Student Compliance Intention Model for Continued Usage of E-Learning in University | SpringerLink
Skip to main content
Springer Nature Link
Log in

Student Compliance Intention Model for Continued Usage of E-Learning in University

  • Conference paper
  • First Online:
Innovative Systems for Intelligent Health Informatics (IRICT 2020)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 72))

  • 1348 Accesses

Abstract

Continued usage of e-learning is important and has been a major challenge. The problem continued usage of e-learning is a lack of student participation, unwillingness to learn, lack of motivation, lack of awareness, behavioral habits and cultural resistance. There are many studies proposed models for continued usage of e-learning. However, the previous models have not conducted research from the point of view of student compliance. If there is no student intention to comply with the rules of using e-learning, then continuing use of e-learning is very unlikely. Compliance with regulation can change culture. Compliance can also be used to ensure continued use in a system, such as the continued usage of an Enterprise System and continued usage of mobile social network service. So, this study proposes student compliance intention model for continued usage of e-learning. The result of this study is the proposed model that will help developer, university, and policy maker to develop e-learning application.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 22879
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 28599
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Bataineh, K.B., Atoum, M.S., Alsmadi, L.A., Shikhali, M.: A silver lining of Coronavirus Jordanian Universities turn to distance education. Int. J. Inf. Commun. Technol. Educ. 17, 11 (2021)

    Article  Google Scholar 

  2. Al-Fraihat, D., Joy, M., Masa’deh, R., Sinclair, J.: Evaluating e-learning systems success: an empirical study. Comput. Hum. Behav. 102, 67–86 (2020)

    Article  Google Scholar 

  3. Alharthi, A.D., Spichkova, M., Hamilton, M.: Sustainability requirements for eLearning systems: a systematic literature review and analysis. Requirements Eng. 24(4), 523–543 (2018)

    Article  Google Scholar 

  4. Lopes, S., Rodrigues, H., Almeida, F., Figueiredo, H., Lopes, S.: MApping key concept e-learning and education: a systematic review through published papers. Comput. Educ. 136, 87–98 (2019)

    Article  Google Scholar 

  5. Al-Busaidi, K.A.: An empirical investigation linking learners’ adoption of blended learning to their intention of full e-learning. Behav. Inf. Technol. 32(11), 1168–1176 (2013)

    Article  Google Scholar 

  6. Islam, A.K.M.N.: Investigating e-learning system usage outcomes in the university context. Comput. Educ. 69, 387–399 (2013)

    Article  Google Scholar 

  7. Najmul Islam, A.K.M., Azad, N.: Satisfaction and continuance with a learning management system: comparing perceptions of educators and students. Int. J. Inf. Learn. Technol. 32(2), 109–123 (2015)

    Article  Google Scholar 

  8. Persico, D., Manca, S., Pozzi, F.: Adapting the technology acceptance model to evaluate the innovative potential of e-learning systems. Comput. Hum. Behav. 30, 614–622 (2014)

    Article  Google Scholar 

  9. Alexander, P.A., The Disciplined Reading and Learning Research Laboratory: Reading Into the Future: Competence for the 21st Century. Educ. Psychol. 47(4), 259–280 (2012)

    Article  Google Scholar 

  10. Cheng, M., Yuen, A.: Student continuance of learning management system use: a longitudinal exploration. Comput. Educ. 120, 241–253 (2018)

    Article  Google Scholar 

  11. Guo, Z., Xiao, L., Toorn, C., Lai, Y., Seo, C.: Promoting online learners’ continuance intention: an integrated flow framework. Inf. Manage. 53, 279–295 (2015)

    Article  Google Scholar 

  12. Limayem, M., Cheung, C.: Predicting continued use of Internet-based learning technologies: the role of habit. Behav. Inf. Technol. 30, 91–99 (2011)

