Abstract

This study attempted to identify the information and communication technology items that affected students’ mathematics and science literacy scores by making use of the 2015 PISA data, The presence of numerous items related to ICT in the PISA and the administration of these items to large groups of people provides researchers with a large data source. However, researchers experience challenges in revealing the significant and beneficial data among the entire data set. So one of the most commonly used data mining method is the Chi-squared Automatic Interaction Detection method (CHAID), which is the decision tree method. As a result of the CHAID analysis, conducted to reveal the ICT items related to mathematics literacy scores, it was revealed that there was a significant relationship between mathematics literacy scores and the eight variables. For science literacy, there was a ten significant relationship variables. There is a relationship between high science and mathematics literacy scores and using digital devices at an early age as well as feeling comfortable with using digital devices at home. As an outcome of the CHAID algorithm, the realization of a significant reduction was achieved in the dimensionality of both models. The selected variables can be used for future research and development of new, parametric models. In the resulting model, apart from the reduction of the number of predictors, the reduction of their categories was also achieved.

Highlights

  • Information and communication technology (ICT) plays a significant role in all spheres of life, including the field of education, where these kinds of resources have gained increasing importance because educational developments should reflect individuals’ needs, expectations and interests

  • The presence of numerous items related to ICT in the Programme for International Student Assessment (PISA) and the administration of these items to large groups of people provides researchers with a large data source

  • The decision tree, which belonged to the Chi-squared Automatic Interaction Detection method (CHAID) analysis in which the science literacy scores were addressed as the dependent variable and a total of 81 variables in the ICT Familiarity Questionnaire is addressed as independent variables, is a rather large diagram including 33 nodes

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Summary

Introduction

Information and communication technology (ICT) plays a significant role in all spheres of life, including the field of education, where these kinds of resources have gained increasing importance because educational developments should reflect individuals’ needs, expectations and interests. By making use of the 2015 PISA data, the present study attempted to identify the information and communication technology items that affected students’ mathematics and science literacy scores.

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Conclusion
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