Perception about and Effect of Adaptive Educational Application on Electronics Topics on Students’ Virtual Spaces, Motivation, Satisfaction and Active Role

Currently, educators seek to offer personalised contents to facilitate autonomy during the educational process. The aim of this mixed study (quantitative and qualitative approach) was to build and analyse the effectiveness of the Adaptive Educational application on electronics topics (AEET) considering Data Science (machine learning algorithm on linear regression). In particular, AEET presents the content about logic gates, considering student learning style, through a web simulator, digital files, and YouTube videos. The participants were 41 students from the National School of Earth Sciences, National Autonomous University of Mexico. The results of the machine learning algorithm on linear regression indicated that the content of AEET positively affected the creation of virtual educational environments, motivation, satisfaction, and active role. At the National School of Earth Sciences, the use of AEET facilitated personalised learning at any time, autonomy, and flexibility of space during the educational process. In conclusion, it was found that AEET is a technological development that improved learning about logic gates through a web simulator, digital files, and YouTube videos.