文章基本信息

标题：AUTOMATIC QUESTION CLASSIFICATION MODELS FOR COMPUTER PROGRAMMING EXAMINATION: A SYSTEMATIC LITERATURE REVIEW
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作者：MUSTAFA KADHIM TAQI ; ROSMAH ALI
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：93
期号：2
出版社：Journal of Theoretical and Applied
摘要：A test is the commonest method to evaluate the progress and potential of candidates in any field, especially in academic fields. In the academic field, exams help evaluate the understanding, applicative ability, and retainable knowledge of a student. Therefore, the questions need to be suitably set, so that all these areas can be judged. The results of these tests help determine if the student is fit for the next level of education. Setting the right question paper is a major challenge for the teachers concerned. The current study aims to analyze the ongoing question classification models with reference to the set of formulated research questions. In order to locate question classification models, relevant keywords were used in the search terms. A set of nine different studies were picked from the search processes. In the studies, 4 stands for journal articles, and 5 stands for conference papers. Question classification has been discussed in the computing domain, especially with respect to computer programming assessment. A more extensive examination of this classification reveals quite a few shortcomings of the prevailing classification methods. These include the absence of suitable taxonomy for computer programming questions, limitation in approaches to handle multi-labelling, and a need for methods compatible to tackle code-mixed question classification. Furthermore, the necessity to develop advanced hybrid feature selection methods in order to enhance the classification performance.
关键词：Question Classification; Feature Selection; Bloom Taxonomy; Computer Programming; Systematic Literature Review