    Article  Google Scholar 

  13. Zhang, Y., Fang, Y., Wei, K., Wang, Z.: Promoting the intention of students to continue their participation in e-learning systems: the role of the communication environment. Inf. Technol. People 25, 356–375 (2012)

    Article  Google Scholar 

  14. Bourelle, A., Bourelle, T., Knutson, A., Spong, S.: Sites of multimodal literacy: comparing student learning in online and face-to-face environments. Comput. Compos. 39, 55–70 (2016)

    Article  Google Scholar 

  15. Yang, S., Zhou, S., Chen, X.: Why do college students continue to use mobile learning? Learning involvement and self-determination theory: College students mobile learning continuance. Br. J. Educ. Technol. 50(2), 626–637 (2018)

    Article  Google Scholar 

  16. Aljaraideh, Y., Al Bataineh, K.: Jordanian students’ barriers of utilizing online learning: a survey study. Int. Educ. Stud. 12, 99–108 (2019)

    Article  Google Scholar 

  17. Al Bataineh, K.B., Ahmed Banikalef, A.A., Albashtawi, A.H.: The effect of blended learning on EFL students’ grammar performance and attitudes: an investigation of Moodle. Arab World Engl. J. 10, 11 (2019)

    Google Scholar 

  18. Wu, B., Zhang, C.: Empirical study on continuance intentions towards e-learning 2.0 systems. Behav. Inf. Technol. 33, 1027–1038 (2014)

    Article  Google Scholar 

  19. Al-samarrie, H., Teng, B.K., Alzahrani, A.I., Alalwan, N.: E-learning continuance satisfaction in higher education: a unified perspective from instructors and students. Student High. Educ. 43, 2003–2019 (2017)

    Article  Google Scholar 

  20. Daghan, G., Akkoyunlu, B.: Modeling the continuance usage intention of online learning environments. Comput. Hum. Behav. 60, 198–211 (2016)

    Article  Google Scholar 

  21. Ji, Z., Yang, Z., Liu, J., Changrui, Y.: Investigating users’ continued usage intentions of online learning applications. Information 10(6), 198 (2019)

    Article  Google Scholar 

  22. Pereira, F., Ramos, A., Gouvea, M., Costa, M.: Satisfaction and continuous use intention of e-learning service in Brazilian public organizations . Comput. Hum. Behav. 46, 139–148 (2015)

    Article  Google Scholar 

  23. Lee, M.C.: Explaining and predicting users’ continuance intention toward e-learning: an extension of the expectation–confirmation model. Comput. Educ. 54, 506–516 (2010)

    Article  Google Scholar 

  24. Hung, M., Chang, I., Hwang, H.G.: Exploring academic teachers’ continuance toward the web-based learning system: the role of causal attributions. Comput. Educ. 57, 1530–1543 (2011)

    Article  Google Scholar 

  25. Tawafak, R., Romli, A., Arshah, R., Malik, S.: Framework design of university communication model (UCOM) to enhance continuous intentions in teaching and e-learning process. Educ. Inf. Technol. 25, 817–843 (2019)

    Article  Google Scholar 

  26. Liang, H.: Ensuring employees’ IT compliance: carrot or stick? Inf. Syst. Res. 24, 279 (2013)

    Article  Google Scholar 

  27. See, B.: Antecedents of continued use and extended use of enterprise systems. Behav. Inf. Technol. 38, 384–400 (2018)

    Article  Google Scholar 

  28. Zhou, T.: Understanding mobile IM continuance usage from the perspectives of network externality and switching costs. Int. J. Mob. Commun. 13(2), 188–203 (2015)

    Article  Google Scholar 

  29. Chang, C.-C.: Exploring the determinants of e-learning systems continuance intention in academic libraries. Libr. Manage. 34, 40–55 (2012)

    Article  Google Scholar 

  30. Tan, M., Shao, P.: An ECM-ISC based study on learners’ continuance intention toward e-learning. Int. J. Emerg. Technol. Learn. (iJET) 10(4), 22 (2015). https://doi.org/10.3991/ijet.v10i4.4543

