Developing an Artificial Intelligence Tutor for Game-Based Learning With a Focus on Self-Reported Emotions and Motivation

• In Event: AERA Poster Session 6
  In Poster Session: Games for 21st Century Learning (San Diego)

Abstract

This study considers higher education chemical engineering students’ experiences of game-based learning (GBL). The focus is on their self-reported emotions and experienced motivation. Through research, an artificial intelligence (AI)-based tutor for GBL was developed in the process industry field. The participating students (N = 70) played five NAPCON games to learn the basic control mechanisms and dynamics of the process industry, solve problems, and act in unexpected situations. After playing, the students’ experiences were examined using an online questionnaire (N = 49). The data indicated neutral feelings toward playing the NAPCON games. Optimistic emotions promoted the students’ motivation to learn and experiences of difficulty, while having to stretch their capability during gameplay increased their experienced stress.

Authors

• Hanna Vuojärvi, University of Lapland

• Marjaana Kangas, University of Lapland

• Heli Ruokamo, University of Lapland

• Liping Sun, University of Lapland