Binary logistic regression classifying the gender of student towards computer learning in European schools

The authors presented a gender prediction model of student based on answers provided into survey during academic year 2011 in Europe. This experimental study is performed in R-language by applying logistic regression on the large data-set available on the website of European Commission. More than 25...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Verma Chaman
Stoffová Veronika
Illés Zoltán
Dahiya Sanjay
Testületi szerző: Conference of PhD students in computer science (11.) (2018) (Szeged)
Dokumentumtípus: Könyv része
Megjelent: 2018
Sorozat:Conference of PhD Students in Computer Science 11
Kulcsszavak:Számítástechnika
Online Access:http://acta.bibl.u-szeged.hu/61761
Leíró adatok
Tartalmi kivonat:The authors presented a gender prediction model of student based on answers provided into survey during academic year 2011 in Europe. This experimental study is performed in R-language by applying logistic regression on the large data-set available on the website of European Commission. More than 2500 schools, 27 countries, and more than 45000 students have participated in the survey held in 2011 and survey was conducted by European Commission on primary schools whose were studying at ISCED level 3 (upper secondary level of education). The dichotomous variable is gender and 6 predictors belong to attitude towards computer learning. The best cut-off and accuracy of the presented model is measured 0.499 and 0.628 respectively at 0.5 thresholds using Receiver Operating Characteristics (ROC) and Area under the curve (AUC) which signifies the model to predict more females with correctly as compared to males.
Terjedelem/Fizikai jellemzők:45-48