    Article  Google Scholar 

  31. Capece, G., Campisi, D.: User satisfaction affecting the acceptance of an e-learning platform as a mean for the development of the human capital. Behav. Inf. Technol. 32, 335–343 (2013)

    Article  Google Scholar 

  32. Lewis, K., Cidon, M., Seto, T., Chen, H., Mahan, J.: Leveraging e-learning in medical education. Int. J. E-Learn. 13 (2014)

    Google Scholar 

  33. Choudhury, S., Pattnaik, S.: Emerging themes in e-learning: a review from the stakeholder perspective. Comput. Educ. 144 (2019)

    Google Scholar 

  34. Muresan, M., Gogu, E.: E-learning challenges and provisions. Soc. Behav. Sci. 92, 600–605 (2013)

    Article  Google Scholar 

  35. Guspatni: Students’ activities in perceptions of and expectations for e-learning: a case in Indonesia. Knowl. Manage. E-learn. 10, 97–112 (2018)

    Google Scholar 

  36. Tobing, R.D.H.: Designing e-learning system for assisting teachers’ profesionalism improvement in indonesia rurall areas. Jurnal Teknologi 78, 65–669 (2016)

    Google Scholar 

  37. Ramadiani, R., Azainil, A., Frisca, F., Hidayanto, A.N., Herkules, H.: An integrated model of e-learning continuance intention in Indonesia. Int. J. Innov. Learn. 26, 1–26 (2019)

    Article  Google Scholar 

  38. Sadikin, M., SK, P.: The implementation of e-learning system governance to deal with user need, institution objective, and regulation compliance. Telkomnika 16, 1332–1344 (2018)

    Article  Google Scholar 

  39. Syam, H.: Hybrid e-learning in industrial revolution 4.0 for Indonesia higher education. Int. J. Adv. Sci. Eng. Inf. Technol. 9, 1183–1189 (2019)

    Article  Google Scholar 

  40. Sfenrianto, S., Tantrisna, E., Akbar, H., Wahyudi, M.: E-learning effectiveness analysis in developing countries: East Nusa Tenggara, Indonesia perspective. Bull. Electr. Eng. Inf. 7, 417–424 (2018)

    Google Scholar 

  41. Rocha, K., Vasconcelos, S.: Compliance with national ethics requirements for human subject research in non biomedical sciences in Brazil: a changing culture? Sci. Eng. Ethics 25, 693–705 (2018)

    Article  Google Scholar 

  42. Sadiq, S., Governatori, G., Naimiri, K.: Modeling control objectives for business process compliance. In: 5th International Conference on Business Process Management, Brisbane (2007)

    Google Scholar 

  43. Abdullah, N.S., Indulska, M., Sadiq, S.: Compliance management ontology – a shared conceptualization for research and practice in compliance management. Inf. Syst. Front. 18(5), 995–1020 (2016)

    Article  Google Scholar 

  44. Kim, S., Kim, Y.: The effect of compliance knowledge and compliance support systems on information security compliance behaviour. J. Knowl. Manage. 21, 986–1010 (2017)

    Article  Google Scholar 

  45. Park, J.: The effects of personalization on user continuance in social networking sites. Inf. Process. Manage. 50, 462–475 (2014)

    Article  Google Scholar 

  46. Bakar-Eveleth, L., Stone, R.W.: Usability, expectation, confirmation, and continuance intentions to use electronic textbooks. Behav. Inf. Technol. 34, 992–1004 (2015)

    Article  Google Scholar 

  47. Basnet, R.B., Doleck, T., Lemay, D.J., Bazelais, P.: Exploring computer science students’ continuance intentions to use Kattis. Educ. Inf. Technol. 23(3), 1145–1158 (2017)

