Causal Inference Thinking of Elementary School Teacher Professional Education Program Students in Determining Digital Strategies to Solve Mathematical Problems

Abstract

This research aims to examine the causal inference thinking of PPG PGSD students in solving mathematical problems. This research uses a qualitative approach with a case study type. The subjects of this research were four pre-service PPG students from PGSD UM. The instruments for this research include researchers, indicator rubrics, validation sheets, researcher notes, mathematical problems, internet networks, laptops, and handphones. Research subjects as data sources produce data that is analyzed in the form of written answers and recorded interviews. The qualitative data analysis technique used in this research is the interactive model. The results of this research show that fast causal inference thinking is characterized by expressing familiarity with mathematical problem solving, expressing familiarity with accessing digital platforms to solve mathematical problems, accessing digital platforms with keywords, correlating the characteristics of information with specific digital platforms, and Accessing specific digital platforms spontaneously. Slow Causal Inference Thinking is characterized by accessing more than one digital platform to understand a piece of information and read the math problem text repeatedly. The digital platforms that the subjects considered to be a solution were the Google and YouTube platforms.