Identifying Player Strategies Through Segmentation: An Interactive Process Visualization Approach

Zhaoqing Teng*, Jonattan Holmes, Francis Dominguez, Johannes Pfau, Mario Escarce Junior, Magy Seif El-Nasr

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Identifying learners’ problem-solving strategies from telemetry data is a critical task for serious games. Traditional methods like sequence mining, text replays, and statistical analysis often necessitate labor-intensive manual iterations to configure data appropriately and typically focus only on predominant trends. To improve our understanding of learner behaviors, this paper introduces a novel interactive visualization system that leverages player journeys-node-edge graphs depicting trends in sequences of player actions. We also present player segmentation, a new approach aimed at revealing and representing strategies that might otherwise be ignored, filtered out, or dismissed as outliers. We evaluated the effectiveness of our system through a mixed-methods study with 12 participants from our target demographic (game analysts). The results show that segmentation significantly reduces the time needed to identify strategies, suggesting that categorizing data based on causal factors can offer analysts more intuitive and insightful explanations.

Original languageEnglish
Title of host publicationSerious Games - 10th Joint International Conference, JCSG 2024, Proceedings
EditorsJan L. Plass, Xavier Ochoa
PublisherSpringer
Pages77-90
Number of pages14
ISBN (Electronic)978-3-031-74138-8
ISBN (Print)978-3-031-74137-1
DOIs
Publication statusPublished - 31 Oct 2024
Event10th Joint Conference on Serious Games, JCSG 2024 - New York City, United States
Duration: 7 Nov 20248 Nov 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15259 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Joint Conference on Serious Games, JCSG 2024
Country/TerritoryUnited States
CityNew York City
Period7/11/248/11/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

  • learning analytics
  • mixed-methods evaluation
  • segmentation
  • visual analytics
  • visualization systems

Fingerprint

Dive into the research topics of 'Identifying Player Strategies Through Segmentation: An Interactive Process Visualization Approach'. Together they form a unique fingerprint.

Cite this