    Article  Google Scholar 

  48. Ifinedo, P.: Determinants of students’ continuance intention to use blogs to learn: an empirical investigation. Behav. Inf. Technol. 37, 381–392 (2018)

    Article  Google Scholar 

  49. Joo, S., Choi, N.: Understanding users’ continuance intention to use online library resources based on an extended expectation-confirmation model. Electron. Libr. 34, 554–571 (2016)

    Article  Google Scholar 

  50. Stone, R.W., Baker-Eveleth, L.: Students’ expectation, confirmation, and continuance intention to use electronic textbooks. Comput. Hum. Behav. 29, 984–990 (2013)

    Article  Google Scholar 

  51. Joo, Y.Z., Kim, N.H.: Factors predicting online university students’ use of a mobile learning management system (m-LMS). Educ. Tech. Res. Dev. 64, 611–630 (2016)

    Article  Google Scholar 

  52. Cheng, Y.: How does task-technology fit influence cloud-based e-learning continuance and impact? Educ. Training 61, 480–499 (2019)

    Article  Google Scholar 

  53. Daneji, A.A., Ayub, A.F., Khambari, M.N.: The effects of perceived usefulness, confirmation and satisfaction on continuance intention in using massive open online course (MOOC). Knowl. Manage. Learn. 11, 201–214 (2019)

    Google Scholar 

  54. Cheng, M., Yuen, A.H.K.: Cultural divides in acceptance and continuance of learning management system use: a longitudinal study of teenagers. Educ. Technol. Res. Develop. 67 (2019)

    Google Scholar 

  55. Lin, K.-M., Chen, N.-S., Fang, K.: Understanding e-learning continuance intention: a negative critical incidents perspective. Behav. Inf. Technol. 30, 77–89 (2011)

    Article  Google Scholar 

  56. Bakar, A.A.: Assessing the effects of UTAUT and self-determination predictor on students continuance intention to use student portal. World Appl. Sci. J. 21, 1484–1489 (2013)

    Google Scholar 

  57. Joo, Y.J., So, H.J., Kim, N.H.: Examination of relationships among students’ self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOC. Comput. Educ. 122, 260–272 (2018)

    Article  Google Scholar 

  58. Kuo, K.M.: Continuance compliance of privacy policy of electronic medical records: the roles of both motivation and habit. BMC Med. Inf. Decis. Making 18, 135 (2018)

    Article  Google Scholar 

  59. Cheng, S.: Continuance intention of e-portfolio system a confirmatory and multigroup invariance analysis of technology acceptance model. Comput. Stand. Interfaces 42, 17–23 (2015)

    Article  Google Scholar 

  60. Huang, Y.M.: The factors that predispose students to continuously use cloud services: Social and technological perspectives. Comput. Educ. 97, 86–96 (2016)

    Article  Google Scholar 

  61. Ifinedo, P.: Examining students’ intention to continue using blogs for learning: Perspectives from technology acceptance, motivational, and social-cognitive frameworks. Comput. Hum. Behav. 72, 189–199 (2017)

    Article  Google Scholar 

  62. Cho, V., Cheng, T., Lai, W.: The role of perceived user-interface design in continued usage intention of self-paced e-learning tools. Comput. Educ. 53, 216–227 (2009)

    Article  Google Scholar 

  63. Lin, T.-C., Chen, C.-J.: Validating the satisfaction and continuance intention of e-learning systems: combining TAM and IS success models. Int. J. Distance Educ. Technol. 10(1), 44–54 (2012)

    Article  MathSciNet  Google Scholar 

  64. Kubra, B.A.G.C.I., Celik, H.E.: Examination of factors affecting continuance intention to use web-based distance learning system via structural equation modelling. Eurasian J. Educ. Res. 18(78), 1–24 (2018)

    Article  Google Scholar 

  65. Wang, L.-Y.-K., Lew, S.-L., Lau, S.-H., Leow, M.-C.: Usability factors predicting continuance of intention to use cloud e-learning application. Heliyon 5(6), e01788 (2019)

