Prediction of the Factors Affecting PISA Mathematics Literacy of Students from Different Countries by Using Data Mining Methods

Autor/inn/en	Aksu, Nursah; Aksu, Gökhan; Saracaloglu, Seda
Titel	Prediction of the Factors Affecting PISA Mathematics Literacy of Students from Different Countries by Using Data Mining Methods
Quelle	In: International Electronic Journal of Elementary Education, 14 (2022) 5, S.613-629 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Aksu, Nursah) ORCID (Aksu, Gökhan) ORCID (Saracaloglu, Seda)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1307-9298
Schlagwörter	Predictor Variables; International Assessment; Achievement Tests; Foreign Countries; Secondary School Students; Numeracy; Data Analysis; Mathematics Achievement; Socioeconomic Status; Time on Task; Parent Background; Educational Attainment; Singapore; Japan; Norway; United States; Turkey; Dominican Republic; Program for International Student Assessment + Suchen Sie Ihr Suchwort? Prädiktor; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen; Ausland; Sekundarschüler; Rechenkompetenz; Auswertung; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Socio-economic status; Sozioökonomischer Status; Zeitaufwand; Elternhaus; Bildungsabschluss; Bildungsgut; Singapur; Norwegen; USA; Türkei; Dominikanische Republik
Abstract	The purpose of this study is to predict the mathematical literacy levels of the students participating in the research through the data obtained from PISA 2015 exam organized by OECD using data mining and to determine the variables that affect mathematics literacy. For this purpose, students' mathematics literacy levels and the variables that affect their mathematics literacy levels were analyzed separately for 6 different countries at different proficiency levels. The population of the research is 519334 students from 72 countries, who have taken PISA 2015 exam. The sample that was determined according to the purpose of the study consists of a total of 34,565 students from Singapore, Japan, Norway, the USA, Turkey, and the Dominican Republic, which have been observed to be at different proficiency levels. In the first stage of the study, analyzes were performed using data mining prediction methods. At this stage, WEKA program was employed and M5P algorithm, which is one of the most common methods, was used. In the second stage of the research, the output variable was predicted from the input variables using Artificial Neural Networks methods to determine the extent to which decision trees obtained by M5P prediction method produce valid results. In the analyzes carried out in MATLAB program, the relationship between students' actual math literacy scores and literacy scores predicted from input variables was examined. As a result of the study, the variables that affect mathematics literacy were found to be the socio-economic status index for Singapore, Norway, the United States, Turkey, and Dominic. On the other hand, the variables influencing mathematics literacy for Japan were found to be mathematics learning time and father's education level. The consistency of the results was as follows: 86.10% for Singapore, 40.26% for Japan, 30.10% for Norway, 39.15% for America, 26.43% for Turkey, and 29.24 % for Dominic. As a result of the study, a differentiation was found among the variables that affect mathematics literacy of the countries at different proficiency levels. (As Provided).
Anmerkungen	International Electronic Journal of Elementary Education. T&K Akademic Rosendalsvein 45, Oslo 1166, Norway. e-mail: iejee@iejee.com; Web site: https://www.iejee.com/index.php/IEJEE/index
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01