Developing a general extended technology acceptance model for E-learning (GETAMEL) by analysing commonly used external factors

Abdullah, Fazil; Ward, Rupert

doi:10.1016/j.chb.2015.11.036

Cited by 986Technology Adoption and User BehaviourOnline and Blended LearningGender and Technology in Education

Developing a general extended technology acceptance model for E-learning (GETAMEL) by analysing commonly used external factors

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Abdullah, Fazil, Ward, Rupert·2016·Computers in Human Behavior

DOI 10.1016/j.chb.2015.11.036

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Earlier studies found that perceived enjoyment had a substantial impact on perceived ease of use and perceived usefulness for e-learning.
“Earlier studies, according to Abdullah and Ward [84,85], found that PE had a substantial impact on the PEOU and PU for e-learning.”
From Acceptance of e-learning in higher education: the role of task-technology fit with the information systems success model (2023) · cites this paper as [85]
Abdullah and Ward reported a substantial and positive relationship between perceived enjoyment and perceived ease of use for e-learning in eight out of eleven research studies.
“Moreover, Abdullah and Ward [85] reported a substantial and optimistic relationship between PE and PEOU for e-learning in eight out of eleven research studies.”
From Acceptance of e-learning in higher education: the role of task-technology fit with the information systems success model (2023) · cites this paper as [85]
Perceived enjoyment is essential in assessing the adoption of e-learning.
“Perceived enjoyment is essential in assessing the adoption of e-learning.”
From Acceptance of e-learning in higher education: the role of task-technology fit with the information systems success model (2023) · cites this paper as [85]
Abdullah and Ward reported a substantial and positive relationship between perceived enjoyment and perceived usefulness for e-learning in eight out of eight studies (100%).
“The same is true between PE and PU, as is evident from eight out of eight studies (100%).”
From Acceptance of e-learning in higher education: the role of task-technology fit with the information systems success model (2023) · cites this paper as [85]

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Factors affecting the intention to use Facebook to support problem-based learning among employees in a Taiwanese manufacturing company
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E-Learning acceptance in a developing country: A case of the Indonesian Open University
Hussein, R., Aditiawarman, U., & Mohamed, N. (2007) · MPG.PuRe (Max Planck Society) · Cited by 31 · see citing works
An empirical study of the key success factors to adopt e-learning in Thailand
Premchaiswadi, W., Porouhan, P., & Premchaiswadi, N. (2012) · International Conference on Information Society · Cited by 30 · see citing works
Integrating Technology Acceptance Model and Task-technology Fit into Blended E-learning System
Ma, C., Chao, C., & Cheng, B. (2013) · Journal of Applied Sciences · doi:10.3923/jas.2013.736.742 · Cited by 29 · see citing works
An Enhanced Technology Acceptance Model for E-Learning Systems in High-Tech Companies in Taiwan: Analyzed by Structural Equation Modeling
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8th World Conference on Mobile and Contextual Learning
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Gender influence in perception and adoption of e-learning platforms
Arenas-Gaitán, J., Cataluña, F. J. R., & Ramírez-Correa, P. (2010) · Deposito de Investigacion Universidad de Sevilla (University of Seville) · Cited by 24 · see citing works
The causal Model of effective factors on Intention to use of information technology among payam noor and Traditional universities students
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Factors affecting the adoption and diffusion of Internet in higher educational institutions in Kenya
Macharia, J. K. N., & Nyakwende, E. (2009) · Journal of Language Technology & Entrepreneurship in Africa · doi:10.4314/jolte.v1i2.41754 · Cited by 22 · see citing works
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Behavioral Intention for Mobile Learning on 3G Mobile Internet Technology in South-West Part of Nigeria
Fadare, O. G., Babatunde, O. H., Theophilus, D., & Lawal, O. O. (2011) · Cited by 18 · see citing works
Investigating the Antecedents of University Students’ Behavioral Intention to Use iPad for Learning
Wu, C.-P. (2013) · International Journal of e-Education e-Business e-Management and e-Learning · doi:10.7763/ijeeee.2013.v3.280 · Cited by 18 · see citing works
An Empirical Study of Learning Object Acceptance in Multimedia Learning Environment
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Factors Affecting the Usefulness of Social Networking ine-Learning at German University of Technology in Oman
Martin, R. (2012) · International Journal of e-Education e-Business e-Management and e-Learning · doi:10.7763/ijeeee.2012.v2.171 · Cited by 17 · see citing works
Extending the Technology Acceptance Model for E-learning: A Case Study of Iran
Moghadam, A. H., & Bairamzadeh, S. (2009) · International Conference on Information Technology: New Generations · doi:10.1109/itng.2009.152 · Cited by 17 · see citing works
Employee Behavior Towards Adoption of E-learning Courses: Validating Technology Acceptance Model
Shah, S. A., Iqbal, N., Janjua, S. Y., & Amjad, S. (2013) · Mediterranean Journal of Social Sciences · doi:10.5901/mjss.2013.v4n14p765 · Cited by 16 · see citing works
Determinant of Mobile Devices Acceptance for Learning among Students in Developing Country
Shittu, T. A., Basha, M. K., Michael, F. O., & Mukthar, A. L. (2013) · Malaysian Online Journal of Educational Technology · doi:10.52380/mojet.2013.1.3.18 · Cited by 15 · see citing works
The Impact of Internal Locus of Control on Perceived Usefulness and Perceived Ease of Use in E-Learning: An Extension of the Technology Acceptance Model
Tseng, A.-H., & Hsia, J.-W. (2008) · International Conference on Cyberworlds (CW) · doi:10.1109/cw.2008.109 · Cited by 15 · see citing works
Computer Assisted Language Learning (CALL)
Rahimpour, M. (2011) · International journal of instructional technology and distance learning · Cited by 15 · see citing works
Open source e-learning anxiety, self-efficacy and acceptance - A partial least square approach
Mohamed, N., & Karim, N. S. A. (2012) · International Journal of Mathematics and Computers in Simulation · Cited by 14 · see citing works
Second Life (SL) in Education: The Intensions to Use at University of Bahrain
Ali, H., Ahmed, A. A., Tariq, T. G., & Safdar, H. (2013) · International Conference on e-Learning (econf) · doi:10.1109/econf.2013.81 · Cited by 14 · see citing works
