A K-means Clustering Analysis to Assess Educators' and Students' Perceptions of Digital Technology in Higher Education
DOI:
https://doi.org/10.56919/usci.2544.001Keywords:
Digital Technology Integration, K-Means Clustering, Digital Technology Perception, Digital TransformationAbstract
Digital technology has transformed the way teaching and learning are approached, shifting from a teacher-centered model to a student-centered one. Educators and students are the key stakeholders driving the integration of digital technology into educational processes. Many studies have examined educators' and students' perceptions of digital technology use through descriptive analyses. However, descriptive analysis cannot uncover complex non-linear relationships between the main explanatory variables. It also depends on domain experts to identify important features for investigating the phenomenon. Therefore, a detailed examination of faculty and student perceptions of digital technology in education is necessary, and machine learning offers powerful tools, such as advanced algorithms, to better detect patterns in data. This study gathers data from educators and students at Nigerian higher education institutions through questionnaires. The data is analyzed using the K-means clustering algorithm to identify trends in perceptions of digital technology use in teaching and learning. The results show three groups among educators: laggards, adorers, and adopters, representing low, moderate, and high levels of integration and perception, respectively. Student perceptions of digital technology integration follow a similar pattern but with greater variability. Findings suggest the need for sufficient digital technology resources in higher education and for strategies to support educators and students with low perceived benefit and low integration of digital technologies in academic activities, especially by integrating professional development training for educators into pedagogy.
References
Abel, V. R., Tondeur, J., & Sang, G. (2022). Teacher perceptions about ICT integration into classroom instruction. Education Sciences, 12(9), 609. DOI: https://doi.org/10.3390/educsci12090609
Ahmed, M., Seraj, R., & Islam, S. M. S. (2020). The k-means Algorithm: A comprehensive survey and performance evaluation. Electronics, 9(8), 1295. DOI: https://doi.org/10.3390/electronics9081295
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. DOI: https://doi.org/10.3389/fpsyg.2022.920317
Akram, H., Yingxiu, Y., Al-Adwan, A. S., & Alkhalifah, A. (2021). Technology integration in higher education during COVID-19: An assessment of online teaching competencies through technological pedagogical content knowledge model. Frontiers in Psychology, 12, 736522. DOI: https://doi.org/10.3389/fpsyg.2021.736522
Alenezi, M., Wardat, S., & Akour, M. (2023). The need of integrating digital education in higher education: Challenges and opportunities. Sustainability, 15(6), 4782. DOI: https://doi.org/10.3390/su15064782
Bell, E., & Barr, D. (2024). Barriers to technology integration in the A-level history classroom in Northern Ireland. Irish Educational Studies, 43(4), 1227–1248. DOI: https://doi.org/10.1080/03323315.2023.2209853
Bonthu, H. (2021, May 21). Detecting and treating outliers | Treating the odd one out! Analytics Vidhya. https://www.analyticsvidhya.com/blog/2021/05/detecting-and-treating-outliers-treating-the-odd-one-out/
Chahuán-Jiménez, K., Lara-Yergues, E., Garrido-Araya, D., Salum-Alvarado, E., Hurtado-Arenas, P., & Rubilar-Torrealba, R. (2025). Cluster analysis of digital competencies among professors in higher education. Frontiers in Education. DOI: https://doi.org/10.3389/feduc.2025.1499856
Chen, Z. L. (2022). Research and application of clustering algorithm for text big data. Computational Intelligence and Neuroscience, 2022(1), 7042778. DOI: https://doi.org/10.1155/2022/7042778
Chiu, T. K. (2022). School learning support for teacher technology integration from a self-determination theory perspective. Educational Technology Research and Development, 70(3), 931–949. DOI: https://doi.org/10.1007/s11423-022-10096-x
Christina, P. I., & Georgiou, D. (2024). Technology education in primary schools: addressing teachers' perceptions, perceived barriers, and needs. International Journal of Technology and Design Education, 34, 485–503. DOI: https://doi.org/10.1007/s10798-023-09828-8
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. DOI: https://doi.org/10.2307/249008
Faig, E. Z. (2023). Exploring the role of technology integration in twenty-first century education. International Journal of Innovative Technologies in Social Science, 4(40).
