skip to main content
research-article

Enhancing e-learning effectiveness: analyzing extrinsic and intrinsic factors influencing students’ use, learning, and performance in higher education

Published: 28 September 2023 Publication History

Abstract

As a result of the pandemic, but also of the rapid advancement of technology in general, e-learning has emerged as a popular method of education, providing students with flexibility and accessibility. Understanding the factors that influence students’ levels of learning and accomplishment in this digital learning environment is therefore critical for teachers and institutions seeking to increase the effectiveness of teaching and knowledge transfer via e-learning platforms. A number of variables that might improve or impair student use, learning, and performance affect how successful e-learning actually is. In order to maximize the benefits of e-learning and guarantee successful student results, educators and policymakers must have a thorough understanding of these elements. The purpose of this study is to investigate the impact of extrinsic and intrinsic factors on students’ use, learning level, and performance in the setting of e-learning in higher education in two countries. This study evaluates the impact of extrinsic elements such as course content, e-learning system quality, institutional and teacher support, as well as intrinsic aspects such as personal innovativeness, self-efficacy, and information sharing in two countries. The study takes a quantitative approach, and the analysis was carried out using the structural equations method to examine the combined influence of numerous extrinsic and intrinsic elements on the use of e-learning, as well as learning level and performance.The research results show that the course content and e-learning system, personal innovativeness, self-efficacy, and knowledge sharing have a positive influence on the intention to use e-learning. Also, the intention of using an e-learning system will increase the actual use of e-learning technologies, which will ultimately result in better learning performance. The findings of this study will help educators, policymakers, and e-learning platform developers create effective ways for optimizing student experiences and promoting good learning outcomes in higher education settings.

