Cited by 471Technology Adoption and User BehaviourEnglish Language Learning and TeachingTechnology-Enhanced Education Studies

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Measuring Students’ Use of Zoom Application in Language Course Based on the Technology Acceptance Model (TAM)

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Alfadda, Hind Abdulaziz, Mahdi, Hassan Saleh·2021·Journal of Psycholinguistic Research

DOI 10.1007/s10936-020-09752-1PMC PMC7781650

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Abstract

The study uses technology acceptance model (TAM) to gain insights into user reactions to the technology adopted for language learning. The study aims to analyze the correlation between the variables of TAM on using Zoom application in language learning, in addition to examining how gender and experience influence the use of technology. The participants of this study comprise of 75 undergraduate English-as-Foreign-Language learners who have studied for their courses online during the COVID-19 pandemic. The results of the study reveal a strong positive correlation between the actual use of Zoom and the students' attitudes and behavioral intention. In addition, there is a positive correlation between computer self-efficacy and other variables (i.e. PU, actual use, PEU, attitude and behavioral intention). Further, while the results reveal that there is no correlation between the gender and any variables of the model, it has been found that experience is positively correlated with the variables of TAM.

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Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
Untitled work
(1980) · Medical Entomology and Zoology · Cited by 25,810
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
From Intentions to Actions: A Theory of Planned Behavior
Ajzen, I. (1985) · Action Control · doi:10.1007/978-3-642-69746-3_2 · Cited by 19,057
Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model
Venkatesh, V. (2000) · Information Systems Research · doi:10.1287/isre.11.4.342.11872 · Cited by 6,664
Computer Self-Efficacy: Development of a Measure and Initial Test
Compeau, D. R., & Higgins, C. A. (1995) · MIS Quarterly · doi:10.2307/249688 · Cited by 6,553
Interpretation of the correlation coefficient: A basic review
Taylor, R. (1990) · Journal of Diagnostic Medical Sonography · doi:10.1177/875647939000600106 · Cited by 2,390
Why do people play on-line games? An extended TAM with social influences and flow experience
Hsu, C., & Lu, H. (2003) · Information & Management · doi:10.1016/j.im.2003.08.014 · Cited by 2,099
e-Learning, online learning, and distance learning environments: Are they the same?
Moore, J. L., Dickson-Deane, C., & Galyen, K. (2011) · The Internet and Higher Education · doi:10.1016/j.iheduc.2010.10.001 · Cited by 2,042
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
An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning
Park, S. Y. (2009) · Educational Technology & Society · Cited by 1,385
Learner readiness for online learning: Scale development and student perceptions
Hung, M.-L., Chou, C., Chen, C.-H., & Own, Z.-Y. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.05.004 · Cited by 1,066
The Journal of Internet Banking and Commerce
(2016) · The Journal of Internet Banking and Commerce · doi:10.4172/1204-5357 · Cited by 925
Does the technology acceptance model predict actual use? A systematic literature review
Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010) · Information and Software Technology · doi:10.1016/j.infsof.2009.11.005 · Cited by 851
Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community
Liu, I.-F., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C. (2009) · Computers & Education · doi:10.1016/j.compedu.2009.09.009 · Cited by 795
Gender differences in computer-related attitudes and behavior: A meta-analysis
Whitley, B. E. (1997) · Computers in Human Behavior · doi:10.1016/s0747-5632(96)00026-x · Cited by 629
Gender, Internet and computer attitudes and experiences
Schumacher, P., & Morahan-Martin, J. (2001) · Computers in Human Behavior · doi:10.1016/s0747-5632(00)00032-7 · Cited by 592
Understanding the Influence of Perceived Usability and Technology Self-Efficacy on Teachers’ Technology Acceptance
Holden, H., & Rada, R. (2011) · Journal of Research on Technology in Education · doi:10.1080/15391523.2011.10782576 · Cited by 584
An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modeling approach
Teo, T. P., & Noyes, J. (2011) · Computers & Education · doi:10.1016/j.compedu.2011.03.002 · Cited by 576
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Lee, D. Y., & Lehto, M. R. (2013) · Computers & Education · doi:10.1016/j.compedu.2012.10.001 · Cited by 565
Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario
Meléndez, A. P., Obra, A. R. D. Á., & Garrido‐Moreno, A. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.12.014 · Cited by 484
Web Acceptance Model (WAM): Moderating effects of user experience
García, J. A. C., Muñoz‐Leiva, F., & Martínez, T. L. (2007) · Information & Management · doi:10.1016/j.im.2007.02.003 · Cited by 413
Mobile-based assessment: Investigating the factors that influence behavioral intention to use
Nikou, S. A., & Economides, A. A. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.02.005 · Cited by 388
User acceptance of information technology
VenkateshViswanath, MorrisMichael, G., DavisGordon, B., & DavisFred, D. (2003) · MIS Quarterly · doi:10.5555/2017197.2017202 · Cited by 365
Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study
Pynoo, B., Devolder, P., Tondeur, J., van Braak, J., Duyck, W., & Duyck, P. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.10.005 · Cited by 341
Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning
Agudo-Peregrina, Á. F., Hernández-García, Á., & Pascual-Miguel, F. J. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.10.035 · Cited by 325
Gender differences in e-learning satisfaction
González‐Gómez, F., Guardiola, J., Rodríguez, Ó. M., & Alonso, M. Á. M. (2011) · Computers & Education · doi:10.1016/j.compedu.2011.08.017 · Cited by 305
A multidimensional approach to determinants of computer use in primary education: teacher and school characteristics
Tondeur, J., Valcke, M., & van Braak, J. (2008) · Journal of Computer Assisted Learning · doi:10.1111/j.1365-2729.2008.00285.x · Cited by 302
Investigating models for preservice teachers’ use of technology to support student-centered learning
Chen, R. (2009) · Computers & Education · doi:10.1016/j.compedu.2009.11.015 · Cited by 301
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
Tarhini, A., HONE, K. S., & Liu, X. (2014) · Journal of Educational Computing Research · doi:10.2190/ec.51.2.b · Cited by 283
e-Learning continuance intention: Moderating effects of user e-learning experience