Gender differences in acceptance by students of training software for office tools
Lefievre, V. (2012) · HAL · Cited by 12 · see citing works
E-Learning Systems Adoption across Cultures: A Comparison Study
Zhao, J., & Tan, W. (2010) · International Conference on E-Product E-Service and E-Entertainment · doi:10.1109/iceee.2010.5661033 · Cited by 12 · see citing works
The acceptance of microblogging in the learning process: The µBAM model
Rejón‐Guardia, F., Sánchez‐Fernández, J., & Muñoz‐Leiva, F. (2013) · Journal of Technology and Science Education · doi:10.3926/jotse.65 · Cited by 12 · see citing works
A behavioral approach to modeling Indian children's ability of adopting to e-learning environment
Deshpande, Y. D., Bhattacharya, S., & Yammiyavar, P. G. (2012) · doi:10.1109/ihci.2012.6481776 · Cited by 11 · see citing works
Factors Influencing The Use of E-Class
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German e-Science Conference 2007
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2013 Fourth International Conference on e-Learning "Best Practices in Management, Design and Development of e-Courses: Standards of Excellence and Creativity"
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Student engagement with an ePortfolio : a case study of pre-service education students
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Does Self-Efficacy Effect on Knowledge Sharing Intention in E-Learning System ? : A Motivational Factor Analysis in Open University Malaysia OUM
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Communication Technologies and Virtual Learning Environment (VLE) in Teaching Literature
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Analyzing trends in technology acceptance studies in education domain
Imtiaz, M. A., & Mirhashemi, M. T. (2013) · International Conference on Current Trends in Information Technology (CTIT) · doi:10.1109/ctit.2013.6749472 · Cited by 6 · see citing works
2013 International Conference on Current Trends in Information Technology (CTIT)
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Applying the Technology Acceptance Model to Investigate Consumers’ Acceptance of Digital Learning System
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Factors Influencing Intention to Use and Application of Web-Based Learning among Students of Shiraz Payame Noor University (Providing a Path Analysis Model)
Seif, M. H., Rastegar, A., Javad, S. M. S., Ardakani, H., & Saeedikiya, M. (2013) · Cited by 1 · see citing works

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Sorted by citations

The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education
Scherer, R., Siddiq, F., & Tondeur, J. (2019) · Computers & Education · doi:10.1016/j.compedu.2018.09.009 · Cited by 1,923 · see citing works
“The selection of external variables comprised subjective norms, computer self-e ﬃ cacy, and facilitating conditions — three of the most prominent predictors of PEU and PU (Abdullah & Ward, 2016; Baydas & Goktas, 2017).”
BackgroundMethodResultInfluential
Evaluating E-learning systems success: An empirical study
Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2019.08.004 · Cited by 1,350 · see citing works
“Based on the literature study conducted by Abdullah and Ward (2016), the five most used external factors by researchers and confirmed to have a relationship with TAM in the context of e-learning are self-efficacy, subjective norm, enjoyment, computer anxiety, and prior experience. According to the review study conduct…”
BackgroundMethodInfluential
College students’ use and acceptance of emergency online learning due to COVID-19
Patricia Aguilera-Hermida, A. (2020) · International Journal of Educational Research Open · doi:10.1016/j.ijedro.2020.100011 · Cited by 1,286 · see citing works
“The ﬁndings from this study conﬁrm previous literature saying that students who are conﬁdent in applying a variety of self-regulated strategies are more likely to accomplish their academic tasks ( Abdullah & Ward, 2016 ; Alghamdi et al., 2020 ).”
Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic
Almaiah, M. A., Al-Khasawneh, A. M., & Althunibat, A. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10219-y · Cited by 1,210 · see citing works
“Abdullah and Ward (2016) also investigated factors influencing e-learning acceptance using TAM.”
Background
Technology acceptance model in educational context: A systematic literature review
Granić, A., & Marangunić, N. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12864 · Cited by 1,204 · see citing works
Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model
Wu, B., & Chen, X. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.10.028 · Cited by 1,178 · see citing works
Information technology and Gen Z: The role of teachers, the internet, and technology in the education of young people
Szymkowiak, A., Melović, B., Dabić, M., Jeganathan, K., & Kundi, G. S. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101565 · Cited by 895 · see citing works
Investigating the influence of the most commonly used external variables of TAM on students’ Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios
Abdullah, F., Ward, R., & Ahmed, E. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.05.014 · Cited by 693 · see citing works
“Based on extensive literature review on extended TAM in the context of e-learning, and in accordance with the GETAMEL developed by Abdullah and Ward (2016) (shown in figure 2), this study proposed the following research hypotheses: Hypothesis 1: SE positively affects students' PEOU of the…”
BackgroundMethodInfluentialSelf-citation
Extending the technology acceptance model (TAM) to predict university students’ intentions to use metaverse-based learning platforms
Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11816-3 · Cited by 637 · see citing works
“The importance of SE as a key determinant of PU and PEU in the educational field is well-established in the literature of technology adoption (Chahal & Rani, 2022; Abdullah et al., 2016 ).”
Background
Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach
Liébana-Cabanillas, F. J., Marinković, V., de Luna, I. R., & Kalinić, Z. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2017.12.015 · Cited by 554 · see citing works
Developing a general extended UTAUT model for M-payment adoption
Al-Saedi, K., Al‐Emran, M., Ramayah, T., & Abusham, E. E. A. A. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101293 · Cited by 592 · see citing works
Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model
Salloum, S. A., Qasim Mohammad Alhamad, A., Al-Emran, M., Abdel Monem, A., & Shaalan, K. (2019) · IEEE Access · doi:10.1109/access.2019.2939467 · Cited by 651 · see citing works
“Although Abdullah and Ward [24] achieved significant results by determining the most frequent factors affecting the e-learning adoption (i.”
