IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i21p15280-d1267182.html

Technology Enhanced Learning in Undergraduate Level Education: A Case Study of Students of Mass Communication

Author

Listed:
  • Dina Naser Tahat

    (Applied Sociology Department, Al Ain University, Abu Dhabi P.O. Box 112612, United Arab Emirates)

  • Mohammed Habes

    (Faculty of Mass Communication, Radio & TV Department, Yarmouk University, Irbid P.O. Box 21163, Jordan)

  • Khalaf Tahat

    (Media & Creative Industries Department United Arab Emirates University UAE, Irbid P.O. Box 21163, Jordan
    Journalism Department, Yarmouk University, Irbid P.O. Box 21163, Jordan)

  • Saadia Anwar Pasha

    (Department of Mass Communication, Allama Iqbal Open University, Islamabad 44000, Pakistan)

  • Razaz Waheeb Attar

    (Department of Business Administration, College of Business and Administration, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia)

  • Waleed Mugahed Al-Rahmi

    (Faculty of Social Science and Humanities, School of Education, University Teknologi Malaysia, Skudai 81310, Johor, Malaysia)

  • Fahad Alblehai

    (Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia)

Abstract

The incorporation of digital technology in education represents a substantial transformation in the realm of academia. In the present day, with new technology being readily available to both educators and students, educational institutions encourage their students to embrace it, enabling students facing geographical constraints to easily continue their education through internet-based learning. The primary objective of this study is to investigate the viewpoints of undergraduate students in the field of mass communication concerning the integration of Information and Communication Technology (ICT) in the UAE. Based on a Technology Acceptance Model (TAM), the data were gathered using structured questionnaires. Results revealed that knowledge sharing and accessibility are significant factors affecting the perceived ease of use and perceived usefulness among the undergraduate students. Further, perceived ease of use significantly affects perceived usefulness. Finally, both perceived ease of use and perceived usefulness remained as significant factors regarding ICT acceptance among the Emirati students. It is concluded that educational institutions must invest significantly in robust IT infrastructure. This step ensures that e-learning experiences are seamless and accessible to all students. Further, to address some students’ connectivity challenges, offering alternative access options or providing offline resources can be beneficial. Finally, the practical implications and limitations are discussed.

