Targeting students’ interests to facilitate their learning of data science

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Authors: Yoshito Hirata, Kazuto Fukuchi, Naoya Todo, Etsuko T. Harada, Jun Sakuma
Cited by: 0
References: 20

Abstract

Collecting and analyzing data are critical abilities that help students learn before they get their first job. However, how lecturers or teachers can encourage students with diverse interests to pursue such data science skills more successfully remains unclear. We conducted a case study on data science education at the University of Tsukuba, involving a total of 8,509 participants between 2019 and 2023. Our experiment shows that preparing introductory videos related to students’ respective colleges increased the objective test score by 16.4%. Additionally, the exercises in which students answered a questionnaire and investigated the results by themselves helped them acquire better skills for managing and analyzing data. Therefore, carefully crafting introduction of data science course to cover students’ diverse interests is crucial for motivating them from their first class.

Fields of Study & Subjects

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

Publication details

Journal / source
Discover Data
Volume
4
Issue
1
Publication date
26 February 2026
Language
EN