Educational Computational Chemistry for In-Service Chemistry Teachers: A Data Mining Approach to E-Learning Environment Redesign

Abstract

The use of technology in education has experienced significant growth in recent years. In this regard, computational chemistry is considered a dynamic element due to the constant advances in computational methods in chemistry, making it an emerging technology with high potential for application in teaching chemistry. This article investigates the characteristics and perceptions of in-service chemistry teachers who participated in an e-learning educational computational chemistry course. Additionally, it examines how educational data mining techniques can contribute to optimising and developing e-learning environments. The results indicate that teachers view incorporating computational chemistry elements in their classes positively but that this is not profoundly reflected in their teaching activity planning. On the other hand, generated statistical models demonstrate that the most relevant variables to consider in the instructional design of an e-learning educational computational chemistry course are related to participation in various course instances and partial evaluations. In this sense, the need to provide additional support to students during online learning is highlighted, especially during critical moments such as evaluations. In conclusion, this study offers valuable information on the characteristics and perceptions of in-service chemistry teachers and demonstrates that educational data mining techniques can help improve e-learning environments.

Integrating PhET Simulations into Elementary Science Education: A Qualitative Analysis

“…Educational researchers are interested in the different aspects of students' learning in specific educational contexts [31][32][33][34][35], especially in digital contexts [36,37]. The present research intended to study students' knowledge phases of Grade 3 students' scientific concepts in the context of PhET simulations.…”