Using Game Mechanics to Measure What Students Learn.

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Title: Using Game Mechanics to Measure What Students Learn.
Authors: Denner, Jill1 jilld@etr.org, Werner, Linda2 linda@soe.ucsc.edu, Campe, Shannon1 shannonc@etr.org, Ortiz, Eloy1 eloyo@etr.org
Source: Proceedings of the European Conference on Games Based Learning. 2021, p123-129. 7p.
Subject Terms: *Active learning, *COVID-19 pandemic, *School children, *Educational games, *Human behavior
Abstract: Despite the growing popularity of teaching children to program games, little is known about the benefits for learning. Making a game involves formulating complex problems, designing systems, and understanding human behavior, but these constructs have proven difficult to measure. In addition, studies of what children learn often ignore the social context in which game programming occurs. In this article, we propose that game mechanics can be used as a window into how the children are thinking and we describe a strategy for using them to analyze students’ games. We describe how the game mechanics categories were identified, and the results of the game analysis, including variation in the mechanics used by students working alone or with a partner. The study involved sixty 10‐14 year old students in the US who spent 10 hours learning to use the Alice programming environment, and 10 hours designing and creating their games, alone or with a partner. Forty games were coded for five game mechanics that require the programmers to think in ways that are dynamic, time dependent, or complex. The results suggest that students were most likely to include mechanics that engage the player and programmer in thinking about dynamic systems, and least likely to include reasoning that resulted in a conditional change in game state based on time. Working with a partner resulted in a broader range of mechanics, which suggests a deeper understanding of how to formulate problems, design systems to represent them, and consider the interaction of the player with that system. The findings contribute to efforts to assess what novice programmers learn by creating games, and suggest that the analysis of game mechanics is a useful strategy for assessing the range of complex problem solving during game design and programming. The findings can also contribute to efforts to create developmentally appropriate instructional approaches that engage students in complex problem solving. [ABSTRACT FROM AUTHOR]
Copyright of Proceedings of the European Conference on Games Based Learning is the property of Academic Conferences & Publishing International Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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DbLabel: Education Research Complete
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PubType: Conference
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  Data: Using Game Mechanics to Measure What Students Learn.
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  Data: <searchLink fieldCode="AR" term="%22Denner%2C+Jill%22">Denner, Jill</searchLink><relatesTo>1</relatesTo><i> jilld@etr.org</i><br /><searchLink fieldCode="AR" term="%22Werner%2C+Linda%22">Werner, Linda</searchLink><relatesTo>2</relatesTo><i> linda@soe.ucsc.edu</i><br /><searchLink fieldCode="AR" term="%22Campe%2C+Shannon%22">Campe, Shannon</searchLink><relatesTo>1</relatesTo><i> shannonc@etr.org</i><br /><searchLink fieldCode="AR" term="%22Ortiz%2C+Eloy%22">Ortiz, Eloy</searchLink><relatesTo>1</relatesTo><i> eloyo@etr.org</i>
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  Data: <searchLink fieldCode="JN" term="%22Proceedings+of+the+European+Conference+on+Games+Based+Learning%22">Proceedings of the European Conference on Games Based Learning</searchLink>. 2021, p123-129. 7p.
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  Data: *<searchLink fieldCode="DE" term="%22Active+learning%22">Active learning</searchLink><br />*<searchLink fieldCode="DE" term="%22COVID-19+pandemic%22">COVID-19 pandemic</searchLink><br />*<searchLink fieldCode="DE" term="%22School+children%22">School children</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+games%22">Educational games</searchLink><br />*<searchLink fieldCode="DE" term="%22Human+behavior%22">Human behavior</searchLink>
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  Data: Despite the growing popularity of teaching children to program games, little is known about the benefits for learning. Making a game involves formulating complex problems, designing systems, and understanding human behavior, but these constructs have proven difficult to measure. In addition, studies of what children learn often ignore the social context in which game programming occurs. In this article, we propose that game mechanics can be used as a window into how the children are thinking and we describe a strategy for using them to analyze students’ games. We describe how the game mechanics categories were identified, and the results of the game analysis, including variation in the mechanics used by students working alone or with a partner. The study involved sixty 10‐14 year old students in the US who spent 10 hours learning to use the Alice programming environment, and 10 hours designing and creating their games, alone or with a partner. Forty games were coded for five game mechanics that require the programmers to think in ways that are dynamic, time dependent, or complex. The results suggest that students were most likely to include mechanics that engage the player and programmer in thinking about dynamic systems, and least likely to include reasoning that resulted in a conditional change in game state based on time. Working with a partner resulted in a broader range of mechanics, which suggests a deeper understanding of how to formulate problems, design systems to represent them, and consider the interaction of the player with that system. The findings contribute to efforts to assess what novice programmers learn by creating games, and suggest that the analysis of game mechanics is a useful strategy for assessing the range of complex problem solving during game design and programming. The findings can also contribute to efforts to create developmentally appropriate instructional approaches that engage students in complex problem solving. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Proceedings of the European Conference on Games Based Learning is the property of Academic Conferences & Publishing International Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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        PageCount: 7
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      – SubjectFull: Active learning
        Type: general
      – SubjectFull: COVID-19 pandemic
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      – SubjectFull: School children
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      – SubjectFull: Educational games
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      – SubjectFull: Human behavior
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      – TitleFull: Using Game Mechanics to Measure What Students Learn.
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            NameFull: Denner, Jill
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            NameFull: Werner, Linda
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            NameFull: Campe, Shannon
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            – D: 01
              M: 01
              Text: 2021
              Type: published
              Y: 2021
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