DATA DRIVEN PEDAGOGY

LEVERAGING ANALYTICS FOR EFFECTIVE E-LEARNING STRATEGIES

Authors

  • Patrick Zingisa Msekelwa Author

DOI:

https://doi.org/10.60087/jklst.vol1.n.p12

Keywords:

E-learning, data-driven pedagogy, Open distance and e-learning, triangulation, fourth industrial revolution, internet based learning

Abstract

The adoption of a data-driven pedagogy is rapidly occurring among Open distance and e-learning institutions. In certain regions, individuals engaged in the field of education encounter obstacles related to data availability and network coverage, despite the existence of digital tools utilized by educators and online learners to enhance the teaching and learning process. This research study employs a social-constructivist theoretical framework as its research paradigm. Additionally, it adopts an interpretivist perspective within the social constructivist paradigm to gather insights from participants who originate from diverse life contexts. The researcher found that employing a mixed methods research methodology, which combines both quantitative and qualitative methods, was the most appropriate choice for their study. The utilization of both study approaches enabled the researcher to triangulate the collected results, hence enhancing the robustness of the findings. The quantitative portion of the study involved a sample size of forty participants. A questionnaire was employed as a means of gathering information, and subsequent data analysis was conducted utilizing charts and tables.  The qualitative component of the study involved conducting interviews with a total of twelve focus groups. The acquired data was subjected to thematic analysis. The findings indicate that a significant proportion of pupils, even those residing in urban and rural areas, derived advantages from the implementation of data-driven teachingv

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Published

21-12-2023

How to Cite

Msekelwa, P. Z. (2023). DATA DRIVEN PEDAGOGY: LEVERAGING ANALYTICS FOR EFFECTIVE E-LEARNING STRATEGIES. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 1(1), 55-68. https://doi.org/10.60087/jklst.vol1.n.p12