This paper is in the following e-collection/theme issue:

Mobile Approaches to Medical Education (59) e-Learning and Digital Medical Education (705) JMIR Theme Issue: COVID-19 Special Issue (2461) Adoption and Change Management of eHealth Systems (731) Machine Learning (1501)

Published on in Vol 7, No 1 (2021): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24032, first published .
Using Machine Learning Algorithms to Predict People’s Intention to Use Mobile Learning Platforms During the COVID-19 Pandemic: Machine Learning Approach

Using Machine Learning Algorithms to Predict People’s Intention to Use Mobile Learning Platforms During the COVID-19 Pandemic: Machine Learning Approach

Using Machine Learning Algorithms to Predict People’s Intention to Use Mobile Learning Platforms During the COVID-19 Pandemic: Machine Learning Approach

Authors of this article:

Iman Akour1 Author Orcid Image ;   Muhammad Alshurideh2, 3 Author Orcid Image ;   Barween Al Kurdi4 Author Orcid Image ;   Amel Al Ali1 Author Orcid Image ;   Said Salloum5 Author Orcid Image
Article Authors Cited by (114) Tweetations (4) Metrics

Journals

  1. Al-Maroof R, Alshurideh M, Salloum S, AlHamad A, Gaber T. Acceptance of Google Meet during the Spread of Coronavirus by Arab University Students. Informatics 2021;8(2):24 View
  2. Alshurideh M, Al Kurdi B, AlHamad A, Salloum S, Alkurdi S, Dehghan A, Abuhashesh M, Masa’deh R. Factors Affecting the Use of Smart Mobile Examination Platforms by Universities’ Postgraduate Students during the COVID-19 Pandemic: An Empirical Study. Informatics 2021;8(2):32 View
  3. Al-Maroof R, Alhumaid K, Akour I, Salloum S. Factors That Affect E-Learning Platforms after the Spread of COVID-19: Post Acceptance Study. Data 2021;6(5):49 View
  4. Alhumaid K, Habes M, Salloum S. Examining the Factors Influencing the Mobile Learning Usage During COVID-19 Pandemic: An Integrated SEM-ANN Method. IEEE Access 2021;9:102567 View
  5. Raheja S, Kasturia S, Cheng X, Kumar M. Machine learning-based diffusion model for prediction of coronavirus-19 outbreak. Neural Computing and Applications 2023;35(19):13755 View
  6. Gumbheer C, Khedo K, Bungaleea A. Personalized and Adaptive Context-Aware Mobile Learning: Review, challenges and future directions. Education and Information Technologies 2022;27(6):7491 View
  7. Elnagar A, Alnazzawi N, Afyouni I, Shahin I, Bou Nassif A, Salloum S. Prediction of the intention to use a smartwatch: A comparative approach using machine learning and partial least squares structural equation modeling. Informatics in Medicine Unlocked 2022;29:100913 View
  8. Peng X, Wang-Trexler N, Magagna W, Land S, Peck K. Learning Agility of Learning and Development Professionals in the Life Sciences Field During the COVID-19 Pandemic: Empirical Study. Interactive Journal of Medical Research 2022;11(1):e33360 View
  9. Rosli M, Saleh N, Md. Ali A, Abu Bakar S, Mohd Tahir L. A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps. Sustainability 2022;14(18):11389 View
  10. Tao T, Sun C, Wu Z, Yang J, Wang J. Deep Neural Network-Based Prediction and Early Warning of Student Grades and Recommendations for Similar Learning Approaches. Applied Sciences 2022;12(15):7733 View
  11. Zhang L, He J, Venkateswaran N. Optimization of Ideological and Political Education under the Epidemic via Mobile Learning Auxiliary Platform in the Era of Digitization. Wireless Communications and Mobile Computing 2022;2022:1 View
  12. Fahmi M, Kostini N, Sunaryo Putra W. Exploring hybrid learning readiness and acceptance model using the extended TAM 3 and TPB approach: An empirical analysis. International Journal of Research in Business and Social Science (2147- 4478) 2022;11(8):321 View
  13. Shi Y, Guo F. Exploring Useful Teacher Roles for Sustainable Online Teaching in Higher Education Based on Machine Learning. Sustainability 2022;14(21):14006 View
