Deep Learning: Connecting Student Needs and Motivation to Metacognition

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Assessment and SoTL - Research

Abstract

The present study investigated the relationships between basic need satisfaction, motivation, metacognitive learning approaches, and academic performance among 464 Anatomy and Physiology students. Overall, expected relationships were found between need satisfaction, autonomous forms of motivation, and deep learning. A more surprising result was that exam scores were only related to competence, introjected regulation, and identified regulation. Essentially, exam scores had no connection to metacognition. These findings suggest that these students were motivated in a variety of different ways that influenced the metacognitive strategies utilized.

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Research Brief and Reflection Panels

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Feb 24th, 3:45 PM

Deep Learning: Connecting Student Needs and Motivation to Metacognition

The present study investigated the relationships between basic need satisfaction, motivation, metacognitive learning approaches, and academic performance among 464 Anatomy and Physiology students. Overall, expected relationships were found between need satisfaction, autonomous forms of motivation, and deep learning. A more surprising result was that exam scores were only related to competence, introjected regulation, and identified regulation. Essentially, exam scores had no connection to metacognition. These findings suggest that these students were motivated in a variety of different ways that influenced the metacognitive strategies utilized.