Technological Acceptance among College Students in The New Normal

Authors

  • Vanessa Cometa University of Mindanao Digos College
  • Kristine S. Costante University of Mindanao Digos College
  • Jeriz W Escorido University of Mindanao Digos College
  • Tessie G. Miralles University of Mindanao Digos College

Keywords:

technology acceptance, college students, descriptive research, blended learning, technological advancement

Abstract

The adoption of technology in the learning process has been extensively researched, focusing on students' level of technological acceptance. This descriptive research study aimed to determine the level of technological acceptance among college students. A
standardized questionnaire was administered to randomly selected respondents. Statistical analyses, including frequency, mean, Mann-Whitney U Test, and Kruskal-Wallis Test, were conducted. The results indicated that there were no significant differences in
technology acceptance based on gender and age. However, significant differences were observed based on year level and program, with third-year students and those in the DTE program exhibiting the highest level of acceptance. Overall, respondents demonstrated a
moderately high level of technology acceptance, with "Intention to Use" obtaining the lowest mean score. To enhance students' understanding of technology's significance and encourage continued technological advancement, especially during the pandemic, the
researchers recommend conducting a seminar titled "Blended Learning: The New Normal and Emerging Technologies.".

References

Aggelidis, V., & Chatzoglou, P. (2009). Using a modified technology acceptance model in hospitals.

International Journal of Medical Informatics, 78(2), 115–26.

https://doi.org/10.1016/j.ijmedinf.2008.06.006.

Alenezi, A. (2011). An adoption of the TAM model to determine factors affecting students'

acceptance of e-learning in institutions of Higher education in Saudi Arabia. [Doctoral

Thesis. Universiti Utara Malaysia].

Alrajawy, I., Norzaidi, M. D., Isaac, O., & Mutahar, A. M. (2017). Examine Factors Influencing the

Intention to use Mobile Learning in Yemen Public Universities. Asian Journal of

Information Technology, 16(2), 287–297.

Alrajawy I., Isaac O., Ghosh A., Nusari M., Al-Shibami A. H., & Ameen A. A. (2018). Determinants of

Student's Intention to Use Mobile Learning in

Yemeni Public Universities: Extending the Technology Acceptance Model (TAM) with

anxiety. International Journal of Management and Human Science (IJMHS), Volume 2,

Issue 2, Pages 1-9, 2018 eISSN: 2590-3748.

Armstrong-Mensah, E., Ramsey-White, K., Yankey B., & Self-Brown, S. (2020). COVID-19 and

Distance Learning: Ef ects on Georgia State University School of Public Health

Students. Frontiers in Public Health, 8.

doi:10.3389/fpubh.2020.57622710.3389/fpubh.2020.576227.

Braun, M. T. (2013). Obstacles to social networking website use among older adults. Computers in

Human Behavior, 29(3), 673–680.

Camilleri, M. A. (2020). Strategic dialogic communication through digital media during COVID-19

crisis. Strategic Corporate Communication in the Digital Age, ed. M. Camilleri (Bingley:

Emerald).

Canough, J. (2016). Ef ective Implementation of Technology. Education Masters. Paper 261.

Calderon, J. (2006). Methods of research and thesis writing (2nd Ed.). Mandaluyong City: National

Bookstore.

Chang, C.-T., Hajiyev, J., & Su, C.-R. (2017). Examining the students' behavioral intention to use

e-learning in Azerbaijan? The general extended technology acceptance model for

e-learning approach. Computers & Education, 111, 128– 143.

https://doi.org/10.1016/j.compedu.2017.04.010.

Charness, N., & Boot, W. R. (2016). Technology, Gaming, and Social Networking. Handbook of the

Psychology of Aging, 389–407. https://doi:10.1016/b978-0-12- 411469-2.00020-0.

Chen, C. H. (2020). A.R. videos as scaf olding to foster students' learning achievements and

motivation in EFL learning. Br. J. Educ. Technol. 51, 657– 672.

https://doi:10.1111/bjet.12902.

Chen, H. R., & Tseng, H. F. (2012). Factors that influence acceptance of web-based e-learning

systems for the in-service education of junior high school teachers in Taiwan. Evaluation

and Program Planning, 35(3), 398–406.

https://doi.org/10.1016/j.evalprogplan.2011.11.007.

Chung, J. E., Park, N., Wang, H., Fulk, J., & McLaughlin, M. (2010). Age differences in perceptions

of online community participation among nonusers: An extension of the Technology

Acceptance Model. Computers in Human Behavior, 26(6), 1674-1684.

