Using gameplay data to examine learning behavior patterns in a serious game.
Research has shown how open-ended serious games can facilitate students' development of specific skills and improve learning performance through problem-solving. However, understanding how students learn these complex skills in a game environment is a challenge, as much research uses typical paper-a...
| Publicado en: | Computers in Human Behavior Vol. 72; pp. 757 - 771 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Elsevier B.V.
Jul2017
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=122721664&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 122721664 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07475632 JC4 jtl: Computers in Human Behavior issn: 07475632 maglogo: N pubinfo: dt: Jul2017 vid: 72 pid: 2410 pub: Elsevier B.V. artinfo: ui: 122721664 10.1016/j.chb.2016.09.062 ppf: 757 ppct: 14 formats: tig: atl: Using gameplay data to examine learning behavior patterns in a serious game. aug: au: Kang, Jina Liu, Min Qu, Wen affil: Learning Technologies Program, The University of Texas at Austin, 1912 Speedway Stop D5700, Austin, TX, 78712-1293, USA Quantitative Psychology Program, University of Notre Dame, 118 Haggar Hall, Notre Dame, IN, 46556, USA su: Games Interviewing Problem solving Learning strategies Data analytics sug: subj: Games Interviewing Problem solving Doll, Toy, and Game Manufacturing Hobby, Toy, and Game Stores Toy and Hobby Goods and Supplies Merchant Wholesalers Learning strategies Data analytics keyword: Learning behavior Learning process Middle school science Pattern mining Problem-solving Serious games analytics Learning behavior Learning process Middle school science Pattern mining Problem-solving Serious games analytics ab: Research has shown how open-ended serious games can facilitate students' development of specific skills and improve learning performance through problem-solving. However, understanding how students learn these complex skills in a game environment is a challenge, as much research uses typical paper-and-pencil assessments and self-reported surveys or other traditional observational and quantitative methods. The purpose of this study is to identify students' learning behavior patterns of problem-solving and explore behavior patterns of different performing groups within an open-ended serious game called Alien Rescue . To accomplish this purpose, this study intends to use gameplay data by incorporating sequential pattern mining and statistical analysis. The findings of this study confirmed the results from previous research (using ex situ data such as interviews) and at the same time provide an analytical approach to understand in-depth students' sequential behavior patterns using in situ gameplay data. This study examined the frequent sequential patterns between low- and high-performing students and showed that problem-solving strategies were different between these two performing groups. By using this integrated analytical method, we can gain a better understanding of the learning pathway of students’ performance and problem-solving strategies of students with different learning characteristics in a serious games context. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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