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Affective Sequences and Student Actions Within Reasoning Mind
Now that the modeling of affective states is beginning to mature, understanding affect dynamics has become an increasingly realistic endeavor. However, the results from empirical studies have not always matched those of theoretical models, which raises questions as to why. In this study, we explore...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334159/ http://dx.doi.org/10.1007/978-3-030-52237-7_35 |
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author | Ocumpaugh, Jaclyn Baker, Ryan S. Karumbaiah, Shamya Crossley, Scott A. Labrum, Matthew |
author_facet | Ocumpaugh, Jaclyn Baker, Ryan S. Karumbaiah, Shamya Crossley, Scott A. Labrum, Matthew |
author_sort | Ocumpaugh, Jaclyn |
collection | PubMed |
description | Now that the modeling of affective states is beginning to mature, understanding affect dynamics has become an increasingly realistic endeavor. However, the results from empirical studies have not always matched those of theoretical models, which raises questions as to why. In this study, we explore the relationship between affective sequences that have been previously explored in the literature and the activities students may engage in when interacting with Reasoning Mind, a blended learning system for elementary mathematics. The strongest correlations are found for students who shift from engaged concentration to frustration, making fewer actions in the system. While confusion is generally associated with positive patterns, and frustration and boredom have unexpectedly similar implications for student activity. |
format | Online Article Text |
id | pubmed-7334159 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73341592020-07-06 Affective Sequences and Student Actions Within Reasoning Mind Ocumpaugh, Jaclyn Baker, Ryan S. Karumbaiah, Shamya Crossley, Scott A. Labrum, Matthew Artificial Intelligence in Education Article Now that the modeling of affective states is beginning to mature, understanding affect dynamics has become an increasingly realistic endeavor. However, the results from empirical studies have not always matched those of theoretical models, which raises questions as to why. In this study, we explore the relationship between affective sequences that have been previously explored in the literature and the activities students may engage in when interacting with Reasoning Mind, a blended learning system for elementary mathematics. The strongest correlations are found for students who shift from engaged concentration to frustration, making fewer actions in the system. While confusion is generally associated with positive patterns, and frustration and boredom have unexpectedly similar implications for student activity. 2020-06-09 /pmc/articles/PMC7334159/ http://dx.doi.org/10.1007/978-3-030-52237-7_35 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Ocumpaugh, Jaclyn Baker, Ryan S. Karumbaiah, Shamya Crossley, Scott A. Labrum, Matthew Affective Sequences and Student Actions Within Reasoning Mind |
title | Affective Sequences and Student Actions Within Reasoning Mind |
title_full | Affective Sequences and Student Actions Within Reasoning Mind |
title_fullStr | Affective Sequences and Student Actions Within Reasoning Mind |
title_full_unstemmed | Affective Sequences and Student Actions Within Reasoning Mind |
title_short | Affective Sequences and Student Actions Within Reasoning Mind |
title_sort | affective sequences and student actions within reasoning mind |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334159/ http://dx.doi.org/10.1007/978-3-030-52237-7_35 |
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