  14. Almulla M. Developing a Validated Instrument to Measure Students’ Active Learning and Actual Use of Information and Communication Technologies for Learning in Saudi Arabia’s Higher Education. Frontiers in Psychology 2022;13 View
  15. Xu J, Che H. A Study on the Usefulness of Stochastic Simulation Algorithms for Teaching and Learning in College Physical Education Classrooms. Mathematical Problems in Engineering 2022;2022:1 View
  16. Almogren A, Aljammaz N. The integrated social cognitive theory with the TAM model: The impact of M-learning in King Saud University art education. Frontiers in Psychology 2022;13 View
  17. Chung D, Jeong P, Kwon D, Han H. Technology acceptance prediction of robo-advisors by machine learning. Intelligent Systems with Applications 2023;18:200197 View
  18. Dibra S, Gerdoçi B, Sula G, Kurti S. Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country. Journal of Computers in Education 2023;10(4):689 View
  19. Kaddoura S, Popescu D, Hemanth J. A systematic review on machine learning models for online learning and examination systems. PeerJ Computer Science 2022;8:e986 View
  20. Hasan D, Aladdin A, Amin A, Rashid T, Ali Y, Al-Bahri M, Majidpour J, Batrancea I, Masca E. Perspectives on the Impact of E-Learning Pre- and Post-COVID-19 Pandemic—The Case of the Kurdistan Region of Iraq. Sustainability 2023;15(5):4400 View
  21. Chen J, Zhou Y, Lv L. Significant and hierarchy of variables affecting online knowledge-sharing using an integrated logit-ISM analysis. Education and Information Technologies 2023;28(1):741 View
  22. Ye J, Lee Y, Wang C, Nong W, Ye J, Sun Y. The Continuous Use Intention for the Online Learning of Chinese Vocational Students in the Post-Epidemic Era: The Extended Technology Acceptance Model and Expectation Confirmation Theory. Sustainability 2023;15(3):1819 View
  23. Rabaa’i A, Zhu X, Jayaraman J, Nguyen T, Jha P. The use of machine learning to predict the main factors that influence the continuous usage of mobile food delivery apps. Model Assisted Statistics and Applications 2022;17(4):247 View
  24. Ağbulut Ü. Forecasting of transportation-related energy demand and CO2 emissions in Turkey with different machine learning algorithms. Sustainable Production and Consumption 2022;29:141 View
  25. BEKAR F, ÇAM H. Analysing user resistance to distance learning systems by academics within the Covid-19 pandemic using the technology acceptance model. Hitit Sosyal Bilimler Dergisi 2022;15(2):373 View
  26. Chen W, Hashmi M. The Construction of Ideological and Political Education in Higher Vocational Schools Based on Smartphone Carriers. Wireless Communications and Mobile Computing 2022;2022:1 View
  27. Rangel-de Lázaro G, Duart J. You Can Handle, You Can Teach It: Systematic Review on the Use of Extended Reality and Artificial Intelligence Technologies for Online Higher Education. Sustainability 2023;15(4):3507 View
  28. Fernandes G, Choi A, Schauer J, Pfammatter A, Spring B, Darwiche A, Alshurafa N. An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods Study. Journal of Medical Internet Research 2023;25:e42047 View
  29. Vásquez Navarro G, Córdova Dávila A, Cano Lengua M, Andrade Arenas L. Design of a mobile app for the learning of algorithms for university students. Advances in Mobile Learning Educational Research 2023;3(1):727 View
  30. Sallam M, Salim N, Barakat M, Al-Mahzoum K, Al-Tammemi A, Malaeb D, Hallit R, Hallit S. Assessing Health Students' Attitudes and Usage of ChatGPT in Jordan: Validation Study. JMIR Medical Education 2023;9:e48254 View
  31. Chapman A. Enhancing Survey Efficiency and Predictive Ability in Energy System Design through Machine Learning: A Workflow-Based Approach for Improved Outcomes. Energies 2023;16(13):4911 View
  32. Lazaro G, Duart J. Moving Learning: A Systematic Review of Mobile Learning Applications for Online Higher Education. Journal of New Approaches in Educational Research 2023;12(2):198 View