BackgroundMethodInfluential
Examining the students’ behavioral intention to use e-learning in Azerbaijan? The General Extended Technology Acceptance Model for E-learning approach
Chang, C., Hajiyev, J., & Su, C.-R. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.04.010 · Cited by 479 · see citing works
The adoption of virtual reality devices: the technology acceptance model integrating enjoyment, social interaction, and strength of the social ties
Lee, J., Kim, J., & Choi, J. Y. (2019) · Telematics and Informatics · doi:10.1016/j.tele.2018.12.006 · Cited by 382 · see citing works
Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model
Mailizar, M., Burg, D., & Maulina, S. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10557-5 · Cited by 420 · see citing works
“The prior studies found that experience positively impacted users’ perceived ease of use toward e-learning usage (Abdullah & Ward, 2016; Armenteros et al., 2013; Chang et al., 2017; De Smet et al., 2012; Lee et al., 2011; Tarhini et al., 2015).”
BackgroundInfluential
Educational Technology Adoption: A systematic review
Granić, A. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10951-7 · Cited by 455 · see citing works
“…& Devedžić, 2021 ; Granić & Marangunić, 2019; Kemp, Palmer & Strelan, 2019; Scherer et al., 2019; Al-Emran, Mezhuyev & Kam-aludin, 2018; Abdullah & Ward,2016), while just few publications addressed other acceptance models and theories, in particular Unified Theory of Acceptance and Use…”
Background
Applying the UTAUT Model to Explain the Students’ Acceptance of Mobile Learning System in Higher Education
Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W. (2019) · IEEE Access · doi:10.1109/access.2019.2957206 · Cited by 349 · see citing works
Determinants of E-government Adoption: Testing the Mediating Effects of Perceived Usefulness and Perceived Ease of Use
Chen, L., & Aklikokou, A. K. (2019) · International Journal of Public Administration · doi:10.1080/01900692.2019.1660989 · Cited by 367 · see citing works
“Other studies have also confirmed the significant effect of perceived ease of use on perceived usefulness (Abdullah & Ward, 2016; Alalwan et al., 2017; Baabdullah et al., 2016; Calisir & Calisir, 2004; Gefen & Straub, 2000; Susanto & Aljoza, 2015; Tobbin, 2010).”
BackgroundInfluential
Students’ Acceptance of the COVID-19 Impact on Shifting Higher Education to Distance Learning in Poland
Rizun, M., & Strzelecki, A. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17186468 · Cited by 318 · see citing works
“Following the GETAMEL [38], Enjoyment (ENJ) is understood as the extent to which the activity of applying any system is perceived to be enjoyable, regardless of the consequences of this system’s usage.”
BackgroundMethodInfluential
Can teachers’ digital competence influence technology acceptance in vocational education?
Antonietti, C., Cattáneo, A., & Amenduni, F. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107266 · Cited by 467 · see citing works
Adoption of O2O food delivery services in South Korea: The moderating role of moral obligation in meal preparation
Roh, M., & Park, K. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2018.09.017 · Cited by 303 · see citing works
My Teacher Is a Machine: Understanding Students’ Perceptions of AI Teaching Assistants in Online Education
Kim, J., Merrill, K., Xu, K., & Sellnow, D. D. (2020) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2020.1801227 · Cited by 288 · see citing works
“Additionally, Abdullah and Ward (2016) completed a meta-analysis using the TAM to better understand the adoption of e-learning, or tools that utilize online technologies for instructional purposes.”
BackgroundMethodResultInfluential
The role of cognitive and affective responses in the relationship between internal and external stimuli on online impulse buying behavior
Kimiagari, S., & Malafe, N. S. A. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102567 · Cited by 329 · see citing works
Technology-enhanced learning in higher education: A bibliometric analysis with latent semantic approach
Shen, C.-W., & Ho, J.-T. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.106177 · Cited by 286 · see citing works
The acceptance and use of interactive whiteboards among teachers: Differences in UTAUT determinants between pre- and post-adopters
Šumak, B., & Šorgo, A. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.07.037 · Cited by 295 · see citing works
The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults
Güner, H., & Acartürk, C. (2018) · Universal Access in the Information Society · doi:10.1007/s10209-018-0642-4 · Cited by 291 · see citing works
“However, external factors that influence perceived usefulness and perceived ease of use may change, such as social influence, anxiety, facilitating conditions, self-satis-faction, self-efficacy, cost tolerance, perceived enjoyment, experience and so on [1].”
Background
Technology anxiety and resistance to change behavioral study of a wearable cardiac warming system using an extended TAM for older adults
Tsai, T.-H., Lin, W., Chang, Y., Chang, P., & Lee, M. (2020) · PLoS ONE · doi:10.1371/journal.pone.0227270 · Cited by 282 · see citing works
“However, it is also important to understand how external variables affect the PEOU and PU [26].”
Background
Using virtual reality for dynamic learning: an extended technology acceptance model
Fussell, S., & Truong, D. (2021) · Virtual Reality · doi:10.1007/s10055-021-00554-x · Cited by 228 · see citing works
“PENJ is another relatively new construct incorporated by Abdullah and Ward (2016) in the General Extended Technology Acceptance Model for E-Learning (GETAMEL).”
BackgroundInfluential
Continuance Intentions to Use Gamification for Training in Higher Education: Integrating the Technology Acceptance Model (TAM), Social Motivation, and Task Technology Fit (TTF)
Vanduhe, V. Z., Nat, M. C., & Hasan, H. F. (2020) · IEEE Access · doi:10.1109/access.2020.2966179 · Cited by 281 · see citing works
“In addition, the easier it is to use the gamified training platform, the greater the user’s intentions to use gamification for training [43].”
