2022 Conference Archive
Deep Learning: Connecting Student Needs and Motivation to Metacognition
Copyright
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Conference Tracks
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.
Session Format
Research Brief and Reflection Panels
1
Publication Type and Release Option
Image (Open Access)
Recommended Citation
Langdon, Jody L.; Botnaru, Diana; and Van Arkel, Johanna, "Deep Learning: Connecting Student Needs and Motivation to Metacognition" (2022). SoTL Commons Conference. 54.
https://digitalcommons.georgiasouthern.edu/sotlcommons/SoTL/2022/54
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.
