머신러닝 모델을 이용한 파이썬 자동채점 연습문제의 타당성 분석

Abstract

This paper analyzed the validity of exercise problems for each unit in Python programming education. Practice questions presentedfor each unit are presented through an online learning system, and each student uploads an answer code and is automaticallygraded. Data such as students’ mid-term exam scores, final exam scores, and practice questions scores for each unit are collectedthrough Python lecture that lasts for one semester. Through the collected data, it is possible to improve the exercise problems foreach unit by analyzing the validity of the automatic scoring exercise problems. In this paper, Orange machine learning tool wasused to analyze the validity of automatic scoring exercises. The data collected in the Python subject are analyzed and comparedcomprehensively by total, top, and bottom groups. From the prediction accuracy of the machine learning model that predicts thestudent’s final grade from the Python unit-by-unit practice problem scores, the validity of the automatic scoring exercises for eachunit was analyzed.