Florian Schimanke, R. Mertens, Bettina Sophie Huck
{"title":"Player Types in Mobile Learning Games – Playing Patterns and Motivation","authors":"Florian Schimanke, R. Mertens, Bettina Sophie Huck","doi":"10.1109/ISM.2018.00035","DOIUrl":null,"url":null,"abstract":"This paper presents results from an analysis of player behavior in the popular mobile learning game \"Where is that\". Playing data of nearly 24,000 unique users were gathered over a period of three months and subsequently analyzed in order to get a better insight in how games are played. The results will then further be used to compare learning results with a spaced repetition approach. Our analysis revealed four distinct clusters of learner types that can be categorized as Learners, Confirmers, Leisure Players and Sporadic Players. The data shows the player types' playing patterns and gives indications about what motivates them to play. It can thus give valuable hints for the design of player interaction in learning games as well as content selection.","PeriodicalId":308698,"journal":{"name":"2018 IEEE International Symposium on Multimedia (ISM)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Symposium on Multimedia (ISM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISM.2018.00035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents results from an analysis of player behavior in the popular mobile learning game "Where is that". Playing data of nearly 24,000 unique users were gathered over a period of three months and subsequently analyzed in order to get a better insight in how games are played. The results will then further be used to compare learning results with a spaced repetition approach. Our analysis revealed four distinct clusters of learner types that can be categorized as Learners, Confirmers, Leisure Players and Sporadic Players. The data shows the player types' playing patterns and gives indications about what motivates them to play. It can thus give valuable hints for the design of player interaction in learning games as well as content selection.
本文将呈现对热门手机学习游戏《Where is that》中的玩家行为的分析结果。我们在3个月内收集了近2.4万名独立用户的游戏数据,并对其进行了分析,以便更好地了解游戏的玩法。这些结果将进一步用于与间隔重复法的学习结果进行比较。我们的分析揭示了四种不同的学习者类型,可分为学习者、确认者、休闲玩家和零星玩家。这些数据显示了玩家类型的游戏模式,并给出了他们玩游戏的动机。因此,它可以为学习型游戏的玩家交互设计和内容选择提供有价值的提示。