Data Literacy Skills Scale Adaptation Study for Graduate Students

Abstract

In the current digital age, data literacy is considered as a crucial skill for individuals, given the vast amount of data generated daily by users and systems. This study aims to adapt the “Data Literacy Skills Scale,” developed by Oguguo, Nannim, Okeke, Ezechukwu, Christopher, and Ugorji (2020), to measure the data literacy skills of graduate students in Turkish. This study employed a quantitative research method. The “Data Literacy Skills Scale,” developed by Oguguo et al. (2020), was utilized as a data collection instrument. The scale comprises 22 statements and four sub-dimensions: data collection and preparation, hypotheses and problem statements, data analysis, and visualization/reporting and interpretation. First, linguistic equivalence studies were conducted to translate the scale from English to Turkish. After this stage, data were collected and validity and reliability analyses were carried out. The study group consisted of 251 graduate students enrolled in master’s or doctoral programs at state universities. Statistical package softwares were used to analyze the data. In the context of validity and reliability studies of the scale, exploratory factor analysis, confirmatory factor analysis, item-total correlation, and Cronbach’s alpha reliability coefficient were utilized. The results of the analyses indicated that the Data Literacy Skills Scale, adapted into Turkish, is a valid and reliable instrument with 17 items and three sub-dimensions. The study revealed that the data literacy skills of graduate students were generally high, while their data analysis skills were relatively low. Based on these findings, recommendations were made to educators, institutions, and students within the broader context of society.