    Article  Google Scholar 

  66. Xue, Y., Liang, H., Liansheng, W.: Punishment, justice, and compliance in mandatory IT settings. Inf. Syst. Res. 22(2), 400–414 (2011)

    Article  Google Scholar 

  67. Ifinedo, P.: Understanding information systems security policy compliance: an integration of the theory of planned behavior and the protection motivation theory. Comput. Secur. 31, 83–95 (2012)

    Article  Google Scholar 

  68. Tsang, N.: An evaluation of the effectiveness of travel advisories with a specific focus on Hong Kong’s outbound travel alert system. J. Vacat. Mark. 24, 307–323 (2018)

    Article  Google Scholar 

  69. Benk, S., Cakmak, A., Budak, T.: An investigation of tax compliance intention: a theory of planned behavior approach. Eur. J. Econ. Finance Adm. Sci. 28, 181–188 (2011)

    Google Scholar 

  70. Shen, Y.: Development and influencing factors of compliance behaviors of investigators in clinical trials. J. Huazhong Univ. Sci. Technol. 34, 284–288 (2014)

    Article  Google Scholar 

  71. Hofeditz, M., Nienaber, A.-M., Dysvik, A., Schewe, G.: “Want to” versus “have to”: intrinsic and extrinsic motivators as predictors of compliance behavior intention. Hum. Resour. Manage. 56(1), 25–49 (2015)

    Article  Google Scholar 

  72. Sommestad, T., Karlzen, H., Hallberg, J.: The theory of planned behavior and information security policy compliance. J. Comput. Inf. Syst. 59, 344–353 (2017)

    Google Scholar 

  73. Foth, M.: Factors influencing the intention to comply with data protection regulations in hospitals: based on gender differences in behaviour and deterrence. Eur. J. Inf. Syst. 25(2), 91–109 (2017)

    Article  Google Scholar 

  74. Rodríguez-Ardura, I., Meseguer-Artola, A.: What leads people to keep on e-learning? An empirical analysis of users’ experiences and their effects on continuance intention. Interact. Learn. Environ. 24, 1030–1053 (2016)

    Article  Google Scholar 

  75. Rodríguez-Ardura, I., Meseguer-Artola, A.: E-learning continuance: the impact of interactivity and the mediating role of imagery, presence and flow. Inf. Manage. 54, 504–516 (2016)

    Article  Google Scholar 

  76. Yoo, C., Sanders, G., Cerveny, R.: Exploring the influence of flow and psychological ownership on security education, training and awareness effectiveness and security compliance. Decis. Support Syst. 108, 107–118 (2018)

    Article  Google Scholar 

  77. Lin, K.-M., Cheng, N., Fang, K.: E-learning continuance intention: moderating effects of user e-learning experience. Comput. Educ. 56, 515–526 (2011)

    Article  Google Scholar 

  78. Bidin, Z., Idris, K., Shamsudin, F.: Predicting compliance intention on Zakah on employment income in Malaysia: an application of reasoned action theory. Jurnal Pengurusan 28, 85–102 (2009)

    Article  Google Scholar 

  79. Lin, X.: Investigating the impacts of organizational factors on employees’ unethical behavior within organization in the context of Chinese firms. J. Bus. Ethics 150, 779–7991 (2018)

    Article  Google Scholar 

  80. Lin, W.-S., Wang, C.: Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Comput. Educ. 58, 88–99 (2012)

    Article  Google Scholar 

  81. Herath, T., Rao, H.R.: Encouraging information security behaviors in organizations: role of penalties, pressures and perceived effectiveness. Decis. Support Syst. 47, 154–165 (2009)

    Article  Google Scholar 

  82. Porumbesu, G., Ceka, N.M.: Can transparency foster more understanding and compliant citizens? Public Adm. Rev. 77, 840–850 (2017)