Fälth, L., & Selenius, H. (2024). Primary school teachers' use and perception of digital technology in early reading and writing education in inclusive settings. Disability and Rehabilitation: Assistive Technology, 19(3), 790–799. DOI: https://doi.org/10.1080/17483107.2022.2125089
García-Morales, V. J., Garrido-Moreno, A., & Martín-Rojas, R. (2021). The transformation of higher education after the COVID disruption: Emerging challenges in an online learning scenario. Frontiers in Psychology, 12, 616059. DOI: https://doi.org/10.3389/fpsyg.2021.616059
Gkrimpizi, T., & Peristeras, V. (2022, October). Barriers to digital transformation in higher education institutions. In Proceedings of the 15th International Conference on Theory and Practice of Electronic Governance (pp. 154–160). DOI: https://doi.org/10.1145/3560107.3560135
Händel, M., Stephan, M., Gläser-Zikuda, M., Kopp, B., Bedenlier, S., & Ziegler, A. (2020). Digital readiness and its effects on higher education students' socio-emotional perceptions in the context of the COVID-19 pandemic. Journal of Research on Technology in Education, 54, 267–280. DOI: https://doi.org/10.1080/15391523.2020.1846147
Hartman, R. J., Townsend, M. B., & Jackson, M. (2019). Educators' perceptions of technology integration into the classroom: a descriptive case study. Journal of Research in Innovative Teaching & Learning, 12(3), 236–249. DOI: https://doi.org/10.1108/JRIT-03-2019-0044
Hwang, G. J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100001. DOI: https://doi.org/10.1016/j.caeai.2020.100001
Karkouti, I. M. (2023). Integrating technology in Qatar's higher education settings: What helps faculty accomplish the job. Technology, Knowledge and Learning, 28(1), 279–305. DOI: https://doi.org/10.1007/s10758-021-09553-y
Karsh, S. M. A. (2018). New technology adoption by business faculty in teaching: Analysing faculty technology adoption patterns. Education Journal, 7(1), 5–15. DOI: https://doi.org/10.11648/j.edu.20180701.12
Kim, S., Cho, S., Kim, J., & Kim, D. (2023). Statistical assessment on student engagement in asynchronous online learning using the k-means clustering algorithm. Sustainability. DOI: https://doi.org/10.3390/su15032049
Kumbo, L. I., Mero, R. F., & Hayuma, B. J. (2023). Navigating the digital frontier: Innovative pedagogies for effective technology integration in education. The Journal of Informatics, 3(1), 14–33. DOI: https://doi.org/10.59645/tji.v3i1.142
Lawrence, J. E., & Tar, U. A. (2018). Factors that influence teachers' adoption and integration of ICT in teaching/learning process. Educational Media International, 55(1), 79–105. DOI: https://doi.org/10.1080/09523987.2018.1439712
Liu, H., Chen, C., Li, Y., Li, Y., & Duan, Z. (2022). Chapter 3 - Individual behavior analysis and trajectory prediction. In Smart Metro Station Systems (pp. 59–76). DOI: https://doi.org/10.1016/B978-0-323-90588-6.00003-2
Mahdum, M., Hadriana, H., & Safriyanti, M. (2019). Exploring teacher perceptions and motivations to ICT use in learning activities in Indonesia. Journal of Information Technology Education: Research, 18, 293–317. DOI: https://doi.org/10.28945/4366
Mather, E., Matashu, M., & Meyer, J. (2022). Students' perceptions of factors influencing the adoption and use of ICT in learning during COVID-19 at one rural based South African University. Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika, 6 (2), 61. DOI: https://doi.org/10.36312/esaintika.v6i2.660
Maylawati, D., Priatna, T., Sugilar, H., & Ramdhani, M. (2020). Data science for digital culture improvement in higher education using K-means clustering and text analytics. International Journal of Electrical and Computer Engineering, 10(5), 4569–4580. DOI: https://doi.org/10.11591/ijece.v10i5.pp4569-4580
Mercader, C., & Gairín, J. (2020). University teachers' perception of barriers to the use of digital technologies: the importance of the academic discipline. International Journal of Educational Technology in Higher Education, 17(1), 4. DOI: https://doi.org/10.1186/s41239-020-0182-x
Mwila, P. (2018). Assessing the attitudes of secondary school teachers towards the integration of ICT in the teaching process in Kilimanjaro, Tanzania. International Journal of Education and Development using Information and Communication Technology, 14(3), 223–238.
