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Knowledge Discovery and Dataset for the Improvement of Digital Literacy Skills in Undergraduate Students

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  • Pongpon Nilaphruek

    (Department of Computer Science, School of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

  • Pattama Charoenporn

    (Department of Computer Science, School of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

Abstract

For over two decades, scholars and practitioners have emphasized the importance of digital literacy, yet the existing datasets are insufficient for establishing learning analytics in Thailand. Learning analytics focuses on gathering and analyzing student data to optimize learning tools and activities to improve students’ learning experiences. The main problem is that the ICT skill levels of the youth are rather low in Thailand. To facilitate research in this field, this study has compiled a dataset containing information from the IC3 digital literacy certification delivered at the Rajamangala University of Technology Thanyaburi (RMUTT) in Thailand between 2016 and 2023. This dataset is unique since it includes demographic and academic records about undergraduate students. The dataset was collected and underwent a preparation process, including data cleansing, anonymization, and release. This data enables the examination of student learning outcomes, represented by a dataset containing information about 45,603 records with students’ certification assessment scores. This compiled dataset provides a rich resource for researchers studying digital literacy and learning analytics. It offers researchers the opportunity to gain valuable insights, inform evidence-based educational practices, and contribute to the ongoing efforts to improve digital literacy education in Thailand and beyond.

Suggested Citation

  • Pongpon Nilaphruek & Pattama Charoenporn, 2023. "Knowledge Discovery and Dataset for the Improvement of Digital Literacy Skills in Undergraduate Students," Data, MDPI, vol. 8(7), pages 1-16, July.
    • Handle: RePEc:gam:jdataj:v:8:y:2023:i:7:p:121-:d:1198512
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    References listed on IDEAS

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    1. Michael Stein & Michael Leitner & Jill C. Trepanier & Kory Konsoer, 2022. "A Dataset of Dropout Rates and Other School-Level Variables in Louisiana Public High Schools," Data, MDPI, vol. 7(4), pages 1-10, April.
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    3. Duc-Hoa Pho & Xuan-An Nguyen & Dinh-Hai Luong & Hoai-Thu Nguyen & Thi-Phuong-Thao Vu & Thi-Thuong-Thuong Nguyen, 2020. "Data on Vietnamese Students’ Acceptance of Using VCTs for Distance Learning during the COVID-19 Pandemic," Data, MDPI, vol. 5(3), pages 1-6, September.
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