Exploring the Affordances of Sequence Mining in Educational Games
Exploring the Affordances of Sequence Mining in Educational Games
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DOI：
10.1145/3434780.3436562
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Manuel J. Gomez;J. A. Ruipérez-Valiente;P. A. Martinez;Y. Kim
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文献类型：
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作者：
Manuel J. Gomez;J. A. Ruipérez-Valiente;P. A. Martinez;Y. Kim
游戏已经成为跨文化、跨年龄的最受欢迎的媒介之一，教育类游戏的使用也在不断增加。有充分的证据支持使用游戏进行学习和评估的好处。然而，我们通常不会发现游戏与教育环境相结合。教师面临的一个主要问题是，他们不知道学生是如何与游戏互动的，因为他们无法正确分析活动对学生的影响。为了改善这个问题，我们可以使用学生与此类教育游戏互动产生的数据，通过将原始数据转换为教师可解释和可操作的有意义的序列来分析序列和错误。在这项研究中，我们使用了来自游戏Shadowspect的数据收集，并使用过程和序列挖掘技术实现了学习分析，以生成两个指标，旨在帮助教师进行适当的评估并更好地理解过程。
Games have become one of the most popular mediums across cultures and ages and the use of educational games is growing. There is ample evidence that supports the benefits of using games for learning and assessment. However, we do not usually find games incorporated into educational environments. One of the main problems that teachers face is to actually know how students are interacting with the game as they cannot analyze properly the effect of the activity on the students. To improve this issue, we can use the data generated by the interaction of students with such educational games to analyze the sequences and errors by transforming raw data into meaningful sequences that are interpretable and actionable for teachers. In this study we use a data collection from our game Shadowspect and implement learning analytics with process and sequence mining techniques to generate two metrics that aim to help teachers make proper assessment and better understand the process.