Cigdem, H., & Topcu, A. (2015). Predictors of instructors' behavioral intention to use learning

management system: A Turkish vocational college example. Computers in Human

Behavior, 52, 22–28. https://doi.org/10.1016/j.chb.2015.05.049.

Crawford, J., K., Rudolph, J., Malkawi, B., Glowatz, M., Burton, R., et al. (2020).COVID-19: 20

countries' higher education intra-period digital pedagogy responses. J. Appl. Learn. Teach.

, 1–20. https://doi:

1080/1475939x.2020.1866654.

Copeland, W. E., McGinnis, E., Bai, Y., Adams, Z., Nardone, H., Devadanam, V., & Hudziak, J. (2021).

Impact of COVID-19 pandemic on college students' mental Health and wellness.

Journal of the American Academy of Child & Adolescent Psychiatry, 60(1), 134–

https://doi.org/10.1016/j.jaac.2020.08.466.

Davis, F. D. (1986). A Technology Acceptance Model for Empirically Testing New End- User

Information Systems. [Theory and Results. Ph.D. Thesis, Massachusetts Institute of

Technology, Cambridge, MA, USA, 1985].

Daud, N., Kassim, N., Said, W., & Noor, M. (2011). Determining Critical Success Factors of Mobile

Banking Adoption in Malaysia. Australian Journal of Basic and Applied Sciences, 5(9),

–265.

Dincer, A. (2020). Understanding the Characteristics of English Language Learners' Out-of-Class

Language Learning through Digital Practices. IAFOR Journal of Education: Technology in

Education Volume 8 – Issue 2.

DePietro, A. (2020). Here's a look at the Impact of Coronavirus (COVID-19) on Colleges and

Universities in the U.S.

https://www.forbes.com/sites/andrewdepietro/2020/04/30/impactcoronavirus-covid19- colleges-universities.

Donitsa, S., & Ramot, R. (2020). Opportunities and challenges: Teacher Education in Israel in the

Covid-19 pandemic. Journal of Education for Teaching, 46(4), 586–595.

https://doi.org/10.1080/02607476.2020.1799708.

Durodolu, O. (2016). Technology Acceptance Model as a predictor of using information systems to

acquire information literacy skills.

Fathema, N., & Sutton, K. L. (2013). Factors influencing faculty members' Learning Management

Systems adoption behavior: An analysis using the Technology Acceptance Model.

International Journal of Trends in

Economics Management & Technology (IJTEMT), 2(6), 20–28. Education and

Information Technologies. 26, pages7057–7077 (2021).

https://doi.org/10.1007/s10639-021-10557-5.

Firat, M. (2016). Determining the Ef ects of LMS Learning Behaviors on Academic Achievement in a

Learning Analytic Perspective. Journal of Information Technology Education: Research,

, 75-87.

Garcia, M. (2017). E-Learning Technology Adoption in the Philippines: An Investigation of Factors

Af ecting Filipino College Students' Acceptance of Learning Management Systems Article in

The International Journal of E-Learning and Educational Technologies in the Digital Media.

Gocotano, T. E., Jerodiaz, M. A., L., Banggay, J. C. P., Nasibog, R., & Go, M. B. (2021). Higher

Education Students' Challenges on Flexible Online Learning Implementation in the Rural

Areas: A Philippine Case.

Gonzalez, T., De La Rubia, M. A., Hincz, K. P., Comas-Lopez, M., Subirats, L., Fort, S., & Sacha, G. M.

(2020). Influence of COVID-19 confinement on students' performance in higher

education. PLoS One, 15(10), e0239490.

Hall, B. C. (2008). Investigating the relationships among computer self-ef icacy, professional

development, teaching experience, and technology integration of teachers. [Doctoral

Dissertation, University of Cincinnati, Cincinnati, Ohio.

Hanham, J., Lee, C. B., & Teo, T. (2021). The influence of technology acceptance, academic

self-efficacy, and gender on academic achievement through online tutoring. Computers &

Education, 172, 104252.

doi:10.1016/j.compedu.2021.10425210.1016/j.compedu.2021.104252

Harvey, H. L., Parahoo, S., & Santally, M. (2017). Should gender dif erences be considered when

assessing student satisfaction in the online learning environment for millennials. Higher

Education Quarterly, 71(2), 141–158.

Hung, C. L., & Chou, C. L. (2014). Examining The Cultural Moderation On The Acceptance Of Mobile

Commerce.

Inozu, J., Sahinkarakas, S., & Yumru, H. (2010). The nature of language learning experiences

beyond the classroom and its learning outcomes. US-China Foreign Language 8, 14–21.

Jones, A. B., & Kauppi, K. (2018). Examining the antecedents of the technology acceptance model

within e-procurement. International Journal of Operations and Production Management,

(1), 22-42.

