Education Data Mining on PISA 2015 Best Ranked Countries: What Makes the Students Go Well

Autor/inn/en	dos Santos, Roberta Alvarenga; Paulista, Cássio Rangel; da Hora, Henrique Rego Monteiro
Titel	Education Data Mining on PISA 2015 Best Ranked Countries: What Makes the Students Go Well
Quelle	In: Technology, Knowledge and Learning, 28 (2023) 1, S.47-78 (32 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (da Hora, Henrique Rego Monteiro)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2211-1662
DOI	10.1007/s10758-021-09572-9
Schlagwörter	Foreign Countries; Achievement Tests; International Assessment; Secondary School Students; High Achievement; Classification; Teamwork; Decision Making; Anxiety; Learning Motivation; Peer Relationship; Physical Activities; Ethics; Teacher Student Relationship; Information Technology; Data Analysis; Academic Aspiration; Employment; Homework; Time on Task; Cooperative Learning; Instructional Program Divisions; Comparative Education; Cross Cultural Studies; Program for International Student Assessment + Suchen Sie Ihr Suchwort? Ausland; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen; Sekundarschüler; Classification system; Klassifikation; Klassifikationssystem; Decision-making; Entscheidungsfindung; Angst; Motivation for studies; Lernmotivation; Peer-Beziehungen; Ethik; Teacher student relationships; Lehrer-Schüler-Beziehung; Informationstechnologie; Auswertung; Dienstverhältnis; Hausaufgabe; Zeitaufwand; Kooperatives Lernen; Vergleichende Erziehungswissenschaft; Cultural comparison; Kulturvergleich
Abstract	The demand for in-depth studies on educational data presupposes the application of technologies that allow data analysis of vast quantities, and subsequently, drawing relevant information and knowledge. The research objective herein is to employ data mining techniques on PISA databases to identify potential patterns that may explain the top-performing countries' success. Accounting for the methodology, data acquisition, bank creation, and countries' data extraction, we ran preprocessing and data cleaning and mining stages, respectively; in the last phase, we used the J48 method for classification purposes. From the decision trees, the study identified the relevant attributes which relate to student educational level aspiration; failure; motivation and anxiety; socioeconomic factors; scientific approaches; the use of information and communication technologies; interactions with friends; physical activity practice; paid work; home assignments; learning time for each discipline; cooperation and teamwork; the student's study program; the teacher's fairness; and the school year in which the student is enrolled. In this regard, results were considered satisfactory for allowing the analyses of these aforementioned relevant attributes associated with PISA best-ranked countries. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01