2018 ASEE Annual Conference & Exposition

Metacognition involves the knowledge and regulation of one’s thinking processes, and, therefore one’s learning. The quality of metacognitive knowledge and the accuracy of self-monitoring directly impacts metacognitive skill and the effectiveness and efficiency of learning. In particular, one’s approaches to learning are entangled with one’s views on the nature of knowledge and learning. Natural development of metacognitive knowledge and skills is inefficient and often leaves gaps and inaccuracies in the resulting mental models of learning processes. Further, self-monitoring is plagued by misattributions and inaccuracies related to poor evidence for these judgements. As part of our NSF IUSE grant we developed a set of modules to engage students in the intentional development of their metacognitive knowledge (e.g., improving mental models) and skills (e.g., making more accurate self-assessments) within the context of existing courses.

In this implementation we sought to understand how students’ conceptions of learning change with metacognitive instruction and how metacognitive instruction affects the alignment of students’ monitoring behaviors and their conceptions of learning. To accomplish this, we implemented metacognitive instruction within three different engineering courses corresponding to different years in school. We looked at the degree of match/mismatch between students’ conceptions of learning and their reports of how they monitor their level of understanding and their learning processes before and after the metacognition modules. We also investigated how these trends varied across year in school. We hypothesized that the effect of the metacognitive instruction modules on reported learning behaviors would depend on prior knowledge and experience with thinking about learning. Further, we hypothesized that the metacognitive instruction modules would increase the coherence between students’ conceptions of learning and students’ reported monitoring behaviors.

A series of six metacognitive instruction modules was implemented in three engineering courses; one at the Freshman level, one at the Sophomore level, and one at the Junior level. Each module consists of a video with reflection questions, an in-class activity, and a post-class assignment. The videos provided general information about metacognition, with examples from a STEM context. The in-class activity and post-class assignment were tailored to the specific class context and were designed to enhance self-awareness or practice metacognitive regulation. Pre- and post-surveys were conducted with Likert scale and free-response questions to capture students conceptions of learning and monitoring behaviors. An additional question captured students’ prior knowledge and experience with examining their learning processes. The data was de-identified and given tracking markers in order to match pre- and post-survey responses. We analyzed the data using and open-coding approach that was informed by what is already known from literature and metacognition frameworks. We focused on conceptions of learning and monitoring strategies.

Our study has implications for students and instructors. For students we make recommendations on approaches to learning that align better with their learning goals, which embody their conceptions of learning. For instructors we offer suggestions for supporting student learning and encouraging student engagement in metacognitive development.