Student Profiles Based on In-Game Performance and Help-Seeking Behaviors in an Online Mathematics Game

• In Event: Immersive Technology and Learning

Abstract

We examined how 7th-grade students (N = 760) in-game performance (the efficiency of problem-solving, the validity of the first action, the frequency of mathematical errors) and help-seeking behaviors (hint request) correlate with their algebraic knowledge in an online mathematics game. The k-means cluster analysis identified four groups of students based on their in-game metrics, and some variabilities in their in-game performance were found. Although hint requests were available, only a few students showed a high percentage of hint requests. The regression analysis revealed that students' in-game performance patterns explained a significant amount of variance in students' algebraic knowledge above and beyond students' prior knowledge, implying that in-game metrics captured using log data provide meaningful information to student understandings and learning.

Authors

• Reilly E. Norum, Worcester Polytechnic Institute
  Presenting Author

• Ji-Eun Lee, Worcester Polytechnic Institute
  Presenting Author

• Erin R Ottmar, Worcester Polytechnic Institute
  Presenting Author