References

[1]
Afzal H, Ali I, Aslam Khan M, and Hamid K A study of University Students’ motivation and its relationship with their academic performance International Journal of Business and Management 2010 5 4 p80
[2]
Agarwal R and Prasad J A conceptual and operational definition of personal innovativeness in the domain of Information Technology Information Systems Research 1998 9 2 204-215
[3]
Ain N, Kaur K, and Waheed M The influence of learning value on learning management system use: An extension of UTAUT2 Information Development 2016 32 5 1306-1321
[4]
Ajzen I The theory of planned behavior Organizational Behavior and Human Decision Processes 1991 50 2 179-211
[5]
Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Prentice Hal.
[6]
Al-Adwan A and Smedley JK Implementing e-learning in the jordanian higher Education Systems: Factors affecting impact International Journal of Education and Development Using Information and Communication Technology 2012 8 1 121-135
[7]
Al-Adwan A, Al-Adwan A, and Smedley J Exploring students’ acceptance of e-learning using Technology Acceptance Model in jordanian universities International Journal of Education and Development Using ICT 2013 8 1 4-18
[8]
Al-Adwan AS, Nofal M, Akram H, Albelbisi NA, and Al-Okaily M Towards a sustainable adoption of E-Learning Systems: The role of Self-Directed Learning Journal of Information Technology Education: Research 2022 21 245-267
[9]
Al-Emran, M., & Mezhuyev, V. (2020). Examining the Effect of Knowledge Management Factors on Mobile Learning Adoption Through the Use of Importance-Performance Map Analysis (IPMA). In A. E. Hassanien, K. Shaalan, & M. F. Tolba (Eds.), Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019 (Vol. 1058, pp. 449–458). Springer International Publishing.
[10]
Al-Emran M and Teo T Do knowledge acquisition and knowledge sharing really affect e-learning adoption? An empirical study Education and Information Technologies 2020 25 3 1983-1998
[11]
Al-Emran, M., Abbasi, G. A., & Mezhuyev, V. (2021). Evaluating the Impact of Knowledge Management Factors on M-Learning Adoption: A Deep Learning-Based Hybrid SEM-ANN Approach. In M. Al-Emran & K. Shaalan (Eds.), Recent Advances in Technology Acceptance Models and Theories (Vol. 335, pp. 159–172). Springer International Publishing.
[12]
Al-Maroof RS, Alhumaid K, and Salloum S The continuous intention to use E-Learning, from two different perspectives Education Sciences 2020 11 1 6
[13]
AL-Nuaimi, M. N., Sawafi, O. S. A., Malik, S. I., Al-Emran, M., & Selim, Y. F. (2022). Evaluating the actual use of learning management systems during the covid-19 pandemic: An integrated theoretical model. Interactive Learning Environments, 1–26.
[14]
Al-Rahmi WM, Alias N, Othman MS, Alzahrani AI, Alfarraj O, Saged AA, and Rahman NSA Use of E-Learning by University students in malaysian higher Educational Institutions: A case in Universiti Teknologi Malaysia Ieee Access : Practical Innovations, Open Solutions 2018 6 14268-14276
[15]
Aldholay AH, Abdullah Z, Ramayah T, Isaac O, and Mutahar AM Online learning usage and performance among students within public universities in Yemen International Journal of Services and Standards 2018 12 2 163
[16]
Almaiah MA, Al-Khasawneh A, and Althunibat A Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic Education and Information Technologies 2020 25 6 5261-5280
[17]
Alqahtani, M. A., Alamri, M. M., Sayaf, A. M., & Al-Rahmi, W. M. (2022). Investigating students’ perceptions of Online Learning Use as a Digital Tool for Educational Sustainability during the COVID-19 pandemic. Frontiers in Psychology, 13.
[18]
Alqurashi E Self-Efficacy in Online Learning environments: A Literature Review Contemporary Issues in Education Research (CIER) 2016 9 1 45-52
[19]
Anderson JC and Gerbing DW Structural equation modeling in practice: A review and recommended two-step approach Psychological Bulletin 1988 103 3 411-423
[20]
Ansong-Gyimah K Students’ perceptions and continuous intention to Use E-Learning Systems: The case of Google Classroom International Journal of Emerging Technologies in Learning (IJET) 2020 15 11 236
[21]
Aparicio M, Bacao F, and Oliveira T Cultural impacts on e-learning systems’ success The Internet and Higher Education 2016 31 58-70
[22]