Karaali, D., Gumussoy, C., & Calisir, F. (2011). Factors af ecting the intention to use a web-based

learning system among blue-collar workers in the automotive industry. Computers in

Human Behavior, 27(1), 343–354.

https://doi.org/10.1016/j.chb.2010.08.012.

Khalil, R., Mansour, A. E., Fadda, W. A., Almisnid, K., Aldamegh, M., AlNafeesah, A., & Al-Wutayd, O.

(2020). The sudden transition to synchronized online learning during the COVID-19

pandemic in Saudi Arabia: A qualitative study exploring medical students' perspectives.

mutahae, 20(1), 1–10.

Lai, C., Shum, M., & Tian, Y. (2016). Enhancing learners' self-directed use of technology for

language learning: the ef ectiveness of an online training platform. Comput. Assist. Lang.

Learn. 29, 40–60. https://doi:10.1080/09588221.2014.889714.

Lee, J.W. (2010). Online support service quality, online learning acceptance, and student

satisfaction. Internet High. Educ. 2010, 13, 277–283.

Lee, D., Lee, S., Olson, D., & Chung, S. (2010). The ef ect of organizational support on ERP

implementation. Industrial Management & Data Systems, 110(2), 269– 283.

https://doi.org/10.1108/02635571011020340.

Mailizar, M., Burg, D., Maulin, S. (2021). Examining university students' behavioural intention to

use e-learning during the COVID-19 pandemic: An extended TAM model.

Mutahar, A. M., Daud, N. M., Thurasamy, R., Isaac, O., & Abdulsalam, R. (2018). The Mediating of

Perceived Usefulness and Perceived Ease of Use : The Case of Mobile Banking in Yemen.

International Journal of Technology Diffusion, 9(2), 21–40.

http://doi.org/10.4018/IJTD.2018040102.

Morris, M. G., Venkatesh, V., & Ackerman, P. L. (2005). Gender and age dif erences in employee

decisions about new technologies: An extension to the theory of planned behavior. IEEE

Transactions on Engineering Management, 52, 69–84.

Nuere, S., and de Miguel, L. (2020). The digital/technological connection with COVID- 19: an

unprecedented challenge in University teaching. Technol. Knowl.Learn.

https://doi:10.1007/s10758-020-09454-6.

NuriAbdalla, S. A. (2019). Extend of TAM Model with Technology anxiety and Self- Ef icacy to

Accept Course websites at University Canada West. International Journal of Information

Technology and Language Studies (IJITLS). Vol. 3, Issue. 2, (2019). pp. 1-7.

Othman, M., & Al Othman, H. (2016). Saudi Teachers' and University Students' Attitudes toward

Computing.

Pan, X. (2020). Technology Acceptance, Technological Self-Ef icacy, and Attitude Toward

Technology-Based Self-Directed Learning: Learning Motivation as a Mediator.

Pantano, E & Di Pietro, L (2012). Understanding Consumer's Acceptance of TechnologyBased

Innovations in Retailing. Journal of Technology Management and Innovation, Volume 7,

(4).

Park, S., Nam, M. W., & Cha, S. B. (2012). University students' behavioral intention to use mobile

learning: Evaluating the technology acceptance model. British Journal of Educational

Technology, 43(4), 592–605. https://doi.org/10.1111/j.14678535.2011.01229.x.

Pike, G. R., Smart, J. C., & Ethington, C. A. (2012). The mediating ef ects of student engagement on

the relationships between academic disciplines and learning outcomes: an extension of

Holland's theory. Res. High. Educ. 53, 550–575. https://doi:10.1007/s11162-011-9239-y.

Popovich, P.M., Gullekson, N., Morris, S. & Morse, B. (2008). Comparing attitudes towards

computer usage by undergraduates from 1986 to 2005. Computer in Human Behavior, Vol.

No. 3, pp. 986-992.

Radanliev, P., De Roure, D., & Walton, R. (2020a). Data mining and analysis of scientific research

data records on Covid-19 mortality, immunity, and vaccine development-In the first wave of

the Covid-19 pandemic. Diabetes Metab. Syndr. Clin. Res. Rev. 14, 1121–1132.

https://doi:10.1016/j.dsx.2020.06.063.

Radanliev, P., De Roure, D., Walton, R., Van Kleek, M., Montalvo, R. M., Santos, O., et al. (2020b).

COVID-19 what have we learned? The rise of social machines and connected devices in

pandemic management following the concepts of predictive, preventive and personalized

medicine. EPMA J. 11, 311–332. https://doi:10.1007/s13167-02000218-x.

