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When Anger Strikes: Using AI Modelling to Understand How Negative Emotions Impact Performance in Digital Math Games.

Ana Zdravkovic Barber1, Steve Engels2, Earl Woodruff1

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Summary
This summary is machine-generated.

Student anger negatively impacts digital math game performance. Emotional regulation support is crucial for effective digital math learning experiences.

Keywords:
AI ModellingAI emotion recognitionDigital Game-Based Learning Environment (DGBLE)affective dynamicsmathematics education

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Area of Science:

  • Educational Technology
  • Cognitive Psychology
  • Learning Sciences

Background:

  • Digital game-based learning environments (DGBLEs) are common in education.
  • Little is known about how student emotions affect digital gameplay performance.

Purpose of the Study:

  • Examine the influence of emotions and arousal on performance in DGBLEs.
  • Investigate differences in performance and emotional impact between math and non-math games.

Main Methods:

  • Thirty-two 5th-grade students played math and non-math digital games.
  • Real-time heart rate and affective data were collected.
  • An interpretable machine learning approach (XGBoost) analyzed the data.

Main Results:

  • Students performed better on non-math games than math games.
  • Real-time anger correlated with lower performance, especially in math games.
  • Other emotions and physiological measures did not significantly predict performance.

Conclusions:

  • Discrete emotions, particularly anger, significantly impact math game performance.
  • Emotional regulation is vital for optimizing digital math learning.
  • Findings underscore the importance of affective dynamics in DGBLEs.