    Article  Google Scholar 

  83. Chen, X., Wu, D., Chen, L., Teng, J.: Sanction severity and employees’ information security policy compliance: investigating mediating, moderating, and control variables. Inf. Manage. 55, 1049–1060 (2018)

    Article  Google Scholar 

  84. Cheng, L., Li, Y., Li, W., Holm, E., Zhai, Q.: Understanding the violation of IS security policy in organizations: an integrated model based on social control and deterrence theory. Comput. Secur. 39, 447–449 (2013)

    Article  Google Scholar 

  85. Choi, M., Song, J.: Social control through deterrence on the compliance with information security policy. Soft Comput. 22, 6765–6772 (2018)

    Article  Google Scholar 

  86. D’Archy, J., Herath, T.: A review and analysis of deterrence theory in the IS security literature: making sense of the disparate findings. Eur. J. Inf. Syst. 20, 643–658 (2011)

    Article  Google Scholar 

  87. Johnston, A., Warkentin, M., Siponen, M.: An enhanced fear appeal rhetorical framework: leveraging threats to the human asset through sanctioning rhetoric. MIS Q. Manage. Inf. Syst. 39, 113–134 (2015)

    Article  Google Scholar 

  88. Johsnton, A., Markentin, W.: Dispositional and situational factors: influences on information security policy violations. Eur. J. Inf. Syst. 25, 231–251 (2016)

    Article  Google Scholar 

  89. Kim, H.L.: Leader power and employees’ information security policy compliance. Secur. J. 32, 391–409 (2019)

    Article  Google Scholar 

  90. Kuo, K.M.: A deterrence approach to regulate nurses’ compliance with electronic medical records privacy policy. J. Med. Syst. 41, 198 (2017)

    Article  Google Scholar 

  91. Mwagwabi, F., Mcgill, T.: Short-term and long-term effects of fear appeals in improving compliance with password guidelines. Commun. Assoc. Inf. Syst. 42, 147 (2018)

    Google Scholar 

  92. Li, H., Sarathy, R., Zhang, J., Luo, X.: Exploring the effects of organizational justice, personal ethics and sanction on internet use policy compliance. Info Syst. J. 24, 479–502 (2014)

    Article  Google Scholar 

  93. Yang, C., Lee, H.: A study on the antecedents of healthcare information protection intention. Inf. Syst. Front. 18, 253–263 (2016)

    Article  Google Scholar 

  94. Son, J.: Out of fear or desire? Toward a better understanding of employees’ motivation to follow IS security policies. Inf. Manage. 48, 296–302 (2011)

    Article  Google Scholar 

  95. Chang, K., Seow, Y.M.: Protective measures and security policy non-compliance intention: IT vision conflict as a moderator. J. Organ. End User Comput. 31, 1–21 (2019)

    Article  Google Scholar 

  96. Hovav, A., Putri, F.F.: This is my device! Why should I follow your rules? Employees’ compliance with BYOD security policy. Pervasive Mob. Comput. 32, 35–49 (2016)

    Article  Google Scholar 

  97. Hwang, I., Kim, D., Kim, T., Kim, S.: Why not comply with information security? An empirical approach for the causes of non-compliance. Online Inf. Rev. 41(1), 2–18 (2017)

    Article  Google Scholar 

  98. Munoz, Y.: Using Fear Appeals in warning labels to promote responsible gambling among VLT players: the key role of depth of information processing. J. Gambl. Stud. 26, 2–18 (2010)

    Article  Google Scholar 

  99. Vance, A., Siponen, M., Pahnila, S.: Motivating IS security compliance: insights from habit and protection motivation theory. Inf. Manage. 49, 190–198 (2012)

    Article  Google Scholar 

  100. Wall, J., Warkentin, M.: Perceived argument quality’s effect on threat and coping appraisals in fear appeals: an experiment and exploration of realism check heuristics. Inf. Manage. 56, 103157 (2019)

