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Data-mining techniques in detecting factors linked to academic achievement.

Catalogue Information
Field name Details
Nuova numerazione 77319
Collocazione UPS BIBL CENTR SL-II-990
Autore MARTINÉZ ABAD, F.
Titolo Data-mining techniques in detecting factors linked to academic achievement. Parte componente di periodico
Descrizione fisica pp. 39-55.
Nota generale Estratto da: School Effectiveness and School Improvement 2017, 28, 1.
Riassunto In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental, cross-sectional design and a sample of 18,935 high school students from 99 educational institutions in Baja California state (Mexico). The information was collected from ENLACE tests and context surveys given to students in Baja Caclifornia. Decision trees were used to apply classification techniques, and the results indicate that personal factors are most indicative of academic performance, followed by school-related and social factors. In conclusion, the paper discusses the similarities between the results obtained and those shown in literature, highlighting how simple decision trees allow a greater explanation and interpretation than other models and techniques.
Tipo di documento RICERCA.
Soggetto SCIENZA.
RENDIMENTO.
ADOLESCENTI.
EDUCAZIONE.
COMPUTER.
AMBIENTE.
SCUOLA SUPERIORE.
TECNOLOGIA.
MESSICO.
Ambito Pedagogico
Autore Secondario CHAPARRO CASO LOPEZ, A. A.
Titolo correlato School Effectiveness and School Improvement 2017, 28, 1.
Accesso online http://search.ebscohost.com/login.aspx?direct=true&db=eue&AN=121184462&lang=it&site=ehost-live
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