Using gameplay data to investigate students' problem-solving behaviors in Zoombinis

Tongxi Liu*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

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Abstract

One of the most critical intellectual abilities in today’s K-12 education is problem-solving skills. In game-based learning environments, it is essential to analyze students’ problem-solving behaviors so that instructors and researchers can provide timely feedback and relevant interventions. However, it is difficult to comprehend how students solve problems in games because game-based learning is always implicit and complicated. This study aims to investigate students’ problem-solving behaviors in a specific puzzle-based game context. Specifically, we used the Continuous Hidden Markov Model (CHMM) to identify students’ problem-solving stages, as well as sequence analysis to examine their problem-solving strategies. According to the findings, CHMM performed well to determine students’ problem-solving stages, and sequence analysis efficiently identified five problem-solving strategies. By applying the integrated techniques, we automatically categorized students’ real-time problem-solving behaviors and examined frequent strategies they applied, which can be used to better understand students’ problem-solving processes and provide real-time interventions for future studies.
Original languageEnglish
Title of host publicationCompanion Proceedings of the 12th International Conference on Learning Analytics & Knowledge, LAK22
Subtitle of host publicationLearning Analytics for Transition, Disruption and Social Change
PublisherSociety for Learning Analytics Research
Pages33-35
Number of pages3
Publication statusPublished - 21 Mar 2022
Event12th International Conference on Learning Analytics & Knowledge, LAK22: Learning Analytics for Transition, Disruption and Social Change - Virtual
Duration: 21 Mar 202225 Mar 2022
https://www.solaresearch.org/events/lak/lak22/
https://www.solaresearch.org/wp-content/uploads/2022/03/LAK22_CompanionProceedings.pdf
https://dl.acm.org/doi/proceedings/10.1145/3506860

Conference

Conference12th International Conference on Learning Analytics & Knowledge, LAK22
Period21/03/2225/03/22
Internet address

User-Defined Keywords

  • Hidden Markov Model
  • Sequence analysis
  • Problem-solving behaviors

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