Suggested Citation

  • Dina Naser Tahat & Mohammed Habes & Khalaf Tahat & Saadia Anwar Pasha & Razaz Waheeb Attar & Waleed Mugahed Al-Rahmi & Fahad Alblehai, 2023. "Technology Enhanced Learning in Undergraduate Level Education: A Case Study of Students of Mass Communication," Sustainability, MDPI, vol. 15(21), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15280-:d:1267182
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/21/15280/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/21/15280/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dufour, Jean-Marie, 1990. "Exact Tests and Confidence Sets in Linear Regressions with Autocorrelated Errors," Econometrica, Econometric Society, vol. 58(2), pages 475-494, March.
    2. Alkahtani Mohammed Ali, 2021. "E-learning for Students With Disabilities During COVID-19: Faculty Attitude and Perception," SAGE Open, , vol. 11(4), pages 21582440211, October.
    3. Nisar Ahmed Dahri & Waleed Mugahed Al-Rahmi & Abeer S. Almogren & Noraffandy Yahaya & Muhammad Saleem Vighio & Qusay Al-Maatuok, 2023. "Mobile-Based Training and Certification Framework for Teachers’ Professional Development," Sustainability, MDPI, vol. 15(7), pages 1-22, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emmanuel Amos & Harry Barton Essel & George Kwame Fobiri & Akwasi Adomako Boakye & Yaw Boateng Ampadu, 2025. "Exploring the Analytics Readiness Among Students in Kumasi Technical University, Ghana," SAGE Open, , vol. 15(3), pages 21582440251, August.
    2. David Llanos-Ruiz & Víctor Abella-García & Vanesa Ausín-Villaverde, 2025. "Virtual Reality in Higher Education: A Systematic Review Aligned with the Sustainable Development Goals," Societies, MDPI, vol. 15(9), pages 1-60, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dufour, Jean-Marie & Farhat, Abdeljelil & Hallin, Marc, 2006. "Distribution-free bounds for serial correlation coefficients in heteroskedastic symmetric time series," Journal of Econometrics, Elsevier, vol. 130(1), pages 123-142, January.
    2. Jean-Marie Dufour & Lynda Khalaf & Marie-Claude Beaulieu, 2010. "Multivariate residual-based finite-sample tests for serial dependence and ARCH effects with applications to asset pricing models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 263-285.
    3. Valkanov, Rossen, 1999. "The Term Structure with Highly Persistent Interest Rates," University of California at Los Angeles, Anderson Graduate School of Management qt8x91m4hg, Anderson Graduate School of Management, UCLA.
    4. Sriananthakumar, Sivagowry, 2013. "Testing linear regression model with AR(1) errors against a first-order dynamic linear regression model with white noise errors: A point optimal testing approach," Economic Modelling, Elsevier, vol. 33(C), pages 126-136.
    5. Firmin Doko Tchatoka & Lauren Slinger & Virginie Masson, 2020. "Revisiting empirical studies on the liquidity effect: An identication-robust approach," School of Economics and Public Policy Working Papers 2020-02, University of Adelaide, School of Economics and Public Policy.
    6. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    7. Kiviet, Jan F. & Dufour, Jean-Marie, 1997. "Exact tests in single equation autoregressive distributed lag models," Journal of Econometrics, Elsevier, vol. 80(2), pages 325-353, October.
    8. Dufour, Jean-Marie & Khalaf, Lynda, 2002. "Exact tests for contemporaneous correlation of disturbances in seemingly unrelated regressions," Journal of Econometrics, Elsevier, vol. 106(1), pages 143-170, January.
    9. Freyberger, Joachim & Rai, Yoshiyasu, 2018. "Uniform confidence bands: Characterization and optimality," Journal of Econometrics, Elsevier, vol. 204(1), pages 119-130.
    10. Marie-Claude BEAULIEU & Jean-Marie DUFOUR & Lynda KHALAF, 2002. "Testing Mean-Variance Efficiency In Capm With Possibly Non-Gaussian Errors : An Exact Simulation-Based Approach," Cahiers de recherche 17-2002, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    11. Peter Hansen, 2003. "Asymptotic Tests of Composite Hypotheses," Working Papers 2003-09, Brown University, Department of Economics.
    12. Helmut Herwartz & Shu Wang, 2024. "Statistical identification in panel structural vector autoregressive models based on independence criteria," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 620-639, June.
    13. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    14. Waleed Mugahed Al-Rahmi & Ahmad Samed Al-Adwan & Qusay Al-Maatouk & Mohd Shahizan Othman & Anas Ratib Alsaud & Abeer S. Almogren & Ali Mugahed Al-Rahmi, 2023. "Integrating Communication and Task–Technology Fit Theories: The Adoption of Digital Media in Learning," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
    15. Banerjee, Anurag N. & Magnus, Jan R., 2000. "On the sensitivity of the usual t- and F-tests to covariance misspecification," Journal of Econometrics, Elsevier, vol. 95(1), pages 157-176, March.
    16. Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 133-153, July.
    17. Jean-Marie Dufour & Malika Neifar, 2004. "Méthodes d’inférence exactes pour un modèle de régression avec erreurs AR(2) gaussiennes," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(4), pages 593-618.
    18. Firmin Doko Tchatoka & Jean‐Marie Dufour, 2014. "Identification‐robust inference for endogeneity parameters in linear structural models," Econometrics Journal, Royal Economic Society, vol. 17(1), pages 165-187, February.
    19. Touhami Abdelkhalek & Jean-Marie Dufour, 2006. "Confidence Regions for Calibrated Parameters in Computable General Equilibrium Models," Annals of Economics and Statistics, GENES, issue 81, pages 1-31.
    20. Elise Coudin & Jean-Marie Dufour, 2020. "Finite-sample generalized confidence distributions and sign-based robust estimators in median regressions with heterogeneous dependent errors," Econometric Reviews, Taylor & Francis Journals, vol. 39(8), pages 763-791, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15280-:d:1267182. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.