Making learning styles and destinations visible: Using dashboards to support secondary education
Keywords:
Career counselling, learning styles, dashboards, Unified Theory of Acceptance and Use of Technology, secondary educationAbstract
The increased accessibility of data analytic tools provides opportunities to improve teaching and learning and career counselling in secondary education. This preliminary study explored the design, development, and deployment of an initiative to use dashboards to provide teachers and career counsellors with tools in the form of dashboards to improve teaching, learning, and guidance. The study applied an action research methodology that drew from the Unified Theory of Acceptance and Use of Technology model in two international secondary schools in Cambodia. Though limited in its scope, the study highlights the potential for dashboards to inform teaching and learning and career counselling when integrated with the school teaching and learning philosophy and professional development.
Downloads
References
Abbad, M. M. M. (2021). Using the UTAUT model to understand students’ usage of e-learning systems in developing countries. Education and Information Technologies, 26(6), 7205–7224. https://doi.org/10.1007/s10639-021-10573-5
Alharbi, S., & Drew, S. (2014). Using the Technology Acceptance Model in understanding academics’ behavioural intention to use Learning Management Systems. International Journal of Advanced Computer Science and Applications, 5, 143–155. https://doi.org/10.14569/IJACSA.2014.050120
Al-Shehri, M. (2017). The effectiveness of D2L system: An evaluation of teaching-learning process in the Kingdom of Saudi Arabia. International Journal of Advanced Computer Science and Applications (IJACSA), 8(1), 442-448. https://doi.org/10.14569/IJACSA.2017.080156
Argyris, C. (1980). Inner contradictions of rigorous research. Academic Press.
Bagozzi, R. (2007). The legacy of the Technology Acceptance Model and a proposal for a paradigm shift. Journal for the Association for Information Systems, 8(4), 244–254. https://doi.org/10.17705/1jais.00122
Bingimlas, K. (2009). Barriers to the successful integration of ICT in teaching and learning environments: A review of the literature. Eurasia Journal of Mathematics Science & Technology Education, 5(3), 235–245. https://doi.org/10.12973/ejmste/75275
Brouns, F., Zorrilla Pantaleón, M. E., Álvarez Saiz, E. E., Solana-González, P., Cobo Ortega, Á., Rocha Blanco, E. R., Collantes Viaña, M., Rodríguez Hoyos, C., De Lima Silva, M., Marta-Lazo, C., Gabelas Barroso, J. A., Arranz, P., García, L., Silva, A., Sáez López, J. M., Ventura Expósito, P., Jordano de la Torre, M., Bohuschke, F., & Viñuales, J. (2015). Elearning, communication and open-data: Massive mobile, ubiquitous and open learning (D2.5 Learning analytics requirements and metrics report). Elearning Communication Open-Data. https://repositorio.unican.es/xmlui/handle/10902/15231
Carr, W., & Kemmis, S. (2006). Becoming critical: Education, knowledge and action research. Routledge.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. Management Information Systems Quarterly, 19(2), 189–211. https://doi.org/10.2307/249688
Darling-Hammond, L., Wilhoit, G., & Pittenger, L. (2014). Accountability for college and career readiness: Developing a new paradigm. Education Policy Analysis Archives, 22(86), 1–38. http://dx.doi.org/10.14507/epaa.v22n86.2014
Global Information Consultants. (n.d.). Study abroad overview. https://www.globaledu.in/study-abroad-overview
Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572–2593. https://doi.org/10.1111/bjet.12864
Herodotou, C., Maguire, C., McDowell, N., Hlosta, M., & Boroowa, A. (2021). The engagement of university teachers with predictive learning analytics. Computers & Education, 173, 104–285. https://doi.org/10.1016/j.compedu.2021.104285
Klein, C., Lester, J., Rangwala, H., & Johri, A. (2019). Technological barriers and incentives to learning analytics adoption in higher education: Insights from users. Journal of Computing in Higher Education, 31(3), 604–625. https://doi.org/10.1007/s12528-019-09210-5
König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608–622. https://doi.org/10.1080/02619768.2020.1809650