Lin, K. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.09.017 · Cited by 277
Thinking Beyond Zoom: Using Asynchronous Video to Maintain Connection and Engagement During the COVID-19 Pandemic
Lowenthal, P. R., Borup, J., West, R. E., & Archambault, L. (2020) · The Journal of Technology and Teacher Education · doi:10.70725/331114ctnutj · Cited by 265
Measuring Student Perceptions of Blackboard Using the Technology Acceptance Model
Landry, B. J. L., Griffeth, R. W., & Hartman, S. J. (2006) · Decision Sciences Journal of Innovative Education · doi:10.1111/j.1540-4609.2006.00103.x · Cited by 228
Computer based assessment: Gender differences in perceptions and acceptance
Terzis, V., & Economides, A. A. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.06.005 · Cited by 195
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Šumak, B., Heričko, M., Pušnik, M., & Polančič, G. (2011) · Informatica · Cited by 166
The Impact of Subjective Norm and Facilitating Conditions on Pre-Service Teachers' Attitude toward Computer Use: A Structural Equation Modeling of an Extended Technology Acceptance Model
Teo, T. P. (2009) · Journal of Educational Computing Research · doi:10.2190/ec.40.1.d · Cited by 158
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
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Moran, M., Hawkes, M. L., & El-Gayar, O. (2010) · Journal of Educational Computing Research · doi:10.2190/ec.42.1.d · Cited by 155
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Wu, W. V., Yen, L. L., & Marek, M. W. (2011) · Educational Technology & Society · Cited by 138
Age, gender, ethnicity and the digital divide: university students’ use of web‐based instruction
Enoch, Y., & Soker, Z. (2006) · Open Learning The Journal of Open Distance and e-Learning · doi:10.1080/02680510600713045 · Cited by 128
Domains and determinants of university students’ self-perceived computer competence
van Braak, J. P. (2004) · Computers & Education · doi:10.1016/j.compedu.2003.09.006 · Cited by 99
Empirical Testing of a Theoretical Extension of the Technology Acceptance Model: An Exploratory Study of Educational Wikis
Liu, X. (2009) · Communication Education · doi:10.1080/03634520903431745 · Cited by 93
The Effects of Computer Self-Efficacy and Technology Acceptance Model on Behavioral Intention in Internet Banking Systems
Ariff, M. S. M., Yeow, S., Zakuan, N., Jusoh, A., & Bahari, A. Z. (2012) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2012.09.1210 · Cited by 89
Social support as a neglected e-learning motivator affecting trainee’s decisions of continuous intentions of usage
Weng, C., Tsai, C., & Weng, A. (2015) · Australasian Journal of Educational Technology · doi:10.14742/ajet.1311 · Cited by 84
Students’ perceptions toward the use of the digital library in weekly web‐based distance learning assignments portion of a hybrid programme
Koohang, A. A. (2004) · British Journal of Educational Technology · doi:10.1111/j.0007-1013.2004.00418.x · Cited by 84
Basic Japanese Grammar and Conversation e-learning through Skype and Zoom Online Application
Dharma, H. R. C., Asmarani, D., & Dewi, U. P. (2017) · Procedia Computer Science · doi:10.1016/j.procs.2017.10.055 · Cited by 69
Factors influencing personal computer usage: the gender gap
Teo, T. S. H., & Lim, V. K. G. (1996) · Women in Management Review · doi:10.1108/09649429610148746 · Cited by 68
Re-visiting college students’ attitudes toward the Internet-based on a 6-T model: Gender and grade level difference
Chou, C., Wu, H., & Chen, C. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.11.004 · Cited by 66
The Relationship among Tertiary Level EFL Students’ Personality, Online Learning Motivation and Online Learning Satisfaction
Shih, H.-F., Chen, S.-H. E., Chen, S.-C., & Wey, S. (2013) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2013.10.442 · Cited by 57
Grit, Growth Mindset, and Deliberate Practice in Online Learning
McClendon, C., Neugebauer, R. M., & King, A. (2017) · Journal of Instructional Research · doi:10.9743/jir.2017.2 · Cited by 55
Factors Affecting University Students' Use of Moodle
Essel, D. D., & Apeanti, W. O. (2016) · International Journal of Information and Communication Technology Education · doi:10.4018/ijicte.2017010102 · Cited by 49
Effective use of zoom technology and instructional videos to improve engagement and success of distance students in engineering
Sayem, A. S. M., Taylor, B. A., McClanachan, M., & Mumtahina, U. (2017) · Acquire (CQUniversity) · Cited by 45
Students' E-Learning Experience through a Synchronous Zoom Web Conference System
Rahayu, D. (2020) · DOAJ (DOAJ: Directory of Open Access Journals) · doi:10.22236/jer_vol5issue1pp68-79 · Cited by 39
The Impact of E-Commerce Security, and National Environment on Consumer adoption of Internet Banking in Malaysia and Singapore
Dauda, Y., Santhapparaj, A. S., Asirvatham, D. A. L., & Raman, M. (2007) · The Journal of Internet Banking and Commerce · Cited by 33
Perceptions of Turkish EFL Students on Online Language Learning Platforms and Blended Language Learning
İstifçi, İ. (2016) · Journal of Education and Learning · doi:10.5539/jel.v6n1p113 · Cited by 31
Effects of Collaborative Online Learning on EFL Leaners’ Writing Performance and Self-efficacy
Tai, H.-C. (2016) · English Language Teaching · doi:10.5539/elt.v9n5p119 · Cited by 28
Facebook Friend Request: Applying the Theory of Reasoned Action to Student-Teacher Relationships on Facebook
Sheldon, P. (2016) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2016.1164167 · Cited by 27
Determining How Social Media Affects Learning English: An Investigation of Mobile Applications Instagram and Snap Chat in TESOL Classroom
Alfadda, H. A. (2020) · Arab World English Journal · doi:10.24093/awej/vol11no1.1 · Cited by 20
Self-citation
An Analysis of the Technology Acceptance Model in Understanding Students' Behavioral Intention to Use University's Social Media
Tantiponganant, P., & Laksitamas, P. (2014) · IIAI International Conference on Advanced Applied Informatics (IIAI-AAI) · doi:10.1109/iiai-aai.2014.14 · Cited by 17
Computer Attitudes and Use Among Novice Teachers: The Moderating Effects of School Environment
Teck, W. K., Choo, G. S., Hanafi, H. F., & Osman, R. (2010) · Malaysian Journal of Learning and Instruction · doi:10.32890/mjli.7.2010.7621 · Cited by 11
Determining How Social Media Affects Learning English: An Investigation of Mobile Applications Instagram and Snap Chat in TESOL ClassroomPreprint
Fadda, H. A. A. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3581296 · Cited by 10
Technology Tools for Teaching in Higher Education
Ferns, S., Cappon, A., Duff, A., Marshall, A. N., Ryan, B. J., Thompson, B. R., Ferguson, C., Deegan, C., MacMahon, C., McCormick-Brighton, C., et al. (2020) · Cited by 6

