학술논문

Insights from DatsFfest Point to New Opportunities for Undergraduate Statistics Courses: Team Collaborations, Designing Research Questions, and Data Ethics
Document Type
Journal Articles
Reports - Research
Author
Noll, Jennifer (ORCID 0000-0002-8156-1728); Tackett, Maria
Source
Teaching Statistics: An International Journal for Teachers. Sum 2023 45(1):S5-S21.
Subject
Undergraduate Students
Statistics Education
Data Science
Teaching Methods
Majors (Students)
Nonmajors
Introductory Courses
Research Methodology
Ethics
Cooperative Learning
Bias
Language
English
ISSN
0141-982X
1467-9639
Abstract
As the field of data science evolves with advancing technology and methods for working with data, so do the opportunities for re-conceptualizing how we teach undergraduate statistics and data science courses for majors and non-majors alike. In this paper, we focus on three crucial components for this re-conceptualization: Developing research questions, professional ethics, and team collaborations. We share vignettes from two teams of undergraduate statistics or data science majors at two different stages of their development (novice and expert) while they worked on a DataFest data challenge. These vignettes shed light on opportunities for re-conceptualizing introductory courses to give more attention to issues of the process of developing focused research questions when given a complex data set, professional ethics and bias, and how to collaborate effectively with others. We provide some implications for teaching and learning as well as an example activity for educators to use in their courses.