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9 results

  • 5 - Metacognition and Self-Regulated Learning

  • from Part I - Foundations
  • Edited by R. Keith Sawyer, University of North Carolina, Chapel Hill
  • Book: The Cambridge Handbook of the Learning Sciences
  • Published online: 14 March 2022
  • Print publication: 07 April 2022, pp 93-113

  • Summary

    Metacognition is thinking about the contents and processes of one’s own cognition. Research shows that metacognition plays important roles in most cognitive tasks, from everyday behaviors to problem-solving to expert performance. This chapter focuses on metacognition’s centrality in learning and in self-regulated learning. When learning, people monitor what they know and whether it is aligned with their intended learning outcome. A learner’s ability to monitor effectively is known as calibration. Learners then control their next actions based on their monitoring, and finally they self-regulate the process of monitoring and controlling their learning by shaping and adapting cognition or behavior by reaching forward by planning for future tasks. Research shows that people learn better when they have strong metacognitive abilities and when they can self-regulate their learning effectively.

  • 27 - Learning Strategies and Self-Regulated Learning

  • from Part V - Metacognition
  • Edited by John Dunlosky, Kent State University, Ohio, Katherine A. Rawson, Kent State University, Ohio
  • Book: The Cambridge Handbook of Cognition and Education
  • Published online: 08 February 2019
  • Print publication: 07 February 2019, pp 696-715

  • Summary

    This chapter briefly surveys historical cornerstones on which current conceptions of learning strategies rest. Building on this foundation, modern research on self-regulated learning, metacognition, motivation, and decision-making is synthesized. Key features of tasks – condition, operations, products, evaluations, and standards (COPES) – are coordinated with major dimensions of motivation (the AEIOU model: attributions, efficacy expectations, incentives, outcome expectations, utility judgments) to account for how learners reach decisions about how to study – how they self-regulate learning. A methodology using traces of learners’ activities is proposed for characterizing temporally unfolding features of self-regulated learning.

  • Relations of multivariate goal profiles to motivation, epistemic beliefs and achievement

  • Mingming Zhou, Olusola O. Adesope, Philip H. Winne, John C. Nesbit
  • Journal: Journal of Pacific Rim Psychology / Volume 13 / 2019
  • Published online by Cambridge University Press: 01 February 2019, e1
  • Print publication: 2019
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  • We examined whether undergraduates’ achievement goal orientations could be represented as profiles and whether profiles were linked to self-reported motivation, epistemic beliefs and academic achievement. Data collected during an undergraduate course were analyzed using a clustering technique. Using the 2 × 2 goal model (Elliot & McGregor, 2001), we identified five achievement goal profiles. Our findings suggest the interaction of goal orientations supports varying interpretations of students’ motivation and learning beliefs. Although no statistically significant differences in achievement were found across clusters, a High-Approach-Low-Avoidance cluster displayed an adaptive profile that was most positive towards learning and self but least anxious about exams. In contrast, a Performance-Avoidance-Dominant cluster demonstrated a maladaptive pattern of lowest self-efficacy and task value, and higher anxiety. Further, High-Approach-Low-Avoidance and Low-Performance-Avoidance clusters recognized that knowledge is not simple and authority could be questioned, compared to the other groups.