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http://dx.doi.org/10.14352/jkaie.2018.22.2.205

Analysis of error data generated by prospective teachers in programming learning  

Moon, Wae-shik (Dept. of Computer Education, Chinju National University of Education)
Publication Information
Journal of The Korean Association of Information Education / v.22, no.2, 2018 , pp. 205-212 More about this Journal
Abstract
As a way to improve the software education ability of the pre - service teachers, we conducted programming learning using two types of programming tools (Python and Scratch) at the regular course time. In programming learning, various types of errors, which are factors that continuously hinder interest, achievement and creativity, were collected and analyzed by type. By using the analyzed data, it is possible to improve the ability of pre-service teachers to cope with the errors that can occur in the software education to be taught in the elementary school, and to improve the learning effect. In this study, logic error (37.63%) was the most frequent type that caused the most errors in programming in both conventional language that input text and language that assembles block. In addition, the detailed errors that show a lot of differences in the two languages are the errors of Python (14.3%) and scratch (3.5%) due to insufficient use of grammar and other errors.
Keywords
Programming language; text input language; drag and drop language; software error; error type;
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