ERIC Number: EJ1285435
Record Type: Journal
Publication Date: 2020
Pages: 14
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-2148-3868
EISSN: N/A
Available Date: N/A
Comparison of Artificial Neural Networks and Logistic Regression Analysis in PISA Science Literacy Success Prediction
Bozak, Ali; Aybek, Eren Can
International Journal of Contemporary Educational Research, v7 n2 p99-111 2020
The present study aims to determine which analysis technique-Artificial Neural Networks (ANNs) or Logistic Regression (LR) Analysis-is better at predicting the science literacy success of the 15-year Turkish students who participated in PISA research carried out in 2015 by using learning time spent on science, test anxiety, environmental awareness, environmental optimism, epistemological beliefs, inquiry-based science teaching and learning practices, instrumental motivation, and disciplinary climate in science classes as the predictor variables. For this purpose, the data from 5895 students who participated in the PISA 2015 test were analyzed. Models were developed using LR and ANNs, and the results were compared. As a result, although the classification performance of artificial neural network is significantly better compared to LR, it is understood that practical significance is low due to the intersection of AUC confidence intervals.
Descriptors: Artificial Intelligence, Networks, Regression (Statistics), Achievement Tests, International Assessment, Foreign Countries, Secondary School Students, Scientific Literacy, Science Achievement, Predictor Variables, Success, Time on Task, Test Anxiety, Epistemology, Science Instruction, Inquiry
International Journal of Contemporary Educational Research. e-mail: ijceroffice@gmail.com; Web site: http://ijcer.net
Publication Type: Journal Articles; Reports - Research
Education Level: Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Turkey
Identifiers - Assessments and Surveys: Program for International Student Assessment
Grant or Contract Numbers: N/A
Author Affiliations: N/A