Predictive reasoning of senior high school students in handling COVID-19 data

Abstract

The purpose of this study is to describe the characteristics of predictive reasoning made by students in solving graph-related problems, particularly related to COVID-19. This is a descriptive qualitative study with data collected from a sample size of 25 senior high school students and analyzed using the generalization-prediction task. The result revealed that there are three types of students’ predictive reasoning made based on (1) data observation, (2) data observation coupled with prior experience, and (3) data observation coupled with prior experience or knowledge. The experience used to make a prediction is obtained from personal life, classroom, and general knowledge about COVID-19. In conclusion, this study improves students’ understanding and ability to reason with graphs and future studies can be conducted with different prediction tasks.