Data-driven goal setting: Searching optimal badges in the decision forest
Goal setting is vital in learning sciences, but the scientific evaluation of optimal learning goals is underexplored. This study proposes a novel methodological approach to determine optimal learning goals. The data in this study comes from a gamified learning app implemented in an undergraduate acc...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | Telematics and Informatics Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772503023000324 |
| _version_ | 1797677712649748480 |
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| author | Julian Langenhagen |
| author_facet | Julian Langenhagen |
| author_sort | Julian Langenhagen |
| collection | DOAJ |
| description | Goal setting is vital in learning sciences, but the scientific evaluation of optimal learning goals is underexplored. This study proposes a novel methodological approach to determine optimal learning goals. The data in this study comes from a gamified learning app implemented in an undergraduate accounting course at a large German university. With a combination of decision trees and regression analyses, the goals connected to the badges implemented in the app are evaluated. The results show that the initial badge set already motivated learning strategies that led to better grades on the exam. However, the results indicate that the levels of the goals could be improved, and additional badges could be implemented. In addition to new goal levels, new goal types are also discussed. The findings show that learning goals initially determined by the instructors need to be evaluated to offer an optimal motivational effect. The new methodological approach used in this study can be easily transferred to other learning data sets to provide further insights. |
| first_indexed | 2024-03-11T22:49:13Z |
| format | Article |
| id | doaj.art-dd560a41327446fc9b65a5ba389ffd59 |
| institution | Directory Open Access Journal |
| issn | 2772-5030 |
| language | English |
| last_indexed | 2024-03-11T22:49:13Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Telematics and Informatics Reports |
| spelling | doaj.art-dd560a41327446fc9b65a5ba389ffd592023-09-22T04:40:04ZengElsevierTelematics and Informatics Reports2772-50302023-09-0111100072Data-driven goal setting: Searching optimal badges in the decision forestJulian Langenhagen0Goethe University Frankfurt, Theodor-W.-Adorno-Platz 4, Frankfurt am Main, 60323, Hessen, GermanyGoal setting is vital in learning sciences, but the scientific evaluation of optimal learning goals is underexplored. This study proposes a novel methodological approach to determine optimal learning goals. The data in this study comes from a gamified learning app implemented in an undergraduate accounting course at a large German university. With a combination of decision trees and regression analyses, the goals connected to the badges implemented in the app are evaluated. The results show that the initial badge set already motivated learning strategies that led to better grades on the exam. However, the results indicate that the levels of the goals could be improved, and additional badges could be implemented. In addition to new goal levels, new goal types are also discussed. The findings show that learning goals initially determined by the instructors need to be evaluated to offer an optimal motivational effect. The new methodological approach used in this study can be easily transferred to other learning data sets to provide further insights.http://www.sciencedirect.com/science/article/pii/S2772503023000324Goal settingGamificationBadgesLearning analyticsEducational data miningDecision trees |
| spellingShingle | Julian Langenhagen Data-driven goal setting: Searching optimal badges in the decision forest Telematics and Informatics Reports Goal setting Gamification Badges Learning analytics Educational data mining Decision trees |
| title | Data-driven goal setting: Searching optimal badges in the decision forest |
| title_full | Data-driven goal setting: Searching optimal badges in the decision forest |
| title_fullStr | Data-driven goal setting: Searching optimal badges in the decision forest |
| title_full_unstemmed | Data-driven goal setting: Searching optimal badges in the decision forest |
| title_short | Data-driven goal setting: Searching optimal badges in the decision forest |
| title_sort | data driven goal setting searching optimal badges in the decision forest |
| topic | Goal setting Gamification Badges Learning analytics Educational data mining Decision trees |
| url | http://www.sciencedirect.com/science/article/pii/S2772503023000324 |
| work_keys_str_mv | AT julianlangenhagen datadrivengoalsettingsearchingoptimalbadgesinthedecisionforest |