  33. El Alaoui El Fels A, Mandi L, Kammoun A, Ouazzani N, Monga O, Hbid M. Artificial Intelligence and Wastewater Treatment: A Global Scientific Perspective through Text Mining. Water 2023;15(19):3487 View
  34. Nguyen V, Duong X, Nguyen L, Nguyen P, Priya J, Truong T, Le H, Pham N, Nguyen X. An extensive investigation on leveraging machine learning techniques for high-precision predictive modeling of CO 2 emission. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 2023;45(3):9149 View
  35. Edo O, Etu E, Tenebe I, Oladele O, Edo S, Diekola O, Emakhu J. Fintech adoption dynamics in a pandemic: An experience from some financial institutions in Nigeria during COVID-19 using machine learning approach. Cogent Business & Management 2023;10(2) View
  36. Suliman M, Zhang W, Sleiman K. Factors affecting students’ intention to use m-learning: Extending the technology acceptance model (TAM). Innovations in Education and Teaching International 2024;61(6):1184 View
  37. Mansour M, Serbest K, Kutlu M, Cilli M. Estimation of lower limb joint moments based on the inverse dynamics approach: a comparison of machine learning algorithms for rapid estimation. Medical & Biological Engineering & Computing 2023;61(12):3253 View
  38. Puspitasari I, Rusydi F, Nuzulita N, Hsiao C. Investigating the role of utilitarian and hedonic goals in characterizing customer loyalty in E-marketplaces. Heliyon 2023;9(8):e19193 View
  39. Ikegwu A, Nweke H, Anikwe C. Recent trends in computational intelligence for educational big data analysis. Iran Journal of Computer Science 2024;7(1):103 View
  40. Kuadey N, Ankora C, Tahiru F, Bensah L, Agbesi C, Bolatimi S. Using machine learning algorithms to examine the impact of technostress creators on student learning burnout and perceived academic performance. International Journal of Information Technology 2024;16(4):2467 View
  41. MOON Z, AL AMİN M, ALI M, HASAN M. ANTECEDENTS TO THE UNDERPRIVILEGED UNDERGRADUATE STUDENTS' INTENTION TO PARTICIPATE IN ONLINE CLASSES. Turkish Online Journal of Distance Education 2024;25(1):118 View
  42. Drissi S, Chefrour A, Boussaha K, Zarzour H. Exploring the effects of personalized recommendations on student’s motivation and learning achievement in gamified mobile learning framework. Education and Information Technologies 2024 View
  43. Li Y. Analysis of English Classroom Teaching Behavior Mode in Environmental Protection Field Based on Deep Learning. International Journal of Computational Intelligence Systems 2024;17(1) View
  44. Guo H, Ye Y, Lin Y, Khan A, Chen S, Liou J. Evaluating the determinants on students’ switching intentions towards distance learning: an extension of the theory of planned behavior. Cogent Social Sciences 2024;10(1) View
  45. Unasiansari I, Sarwoprasodjo S, Hubeis A, Kinseng R. Investigating Teacher’s Digital Technology use Through a Modified Technology Acceptance Model Framework: a Survey In Indonesia Capital City Buffer Areas. Revista de Gestão Social e Ambiental 2024;18(9):e07679 View
  46. Islam A, Bukhari F, Awais Sattar M, Kashif A. DETERMINING STUDENT'S ONLINE ACADEMIC PERFORMANCE USING MACHINE LEARNING TECHNIQUES. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 2024;14(3):109 View
  47. Zhang Y, Jahng S. Within the Ecology of communication: Identifying Crucial Elements that Drive Use Intentions on Knowledge-sharing Platforms. Sage Open 2024;14(4) View
  48. Ahmady S, Khajeali N, Kohan N, Zarei A, Biswas B, Barzegar M, Moghaddam A, Namaziandost E. Medical students’ perception of mobile learning during COVID-19 in Iran: A national study. PLOS ONE 2024;19(10):e0308248 View
  49. Borazon E, Marques S, Saycon D. E-learning adoption: a comparative analysis of public sentiments during COVID-19. Information Technology for Development 2024:1 View
  50. Valencia-Arias A, Uribe-Gómez J, Flores-Siapo E, Palacios-Moya L, Gallegos A, Martínez Rojas E, Choudhury A. Application of Artificial Neural Networks to Predict the Use of Mobile Learning by University Students. Human Behavior and Emerging Technologies 2024;2024(1) View

