Using Serious Game Analytics to Inform Digital Curricular Sequencing
| Autor: | Tiffany Barnes, Teomara Rutherford, Christa Cody, Sarah Kessler, Zhongxiu Peddycord-Liu, Collin F. Lynch |
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| Rok vydání: | 2017 |
| Předmět: |
Multimedia
business.industry Computer science 05 social sciences 050301 education Flexibility (personality) Serious game computer.software_genre Analytics ComputingMilieux_COMPUTERSANDEDUCATION Mathematics education Educational content 0501 psychology and cognitive sciences Digital learning business 0503 education computer 050104 developmental & child psychology |
| Zdroj: | CHI PLAY |
| DOI: | 10.1145/3116595.3116620 |
| Popis: | This paper applied serious game analytics to inform digital curricular sequencing in a longitude, curriculum-integrated math game, ST Math. When integrating serious games into classrooms, teachers may have the flexibility to change the order of math objectives for student groups to play. However, it is unclear how teacher decisions, as well as the sequencing of the original curricular order affect students. Moreover, few researchers have applied data-driven methods to inform content ordering in educational games, where the nature of educational content and student behaviors are different from many e-learning platforms. In this paper, we present a novel method that suggests curricular sequencing based on the prediction relationship between math objectives. Our results include specific design recommendations for ST Math, and general data-driven insights for digital curricular design, such as the pacing of objectives and the ordering of math concepts. Our method can potentially be applied to data from a wide range of games and digital learning platforms, enabling developers to better understand how to sequence educational content. |
| Databáze: | OpenAIRE |
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