Artino AR Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training*: Predicting satisfaction with online training Journal of Computer Assisted Learning 2007 24 3 260-270
[23]
Babie, S., Cicin-Sain, M., & Bubas, G. (2016). A study of factors influencing higher education teachers’ intention to use E-learning in hybrid environments. 2016 39th International Convention on Information and Communication Technology Electronics and Microelectronics (MIPRO), 998–1003.
[24]
Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman.
[25]
Basri, W. S., Alandejani, J. A., & Almadani, F. M. (2018). ICT Adoption Impact on Students’ Academic Performance: Evidence from Saudi Universities. Education Research International, 2018, 1–9.
[26]
Bento, F., Costa, C. J., & Aparicio, M. (2017). S.I. success models, 25 years of evolution. 2017 12th Iberian Conference on Information Systems and Technologies (CISTI), 1–6.
[27]
Brown, L. V. (2007). Psychology of motivation. Nova Science Publishers.
[28]
Čevra B, Kapo A, Zaimović T, and Turulja L E-learning in Organizations: Factors affecting individual Job Performances International Journal of Emerging Technologies in Learning (IJET) 2022 17 02 189-208
[29]
Chen M, Wang X, Wang J, Zuo C, Tian J, and Cui Y Factors affecting College Students’ continuous intention to Use Online Course platform SN Computer Science 2021 2 2 114
[30]
Cheng YY, Tung WF, Yang MH, and Chiang CT Linking relationship equity to brand resonance in a social networking brand community Electronic Commerce Research and Applications 2019 35 July 2018 100849
[31]
Cheung R and Vogel D Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning Computers & Education 2013 63 160-175
[32]
Chiu CM, Chiu CS, and Chang HC Examining the integrated influence of fairness and quality on learners’ satisfaction and web-based learning continuance intention Information Systems Journal 2007 17 3 271-287
[33]
Cidral WA, Oliveira T, Felice MD, and Aparicio M E-learning success determinants: Brazilian empirical study Computers & Education 2018 122 273-290
[34]
Davis FD Perceived usefulness, perceived ease of use, and user acceptance of information technology MIS Quarterly 1989 13 3 319-339
[35]
DeLone WH and McLean ER Information Systems Success: The Quest for the Dependent Variable Information Systems Research 1992 3 1 60-95
[36]
DeLone WH and McLean ER The DeLone and McLean Model of Information Systems Success: A ten-year update Journal of Management Information Systems 2003 19 4 9-30
[37]
Elfaki N, Abdulraheem I, and Abdulrahim R Impact of E-learning VS traditional learning on students’ performance and attitude International Journal of Medical Research & Health Sciences 2019 8 10 76-82
[38]
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th Edition). Prentice Hall; 7 edition.
[39]
Harandi SR Effects of e-learning on students’ motivation Procedia - Social and Behavioral Sciences 2015 181 423-430
[40]
Hassanzadeh A, Kanaani F, and Elahi S A model for measuring e-learning systems success in universities Expert Systems with Applications 2012 39 12 10959-10966
[41]
Hew TS and Kadir SLSA Predicting the acceptance of cloud-based virtual learning environment: The roles of self determination and Channel Expansion Theory Telematics and Informatics 2016 33 4 990-1013
[42]
Ho NTT, Sivapalan S, Pham HH, Nguyen TM, Van Pham AT, and Dinh HV Students’ adoption of e-learning in emergency situation: The case of a vietnamese university during COVID-19 Interactive Technology and Smart Education 2020 17 4 1-24
[43]
Huang CH Exploring the continuous usage intention of Online Learning Platforms from the perspective of Social Capital Information 2021 12 4 141
[44]
Hurt, H. T., Joseph, K., & Cook, C. D. (2013). Individual Innovativeness (II) from Measurement Instrument Database for the Social Scienc. www.midss.ie.
[45]
Im T and Kang M Structural Relationships of factors which Impact on Learner Achievement in Online Learning Environment The International Review of Research in Open and Distributed Learning 2019 20 1 112-124
[46]
Islam AKMN Investigating e-learning system usage outcomes in the university context Computers & Education 2013 69 387-399
[47]
Islam AKMN E-learning system use and its outcomes: Moderating role of perceived compatibility Telematics and Informatics 2016 33 1 48-55
[48]
