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Generating Fill-in-Blank Tests to Detect Understanding Failures of Programming

Authors:
So Asai
Yoshiharu Yamauchi
Yusuke Kajiwara
Hiromitsu Shimakawa

Keywords: programming, e-learning, text mining, clutering

Abstract:
This paper proposes a method to generate a fill-inthe-blank test to detect the understanding failures of students in introductory programming course as early as possible. In programming class in educational institutions, what is important for novices is to make them acquire abilities to exert knowledge and skills in programming in an appropriate way according to each situation. The method pays special attention to the fact that students sharing specific understanding failures are likely to write similar inappropriate code. To generate a fill-in-the-blank test, the proposed method determines code fragments to be blanked out in model code, differentiating inappropriate code written by past students from the model code. An experiment has revealed the method can detect students having understanding failure with high precision rates. The fill-in-the-blank tests generated with our method prevent students from leaving their understanding failure unsolved, because teachers can intensively supervise students who fail to acquire abilities to fully exert the knowledge and the skills in the early stages of the programming course.

Pages: 25 to 32

Copyright: Copyright (c) IARIA, 2017

Publication date: September 10, 2017

Published in: conference

ISSN: 2308-4340

ISBN: 978-1-61208-583-8

Location: Rome, Italy

Dates: from September 10, 2017 to September 14, 2017