    Article  Google Scholar 

  101. Sakib, M.N., Zolfagharian, M., Yazdanparastc, A.: Does parasocial interaction with weight loss vloggers affect compliance? The role of vlogger characteristics, consumer readiness, and health consciousness. J. Retail. Consum. Serv. 52, 101733 (2019)

    Article  Google Scholar 

  102. Sharma, S., Wakentin, M.: Do I really belong?: impact of employment status on information security policy compliance. Comput. Secur. 87, 101397 (2018)

    Article  Google Scholar 

  103. Lee, N., Kim, J., Kim, E., Kwon, O.: The influence of politeness behavior on user compliance with social robots in a healthcare service setting. Int. J. Soc. Robot. 9(5), 727–743 (2017)

    Article  Google Scholar 

  104. Merhi, M.I., Ahluwalia, P.: Examining the impact of deterrence factors and norms on resistance to Information Systems Security. Comput. Hum. Behav. 92, 37–46 (2019)

    Article  Google Scholar 

  105. Warkentin, M., Johnston, A.C., Shropshire, J.: The influence of the informal social learning environment on information privacy policy compliance efficacy and intention. Eur. J. Inf. Syst. 20(3), 267–284 (2011)

    Article  Google Scholar 

  106. Kitchenham, B.: Procedures for performing systematic reviews. Keele University, UK and National ICT Australia (2004)

    Google Scholar 

  107. Albashtawi, A.H., Al Bataineh, K.B.: The effectiveness of Google classroom among EFL students in Jordan: an innovative teaching and learning online platform. Int. J. Emerg. Technol. Learn. 15, 78–88 (2020)

    Article  Google Scholar 

  108. Al-Rahmi, A.M., Ramin, A.K., Alamri, M.M., Al-Rahmi, W.M., Yahaya, N., Abualrejal, H., Al-Maatouk, Q.: Evaluating the intended use of decision support system (DSS) via academic staff: an applying technology acceptance model (TAM). Int. J. Recent Technol. Eng 58, 1565–1575 (2019)

    Google Scholar 

  109. Alamri, M.M., Al-Rahmi, W.M., Yahaya, N., Al-Rahmi, A.M., Abualrejal, H., Zeki, A.M., Al-Maatouk, Q.: Towards adaptive e-learning among university students: by applying technology acceptance model (TAM). Int. J. Eng. Adv. Technol. 8, 270–279 (2019)

    Article  Google Scholar 

  110. Liao, H.L., Lu, H.P.: The role of experience and innovation characteristics in the adoption and continued use of e-learning websites. Comput. Educ. 51(4), 1405–1416 (2008)

    Article  MathSciNet  Google Scholar 

  111. Jimenez, P., Iyer, G.S.: Tax compliance in a social setting: The influence of social norms, trust in government, and perceived fairness on taxpayer compliance. Adv. Comput. 34, 17–26 (2016)

    Google Scholar 

  112. Herath, T., Rao, H.R.: Protection motivation and deterrence: a framework for security policy compliance in organisations. Eur. J. Inf. Syst. 18, 106–125 (2009)

    Article  Google Scholar 

  113. Bobek, D., Hageman, A., Kelliher, C.: Analyzing the role of social norms in tax compliance behavior. J. Bus. Ethics 115, 451–468 (2013)

    Article  Google Scholar 

  114. Johnston, A.C., Warkentin, M.: Information privacy compliance in the healthcare industry. Inf. Manage. Comput. Secur. 16, 5–19 (2008)

    Article  Google Scholar 

  115. Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. Manage. Inf. Syst. 13, 319 (1989)

    Article  Google Scholar 

  116. Bhattacherjee, A.: Understanding information systems continuance: an expectation-confirmation model. MIS Q. 25(3), 351 (2001)

    Article  Google Scholar 

  117. Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991)