Nair, A. (2022, May 21). Standardization vs Normalization. Towards Data Science. https://towardsdatascience.com/standardization-vs-normalization-dc81f23085e3
Ndebele, C., & Mbodila, M. (2022). Examining technology acceptance in learning and teaching at a historically disadvantaged university in South Africa through the technology acceptance model. Education Sciences, 12(1), 54. DOI: https://doi.org/10.3390/educsci12010054
Ohei, K. N., & Brink, R. (2019). A framework development for the adoption of information and communication technology web technologies in higher education systems. South African Journal of Information Management, 21(1), 1–12. DOI: https://doi.org/10.4102/sajim.v21i1.1030
Panakaje, N., Ur Rahiman, H., Parvin, S. M. R., P, S., K, M., Yatheen, & Irfana, S. (2024). Revolutionizing pedagogy: navigating the integration of technology in higher education for teacher learning and performance enhancement. Cogent Education, 11(1). DOI: https://doi.org/10.1080/2331186X.2024.2308430
Paul, S., & Lal, K. (2018). Adoption of digital technologies in tertiary education: Evidence from India. Journal of Educational Technology Systems, 47(1), 128–147. DOI: https://doi.org/10.1177/0047239518768513
Qasem, A. A. A., & Viswanathappa, G. (2016). Teachers' perception Towards ICT Integration: Professional Development Through Blended Learning. Main Issues of Pedagogy and Psychology, 4(1), 20–26. DOI: https://doi.org/10.24234/miopap.v10i1.137
Rogers, E. M. (2003). Diffusion of innovations. Free Press.
Salem, N., & Mohammadzadeh, B. (2018). A study on the integration of ICT by EFL teachers in Libya. EURASIA Journal of Mathematics, Science and Technology Education, 14(7), 2787–2801. DOI: https://doi.org/10.29333/ejmste/90594
Sammouda, R., & El-Zaart, A. (2021). An optimized approach for prostate image segmentation using K‐Means clustering algorithm with elbow method. Computational Intelligence and Neuroscience, 2021(1), 4553832. DOI: https://doi.org/10.1155/2021/4553832
Saraswat, S., Agrohi, V., Kumar, M., Lamba, M., & Kaur, R. (2024). Unveiling consumer segmentation: Harnessing K-means clustering using elbow and silhouette for precise targeting. In G. Fortino, A. Kumar, A. Swaroop, & P. Shukla (Eds.), Proceedings of Third International Conference on Computing and Communication Networks. ICCCN 2023. Lecture Notes in Networks and Systems (Vol. 917). Springer. DOI: https://doi.org/10.1007/978-981-97-0892-5_28
Singun, A. J. (2025). Unveiling the barriers to digital transformation in higher education institutions: a systematic literature review. Discover Education, 4(1), 37. DOI: https://doi.org/10.1007/s44217-025-00430-9
Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
Turugare, M., & Rudhumbu, N. (2020). Integrating technology in teaching and learning in universities in Lesotho: Opportunities and challenges. Education and Information Technologies, 25(5), 3593–3612. DOI: https://doi.org/10.1007/s10639-019-10093-3
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. DOI: https://doi.org/10.2307/30036540
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