Collaborative problem-solving process in a science serious game: Exploring group action similarity trajectory

Jina Kang, Dongwook An, Lili Yan, Min Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Collaborative problem-solving (CPS) as a key competency required in the 21st century. There has been an increasing need to understand CPS since it involves not only cognitive but also social processes, and thus its process is difficult to examine. Recent research has highlighted that computer-based learning environments provide an opportunity for students to collaborate with others to solve scientific problems and facilitate their knowledge building process, which can be dynamically tracked within the systems. However, limited research has attempted to identify CPS process captured in the computer-based learning environments designed for supporting CPS. This study therefore aimed to investigate students' CPS process in a serious game, Alien Rescue, by analyzing a student's daily tool use action sequence generated in the game. First, we computed a daily gameplay action similarity among students in a group using a similarity coefficient, Jaccard (Jac). Each group's Jac coefficients over the entire gameplay period (i.e. six days over three weeks) were considered as the group action similarity trajectory. The Jac coefficient of each day was entered as a single feature (i.e. a total of six features) to conduct a KmL cluster analysis that clusters longitudinal data. Three clusters of groups with similar behavior traits (i.e. group action similarity trajectories) were identified. The groups' background information (e.g. solution scores, knowledge gain scores) further provided how the groups' CPS traits can be related to their learning performance.

Original languageEnglish (US)
Title of host publicationEDM 2019 - Proceedings of the 12th International Conference on Educational Data Mining
EditorsCollin F. Lynch, Agathe Merceron, Michel Desmarais, Roger Nkambou
PublisherInternational Educational Data Mining Society
Pages336-341
Number of pages6
ISBN (Electronic)9781733673600
StatePublished - 2019
Externally publishedYes
Event12th International Conference on Educational Data Mining, EDM 2019 - Montreal, Canada
Duration: Jul 2 2019Jul 5 2019

Publication series

NameEDM 2019 - Proceedings of the 12th International Conference on Educational Data Mining

Conference

Conference12th International Conference on Educational Data Mining, EDM 2019
Country/TerritoryCanada
CityMontreal
Period7/2/197/5/19

Keywords

  • Collaborative problem-solving
  • Jaccard coefficient
  • KmL cluster analysis
  • Learning process
  • Science learning
  • Serious game

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications

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