Jameel A, Hamzah AK, Shaikhli TA, and Alanssari AI System characteristics and behavioural intention to use E-Learning Turkish Journal of Computer and Mathematics Education (TURCOMAT) 2021 12 10 7724-7733
[49]
Jameel, A. S., Karem, M. A., & Ahmad, A. R. (2022). Behavioral Intention to Use E-Learning Among Academic Staff During COVID-19 Pandemic Based on UTAUT Model. In M. Al-Emran, M. A. Al-Sharafi, M. N. Al-Kabi, & K. Shaalan (Eds.), Proceedings of International Conference on Emerging Technologies and Intelligent Systems (Vol. 299, pp. 187–196). Springer International Publishing.
[50]
Jawad YALA and Shalash B The impact of E-Learning strategy on students’ academic achievement. Case Study: Al- Quds Open University International Journal of Higher Education 2020 9 6 44
[51]
Kew SN, Petsangsri S, Ratanaolarn T, and Tasir Z Examining the motivation level of students in e-learning in higher education institution in Thailand: A case study Education and Information Technologies 2018 23 6 2947-2967
[52]
Khechine H, Lakhal S, and Ndjambou P A meta-analysis of the UTAUT model: Eleven years later: A meta-analysis of the UTAUT model: Eleven years later Canadian Journal of Administrative Sciences / Revue Canadienne Des Sciences de l’Administration 2016 33 2 138-152
[53]
Kim, J., & Lee, K. H. (2017). Influence of integration on interactivity in social media luxury brand communities. Journal of Business Research October, 0–1.
[54]
Kim B and Park MJ Effect of personal factors to use ICTs on e-learning adoption: Comparison between learner and instructor in developing countries Information Technology for Development 2018 24 4 706-732
[55]
Koufaris M and Hampton-Sosa W The development of initial trust in an online company by new customers Information and Management 2004 41 3 377-397
[56]
Kurt ÖE Examining an e-learning system through the lens of the information systems success model: Empirical evidence from Italy Education and Information Technologies 2019 24 2 1173-1184
[57]
Kurtlu A and Uçar M A scale development study on the expectations of university students from the accounting course in the digitalization process Anali Ekonomskog Fakulteta u Subotici 2022 48 155-173
[58]
Lawson-Body A, Willoughby L, Lawson-Body L, and Tamandja EM Students’ acceptance of E-books: An application of UTAUT Journal of Computer Information Systems 2020 60 3 256-267
[59]
Lee JK and Lee WK The relationship of e-Learner’s self-regulatory efficacy and perception of e-Learning environmental quality Computers in Human Behavior 2008 24 1 32-47
[60]
Lehlohonolo, S. (2019). Exploring the Impact of Institutional Support on Students’ E-Learning Intentions: Moderating Effect of Age, Gender and Internet Access. ADVED 2019- 5th International Conference on Advances in Education and Social Sciences, 221–230. https://www.ocerints.org/adved19_e-publication/papers/256.pdf.
[61]
Lin HC and Chang CM What motivates health information exchange in social media? The roles of the social cognitive theory and perceived interactivity Information and Management 2018 55 6 771-780
[62]
Liu Y, Li H, and Carlsson C Factors driving the adoption of m-learning: An empirical study Computers & Education 2010 55 3 1211-1219
[63]
Lu J, Yao JE, and Yu CS Personal innovativeness, social influences and adoption of wireless internet services via mobile technology The Journal of Strategic Information Systems 2005 14 3 245-268
[64]
Masrom, M. (2007). Technology Acceptance Model and E-learning. 12th International Conference on Education, Sultan Hassanal Bolkiah Institute of Ed.
[65]
Mathieson K Predicting user intentions: Comparing the Technology Acceptance Model with the theory of Planned Behavior Information Systems Research 1991 2 3 173-191
[66]
Mohammadi H Investigating users’ perspectives on e-learning: An integration of TAM and IS success model Computers in Human Behavior 2015 45 359-374
[67]
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217–230.
[68]
Nguyen, H. T. H., Pham, H. V., Vu, N. H., & Hoang, H. T. (2020). Factors influencing students’ intention to use E-learning system: A case study conducted in Vietnam. International Journal of Emerging Technologies in Learning (IJET), 15(18), 165.
[69]
Osei HV, Kwateng KO, and Boateng KA Integration of personality trait, motivation and UTAUT 2 to understand e-learning adoption in the era of COVID-19 pandemic Education and Information Technologies 2022 27 8 10705-10730