Background
Acceptance and resistance of telehealth: The perspective of dual-factor concepts in technology adoption
Tsai, J.-M., Cheng, M.-J., Tsai, H.-H., Hung, S.-W., & Chen, Y.-L. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.03.003 · Cited by 257 · see citing works
Motivation and Continuance Intention towards Online Instruction among Teachers during the COVID-19 Pandemic: The Mediating Effect of Burnout and Technostress
Pânişoară, I. O., Lazăr, I., Pânişoară, G., Chirca, R., & Ursu, A. S. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17218002 · Cited by 268 · see citing works
“Self-Determination Theory (SDT) involves self-efficacy, a similar concept to perceived competence [32] and one of the most used predictors of motivational models for e-learning [33].”
Background
COVID-19 and Higher Education: First-Year Students’ Expectations toward Distance Learning
Cicha, K., Rizun, M., Rutecka, P., & Strzelecki, A. (2021) · Sustainability · doi:10.3390/su13041889 · Cited by 243 · see citing works
“To ﬁll this gap, Abdullah and Ward [47] developed the GETAMEL (General Extended Technology Acceptance Model for E-Learning), where they elaborated on the external factors and distinguished the following indicators: Experience, Subjective Norms, Enjoyment, Computer Anxiety, and Self-Efﬁcacy.”
BackgroundMethodResultInfluential
The adequacy of UTAUT-3 in interpreting academician’s adoption to e-Learning in higher education environments
Gunasinghe, A., Hamid, J. A., Khatibi, A., & Azam, S. M. F. (2019) · Interactive Technology and Smart Education · doi:10.1108/itse-05-2019-0020 · Cited by 233 · see citing works
Evaluation of Online Video Usage and Learning Satisfaction: An Extension of the Technology Acceptance Model
Nagy, J. T. (2018) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v19i1.2886 · Cited by 244 · see citing works
Exploring the role of intrinsic motivation in ChatGPT adoption to support active learning: An extension of the technology acceptance model
Lai, C. Y., Cheung, K. Y., & Chan, C. S. (2023) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2023.100178 · Cited by 280 · see citing works
A Technology Acceptance Model Survey of the Metaverse Prospects
Aburbeian, A. M., Owda, A. Y., & Owda, M. (2022) · Applied Informatics · doi:10.3390/ai3020018 · Cited by 216 · see citing works
A taxonomy of factors affecting attitudes towards educational technologies for use with technology acceptance models
Kemp, A., Palmer, E., & Strelan, P. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12833 · Cited by 243 · see citing works
Online learning satisfaction in higher education during the COVID-19 pandemic: A regional comparison between Eastern and Western Chinese universities
Jiang, H., Islam, A. Y. M. A., Gu, X., & Spector, J. M. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10519-x · Cited by 212 · see citing works
Predicting student satisfaction of emergency remote learning in higher education during COVID-19 using machine learning techniques
Ho, I. M. K., Cheong, K. Y., & Weldon, A. (2021) · PLoS ONE · doi:10.1371/journal.pone.0249423 · Cited by 231 · see citing works
“Apart from the aforementioned models, other technology acceptance and Elearning quality models have been developed with an emphasis on usefulness and ease of use [8, 35].”
Background
Cultural impacts on e-learning systems' success
Aparício, M., Bação, F., & Oliveira, T. (2016) · The Internet and Higher Education · doi:10.1016/j.iheduc.2016.06.003 · Cited by 192 · see citing works
“Education and e-learning have been the subject of several studies, e.g., modeling e-learning systems’ adoption (Abdullah & Ward, 2016; Chen & Liu, 2013; Tarhini, Hone, Liu, & Tarhini, 2016), satisfaction (Aggelidis & Chatzoglou, 2012; Kassim, Jailani, Hairuddin, & Zamzuri, 2012), and success (Wang,…”
Virtual reality technology in construction safety training: Extended technology acceptance model
Zhang, M., Shu, L., Luo, X., Yuan, M.-Q., & Zheng, X.-Z. (2022) · Automation in Construction · doi:10.1016/j.autcon.2021.104113 · Cited by 169 · see citing works
An investigation of the influence of intrinsic motivation on students’ intention to use mobile devices in language learning
Sun, Y., & Gao, F. (2019) · Educational Technology Research and Development · doi:10.1007/s11423-019-09733-9 · Cited by 200 · see citing works
An expectancy value theory (EVT) based instrument for measuring student perceptions of generative AI
Chan, C. K. Y., & Zhou, W. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00284-4 · Cited by 192 · see citing works
“TAM posits that the perceived usefulness (PU) and perceived ease of use (PEOU) of a technology are key determinants of its acceptance and use (Abdullah & Ward, 2016; Davis, 1989).”
Acceptance of e-learning in higher education: the role of task-technology fit with the information systems success model
Alyoussef, I. Y. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e13751 · Cited by 181 · see citing works
“Earlier studies, according to Abdullah and Ward [84,85], found that PE had a substantial impact on the PEOU and PU for e-learning.”
BackgroundResultInfluential
Examination of students' acceptance of and intention to use learning management systems using extended TAM
YALÇIN, M. E., & Kutlu, B. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12798 · Cited by 189 · see citing works
Technology acceptance of four digital learning technologies (classroom response system, classroom chat, e-lectures, and mobile virtual reality) after three months’ usage
Sprenger, D. A., & Schwaninger, A. (2021) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-021-00243-4 · Cited by 205 · see citing works
The Influence of Values on E-learning Adoption
Mehta, A., Morris, N. P., Swinnerton, B. J., & Homer, M. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.103617 · Cited by 190 · see citing works
Do knowledge acquisition and knowledge sharing really affect e-learning adoption? An empirical study
Al‐Emran, M., & Teo, T. P. (2019) · Education and Information Technologies · doi:10.1007/s10639-019-10062-w · Cited by 185 · see citing works
“Under these conditions, e-learning scholars anticipated that more studies have to be carried out to understand the determinants that affect e-learning adoption (Abdullah and Ward 2016; Salloum et al. 2019).”
