ANALYSIS OF THE WEB APPLICATION ON BAYES’ THEOREM CONSIDERING DATA SCIENCE AND TECHNOLOGICAL ACCEPTANCE MODEL

Authors : Ricardo-adan SALAS-RUEDA, Erika-patricia SALAS-RUEDA, Erika-patricia SALAS-RUEDA

Pages : 55-78

Doi:10.17718/tojde.961819

View : 11 | Download : 8

Publication Date : 2021-07-01

Article Type : Research Paper

Abstract :This mixed research aims to design and implement the Web Application on Bayes’ Theorem insert ignore into journalissuearticles values(WABT); in the Statistical Instrumentation for Business subject. WABT presents the procedure to calculate the probability of Bayes’ Theorem through the simulation of data about the supply of products. Technology Acceptance Model insert ignore into journalissuearticles values(TAM);, machine learning and data science are used to analyze the impact of WABT on the educational process. The results of machine learning insert ignore into journalissuearticles values(60%, 70% and 80% of training); indicate that WABT positively influences the Motivation, Autonomy, Personalized learning and Active role. Data science identifies predictive models of the impact of WABT on the teaching and learning process through the decision tree technique. In addition, WABT is a pleasant, simple, useful and innovative web tool for the educational field. Finally, teachers can use TAM model, data science and machine learning in order to identify the impact of digital tools on the educational process.
Keywords : Technology, learning, TAM model, data science, learning machine