Analysis of Discrepancies in Learning Awareness of Data Science Across Disciplines
A Case Study of Nihon Uni-versity, College of Humanities and Sciences
DOI:
https://doi.org/10.52731/lir.v004.321Keywords:
data science, artificial intelligence, mathematics, curriculumAbstract
In recent years, there has been a growing demand for data science education alongside rapid advancements in technology, particularly in AI. However, despite various attempts to innovate curricula and teaching methods at universities, there is limited research on students' awareness of their learning needs in this field. Hence, this study investigated the recognition of the importance of data science and willingness to take related courses among a diverse range of students, includ-ing those from both scientific and non-scientific disciplines. The results revealed that although 90% of the students recognized the necessity of data science in the future, less than half were considering taking related courses. In our faculty, we are considering measures, such as compul-sory courses and certification systems, to enhance students' knowledge and skills in data science and make them more accessible to a wider range of students. This paper summarizes the back-ground and findings of the study.
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