Background
Learning management systems and technology acceptance models: A systematic review
Al-Nuaimi, M. N., & Al‐Emran, M. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10513-3 · Cited by 169 · see citing works
“These results are consistent partially with the results of previous meta-analyses conducted with the aim of discovering the most common external factors used to extend TAM in studies that examine e-learning adoption (Abdullah et al., 2016; Abdullah & Ward, 2016).”
BackgroundResult
Understanding secondary students’ continuance intention to adopt AI-powered intelligent tutoring system for English learning
Ni, A., & Cheung, A. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-11305-z · Cited by 169 · see citing works
“Previous research has indicated that self-efficacy is an important antecedent of perceived usefulness and perceived ease of use, affecting individuals’ technology adoption behavior (Abdullah et al., 2016; Altalhi, 2021).”
BackgroundMethodResultInfluential
The role of technology readiness in individuals' intention to use health and fitness applications: a comparison between users and non-users
Chiu, W., & Cho, H. (2020) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-09-2019-0534 · Cited by 172 · see citing works
An LLM-Driven Chatbot in Higher Education for Databases and Information Systems
Neumann, A. T., Yin, Y., Sowe, S. K., Decker, S., & Jarke, M. (2024) · IEEE Transactions on Education · doi:10.1109/te.2024.3467912 · Cited by 187 · see citing works
“Factors, such as SE, subjective norm, enjoyment, computer anxiety, and experience often shape students’ PEOU, and PU, particularly in e-learning contexts [80].”
Investigating pre-service teachers’ acceptance of Web 2.0 technologies in their future teaching: a Chinese perspective
Teo, T. P., Sang, G., Mei, B., & Hoi, C. K. W. (2018) · Interactive Learning Environments · doi:10.1080/10494820.2018.1489290 · Cited by 184 · see citing works
“To date, a wide range of factors have been reported in empirical research conducted under the framework of technology acceptance (Abdullah & Ward, 2016).”
Background
Examining Teachers’ Behavioral Intention to Use E-learning in Teaching of Mathematics: An Extended TAM Model
Mailizar, M., Almanthari, A., & Maulina, S. (2021) · Contemporary Educational Technology · doi:10.30935/cedtech/9709 · Cited by 160 · see citing works
“Abdullah and Ward (2016) conducted a meta-analysis study and found that subjective norm, experience, perceived enjoyment, computer anxiety and self-efficacy were the most commonly used external factors for TAM.”
Background
To use or not to use? Understanding doctoral students’ acceptance of ChatGPT in writing through technology acceptance model
Zou, M., & Huang, L. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1259531 · Cited by 195 · see citing works
Extended Technology Acceptance Model to Predict Mobile-Based Money Acceptance and Sustainability: A Multi-Analytical Structural Equation Modeling and Neural Network Approach
Gbongli, K., Xu, Y., & Amedjonekou, K. M. (2019) · Sustainability · doi:10.3390/su11133639 · Cited by 155 · see citing works
“TAM has also been applied and empirically supported in the prediction of the adoption of E-commerce [46], mobile marketing [54], mobile wallets [55], e-learning [56]; mobile banking [57], Big Data [58], business-related technologies [59] and much other information.”
Method
Information and Communications Technology Used in Higher Education: An Empirical Study on Digital Learning as Sustainability
Sayaf, A. M., Alamri, M. M., Alqahtani, M. A., & Al-Rahmi, W. M. (2021) · Sustainability · doi:10.3390/su13137074 · Cited by 169 · see citing works
“CA is a phenomenon that has been widely researched since the start of the Digital Revolution in the 1980s and is still important today [50,51].”
Background
Impact of information and communication technology in Nigerian small-to medium-sized enterprises
Okundaye, K., Fan, S. K., & Dwyer, R. J. (2019) · Journal of Economics Finance and Administrative Science · doi:10.1108/jefas-08-2018-0086 · Cited by 145 · see citing works
Modeling the intention to use machine translation for student translators: An extension of Technology Acceptance Model
Yang, Y., & Wang, X. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.01.015 · Cited by 156 · see citing works
Commonly Used External TAM Variables in e-Learning, Agriculture and Virtual Reality Applications
Jiménez, I. A. C., García, L. C. C., Violante, M. G., Marcolin, F., & Vezzetti, E. (2020) · Future Internet · doi:10.3390/fi13010007 · Cited by 166 · see citing works
“It is a common interest among academics who develop TAM extensions, to comprehend the relationships existing between external variables and TAM’s two main determinants PU and PEOU [6].”
BackgroundMethodInfluential
Using Mobile Food Delivery Applications during COVID-19 Pandemic: An Extended Model of Planned Behavior
Amin, M. A., Arefin, M. S., Alam, M. R., Ahammad, T., & Hoque, M. R. (2021) · Journal of Food Products Marketing · doi:10.1080/10454446.2021.1906817 · Cited by 159 · see citing works
“Subjective norms, behavioral intention, and continuance behavior Subjective norms (SN) refer to the extent to which people feel pressure from others (family, friends, and colleagues) of their community who are important to them to act in a certain way (Abdullah & Ward, 2016; Ham et al., 2015).”
Background
Impact of Government Capacity and E-Government Performance on the Adoption of E-Government Services
Mensah, I. K. (2019) · International Journal of Public Administration · doi:10.1080/01900692.2019.1628059 · Cited by 140 · see citing works
“…model in fields such as e-government (Alryalat, 2017; Dahi & Ezziane, 2015; Ma & Zheng, 2018; Mensah, Vera, & Mi, 2018; Sebetci, 2015), e-learning (Abdullah & Ward, 2016; Gamble, 2018; Mohammadi, 2015), e-health (Chauhan & Jaiswal, 2017; de Veer et al., 2015; Hoque, Bao, & Sorwar, 2017; Hossain,…”
The effect of blended learning on the achievement of ninth grade students in science and their attitudes towards its use
Alsalhi, N. R., Eltahir, M. E., & Al-Qatawneh, S. S. (2019) · Heliyon · doi:10.1016/j.heliyon.2019.e02424 · Cited by 140 · see citing works
“In the late 1990s, such educational courses came to be hosted on internal networks, and after that they were put on learning management systems (LMSs) in the late 1990s (Abdullah and Ward, 2016; Hubackova, 2015).”
