Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior
Educational video games, with various motivational features and scaffolding support, have high potential for facilitating optimal learning and achievement. However, research on how students utilize game features, identify useful information, and explore solutions to in-game problem scenarios continu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Computers and Education Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666557322000441 |
| _version_ | 1828118372849549312 |
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| author | Zhenhua Xu Ana Zdravkovic Matthew Moreno Earl Woodruff |
| author_facet | Zhenhua Xu Ana Zdravkovic Matthew Moreno Earl Woodruff |
| author_sort | Zhenhua Xu |
| collection | DOAJ |
| description | Educational video games, with various motivational features and scaffolding support, have high potential for facilitating optimal learning and achievement. However, research on how students utilize game features, identify useful information, and explore solutions to in-game problem scenarios continues to be under-researched. This study aims to unpack the mechanisms underlying users’ in-game behaviors to identify emergent markers of optimal problem-solving performance in an educational video game. Survey data and computer logs were collected from 61 participants (36.4% middle and high-school students, Mage = 13; 63.6% university students, Mage = 21) to address the research inquiry of the present study. Results from the regression analysis not only showed an important link between individual characteristics (i.e., self-efficacy, prior knowledge) and success-striving in-game behavior, but also highlighted the role of self-regulated help-seeking behavior in determining students’ optimal problem-solving pathways. Our findings add new perspectives to existing research of what learning behaviors are crucial for promoting self-regulation in digital game-based learning. These findings provide useful insight on how to design scaffolding tools in an open-ended problem-solving space to encourage student engagement in effective help-seeking behaviors for optimal learning performance. |
| first_indexed | 2024-04-11T13:30:10Z |
| format | Article |
| id | doaj.art-9e7a65a4997b483f828cb0a007c776c6 |
| institution | Directory Open Access Journal |
| issn | 2666-5573 |
| language | English |
| last_indexed | 2024-04-11T13:30:10Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computers and Education Open |
| spelling | doaj.art-9e7a65a4997b483f828cb0a007c776c62022-12-22T04:21:50ZengElsevierComputers and Education Open2666-55732022-12-013100117Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behaviorZhenhua Xu0Ana Zdravkovic1Matthew Moreno2Earl Woodruff3Department of Applied Psychology and Human Development, University of Toronto, Canada; Corresponding author at: University of Toronto, 252 Bloor St W, Toronto, ON. M5S 1V6, Canada.Department of Applied Psychology and Human Development, University of Toronto, CanadaDepartment of Curriculum, Teaching and Learning, University of Toronto, CanadaDepartment of Applied Psychology and Human Development, University of Toronto, CanadaEducational video games, with various motivational features and scaffolding support, have high potential for facilitating optimal learning and achievement. However, research on how students utilize game features, identify useful information, and explore solutions to in-game problem scenarios continues to be under-researched. This study aims to unpack the mechanisms underlying users’ in-game behaviors to identify emergent markers of optimal problem-solving performance in an educational video game. Survey data and computer logs were collected from 61 participants (36.4% middle and high-school students, Mage = 13; 63.6% university students, Mage = 21) to address the research inquiry of the present study. Results from the regression analysis not only showed an important link between individual characteristics (i.e., self-efficacy, prior knowledge) and success-striving in-game behavior, but also highlighted the role of self-regulated help-seeking behavior in determining students’ optimal problem-solving pathways. Our findings add new perspectives to existing research of what learning behaviors are crucial for promoting self-regulation in digital game-based learning. These findings provide useful insight on how to design scaffolding tools in an open-ended problem-solving space to encourage student engagement in effective help-seeking behaviors for optimal learning performance.http://www.sciencedirect.com/science/article/pii/S2666557322000441Digital game-based learningOptimal learning pathwaysIndividual learning characteristicsSelf-regulated help-seeking skillScaffolding tools |
| spellingShingle | Zhenhua Xu Ana Zdravkovic Matthew Moreno Earl Woodruff Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior Computers and Education Open Digital game-based learning Optimal learning pathways Individual learning characteristics Self-regulated help-seeking skill Scaffolding tools |
| title | Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior |
| title_full | Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior |
| title_fullStr | Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior |
| title_full_unstemmed | Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior |
| title_short | Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior |
| title_sort | understanding optimal problem solving in a digital game the interplay of learner attributes and learning behavior |
| topic | Digital game-based learning Optimal learning pathways Individual learning characteristics Self-regulated help-seeking skill Scaffolding tools |
| url | http://www.sciencedirect.com/science/article/pii/S2666557322000441 |
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