S. A., Al-Emran, M., Abdallah, S., & Shaalan, K. (2017, September). Analyzing the Arab gulf newspapers using text min-ing techniques. In International Conference on Advanced Intelligent Systems and Informatics (pp. 396-405). Springer, Cham.
Salloum, S. A., Al-Emran, M., & Shaalan, K. (2016). A survey of lexical functional grammar in the Arabic context. International Journal of Computing and Network Technology, 4(03).
Salloum, S. A., Maqableh, W., Mhamdi, C., Al Kurdi, B., & Shaalan, K. (2018). Studying the social media adoption by university students in the United Arab Emirates. International Journal of Information Technology and Language Studies, 2(3), 83-95.
Salloum, S. A., Al-Emran, M., Habes, M., Alghizzawi, M., Ghani, M. A., & Shaalan, K. (2021). What Impacts the Acceptance of E-learning Through Social Media? An Empirical Study. Recent Advances in Technology Acceptance Models and Theories, 419-431.
———. (2021). Predicting the Intention to Use Social Media Sites: A Hybrid SEM-Machine Learning Approach. Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021: 324.
Salloum, S. A., & Al-Emran, M. (2018). Factors affecting the adoption of E-payment systems by university students: Extending the TAM with trust. International Journal of Electronic Business, 14(4), 371-390.
Salloum, S. A., Alshurideh, M., Elnagar, A., & Shaalan, K. (2020, April). Machine learning and deep learning techniques for cyber-security: a review. In Joint European-US Workshop on Applications of Invariance in Computer Vision (pp. 50-57). Springer, Cham, 50–57.
Salloum, S. A., Mhamdi, C., Al Kurdi, B., & Shaalan, K. (2018). Factors affecting the adoption and meaningful use of social media: a structural equation modeling approach. International Journal of Information Technology and Language Studies, 2(3), 96-109.
Sami Alkalha, Ziad et al. (2012). European Journal of Economics, Finance and Administrative Sciences Investigating the Effects of Human Resource Policies on Organizational Performance: An Empirical Study on Commercial Banks Operating in Jordan.
Song, Y., & Kong, S. C. (2017). Investigating students’ acceptance of a statistics learning platform using technology acceptance model. Journal of Educational Computing Research, 55(6), 865-897.
Suleman, M., Soomro, T. R., Ghazal, T. M., & Alshurideh, M. (2021, June). Combating Against Potentially Harmful Mobile Apps. In The International Conference on Artificial Intelligence and Computer Vision (pp. 154-173). Springer, Cham.
Sultan, R. A., Alqallaf, A. K., Alzarooni, S. A., Alrahma, N. H., AlAli, M. A., & Alshurideh, M. T. (2021, June). How Students In-fluence Faculty Satisfaction with Online Courses and Do the Age of Faculty Matter. In The International Conference on Artificial Intelligence and Computer Vision (pp. 823-837). Springer, Cham.
Al Suwaidi, F., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The impact of innovation management in SMEs performance: A systematic review. In International Conference on Advanced Intelligent Systems and Informatics (pp. 720-730). Springer, Cham.
Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1), 243-257.
Tarhini, A., Hone, K., & Liu, X. (2015). A cross‐cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between B ritish and L ebanese university students. British Journal of Educational Tech-nology, 46(4), 739-755.
Teo, T. (2012). Examining the intention to use technology among pre-service teachers: An integration of the technology acceptance model and theory of planned behavior. Interactive Learning Environments, 20(1), 3-18.
Thatcher, J. B., & Perrewe, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and com-puter self-efficacy. MIS quarterly, 26(4), 381-396.
Trial, D. “Model Fit.” https://www.smartpls.com/documentation/algorithms-and-techniques/model-fit.
Tsai, T. H., Lin, W. Y., Chang, Y. S., Chang, P. C., & Lee, M. Y. (2020). Technology anxiety and resistance to change behavioral study of a wearable cardiac warming system using an extended TAM for older adults. PloS one, 15(1), e0227270.
Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Jour-nal of Information technology theory and application, 11(2), 5-40.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
Wong, K. T., Teo, T., & Russo, S. (2012). Influence of gender and computer teaching efficacy on computer acceptance among Ma-laysian student teachers: An extended technology acceptance model. Australasian Journal of Educational Technology, 28(7).
Zhang, S. X., Wang, Y., Rauch, A., & Wei, F. (2020). Unprecedented disruption of lives and work: Health, distress and life satisfac-tion of working adults in China one month into the COVID-19 outbreak. Psychiatry research, 288, 112958.