Background
Understanding Student Acceptance of Online Learning Systems in Higher Education: Application of Social Psychology Theories with Consideration of User Innovativeness
Kim, E.-J., Kim, J. J., & Han, S.-H. (2021) · Sustainability · doi:10.3390/su13020896 · Cited by 165 · see citing works
“Yu and Yu [42] developed a theoretical framework based on TPB to investigate factors inducing student online learning utilization.”
Background
Comparison of students’ use and acceptance of emergency online learning due to COVID-19 in the USA, Mexico, Peru, and Turkey
Aguilera-Hermida, A. P., Quiroga-Garza, A., Gómez-Mendoza, S., Villanueva, C. A. D. R., Avolio, B., & Avcı, D. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10473-8 · Cited by 148 · see citing works
“The more experience users have, the easier the use of technology will be (Abdullah and Ward 2016; Davis 1989; Maldonado et al. 2009; Thongsri et al. 2018).”
BackgroundMethodResultInfluential
Technological acceptance of LINE in flipped EFL oral training
Hsieh, J. C., Huang, Y., & Wu, W. V. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.12.066 · Cited by 154 · see citing works
“Diverse theoretical models have been proposed to account for a user's ﬁ nal acceptance behavior (Lee, Kozar, & Larsen, 2003) and TAM has been extended in numerous ways over the years (e.g., Abdullah & Ward, 2016; Mohammadi, 2015; Ros et al., 2015).”
Background
Understanding farmers’ ecological conservation behavior regarding the use of integrated pest management- an application of the technology acceptance model
Rezaei, R., Safa, L., & Ganjkhanloo, M. M. (2020) · Global Ecology and Conservation · doi:10.1016/j.gecco.2020.e00941 · Cited by 140 · see citing works
Application of innovation diffusion theory to the E-learning process: higher education context
Pinho, C. S. B., Franco, M., & Mendes, L. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10269-2 · Cited by 154 · see citing works
“In addition, the literature also reveals individuals are somewhat reluctant to accept and subsequently use this technology (Rym et al. 2013; Abdullah and Ward 2016).”
Background
Applying the technology acceptance model to understand maths teachers’ perceptions towards an augmented reality tutoring system
İbi̇li̇, E., Resnyansky, D., & Billinghurst, M. (2019) · Education and Information Technologies · doi:10.1007/s10639-019-09925-z · Cited by 134 · see citing works
“Abdullah and Ward (2016) reported on seven studies that investigated the effects of losing perceived usefulness, and two of these studies found that ANX had a significant effect on PU, but not others.”
BackgroundMethodInfluential
Behavioral Intention to Use Mobile Learning: Evaluating the Role of Self-Efficacy, Subjective Norm, and WhatsApp Use Habit
Kumar, J. A., Bervell, B., Annamalai, N., & Osman, S. B. (2020) · IEEE Access · doi:10.1109/access.2020.3037925 · Cited by 145 · see citing works
“Conversely, use perception which may be resulting from the effortless use of mobile learning, could also be attributed from having high mobile learning self-efﬁcacy [46], [78], [83].”
BackgroundResult
Predicting behavioral intention to use e-learning system: A case-study in Begum Rokeya University, Rangpur, Bangladesh
Humida, T., Al Mamun, M. H., & Keikhosrokiani, P. (2022) · Education and Information Technologies · doi:10.1007/s10639-021-10707-9 · Cited by 133 · see citing works
“Abdullah et al. discovered Self-Efficacy (SE) as the most usual external factor used in the TAM model (Abdullah & Ward, 2016; Keikhosrokiani, 2019; Keikhosrokiani et al., 2019).”
BackgroundMethodInfluential
Do cultural differences affect users’ e‐learning adoption? A meta‐analysis
Zhao, Y., Wang, N., Li, Y., Zhou, R., & Li, S. (2020) · British Journal of Educational Technology · doi:10.1111/bjet.13002 · Cited by 132 · see citing works
Factors affecting the adoption of e-learning in Indonesia: Lesson from Covid-19
Siron, Y., Wibowo, A., & Narmaditya, B. S. (2020) · Journal of Technology and Science Education · doi:10.3926/jotse.1025 · Cited by 139 · see citing works
“In the e-learning context, Abdullah and Ward (2016) pointed out that factor enjoyment has positive influences on perceived ease to use and perceived usefulness.”
BackgroundMethodResultInfluential
Impact of flipped classroom on EFL learners' appropriate use of refusal: achievement, participation, perception
Haghighi, H., Jafarigohar, M., Khoshsima, H., & Vahdany, F. (2018) · Computer Assisted Language Learning · doi:10.1080/09588221.2018.1504083 · Cited by 130 · see citing works
“Abdullah and Ward’s (2016) study revealed that self-efficacy, subjective norm, enjoyment, computer anxiety, and experience were the most frequently used external factors affecting perceived usefulness and the perceived ease of use.”
Background
Digital technology adoption scale in the blended learning context in higher education: Development, validation and testing of a specific tool
Lazăr, I., Pânişoară, G., & Pânişoară, I. O. (2020) · PLoS ONE · doi:10.1371/journal.pone.0235957 · Cited by 149 · see citing works
“The research on computer anxiety is a concept that has been largely studied after the beginning of the Digital Revolution in the 1980s and is still applicable nowadays [37, 49, 50].”
BackgroundMethodResultInfluential
Extending the technology acceptance model of college learners' mobile‐assisted language learning by incorporating psychological constructs
Hsu, H., & Lin, C. (2021) · British Journal of Educational Technology · doi:10.1111/bjet.13165 · Cited by 147 · see citing works
Factors influencing consumer use of a sport-branded app: the technology acceptance model integrating app quality and perceived enjoyment
Won, D., Chiu, W., & Byun, H. (2022) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-09-2021-0709 · Cited by 144 · see citing works
Understanding university students’ behavioral intention to use Edmodo through the lens of an extended technology acceptance model
Ünal, E., & Uzun, A. M. (2020) · British Journal of Educational Technology · doi:10.1111/bjet.13046 · Cited by 128 · see citing works
Preschool Teachers’ Technology Acceptance During the COVID-19: An Adapted Technology Acceptance Model
Hong, X., Zhang, M., & Liu, Q. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.691492 · Cited by 149 · see citing works
“Similarly, computer self-eﬃcacy and perception of external control play a positive eﬀect upon the perceived ease of use (Abdullah and Ward, 2016).”