[70]
Paola Torres Maldonado U, Feroz Khan G, Moon J, and Rho J E-learning motivation and educational portal acceptance in developing countries Online Information Review 2011 35 1 66-85
[71]
Petrov, V., Drašković, Z., Ćelić, Đ., & Rus, M. (2023). Determinants of learning outcomes with online teaching based on students’ perception. Strategic Management, online-first,.
[72]
Pham QT and Huynh MC Learning achievement and knowledge transfer: The impact factor of e-learning system at Bach Khoa University, Vietnam International Journal of Innovation 2018 6 3 194-206
[73]
Ratna PA and Mehra S Exploring the acceptance for e-learning using technology acceptance model among university students in India International Journal of Process Management and Benchmarking 2015 5 2 194
[74]
Rovai AP, Wighting MJ, Baker JD, and Grooms LD Development of an instrument to measure perceived cognitive, affective, and psychomotor learning in traditional and virtual classroom higher education settings The Internet and Higher Education 2009 12 1 7-13
[75]
Saadé RG, Nebebe F, and Tan W Viability of the Technology Acceptance Model in Multimedia Learning environments: A comparative study Interdisciplinary Journal of E-Skills and Lifelong Learning 2007 3 1 175-184
[76]
Salamat L, Ahmad G, Bakht M, and Saifi I Effects of e-learning on students’ academic learning at university level Asian Innovative Journal of Social Science & Humanities 2018 2 2 1-12
[77]
Salleh, S. M., Yusof, H. S. M., Mohammed, N. H., Zahari, A. S. M., & Hamzah, S. F. M. (2020). Knowledge Sharing in Online Community: A Review. Journal of Physics: Conference Series, 1529(2), 022052.
[78]
Salloum SA, Alhamad AQM, Al-Emran M, Monem AA, and Shaalan K Exploring students’ Acceptance of E-Learning through the development of a Comprehensive Technology Acceptance Model Ieee Access : Practical Innovations, Open Solutions 2019 7 128445-128462
[79]
Sekerdej M and Szwed P Perceived self-efficacy facilitates critical reflection on one’s own group Personality and Individual Differences 2021 168 110302
[80]
Selim HM Critical success factors for e-learning acceptance: Confirmatory factor models Computers & Education 2007 49 2 396-413
[81]
Seta, H. B., Wati, T., Muliawati, A., & Hidayanto, A. N. (2018). E-Learning Success Model: An Extention of DeLone & McLean IS’ Success Model. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 6(3).
[82]
Shadiev, R., Yu, J., & Sintawati, W. (2021). Exploring the impact of learning activities supported by 360-Degree Video Technology on Language Learning, intercultural communicative competence development, and knowledge sharing. Frontiers in Psychology, 12,.
[83]
Shih, M., Feng, J., & Tsai, C. C. (2008). Research and trends in the field of e-learning from 2001 to 2005: A content analysis of cognitive studies in selected journals. Computers & Education, 51(2), 955–967.
[84]
Shroff, R. H., Deneen, C. C., & Ng, E. M. W. (2011). Analysis of the technology acceptance model in examining students’ behavioural intention to use an e-portfolio system. Australasian Journal of Educational Technology, 27(4),.
[85]
Siron, Y., Wibowo, A., & Narmaditya, B. S. (2020). Factors affecting the adoption of e-learning in Indonesia: Lesson from Covid-19. Journal of Technology and Science Education, 10(2), 282.
[86]
Sukendro S, Habibi A, Khaeruddin K, Indrayana B, Syahruddin S, Makadada FA, and Hakim H Using an extended Technology Acceptance Model to understand students’ use of e-learning during Covid-19: Indonesian sport science education context Heliyon 2020 6 11 e05410
[87]
Sun PC, Tsai RJ, Finger G, Chen YY, and Yeh D What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction Computers & Education 2008 50 4 1183-1202
[88]
Tam, C., & Oliveira, T. (2016). Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective. Computers in Human Behavior, 61, 233–244.
[89]
Tarhini A, Hone K, and Liu X Measuring the moderating effect of gender and age on E-Learning Acceptance in England: A structural equation modeling Approach for an Extended Technology Acceptance Model Journal of Educational Computing Research 2014 51 2 163-184
[90]
