Metacognitive calibration in introductory physics courses: Predictors and interventions

Student learning in introductory science, technology, engineering, and mathematics (STEM) courses is often self-regulated. For self-regulated learning to be effective, students need to engage in accurate metacognitive monitoring in order to make appropriate metacognitive control decisions. However, the accuracy with which individuals’ monitor their task performance appears to largely overlap with their ability to perform that task. Two overarching goals motivate this dissertation and are explored over three studies. The first goal is to examine differences in both the initial metacognitive accuracy and the change in metacognitive accuracy over time to identify the trajectories in the accuracy of students’ metacognitive monitoring over the course of a semester. The second goal for the dissertation is to explore the effect that viewing animated-narrated solution videos has on metacognitive monitoring accuracy for students enrolled in introductory physics courses. The first study examines the relationship between domain ability and metacognitive calibration within the domain, and proposes a measure to examine metacognitive awareness. The second study investigates the trajectories in the accuracy of students’ metacognitive monitoring over the course of a semester. In addition, this study explores the effect that providing students with feedback about their metacognitive accuracy. By exploring the constructs related to accurate metacognitive monitoring, these two studies aim to identify the characteristics of students whose metacognitive judgments do not align with their ability before the first exam in order to design appropriate interventions so that these students do not find themselves in a hole from which they cannot recover. Besides identifying students at risk of overconfidence, understanding the role that academic goal orientations and epistemological beliefs play in making metacognitive judgments is crucial for designing effective interventions aimed at preparing students for exams. The results from these two studies indicate that low-performing students are less accurate at predicting their exam grades both before and after exams, and that these students tend to be aware that their initial predictions were overconfident, but they lack the awareness to sufficiently adjust their predictions after taking the exams. In addition, while most students do not improve their metacognitive calibration over the course of a semester, some students are able to improve the accuracy of their predictions. However, providing students with feedback may lead to greater overconfidence for low-performing students. The third study presents the results from three experiments that investigate the effect that viewing solution videos on problem-solving has on metacognitive calibration of low-performing students. The results indicate that students learn from the solution videos and make more accurate confidence judgments for problems that are similar to the problems in the video solutions, however these students are overconfident after attempting transfer problems. In addition, attempting the problems before viewing the solutions does not seem to benefit low-performing students, and may lead to unwarranted overconfidence for very difficult problems. As a whole, the three studies presented within this dissertation investigate metacognitive monitoring within self-regulated learning environments, specifically introductory STEM classrooms. The findings extend existing research concerning differences in metacognitive awareness and accuracy, changes in metacognitive calibration over time, and the effect that monitoring accuracy feedback and worked-examples have on learning and metacognitive accuracy.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Educational Psychology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Morphew, Jason Wade

Contributors dc:contributor

• Mestre, Jose P.
• Stine-Morrow, Liz
• Lindgren, Robb
• Perry, Michelle

• Metacognition, Calibration, Self-Regulated Learning, STEM education

Statement dc:rights

• © 2019 Jason Wade Morphew

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/105170

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/105170