Construction and evaluation of a web application for the educational process on Normal Distribution considering the science of data and machine learning

Keywords: ICT, TPACK model, technology, data science, machine learning

Abstract

This mixed research aims at the planning, construction and implementation of a web application to facilitate the educational process on the Normal Distribution through the technological, pedagogical and content knowledge of the Technological Pedagogical Content Knowledge (TPACK) model. This study proposes the use of the PHP programming language (technological knowledge), the topics of Normal Distribution (content knowledge) and computer simulation (pedagogical knowledge) to create the Web Application on the Educational Process of Statistics (WAEPS). The sample consists of 61 students who took the subject Statistical Instrumentation for Business during the 2018 school year. The results of the linear regression (machine learning with 50% and 70% of training) indicate that the WAEPS facilitates the educational process on statistics. In fact, the WAEPS promotes the active role in the student, develops mathematical skills and facilitates the assimilation of knowledge about the calculation of upper and lower limits in the Normal Distribution by means of data simulation, interactivity and navigation. Even students consider that this web application is innovative and useful for the educational field. In addition, data science (decision tree technique) identifies various predictive models on the impact of the WAEPS in the educational process. Finally, the TPACK model is an ideal frame of reference to innovate the teaching–learning process through technological, pedagogical and content knowledge.

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References


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Published
2019-03-29
How to Cite
Salas-Rueda R.-A. (2019). Construction and evaluation of a web application for the educational process on Normal Distribution considering the science of data and machine learning. Research in Learning Technology, 27. https://doi.org/10.25304/rlt.v27.2085
Section
Original Research Articles