The objective of the research is to develop a methodology to analyze a set of data extracted from a Learning Management System (LMS), in order to implement a Dashboard, which can be used by teachers to make timely and relevant decisions to improve the teaching-learning processes. The methodology used consisted of the analysis of 9,257 records extracted through simple random sampling from a population of 100,000 records. The indicators analyzed were: number of accesses, course grades, time spent, number of courses enrolled and number of activities developed. The results show the data analysis in the KNIME data mining analysis platform, the model was implemented in five phases: Requirements definition, model design, development, implementation and evaluation of results. The results are taken as a recommendation to design and implement a customized Dashboard for teachers to identify observable behavioral patterns that allow them to make decisions to improve the teaching-learning processes of students.
|Title of host publication||Proceedings of 2021 13th International Conference on Education Technology and Computers, ICETC 2021|
|Publisher||Association for Computing Machinery|
|Number of pages||8|
|State||Published - 22 Oct 2021|
|Event||13th International Conference on Education Technology and Computers, ICETC 2021 - Virtual, Online, China|
Duration: 22 Oct 2021 → 25 Oct 2021
|Name||ACM International Conference Proceeding Series|
|Conference||13th International Conference on Education Technology and Computers, ICETC 2021|
|Period||22/10/21 → 25/10/21|
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