Personalised learning model for academic leveling and improvement in higher education

Abstract

This study's innovative objective was to develop a personalised learning model to equate students' entry level knowledge as they entered the School of Medicine and Health Sciences at Tecnologico de Monterrey in Mexico in 2019. This was necessitated by a difference in the depth and approach to preparatory content. The methodology focused on adapting the learning process to the students' specific knowledge requirements in cell biology and chemistry courses to enrich knowledge and improve academic performance. We implemented a diagnostic test at the start of the course to determine the students' level of mastery in these subjects. The students were allowed to learn at their own pace and were expected to improve their low initial scores by constructing their learning paths. The professor served as an advisor. At the end of the course the students retook the exam to measured the difference between the diagnostic test results and the terminal level of knowledge. The research design was non-experimental, observing the phenomenon as it occurred in the natural context, using an interval-type scale (quantitative) questionnaire. The analysis of the learning model's results showed an increase in the students' knowledge and satisfaction and demonstrated the model's usefulness for understanding educational content.

Implications for practice or policy:

• This study presents a personalised learning model that emulates adaptive learning and provides flexibility and autonomy to students for acquiring knowledge.
• The participating students self-assessed their entry level of knowledge in chemistry and biology via the online diagnostic test using Canvas, the learning management system (LMS) of Tecnologico de Monterrey.
• The ability to asking questions to the professors, in synchronous feedback sessions, was facilitated by the interactive communication platform, to enrich the learning experience.