Ability to Solve Complex Social Problems of Prospective Teachers according to Gender and Computational Thinking

Abstract

Entering the 21st century, computational thinking has become a basic skill that all students must have. This research aims to determine gender differences in learning outcomes to solve social problems, differences in students' levels of computational thinking by gender, and the influence of students' levels of computational thinking on learning outcomes in solving social problems. This research uses a descriptive verification method with a quantitative analysis approach. The number of research subjects was 256 students, who came from the Faculty of Teacher Training and Education, Sebelas Maret University. The quantitative data analysis used is based on the results of computational thinking ability tests using the Wilcoxon Test. Further analysis of this research uses K-Means for clustering, while analysis of the relationship between variables uses Spearman's rho. This research shows that there is an influence of gender on learning outcomes for solving social problems, there is no significant relationship between students' level of computational thinking and gender, and there is a significant influence of students' level of computational thinking on learning outcomes for solving social problems. The results of this research show that the two factors above play a large role in influencing student learning outcomes. This capability works in synergy with the computational level of thinking. With the right efforts, growing computational thinking skills can improve students' ability to solve various learning problems.