A Personalized Mobile Learning System for Solving STEM Teachers’ TPACK Problems

Abstract

STEM education is an educational concept that encourages learners to learn and integrate the knowledge of science, technology, engineering, and mathematics. If we consider an in-service teacher as a learner, then we can apply the STEM concept using computer engineering techniques to build tools to promote the learning of scientific knowledge for them. This research proposed the design and development of an adaptive mobile learning through computer engineering processes. We designed algorithms to select learning media by analyzing data consisting of a learners' learning styles, learning problems, learning media attributes, mobile device capabilities and network quality to create a personalized learning environment. This study focused on the development of teaching knowledge regarding TPACK framework in a domain of digital science learning approaches, where 78 in-service secondary school science teachers participated in this study. The results of our study indicated that the algorithms can work effectively with more than 65% of user satisfaction in at least good level, and more than 90% user satisfaction in at least moderate level. The learners have significantly improved learning achievements in almost all kinds of knowledge based on the TPACK framework with 95% confidence level. The results show that our system is promising to provide learning tools to improve STEM teachers’ proficiencies under the TPACK framework.