Li, J. (2020). Blockchain technology adoption: Examining the fundamental drivers. Proceedings of the 2020 2nd International Conference on Management Science and Industrial Engineering, 253–260. https://doi.org/10.13140/RG.2.2.30288.25602/1
Lin, C.-P., & Anol, B. (2008). Learning online social support: An investigation of network Information Technology based on UTAUT. CyberPsychology & Behavior, 11(3), 268–272. https://doi.org/10.1089/cpb.2007.0057
Moore, G. C., & Benbasat, I. (1996). Integrating Diffusion of Innovations and Theory of Reasoned Action models to predict utilization of information technology by end-users. In K. Kautz & J. Pries-Heje (Eds.), Diffusion and Adoption of Information Technology: Proceedings of the first IFIP WG 8.6 working conference on the diffusion and adoption of information technology, Oslo, Norway, October 1995 (pp. 132–146). Springer. https://doi.org/10.1007/978-0-387-34982-4_10
Nistor, N., Lerche, T., Weinberger, A., Ceobanu, C., & Heymann, O. (2012). Towards the integration of culture into the Unified Theory of Acceptance and Use of Technology. British Journal of Educational Technology, 45(1), 36–55. https://doi.org/10.1111/j.1467-8535.2012.01383.x
Prusak, L. (2010, October 7). What can’t be measured. Harvard Business Review. https://hbr.org/2010/10/what-cant-be-measured
Raffaghelli, J. E., Rodríguez, M. E., Guerrero-Roldán, A.-E., & Bañeres, D. (2022). Applying the UTAUT model to explain the students’ acceptance of an early warning system in Higher Education. Computers & Education, 182, 1-14. https://doi.org/10.1016/j.compedu.2022.104468
Sagor, R. (2000). Guiding school improvement with action research. Association for Supervision and Curriculum Development. http://site.ebrary.com/id/10115189
Setyohadi, D. B., Artisan, M., Sinaga, B. L., & Hamid, N. A. A. (2017). Social critical factors affecting intentions and behaviours to use e-Learning: An empirical investigation using Technology Acceptance Model. Science Alert, 10(4), 271–280. https://doi.org/10.3923/ajsr.2017.271.280
Sheppard, B., Hartwick, J., & Warshaw, P. (1988). The Theory of Reasoned Action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15(1), 325–343. https://doi.org/10.1086/209170
Simonsen, J. (2009). The challenges for action research projects. Scandinavian Journal of Information Systems, 21(1), 124–141.
Sykes, T. A., Venkatesh, V., & Gosain, S. (2009). Model of Acceptance with peer support: A social network perspective to understand employees’ system use. Management Information Systems Quarterly, 33(2), 371–393. https://doi.org/10.2307/20650296
Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. Management Information Systems Quarterly, 19(4), 561–570. https://doi.org/10.2307/249633
Thanh, T., Td, D., Le, D. H., & Jr, P. G. A. (2021). Simple student grades analytics dashboards in higher education in Vietnam. Journal of Contemporary Issues in Business and Government, 27(1), 445–453.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1994). Influence of experience on personal computer utilization: Testing a conceptual model. Journal of Management Information Systems, 11(1), 167–187. https://doi.org/10.1080/07421222.1994.11518035
Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. Advances in Experimental Social Psychology, 29(2), 271–360. https://doi.org/10.1016/S0065-2601(08)60019-2
Van Raaij, E., & Schepers, J. (2008). The acceptance and use of virtual learning environment in China. Computers & Education, 50(1), 838–852. https://doi.org/10.1016/j.compedu.2006.09.001
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. https://doi.org/10.2307/30036540
Wang, H., & Wang, S. (2010). User acceptance of mobile internet based on the Unified Theory of Acceptance and Use of Technology: Investigating the determinants and gender differences. Scientific Journal Publishers, 38(3), 415–426. https://doi.org/10.2224/SBP.2010.38.3.415
Young, M. R., Rapp, E. M., & Murphy, J. W. (2010). Action research: Enhancing classroom practice and fulfilling educational responsibilities. Journal of Instructional Pedagogies, 1-10. http://files.eric.ed.gov/fulltext/EJ1096942.pdf
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The articles published by this journal are licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
