Engineering students' self-reflections, teamwork behaviors, and academic performance

Abstract

This complete research paper explores the relationship between engineering students' self-reflection, teamwork, and academic performance. Prior studies in engineering education emphasize the importance of using effective teaching strategies to enhance students' academic performances. These strategies help engineering educators in multiple ways, including creating a stimulating learning environment, actively involving students in the learning process, enhancing students' engagement, and improving students' learning. Two effective strategies include utilizing collaborative teamwork and providing opportunities for students to reflect on their learning experiences. We simultaneously introduced these two strategies in an engineering class of 120 students to explore the relationship between engineering students' self-reflection, teamwork, and academic performance. The data were collected using two specific technology tools. We used CourseMIRROR [1]-[3] to collect students' reflection data, and CATME Smarter Teamwork [4]-[6] to collect students' peer evaluation of team membership. CourseMIRROR was used in 26 lectures to collect students' reflection data, and we collected a total of 3430 student reflections (~60% completion). The reflection data comprised of two aspects: 1) muddiest point (MP) which describes the confusing aspect of the lecture, and 2) point of interest (POI) which relates to interesting aspects of the given lecture. Additionally, CATME based data was collected from five dimensions: contributing to the team's work; interacting with teammates; keeping the team on track; expecting quality, and having relevant knowledge skills and abilities. The CATME team membership survey was conducted four times during the semester. We further collected data on students' academic performances based on three exams. We also collected students' race and gender information (i.e., as demographic information). Specifically, we explored the unique contribution of two learning strategies (i.e., teamwork and self-reflection) to predict students' academic performances after controlling for demographic variables. We used stepwise hierarchical and simultaneous hierarchical regression analyses to explore the unique contribution of each strategy over and above the other. The results indicated that teamwork performance is a strong and positive predictor of engineering students' performance in their course exams. The study also discusses the implications and future directions of the research.