EXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING

The aim of the study is to examine middle school students’ interest in STEM professions using data mining. Data mining is one of the data analysis methods used successfully in different fields, including education, in recent years. Classification analysis and decision tree techniques, which are amon...

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Autores principales:	Sevda GÖKTEPE YILDIZ, Seda GÖKTEPE KÖRPEOĞLU
Formato:	article
Lenguaje:	DE EN FR TR
Publicado:	Fırat University 2021
Materias:	educational data mining stem interest in stem professions middle school students Social Sciences H Social sciences (General) H1-99
Acceso en línea:	https://doaj.org/article/40514a5399e347e48a39549e71ae793f
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spelling	oai:doaj.org-article:40514a5399e347e48a39549e71ae793f2021-11-24T09:20:33ZEXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING2148-416310.29228/JASSS.45987https://doaj.org/article/40514a5399e347e48a39549e71ae793f2021-01-01T00:00:00Zhttps://jasstudies.com/index.jsp?mod=tammetin&makaleadi=f91a8f49-7d1a-46f1-8d08-8e6d0adcbd42.pdf&key=45987https://doaj.org/toc/2148-4163The aim of the study is to examine middle school students’ interest in STEM professions using data mining. Data mining is one of the data analysis methods used successfully in different fields, including education, in recent years. Classification analysis and decision tree techniques, which are among the educational data mining methods, are used in this study. The sample of the study consists of 300 middle school students from different classes in various districts of Istanbul. The research has a descriptive feature and is conducted in accordance with the general survey model. The data in the study were collected through the STEM Career Interest Survey (STEM-CIS). STEM-CIS consists of four sub-dimensions (science, mathematics, technology, engineering professions) and personal information sections. The information in the personal information section of the scale is related to the type of school, grade level, gender, academic achievement, mother and father occupation, education level of the mother and father, income level, number of family members, number of siblings and are the variables whose effects have been investigated in this study. According to the results of the research, J48 algorithm is the algorithm with the highest accuracy rate in classifying data. It is seen that the father occupation variable has the most important effect on students’ interest in STEM professions. In addition, in the classification, after the father occupation variable, the variables of mother occupation, mother's education level and gender have the most important effects, respectively. Regarding the effect of other variables examined in the study, different groups can be studied. A longitudinal study can be conducted to measure whether students’ interest in STEM professions has changed during high school years. It is thought that this study will shed light on future studies in terms of being an example of the application of data mining to the field of educational sciences.Sevda GÖKTEPE YILDIZSeda GÖKTEPE KÖRPEOĞLUFırat Universityarticleeducational data miningsteminterest in stem professionsmiddle school studentsSocial SciencesHSocial sciences (General)H1-99DEENFRTRJournal of Academic Social Science Studies , Vol 13, Iss 83, Pp 89-106 (2021)
institution	DOAJ
collection	DOAJ
language	DE EN FR TR
topic	educational data mining stem interest in stem professions middle school students Social Sciences H Social sciences (General) H1-99
spellingShingle	educational data mining stem interest in stem professions middle school students Social Sciences H Social sciences (General) H1-99 Sevda GÖKTEPE YILDIZ Seda GÖKTEPE KÖRPEOĞLU EXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING
description	The aim of the study is to examine middle school students’ interest in STEM professions using data mining. Data mining is one of the data analysis methods used successfully in different fields, including education, in recent years. Classification analysis and decision tree techniques, which are among the educational data mining methods, are used in this study. The sample of the study consists of 300 middle school students from different classes in various districts of Istanbul. The research has a descriptive feature and is conducted in accordance with the general survey model. The data in the study were collected through the STEM Career Interest Survey (STEM-CIS). STEM-CIS consists of four sub-dimensions (science, mathematics, technology, engineering professions) and personal information sections. The information in the personal information section of the scale is related to the type of school, grade level, gender, academic achievement, mother and father occupation, education level of the mother and father, income level, number of family members, number of siblings and are the variables whose effects have been investigated in this study. According to the results of the research, J48 algorithm is the algorithm with the highest accuracy rate in classifying data. It is seen that the father occupation variable has the most important effect on students’ interest in STEM professions. In addition, in the classification, after the father occupation variable, the variables of mother occupation, mother's education level and gender have the most important effects, respectively. Regarding the effect of other variables examined in the study, different groups can be studied. A longitudinal study can be conducted to measure whether students’ interest in STEM professions has changed during high school years. It is thought that this study will shed light on future studies in terms of being an example of the application of data mining to the field of educational sciences.
format	article
author	Sevda GÖKTEPE YILDIZ Seda GÖKTEPE KÖRPEOĞLU
author_facet	Sevda GÖKTEPE YILDIZ Seda GÖKTEPE KÖRPEOĞLU
author_sort	Sevda GÖKTEPE YILDIZ
title	EXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING
title_short	EXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING
title_full	EXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING
title_fullStr	EXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING
title_full_unstemmed	EXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING
title_sort	examination of middle school students’ interests in stem professions using educational data mining
publisher	Fırat University
publishDate	2021
url	https://doaj.org/article/40514a5399e347e48a39549e71ae793f
work_keys_str_mv	AT sevdagoktepeyildiz examinationofmiddleschoolstudentsinterestsinstemprofessionsusingeducationaldatamining AT sedagoktepekorpeoglu examinationofmiddleschoolstudentsinterestsinstemprofessionsusingeducationaldatamining
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EXAMINATION OF MIDDLE SCHOOL STUDENTS’ INTERESTS IN STEM PROFESSIONS USING EDUCATIONAL DATA MINING

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