Research works printed but not linked: 2

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of technology acceptance model: Four longitudinal field studies. Management Science, 46, 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926. · DOI · Paper page
Wu, W. C. V., Hsieh, J. S. C., & Yang, J. C. (2017). Creating an online learning community in a flipped classroom to enhance EFL learners’ oral proficiency. Journal of Educational Technology & Society, 20(2), 142–157.

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Authors: Alfadda, H. A., & Mahdi, H. S.
Affiliations: King Saud University (SA)
University of Bisha (SA)
Corresponding author: Alfadda, Hind Abdulaziz
Mahdi, Hassan Saleh
ORCID: Alfadda, Hind Abdulaziz
Mahdi, Hassan Saleh
Venue: Journal of Psycholinguistic Research
Publisher: Springer Science and Business Media LLC
Published: 2021-01-05
Volume: 50
Issue: 4
Pages: 883-900
ISSN: 0090-6905 (ISSN-L)
1573-6555
DOI: 10.1007/s10936-020-09752-1
PMC: PMC7781650
OpenAlex: W3118764021
Cited by: 438
References: 68
Citations by year: 2026: 46 · 2025: 83 · 2024: 79 · 2023: 117 · 2022: 80 · 2021: 33
FWCI: 65.89
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Journal of Psycholinguistic Research (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: King Saud University
Topics: Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Social Sciences › Education › English Language Learning and Teaching
Social Sciences › Education › Technology-Enhanced Education Studies
Keywords: Zoom, technology acceptance model, online language learning, English as a foreign language, computer self-efficacy, perceived usefulness, perceived ease of use, user attitudes, behavioral intention, technology use, gender differences, user experience, COVID-19 remote learning
MeSH terms: COVID-19, Adult, Attitude to Computers, Female, Humans, Language, Male, Surveys and Questionnaires, Students, Technology, Models, Educational, Education, Distance, Self Efficacy, Intention, Young Adult

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Measuring Students’ Use of Zoom Application in Language Course Based on the Technology Acceptance Model (TAM)

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