Background
Technology, Demographic Characteristics and E-Learning Acceptance: A Conceptual Model Based on Extended Technology Acceptance Model
Tarhini, A., Elyas, T., Akour, M. A., & Al-Salti, Z. S. (2016) · Higher Education Studies · doi:10.5539/hes.v6n3p72 · Cited by 123 · see citing works
“Strong evidence supported the important role that PEU play in predicting the BI (Davis, 1989; Igbaria et al., 1997; Tarhini, Hone, & Liu, 2014a; Masa’deh et al., 2015; Abdullah & Ward, 2016; Esterhuyse & Scholtz, 2016).”
Background
What drives students’ intention to use tablet computers: An extended technology acceptance model
Zheng, J., & Li, S. (2020) · International Journal of Educational Research · doi:10.1016/j.ijer.2020.101612 · Cited by 132 · see citing works
What drives college students to use AI for L2 learning? Modeling the roles of self-efficacy, anxiety, and attitude based on an extended technology acceptance model
Chen, D., Liu, W., & Liu, X. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104442 · Cited by 156 · see citing works
The influence of technology acceptance, academic self-efficacy, and gender on academic achievement through online tutoring
Hanham, J., Lee, C. B., & Teo, T. (2021) · Computers & Education · doi:10.1016/j.compedu.2021.104252 · Cited by 141 · see citing works
Student continuance of learning management system use: A longitudinal exploration
Cheng, M., & Yuen, A. H. K. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.02.004 · Cited by 121 · see citing works
Investigating the antecedents of university students’ perceived ease of using the Internet for learning
Huang, F., Teo, T. P., & Scherer, R. (2020) · Interactive Learning Environments · doi:10.1080/10494820.2019.1710540 · Cited by 138 · see citing works
“I am Still Learning”: Modeling LMS Critical Success Factors for Promoting Students’ Experience and Satisfaction in a Blended Learning Environment
Ghazal, S., Al‐Samarraie, H., & Aldowah, H. A. (2018) · IEEE Access · doi:10.1109/access.2018.2879677 · Cited by 128 · see citing works
“[49], Abdullah and Ward [183],”
Video conferencing in the e-learning context: explaining learning outcome with the technology acceptance model
Bailey, D., Almusharraf, N., & Almusharraf, A. M. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10949-1 · Cited by 141 · see citing works
“Previous studies utilized the TAM to examine factors related but not limited to experience, perceived usefulness, technology anxiety, and technology self-efficacy (Abdullah & Ward, 2016; Chang et al., 2017).”
BackgroundMethod
Technology enhanced learning acceptance among university students during Covid-19: Integrating the full spectrum of Self-Determination Theory and self-efficacy into the Technology Acceptance Model
Rosli, M. S., & Saleh, N. S. (2022) · Current Psychology · doi:10.1007/s12144-022-02996-1 · Cited by 136 · see citing works
“This step could improve students’ PEU because improvements will be made based on their input (Abdullah et al., 2016).”
BackgroundResultInfluential
Understanding MOOC continuance: An empirical examination of social support theory
Hsu, G. J. Y., Chen, C., & Ting, P.-F. (2018) · Interactive Learning Environments · doi:10.1080/10494820.2018.1446990 · Cited by 115 · see citing works
“Therefore, our proposed model is in line with Davis (1986), Davis et al. (1989), Venkatesh and Morris (2000), Moon and Kim (2001), Chen et al. (2012), and Abdullah and Ward (2016) who suggested the TAM has the robust and well explanation for behavior intention toward the information system.”
BackgroundResult
Mobile learning acceptance and use in higher education during social distancing circumstances: an expansion and customization of UTAUT2
Sitar‐Tăut, D., & Mican, D. (2021) · Online Information Review · doi:10.1108/oir-01-2021-0017 · Cited by 125 · see citing works
System Quality and Student’s Acceptance of the E-learning System: The Serial Mediation of Perceived Usefulness and Intention to Use
Alkhawaja, M. I., Halim, M. S. A., Abumandil, M. S. S., & Al‐Adwan, A. S. (2022) · Contemporary Educational Technology · doi:10.30935/cedtech/11525 · Cited by 114 · see citing works
“In the context of the information system, the D&M model and TAM are the most popular models used to explain the adoption and success of information systems in education (Abdullah & Ward, 2016; Almaiah, 2018; Almaiah et al., 2016, 2020).”
Method
Automated writing evaluation (AWE) feedback: a systematic investigation of college students’ acceptance
Zhai, N., & Ma, X. (2021) · Computer Assisted Language Learning · doi:10.1080/09588221.2021.1897019 · Cited by 113 · see citing works
“The result does not concur with previous studies (Abdullah & Ward, 2016; Aburub & Alnawas, 2019; Li et al., 2019), where computer anxiety was found to have a negative relationship with perceived ease of use.”
BackgroundResultInfluential
All the same or different? Revisiting measures of teachers' technology acceptance
Scherer, R., Siddiq, F., & Tondeur, J. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.103656 · Cited by 133 · see citing works
Mobile learning acceptance in social distancing during the COVID ‐19 outbreak: The mediation effect of hedonic motivation
Sitar‐Tăut, D. (2021) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.261 · Cited by 119 · see citing works
“Sometimes its complexity is disapproved due to the confusing nature of some items and to the low impact on the overall performance of the outputs compared to UTAUT (Abdullah & Ward, 2016).”
