Exploring Computer Anxiety among Prospective Teachers in Himachal Pradesh, India
Article Sidebar
-
Prospective Teachers, Computer, Computer Anxiety
Abstract
This study explores computer anxiety among prospective teachers, defined as the fear or apprehension some individuals experience when using technology. The primary objectives were to assess the overall level of computer anxiety and to examine differences based on gender and academic stream. Utilizing a descriptive survey method, the research involved 100 participants enrolled in a B.Ed. program, comprising 59 females and 41 males, with 53 from the science stream and 47 from the humanities stream. Data were collected using a self-developed Computer Anxiety Scale (CAS) with a reliability coefficient of 0.81. The results indicated a moderate level of computer anxiety across all participants, with no significant differences observed based on gender or academic stream. These findings suggest that while prospective teachers exhibit moderate computer anxiety, this anxiety is consistent regardless of gender or academic background. The study highlights the need for targeted interventions to reduce computer anxiety and enhance technological competence among future educators.
Full text article
References
Akram, H., Abdelrady, A. H., Al-Adwan, A. S., & Ramzan, M. (2022). Teachers’ Perceptions of Technology Integration in Teaching-Learning Practices: A Systematic Review. Frontiers in Psychology, 13, 920317. https://doi.org/10.3389/fpsyg.2022.920317
Al Mulhim, E. N., & Almulhem, F. A. (2024). Techno-anxiety and techno-satisfaction during the COVID-19 pandemic: The case of special education teachers. Frontiers in Education, 9, 1384925. https://doi.org/10.3389/feduc.2024.1384925
Almaiah, M. A., Alfaisal, R., Salloum, S. A., Hajjej, F., Thabit, S., El-Qirem, F. A., Lutfi, A., Alrawad, M., Al Mulhem, A., Alkhdour, T., Awad, A. B., & Al-Maroof, R. S. (2022). Examining the Impact of Artificial Intelligence and Social and Computer Anxiety in E-Learning Settings: Students’ Perceptions at the University Level. Electronics, 11(22), 3662. https://doi.org/10.3390/electronics11223662
Anderson, S. E., & Putman, R. S. (2020). Special Education Teachers’ Experience, Confidence, Beliefs, and Knowledge About Integrating Technology. Journal of Special Education Technology, 35(1), 37–50. https://doi.org/10.1177/0162643419836409
Beckers, T., Hermans, D., Lange, I., Luyten, L., Scheveneels, S., & Vervliet, B. (2023). Understanding clinical fear and anxiety through the lens of human fear conditioning. Nature Reviews Psychology, 2(4), 233–245. https://doi.org/10.1038/s44159-023-00156-1
Chen, X., & Ibrahim, Z. (2023). A Comprehensive Study of Emotional Responses in AI-Enhanced Interactive Installation Art. Sustainability, 15(22), 15830. https://doi.org/10.3390/su152215830
Dickson, S. M., Idayana Alabere, & Ijeoma Peace Okechukwu. (2024). Web Technology Skills Acquisition by Computer Science Students at Polytechnics in Akwa Ibom State, Nigeria. Journal of Digital Learning and Distance Education, 2(11), 809–818. https://doi.org/10.56778/jdlde.v2i11.229
Erebak, S., & Turgut, T. (2021). Anxiety about the speed of technological development: Effects on job insecurity, time estimation, and automation level preference. The Journal of High Technology Management Research, 32(2), 100419. https://doi.org/10.1016/j.hitech.2021.100419
Fernández-Batanero, J.-M., Román-Graván, P., Reyes-Rebollo, M.-M., & Montenegro-Rueda, M. (2021). Impact of Educational Technology on Teacher Stress and Anxiety: A Literature Review. International Journal of Environmental Research and Public Health, 18(2), 548. https://doi.org/10.3390/ijerph18020548
Gröstenberger, E., & Selinger, A. (2023). The effect of gender and age on computer self-efficacy, computer anxiety and perceived enjoyment among Austrian secondary school teachers. MAP Education and Humanities, 4(1), 1–9. https://doi.org/10.53880/2744-2373.2023.4.1
Javaid, M., Haleem, A., Singh, R. P., Suman, R., & Gonzalez, E. S. (2022). Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability. Sustainable Operations and Computers, 3, 203–217. https://doi.org/10.1016/j.susoc.2022.01.008
Kang, Q., Lu, J., & Xu, J. (2021). Is e-reading environmentally more sustainable than conventional reading? Evidence from a systematic literature review. Library & Information Science Research, 43(3), 101105. https://doi.org/10.1016/j.lisr.2021.101105
Kumar, R., Verma, A., Shome, A., Sinha, R., Sinha, S., Jha, P. K., Kumar, R., Kumar, P., Shubham, Das, S., Sharma, P., & Vara Prasad, P. V. (2021). Impacts of Plastic Pollution on Ecosystem Services, Sustainable Development Goals, and Need to Focus on Circular Economy and Policy Interventions. Sustainability, 13(17), 9963. https://doi.org/10.3390/su13179963
Lucky, A. (2022). Influence Of Computer Assisted Instruction On Primary Education In Nigeria. Indonesian Journal of Learning and Instruction, 5(1). https://doi.org/10.25134/ijli.v5i1.5868
Nastjuk, I., Herrenkind, B., Marrone, M., Brendel, A. B., & Kolbe, L. M. (2020). What drives the acceptance of autonomous driving? An investigation of acceptance factors from an end-user’s perspective. Technological Forecasting and Social Change, 161, 120319. https://doi.org/10.1016/j.techfore.2020.120319
Popoola, S. O., & Adedokun, O. O. (2023). Computer self-efficacy, computer anxiety, cognitive skills, and use of electronic library resources by social science undergraduates in a tertiary university in Nigeria. Journal of Librarianship and Information Science, 55(1), 111–122. https://doi.org/10.1177/09610006211063938
Qu, K., & Wu, X. (2024). ChatGPT as a CALL tool in language education: A study of hedonic motivation adoption models in English learning environments. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12598-y
Radyuli, P., Menrisal, & Diati, L. S. (2022). Design of E-Learning Media Modules Based on FlipBook Maker Pro in Basic Computer Networking Subjects at SMKN 1 Tanjung Raya Even Semester Academic Year 2021/2022. Journal of Digital Learning and Distance Education, 1(3), 87–93. https://doi.org/10.56778/jdlde.v1i3.19
Todman, J. (2000). Gender differences in computer anxiety among university entrants since 1992. Computers & Education, 34(1), 27–35. https://doi.org/10.1016/S0360-1315(99)00036-6
Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., Liu, X., Wu, Y., Dong, F., Qiu, C.-W., Qiu, J., Hua, K., Su, W., Wu, J., Xu, H., Han, Y., Fu, C., Yin, Z., Liu, M., … Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4), 100179. https://doi.org/10.1016/j.xinn.2021.100179
Yuan, G. N., Marquez, G. P. B., Deng, H., Iu, A., Fabella, M., Salonga, R. B., Ashardiono, F., & Cartagena, J. A. (2022). A review on urban agriculture: Technology, socio-economy, and policy. Heliyon, 8(11), e11583. https://doi.org/10.1016/j.heliyon.2022.e11583
Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023). Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis. International Journal of Educational Technology in Higher Education, 20(1), 49. https://doi.org/10.1186/s41239-023-00420-7
Authors
Copyright (c) 2024 JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION
This work is licensed under a Creative Commons Attribution 4.0 International License.
<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.