Books/Policy Documents

  1. Naqvi R, Soomro T, Alzoubi H, Ghazal T, Alshurideh M. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). View
  2. Al Batayneh R, Taleb N, Said R, Alshurideh M, Ghazal T, Alzoubi H. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). View
  3. Sultan R, Alqallaf A, Alzarooni S, Alrahma N, AlAli M, Alshurideh M. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). View
  4. Ghazal T, Alshurideh M, Alzoubi H. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). View
  5. Gaid M, Salloum S. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). View
  6. Agha K, M. Alzoubi H, Alshurideh M. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). View
  7. Amarneh B, Alshurideh M, Al Kurdi B, Obeidat Z. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). View
  8. Pierpaolo L, Antonia T. Internet of Things for Smart Environments. View
  9. Nuseir M, Qasim A, Refae G. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  10. Farrukh M, Soomro T, Ghazal T, Alzoubi H, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  11. Said Alhadrami A, Rateb Darawsheh S, Sadu Al-Shaar A, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  12. Nuseir M, Refae G, Urabi S. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  13. Huwari I, Darawsheh S, Al-Shaar A, Alshurideh H. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  14. Lee K, Nawanir G, Cheng J, Alzoubi H, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  15. Shaqrah M, Mohammad A, Aldaihani F, Al-Hawary S, Alshurideh M, AlTaweel I, Abazeed R, Mohammad A, Al Kurdi D. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  16. El khatib M, Al Abdooli K, Alhammadi R, Alshamsi F, Abdulla N, Al Hammadi A, Alzoubi H, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  17. Nuseir M, Aljumah A, El Refae G, Alshurideh M, Urabi S, Al Kurdi B. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  18. Ramu S, Guddeti R, Mohan B. Artificial Intelligence and Soft Computing. View
  19. El khatib M, Al-Shalabi A, Alamim A, Alblooshi H, Alhosani S, Al-Kaabi E, Alzoubi H, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  20. Abuanzeh A, Qtaishat G, Sakher S, Al-eassa A, Alshurideh M. Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022. View
  21. Al-Momani M, Hasan M. The Implementation of Smart Technologies for Business Success and Sustainability. View
  22. Mohammad Rababah A, Ali Alzoubi J, Rateb Darawsheh S, Al-Shaar A, Alshurideh M, Alkhasawneh T. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  23. Ghani M, Razak N, Tahir P, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  24. Nadi A, Hossain S, Hasan A, Sofin M, Shabab S, Sohan M, Yuan C. Novel Financial Applications of Machine Learning and Deep Learning. View
  25. Yousef jarrah H, alwaely S, Alkhasawneh T, Darawsheh S, Al-Shaar A, Turki Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  26. Varma A, Taleb N, Said R, Ghazal T, Ahmad M, Alzoubi H, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  27. Nuseir M, Refae G, Alshurideh M, Urabi S, Kurdi B. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  28. Al-Dmour N, Said R, Alzoubi H, Alshurideh M, Ali L. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  29. Štefancová V, Čulík K, Abramović B, Pálková A. TRANSBALTICA XIII: Transportation Science and Technology. View
  30. Al-Quran A, Dalbouh R, Alshura M, Al-Azzam M, Aldaihani F, Smadi Z, Al-hawajreh K, Al-Hawary S, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  31. Alsharhan A, Salloum S. The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022). View