Tawafak RM, Malik SI, Mathew R, Ashfaque MW, Jabbar J, AlNuaimi MN, ElDow A, and Alfarsi G A combined model for continuous intention to Use E-Learning System International Journal of Interactive Mobile Technologies (IJIM) 2021 15 03 113
[91]
Taylor NJ Public grid computing participation: An exploratory study of determinants Information & Management 2007 44 1 12-21
[92]
Tsai CL, Cho MH, Marra R, and Shen D The Self-Efficacy Questionnaire for Online Learning (SeQoL) Distance Education 2020 41 4 472-489
[93]
Turner M, Kitchenham B, Brereton P, Charters S, and Budgen D Does the technology acceptance model predict actual use? A systematic literature review Information and Software Technology 2010 52 5 463-479
[94]
Twum KK, Ofori D, Keney G, and Korang-Yeboah B Using the UTAUT, personal innovativeness and perceived financial cost to examine student’s intention to use E-learning Journal of Science and Technology Policy Management 2022 13 3 713-737
[95]
Urbach N, Smolnik S, and Riempp G An empirical investigation of employee portal success The Journal of Strategic Information Systems 2010 19 3 184-206
[96]
Vassilikopoulou A, Lepetsos A, and Siomkos G Crises through the consumer lens: The role of trust, blame and risk Journal of Consumer Marketing 2018 35 5 502-511
[97]
Venkatesh M and Davis User Acceptance of Information Technology: Toward a unified view MIS Quarterly 2003 27 3 425-478
[98]
Venkatesh T and Xu Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology MIS Quarterly 2012 36 1 157
[99]
Vladova G, Ullrich A, Bender B, and Gronau N Students’ Acceptance of Technology-Mediated teaching – how it was Influenced during the COVID-19 pandemic in 2020: A study from Germany Frontiers in Psychology 2021 12 636086
[100]
Wang YS, Wang HY, and Shee DY Measuring e-learning systems success in an organizational context: Scale development and validation Computers in Human Behavior 2007 23 4 1792-1808
[101]
Wang YS, Wu MC, and Wang HY Investigating the determinants and age and gender differences in the acceptance of mobile learning British Journal of Educational Technology 2009 40 1 92-118
[102]
Wang CH, Shannon DM, and Ross ME Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning Distance Education 2013 34 3 302-323
[103]
Wang H, Tlili A, Lehman JD, Lu H, and Huang R Investigating feedback implemented by instructors to support online competency-based learning (CBL): A multiple case study International Journal of Educational Technology in Higher Education 2021 18 1 5
[104]
Wen GKY, Ern ECJ, Khoo XQ, Sim C, Yap JJ, Teh SY, and A STUDY OF BEHAVIORAL INTENTION OF UNDERGRADUATES TOWARDS THE USAGE OF E- LEARNING SYSTEMS International Journal of Modern Education 2022 4 14 10-20
[105]
Yi MY and Hwang Y Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model International Journal of Human-Computer Studies 2003 59 4 431-449
[106]
Yuen, A. J. K., & Ma, W. W. K. (2004). Knowledge sharing and teacher acceptance of Web based learning system. In R. Atkinson, C. McBeath, D. Jonas-Dwyer, & R. Phillips, Beyond the Comfort Zone: Proceedings of the 21st ASCILITE Conference (pp. 975–983).
[107]
Zapata, L., De La Fuente, J., Martínez Vicente, J. M., González Torres, M. C., & Artuch, R. (2016). Relations between the personal self-regulation and learning approach, coping strategies, and self-regulation learning, in university students (PROCESS). International Journal of Developmental and Educational Psychology. Revista INFAD de Psicología, 4(1), 175.
[108]
Zhang, Z., Cao, T., Shu, J., & Liu, H. (2022). Identifying key factors affecting college students’ adoption of the e-learning system in mandatory blended learning environments. Interactive Learning Environments, 30(8), 1388–1401.
[109]
Zimmerman, B. J. (2000). Self-Efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82–91.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Education and Information Technologies
Education and Information Technologies  Volume 29, Issue 8
Jun 2024
1309 pages

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 28 September 2023
Accepted: 19 September 2023
Received: 04 July 2023

Author Tags

  1. E-learning
  2. Learning success
  3. Personal-innovativeness
  4. Self-efficacy
  5. Knowledge-sharing
  6. Learning performance

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 28 Dec 2024

Other Metrics

Citations

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media