Rajan, C., & Baral, R. (2015). Adoption of ERP system: An empirical study of factors influencing the

usage of ERP and its impact on end user. IIMB Management Review, 27(2), 105–117.

https://doi.org/10.1016/j.iimb.2015.04.008.

Rillo, R. M., & Alieto, E. O. (2018). Indirectness Markers in Korean and Persian English Essays:

Implications for Teaching Writing to EFL Learners. The Journal of English As An

International Language. Volume 13 – 2.2.

Sam, H. K., Ekhsan, A., Othman, A., & Nordin, Z. S. (2005). Computer SelfEf icacy, Computer

Anxiety, and Attitudes toward the Internet : A Study among Undergraduates in Unimas.

Educational Technology & Society, 8(4), 205–219.

Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A

meta-analytic structural equation modeling approach to explaining teachers' adoption of

digital technology in education. Computers & Education, 128, 13–35. Retrieved from

https://doi.org/10.1016/J.COMPEDU.2018.09.009.

Shin, J., Seo, M., & Lew, Y. K. (2022). Sustainability of Digital Capital and Social Support during

COVID-19: Indonesian Muslim Diaspora's Case in South Korea. Sustainability. 14. 7457.

3390/su14127457.

Solomon Osho, G. & Williams, F. (2018). An Empirical Investigation of the Impacts of Web-Based

Distance Education: Evidence for Justice Studies. Journal of Educational Issues ISSN

-2263 2018, Vol. 4, No. 2. https://doi.org/10.5296/jei.v4i2.13049.

Suki, N. M. (2011). Exploring The Relationship Between. Perceived usefulness,

Perceived Ease Of Use, Perceived Enjoyment, Attitude And Subscribers' Intention Towards

Using 3g Mobile Services. Journal of Information Technology Management. Vol. 12 (1).

Tarhini, A., Hone, K., & Liu, X. (2013). Factors Af ecting Students' Acceptance of e- Learning

Environments in Developing Countries: A Structural Equation Modeling Approach.

International Journal of Information and Education Technology, 3(1), 54-59.

https://doi.org/10.7763/IJIET.2013.V3.233.

Terblanche, N., Kidd, M. (2022). Adoption Factors and Moderating Ef ects of Age and Gender That

Influence the Intention to Use a Non-Directive Reflective Coaching Chatbot. SAGE Open.

April 2022. https://doi:10.1177/21582440221096136

Teo, T. (2011). Technology Acceptance in Education: Research and Issues, 1–5.

Teo, T. (2013). A comparison of non-nested models in explaining teachers' intention to use

technology. British Journal of Educational Technology, Vol.44 (3), E81- E84.

https://doi:10.1111/j.1467-8535.2012.01350.x.

Teo, T., Fan, X., & Du, J. (2015). Technology acceptance among pre-service teachers: Does gender

matter? Australasian Journal of Educational Technology, 31, 235– 251.

https://doi.org/10.14742/ajet.1672.

Thakur, R., & Srivastava, S. (2014). Mobile Technology Acceptance Among Turkish Travelers.

Venkatesh, V., Thong, J. Y. L., & Xin Xu (2018). Consumer Acceptance and Use of Information

Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS

Quarterly, Vol. 36, No. 1 (March 2012), pp. 157-178 https://doi.org/10.2307/41410412.

Vladova, G., Ullrich, A., Bender, B., Gronau, N. (2021). Students' Acceptance of

Technology-Mediated Teaching – How It Was Influenced During the COVID-19 Pandemic in

: A Study From Germany.

Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009). Investigating the determinants and age and gender

dif erences in the acceptance of mobile learning. British Journal.

Wang, X. & Lee, K. (2020). The paradox of technology innovativeness and risk perceptions – A

profile of Asian smartphone users. Telematics and Informatics. Educational Technology,

(1), 92-118.

Watermeyer, R., Courtois, A., and Lauder, H. (2020). Reacting to Covid-19 by slashing fixed-term

staf would be a disaster. Times Higher Education.

Whitley, B. E., Jr. (1997). Gender dif erences in computer-related attitudes and behavior: A

meta-analysis. Computers in Human Behavior, 13, 1–22.

Wen, Y. & Kwon, O. (2010). An empirical study of the factors af ecting social network service use.

Computers in Human Behaviour.

Downloads

Published

2023-08-01

How to Cite

Cometa, V., Costante , K. S., Escorido, J. W., & Miralles, T. G. (2023). Technological Acceptance among College Students in The New Normal. Conference on English Language Teaching, 219–235. Retrieved from https://proceedings.uinsaizu.ac.id/index.php/celti/article/view/489