| Owner: |
Xin Tang
|
| Owner Email: |
tangxin09@gmail.com
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| Paper Title: |
High School Students' Optimal Learning Moments: A Network Analysis Approach
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| Session Title: |
Motivation in Education SIG Poster Session: Process, Methods, and Outcomes
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| Paper Type: |
Poster Presentation
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| Presentation Date: |
4/19/2020
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| Presentation Location: |
Online
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| Descriptors: |
Emotion/Emotional Regulation, Motivation, Research Methodology
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| Methodology: |
Quantitative
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| Author(s): |
Xin Tang, University of Helsinki; Jari Lavonen, University of Helsinki; Barbara Schneider, Michigan State University; Joseph S. Krajcik, Michigan State University; Katariina Salmela-Aro, Cicero Learning, University of Helsinki
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| Unit: |
SIG-Motivation in Education
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| Abstract: |
The present study examined the emotional and motivational correlates of optimal learning moments (OLM) by using the co-occurrence network analysis and by including data in and outside of school settings. Two first-year high school samples were measured using the experience sampling method. The first sample consisted of 282 students and was assessed in science lessons only. The second sample consisted of 59 students and was assessed over two weeks in and outside of school. The results, in general, were consistent across the situations, which shows OLM co-occurred highly with positive emotions and motivations (e.g., enjoyment, concentration, success). However, OLM only co-occurred moderately with epistemic emotions such as curiosity and inquisitiveness, but those co-occurrences were higher in school settings.
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| DOI: |
https://doi.org/10.3102/1574486
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