Do Scientific Reasoning Processes Predict Motivation During Game-Based Learning Using Multichannel Data?

• In Event: AERA Poster Session 6
  In Poster Session: Motivation and Self-Regulation in Technology-Based Environments

Abstract

Understanding relationships between scientific-reasoning processes and motivation while learning continues to be a challenge with game-based learning environments (GBLEs). We examined whether scientific-reasoning processes, captured using eye tracking and performance, predicted Intrinsic Motivation Inventory (IMI) scores after game-based learning with CRYSTAL ISLAND. Ninety-nine students attempted to solve an illness by gathering clues about microbiology and testing hypotheses to provide a correct diagnosis to complete the game. Analyses revealed predictive relationships between IMI scores and average time fixating on areas-of-interest related to scientific-reasoning processes. Additionally, IMI scores predicted final-game score (i.e., in-game actions toward solving the mystery) but not performance on pre/post-test assessments. Implications are provided toward designing adaptive GBLEs that capture scientific-reasoning processes to optimize learning using multichannel data.

Authors

• Elizabeth Brooke Cloude, University of Central Florida

• Megan Wiedbusch, University of Central Florida

• Franz Wortha, Universität Greifswald

• Roger Azevedo, University of Central Florida

• James Lester, North Carolina State University