  32. . Applied Big Data Analytics and Its Role in COVID-19 Research. View
  33. Al-Adamat A, Falaki N, Al-Azzam M, Aldaihani F, Almomani R, Mohammad A, Alshura M, Al-Hawary S, Al Kurdi D, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  34. Darawsheh S, Al-Shaar A, Hassan K, Almahdi L, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  35. Metsai A, Tabakis I, Karamitsios K, Kotrotsios K, Chatzimisios P, Stalidis G, Goulianas K. New Realities, Mobile Systems and Applications. View
  36. Ganguly C, Nayak S, Gupta A. Artificial Intelligence, Machine Learning, and Mental Health in Pandemics. View
  37. Nuseir M, Aljumah A, Urabi S, Alshurideh M, Al Kurdi B. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  38. El khatib M, Beshwari F, Beshwari M, Beshwari A, Alzoubi H, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  39. Hamour R, Alfouri A, Alshurideh M. The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. View
  40. Faiz T, Aldmour R, Ahmed G, Alshurideh M, Paramaiah C. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  41. Sakher S, Al Fouri A, Al Fouri S, Alshurideh M. The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. View
  42. Ghazal T, Hasan M, Abdullah S, Bakar K, Al-Dmour N, Said R, Abdellatif T, Moubayed A, Alzoubi H, Alshurideh M, Alomoush W. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  43. Alkhlifat M, Al-Nsour S, Aldaihani F, Ababneh R, Alkhawaldeh M, Alshurideh M, Al-Hawary S. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  44. Darawsheh S, Alshurideh M, Al-Shaar A, Barsom R, Elsayed A, Ghanem R. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  45. Alahmead E, Boser S, Masa’deh R, Alshurideh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  46. Almatrooshi F, Alhammadi S, Salloum S, Shaalan K. Proceedings of International Conference on Emerging Technologies and Intelligent Systems. View
  47. Ahmad A, Abuhashesh M, Nusairat N, AbedRabbo M, Masa’deh R, Al Khasawneh M. The Effect of Information Technology on Business and Marketing Intelligence Systems. View
  48. Cui Q. Tenth International Conference on Applications and Techniques in Cyber Intelligence (ICATCI 2022). View
  49. Dasmahapatra J, Sil R, Dasmahapatra M. Intelligent Systems Design and Applications. View
  50. Nuseir M, Akour I, Alzoubi H, Al Kurdi B, Alshurideh M, AlHamad A. Cyber Security Impact on Digitalization and Business Intelligence. View
  51. Akour I, Nuseir M, Alshurideh M, Alzoubi H, Al Kurdi B, AlHamad A. Cyber Security Impact on Digitalization and Business Intelligence. View
  52. Akour I, Nuseir M, Alshurideh M, Alzoubi H, Al Kurdi B, AlHamad A. Cyber Security Impact on Digitalization and Business Intelligence. View
  53. Alshurideh M, Nuseir M, Al Kurdi B, Alzoubi H, Hamadneh S, AlHamad A. Cyber Security Impact on Digitalization and Business Intelligence. View
  54. Alshurideh M, Hamadneh S, Alzoubi H, Al Kurdi B, Nuseir M, Al Hamad A. Cyber Security Impact on Digitalization and Business Intelligence. View
  55. Hamadneh S, Akourm I, Al Kurdi B, Alzoubi H, Alshurideh M, AlHamad A. Cyber Security Impact on Digitalization and Business Intelligence. View
  56. Nuseir M, Alquqa E, Alzoubi H, Alshurideh M, Al Kurdi B, AlHamad A. Cyber Security Impact on Digitalization and Business Intelligence. View
  57. Fedajev A, Jovanović D, Veličković M. Online Education During COVID-19 and Beyond. View
  58. Bukhowa B, Alhalwachi L, Alkhater N, Taqi N, Burshaid B, Danish F. Business Development via AI and Digitalization. View