Investigation of Variables Predicting Response Time in PISA Mathematics Items


One of the most important contributions of the developing technology to the measurement and evaluation process in education is undoubtedly the application of tests in computer environment. Compared to paper-and-pencil tests, due to its technological infrastructure computer-based tests have some advantages such as reporting scores at the end of the test, supporting innovative item formats and recording response time. The purpose of this study is to investigate the relationship between variables predicting the response time in multiple-choice and open-ended mathematics items. For this purpose, 26 released mathematics items of International Student Assessment Program (PISA) application in 2012 were implemented over a computer-based test application at the beginning of 2018-2019 academic term. The test was applied to 124 ninth grade students in a high school in the Mediterranean region. Within the scope of the study, the regression analysis was conducted to predict test response time variable by gender, daily computer usage time, mathematics exam grade, Turkish exam grade and response length (only for open-ended responses) variables. Findings obtained from the study showed that female students spend more time in answering both multiple-choice and open-ended items. It was also determined that there was a moderate significant relationship between the response time of multiple choice and open-ended items and the raw scores obtained from these items. The results of the analysis showed that the mathematics exam grade was not among the variables that was predicting the response time of both item types. Daily computer usage time was the first variable entering the model in multiple-choice items, whereas it was the response length in open-ended items.

How to Cite
GÖKÇE, Semirhan; AYDOĞAN YENMEZ, Arzu. Investigation of Variables Predicting Response Time in PISA Mathematics Items. Başkent University Journal of Education, [S.l.], v. 7, n. 2, p. 238-249, july 2020. ISSN 2148-3272. Available at: <>. Date accessed: 11 aug. 2020.
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