Bridging Data Science and Information Literacy

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Authors: Shintaro Tajiri, Kunihiko Takamatsu, Naruhiko Shiratori, Shotaro Imai, Sayaka Matsumoto, Tetsuya Oishi, Masao Mori, Masao Murota
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Abstract

This paper presents an analysis of implementing a university-wide data science education initiative at Hokuriku University, focusing on the integration of Tableau visualization platform and multi-instructor assessment management.The study examines data from 1,004 first-year students across four faculties over two academic years (2022-2023), analyzing both learning outcomes and assessment patterns among different instructors.Results indicate that while Tableau integration enhanced student engagement through hands-on analysis of real-world campus data, with completion rates exceeding 90% across most departments, significant variations emerged in grade distributions among instructors despite standardized assessment criteria.Statistical analysis using Kruskal-Wallis tests and Dunn's test with Bonferroni Correction revealed specific patterns in these variations, suggesting the influence of both instructor assessment styles and student population characteristics.These findings provide valuable insights for institutions implementing similar university-wide data science education programs, particularly regarding assessment standardization in multi-instructor environments.

Fields of Study & Subjects

Statistics Education and Methodologies Teaching and Learning Programming Online Learning and Analytics

Publication details

Journal / source
International Journal of Institutional Research and Management
Volume
10
Issue
1
Pages
1–1
Publication date
1 January 2026
Language
EN