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Session Type: Symposium
Motivation regulation (MR) is associated with increases in motivation, better learning, and higher performance. In theory, these associations are stronger for students who engage in optimal (vs. maladaptive) forms of regulation. Optimal regulation involves identifying motivational problems and concerns as they arise and selectively implementing strategies that address these problems in a task/context-appropriate manner. This symposium includes four empirical papers that examine the unique patterns of strategy use associated with optimal regulation in different contexts and the factors (such as motivational beliefs and metamotivational awareness) that may lead students to exhibit such patterns. Collectively, our findings provide new insights into MR as a dynamic, multistep, and multifaceted process.
Yang-Hsin Fan, University of Texas at Austin
Patricia Chen, University of Texas at Austin
David B. Miele, Boston College
Dynamic Motivation Regulation: Stability, Predictors, and Outcomes of Motivation-Regulation Profiles among Sixth-Grade Students - Yang-Hsin Fan, University of Texas at Austin; Jing-Yi Shen, Beijing Normal University; Patricia Chen, University of Texas at Austin
Do Students’ Exam-Specific Motivational Regulation Profiles Differ in Initial Motivation Regulation and Exam-Specific Learning Outcomes? - Serena Luo, The Ohio State University; Kaicheng Zhang, Michigan State University; Cristina D. Zepeda, Vanderbilt University
How Motivational Regulation Shapes and Is Shaped by Motivational Beliefs Over Time: Time-Lagged Network Analysis - Yeo-eun Kim, Sungkyunkwan University; Patrick N. Beymer, University of Cincinnati; Emily Quinn Rosenzweig, Teachers College, Columbia University
Examining Metamotivational Awareness as a Component of Optimal Strategy Use - Erika Alvarez-Atencio, Universidad Complutense de Madrid; David B. Miele, Boston College; Jesús M. Alvarado, Universidad Complutense de Madrid