Factors Influencing Intention to Technological Use in Older Adults. The TAM Model Aplication
Martín‐García, A. V., Redolat, R., & Hernandis, S. P. (2021) · Research on Aging · doi:10.1177/01640275211063797 · Cited by 127 · see citing works
“…in the literature, several recent reviews suggest that there is neither a unique formulation of these models for each type of technological use, nor a consensus on the importance of the main constructs that they propose (Abdullah & Ward, 2016; Grani´c & Maranguni´c, 2019; Scherer et al., 2019).”
Background
Technology acceptance model in technology-enhanced OCLL contexts: A self-determination theory approach
Fathali, S., & Okada, T. (2018) · Australasian Journal of Educational Technology · doi:10.14742/ajet.3629 · Cited by 112 · see citing works
“In a review of 107 studies that added external variables to the basic TAM and proposed new models, Abdullah and Ward (2016) found five excessively and commonly used variables for the extension – self-efficacy, subjective norm, perceived enjoyment, computer anxiety, and computer use experience.”
Background
Factors influencing teachers’ innovative teaching behaviour with information and communication technology (ICT): the mediator role of organisational innovation climate
Chou, C.-M., Shen, C.-H., Hsiao, H.-C., & Shen, T.-C. (2019) · Educational Psychology · doi:10.1080/01443410.2018.1520201 · Cited by 109 · see citing works
“It is clear that, compared with the acceptance of technological innovation, organizations ’ innovation climate is significantly and positively related to innovative teaching using ICT (Abdullah & Ward, 2016; Lau & Yuen, 2014; Obiri-Yeboah, Kwarteng, & Kyere-Djan, 2013; Wang et al., 2014).”
Background
FROM PHYSICAL TO DIGITAL: INVESTIGATING CONSUMER BEHAVIOUR OF SWITCHING TO MOBILE WALLET
Alaeddin, O., Altounjy, R., Zainudin, Z., & Kamarudin, F. (2018) · Polish Journal of Management Studies · doi:10.17512/pjms.2018.17.2.02 · Cited by 108 · see citing works
“…study the players acceptance of social network games (Park et al., 2014), adoption of mobile cloud service (Park and Kim, 2014) and huge number of researches have been adopted TAM for e-learning acceptance (Abdullah and Ward, 2016; Chang et al., 2017; Ratna and Mehra, 2015; Tarhini et al., 2017).”
Background
Innovative online learning strategies for the successful construction of student self-awareness during the COVID-19 pandemic: Merging TAM with TPB
Yao, Y., Wang, P., Jiang, Y., Li, Q., & Li, Y. (2022) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2022.100252 · Cited by 119 · see citing works
“…model proved appropriate, though studies have found no signi ﬁ cant psychological differences in student satisfaction and acceptance of online learning, research tables clarify that TAM is affected by factors such as self-ef ﬁ - cacy, enjoyment behaviors, and anxiety (Abdullah & Ward, 2016).”
Result
The effect of subjective norms on preservice and in‐service teachers’ behavioural intentions to use technology: A multigroup multimodel study
Ursavaş, Ö. F., Yalçın, Y., & Bakır-Yalçın, E. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12834 · Cited by 103 · see citing works

Using a General Extended Technology Acceptance Model for E-Learning (GETAMEL). A Literature Review of Empirical Studies
Strzelecki, A., Cicha, K., Rizun, M., & Rutecka, P. (2022) · Proceedings of the International Conference on Information Systems Development · doi:10.62036/isd.2022.57 · Cited by 4 · see citing works
Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model
Salloum, S. A., Qasim Mohammad Alhamad, A., Al-Emran, M., Abdel Monem, A., & Shaalan, K. (2019) · IEEE Access · doi:10.1109/access.2019.2939467 · Cited by 651 · see citing works
Students’ acceptance of e-learning: extending the technology acceptance model with self-regulated learning and affinity for technology
Barz, N., Benick, M., Dörrenbächer‐Ulrich, L., & Perels, F. (2024) · Discover Education · doi:10.1007/s44217-024-00195-7 · Cited by 40 · see citing works
Acceptance of E-learning Technology by Using the Technology Acceptance Model (TAM) Method
Hasan, I., Abdullah, S., & Ahmad, D. T. (2025) · International Journal of Science and Environment (IJSE) · doi:10.51601/ijse.v5i3.209 · Cited by 1 · see citing works
Are Computer Experience and Anxiety Irrelevant? Towards a Simple Model for Adoption of E-Learning Systems
Hanif, A., Siddiqi, A. F., & Jalil, Z. (2019) · International Journal of Engineering Pedagogy (iJEP) · doi:10.3991/ijep.v9i5.11488 · Cited by 18 · see citing works

Authors: Abdullah, F., & Ward, R.
Affiliations: University of Huddersfield (GB)
Corresponding author: Abdullah, Fazil
ORCID: Ward, Rupert
Venue: Computers in Human Behavior
Publisher: Elsevier BV
Published: 2016-03
Volume: 56
Pages: 238-256
ISSN: 0747-5632 (ISSN-L)
DOI: 10.1016/j.chb.2015.11.036
OpenAlex: W2214098284
Cited by: 986
References: 146
Citations by year: 2026: 67 · 2025: 88 · 2024: 113 · 2023: 155 · 2022: 157 · 2021: 163 · 2020: 96 · 2019: 76 · 2018: 39 · 2017: 22 · 2016: 10
FWCI: 46.53
Type: journal article
Language: en
Open access: green
eprints.hud.ac.uk
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Computers in Human Behavior (publishedVersion)
University of Huddersfield Repository (University of Huddersfield) (submittedVersion)
Huddersfield Research Portal (University of Huddersfield) (submittedVersion, cc-by-nc-nd)
Topics: Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Social Sciences › Education › Online and Blended Learning
Social Sciences › Gender Studies › Gender and Technology in Education
Keywords: technology acceptance model, e-learning adoption, extended technology acceptance model, self-efficacy, subjective norms, enjoyment, computer anxiety, user experience, perceived ease of use, perceived usefulness, external factors, student acceptance of technology

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