Gender Differences in Cognitive Load when Applying Game-Based Learning with Intelligent Robots

Abstract

The application of artificial intelligence (AI) in education is now widespread, and the use of robots in education has demonstrated a positive influence on students’ behavior and development. However, the use of emerging technologies usually results in cognitive load, especially for elementary school students whose learning capacity has not yet been established. In addition, students of different genders have different physical, psychological and learning characteristics, so gender differences affect cognitive load. Cognitive load can be divided into two types: positive cognitive load and negative cognitive load. Usually, positive cognitive load results in good learning performance while negative cognitive load results in bad learning performance. Therefore, we use the cognitive load theory to define learning efficiency as the co-impact of learning performance and cognitive load. We take game-based intelligent robots for Chinese idiom learning as an example, and explore the impacts of gender differences on elementary school students. To achieve these aims, this study combined games and Zenbo robots, and applied them to educate elementary school students in the use of Chinese idioms. Secondly, this study conducted an experiment and analyzed the experimental results. The participants were 24 fourth-grade elementary school students from the central region of Taiwan. Results showed that this system is more beneficial for boys as their cognitive load was significantly lower. Boys’ learning performance was also better, although the difference did not reach significance. Furthermore, learning efficiency for boys was significantly higher. Reasons for these results are explained.

Keywords

• artificial intelligence
• cognitive load theory
• game-based learning
• gender differences
• robots