    Article  Google Scholar 

  118. Bandura, A.: Social cognitive theory: an agentive perspective. Ann. Rev. Psychol. 52(1), 1–26 (2001)

    Article  MathSciNet  Google Scholar 

  119. H. C. Black, 6th ed. St. paul, MN, West Publishing (1990)

    Google Scholar 

  120. Karimi, S.: The impact of entrepreneurship education: a study of Iranian Students’ entrepreneurial intentions and opportunity identification. J. Small Bus. Manage. 54, 187–209 (2014)

    Article  Google Scholar 

  121. Swain, J.A.: Influences on student intention and behavior toward environmental sustainability. J. Bus. Ethics 124, 465–484 (2014)

    Article  Google Scholar 

  122. Potishuk, V., Kratzer, J.: Factors affecting entrepreneurial intentions and entrepreneurial attitudes in higher education. J. Entrepreneurship Educ. 20, 25–44 (2017)

    Google Scholar 

  123. Maresch, D., Harms, R., Kailer, N., Wimmer-Wurm, B.: The impact of entrepreneurship education on the entrepreneurial intention of students in science and engineering versus business studies university programs. Technol. Forecast. Soc. Change 104, 172–179 (2016)

    Article  Google Scholar 

  124. Ajayi, I.H., Ahmad, N.N., Fadhil, A.: A proposed conceptual model for flipped learning. J. Theor. Appl. Inf. Technol. 32, 527–541 (2017)

    Google Scholar 

  125. Ali, A.: Factors affecting Halal meatC purchase intention: evidence from international Muslim students in China. Brit. Food J. 119, 527–541 (2017)

    Article  Google Scholar 

  126. Hamidi, H., Chavoshi, A.: Analysis of the essential factors for the adoption of mobile learning in higher education: a case study of students of the University of Technology. Telematics Inform. 35, 1053–1070 (2018)

    Article  Google Scholar 

  127. Joo, Y.J., Park, S., Shin, E.K.: Students’ expectation, satisfaction, and continuance intention to use digital textbooks. Comput. Hum. Behav. 69, 83–90 (2017)

    Article  Google Scholar 

  128. Hew, K.F., Cheung, W.S.: Students’ and instructors’ use of massive open online courses (MOOCs): motivations and challenges. Educ. Res. Rev. 12, 45–58 (2014)

    Article  Google Scholar 

  129. Kang, M., Liew, B., Kim, J., Jung, H.: Learning presence as a predictor of achievement and satisfaction in online learning environments. Int. J. E-Learn. 13, 193–208 (2014)

    Google Scholar 

  130. Vershitskaya, E.R., Mikhaylova, A.V., Gilmanshina, S.I., Dorozhkin, E.M., Epaneshnikov, V.V.: Present-day management of universities in Russia: prospects and challenges of e-learning. Educ. Inf. Technol. 25(1), 611–621 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Azman Hashim International Business School, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Ken Ditha Tania, Norris Syed Abdullah & Norasnita Ahmad

  2. Faculty of Computer Science, Sriwijaya University, Palembang, Indonesia

    Ken Ditha Tania & Samsuryadi Sahmin

Authors
  1. Ken Ditha Tania
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Norris Syed Abdullah
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Norasnita Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Samsuryadi Sahmin
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia

    Faisal Saeed

  2. School of Computing, Information Systems Department, Universiti Utara Malaysia, Sintok, Malaysia

    Fathey Mohammed

  3. Sanaa’a Community College, Sana'a, Yemen

    Abdulaziz Al-Nahari

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tania, K.D., Abdullah, N.S., Ahmad, N., Sahmin, S. (2021). Student Compliance Intention Model for Continued Usage of E-Learning in University. In: Saeed, F., Mohammed, F., Al-Nahari, A. (eds) Innovative Systems for Intelligent Health Informatics. IRICT 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 72. Springer, Cham. https://doi.org/10.1007/978-3-030-70713-2_86

Download citation

Publish with us

Policies and ethics