The Relationship between Digital Literacy and the Effectiveness of ChatGPT Utilization in Academic Information Retrieval

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Abstract

The increasing integration of ChatGPT into higher education has underscored its potential to support academic information retrieval; however, its effective use depends on students’ digital literacy, particularly their ability to critically understand, evaluate, and apply information. This study aimed to examine students’ digital literacy levels, the effectiveness of ChatGPT use in academic information retrieval, and the relationship between these variables among 2022 cohort Library and Information Science students at Universitas Negeri Padang. A quantitative correlational design was employed, involving 100 students selected through total sampling. Data were collected using a Likert-scale questionnaire and analyzed using validity, reliability, normality, descriptive, and Pearson Product Moment correlation tests with IBM SPSS Statistics. The findings showed that students’ digital literacy was categorized as high, with a grand mean score of 3.14, while the effectiveness of ChatGPT use was also categorized as high, with a grand mean score of 3.04. The correlation analysis revealed a strong and significant relationship between digital literacy and the effectiveness of ChatGPT use, as indicated by a correlation coefficient of 0.660 and a significance value of 0.000 (< 0.05). These findings indicate that higher levels of digital literacy are associated with more effective ChatGPT utilization in academic information retrieval. This study contributes to the growing literature on artificial intelligence use in higher education and highlights the importance of strengthening students’ digital literacy and information evaluation skills to promote ethical, critical, and responsible ChatGPT-assisted academic practices.

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Article Details

How to Cite
Nabilah, S. C., & Marlini, M. (2026). The Relationship between Digital Literacy and the Effectiveness of ChatGPT Utilization in Academic Information Retrieval. Journal of Multidisciplinary Science: MIKAILALSYS, 4(2), 1510-1526. https://doi.org/10.58578/mikailalsys.v4i2.10298

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