Educational engineering for models of academic success in Thai Universities during the COVID-19 Pandemic learning strategies for lifelong learning

Abstract

The COVID-19 pandemic has had a devastating impact on the Thai education system, as many universities had to transfer their learning management to e-learning. This research aims (1) to study and compare the academic performance of higher education students affected by the COVID-19 health crisis, and (2) to build a model of academic performance with instructional engineering technology to support the learning management process of higher education institutions. The research approaches were carried out according to the theory of data mining techniques using the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. The data collection was divided into two parts according to the education situation. The first part was a normal situation with data collected from 173 students during the second semester of the 2019 academic year. The second part, on the other hand, was an abnormal situation, with data collected from 167 students during the first semester of the academic year 2020. It was found that traditional and online teaching and learning enabled students to achieve similar academic results. The data collected and analyzed from both situations showed that the students' learning outcomes were not different. In addition, the appropriate grouping of learners allows for three sub-groups to be classified according to the research findings. Therefore, consideration should be given to grouping learners with similar characteristics in a small group and designing more effective learning activities. This issue will be the subject of future study.