Abstract
The purpose of this study was to explore the factors that might affect learning performance and collaborative problem solving (CPS) awareness in science, technology, engineering, and mathematics (STEM) education. We collected and analyzed data on important factors in STEM education, including learning strategy and learning behaviors, and examined their interrelationships with learning performance and CPS awareness, respectively. Multiple data sources, including learning tests, questionnaire feedback, and learning logs, were collected and examined following a learning analytics approach. Significant positive correlations were found for the learning behavior of using markers with learning performance and CPS awareness in group discussion, while significant negative correlations were found for some factors of STEM learning strategy and learning behaviors in pre-learning with some factors of CPS awareness. The results imply the importance of an efficient approach to using learning strategies and functional tools in STEM education.
Highlights
In the twenty-first century, international concern over science, technology, engineering, and mathematics (STEM) education has increased
Data collection In order to investigate factors that might affect the cultivation of collaborative problem solving (CPS) skills, we examined the relationships between CPS awareness and learning performance, the STEM learning strategy (SLS) used, and the learning behaviors in learning scientific materials during individual pre-learning and collaborative work
Changes in learning performance The pre-posttests consist of ten questions about knowledge related to CO2 and disaster reduction
Summary
In the twenty-first century, international concern over science, technology, engineering, and mathematics (STEM) education has increased. We currently face many global issues, including climate change, overpopulation and wellbeing, resource management, health, and biodiversity, that put great pressure on institutions involved in developing science and technology and that require continued development of STEM education (Gough, 2015; Thomas & Watters, 2015). Considering the complexity and diversity of these issues and the great need for the ability to integrate knowledge and skills in science, technology, engineering, and mathematics to solve real problems (Newhouse, 2016), science learning seems to be a powerful way of thinking and understanding the basis of these issues (Thomas & Watters, 2015). According to Kelley and Knowles (2016), it is indicated that the foundation of STEM learning framework is the situated STEM learning, which is based on the situated cognition theory. As one of the critical themes of STEM, acquiring knowledge and skills through solving problems with real-world scenarios is crucial in STEM learning, for the reasons such as it helps students to prepare for real life, and solve life problems and work problems, by using science, technology, engineering, and mathematicsrelated knowledge and skills (Holmlund, Lesseig, & Slavit, 2018)
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