Abstract Number:
1157
Submission Type:
Invited Paper Session
Participants:
Samantha Robinson (1), Nicholas Horton (3), Jyotishka Datta (2), Matt Hayat (4), Randi Garcia (5), Johanna Hardin (6), Samantha Robinson (1), Lindsay Poirier (5)
Institutions:
(1) University of Arkansas, N/A, (2) Virginia Tech, N/A, (3) Amherst College, N/A, (4) Georgia State University, N/A, (5) Smith College, N/A, (6) Pomona College, N/A
Chair:
Discussant:
Session Organizer:
Speaker(s):
Session Description:
The widely implemented Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report, first introduced in 2005 and updated in 2016, dramatically changed the way students learn introductory statistics. At the same time, the ever-increasing demand for data scientists in government, industry, and academia has led to the rapid development of data science programs throughout higher education. With recent technological advancements and the increasing availability and instructional usage of real-world datasets within statistics and data science courses and programs, there is wide agreement that ethics must be integrated into the curricula. The main question is how and when to make it happen. This session will focus on recent curricular work on the topic of data science ethics, providing various considerations and recommendations about exactly how we should approach ethics in the biostatistics, statistics and data science classroom.
Presenters will describe several innovative course and curriculum developments which: 1) incorporate ethics into established curricula and, also, integrate ethics into undergraduate-level introductory statistics courses based on recommendations in the GAISE, 2) focus on community-based and justice-focused data science curriculum, 3) present a framework for bringing together key data science practices with ethical topics, 4) demonstrate the benefit of incorporating philosophers when developing data science ethics courses, and 5) utilize data ethnography to help students examine the diverse cultural forces operating within and through data. In order to summarize the impactful developments described by the speakers and contextualize how our community can bridge teaching and practice, the session will end with comments from a discussant.
Biostatistics, statistics, and data science curricula are constantly changing and evolving as the science changes. Finding space in crowded curricula to incorporate ethics and establishing best practices for doing so can be challenging especially as more technical skills are added but ethical considerations are arguably one of the most relevant and increasingly essential areas of biostatistics, statistics, and data science education. This session will promote discussion of data science ethics and promote sharing of innovative ways ethics have been brought into educational programs. The speakers come from a range of different program sizes and types, so educators from a wide range of institutions will find something relevant in this session.
List of invited speakers (who have agreed to present):
1. Matt Hayat, Georgia State University, mhayat@gsu.edu, Presentation Title: "Integrating Ethics into GAISE"
2. Randi Garcia, Smith College, rgarcia@smith.edu, Presentation Title: "A Multimodal Approach to Integrating Ethics into an Undergraduate Data Science Curriculum"
3. Jo Hardin, Pomona College, jo.hardin@pomona.edu, Presentation Title: "Philosophy as Integral to a Data Science Ethics Course"
4. Samantha Robinson, University of Arkansas, sewrob@uark.edu, Presentation Title: "The Philosopher Crossover: Benefits of Collaboration when Developing a Data Science Ethics Course"
5. Lindsay Poirier, Smith College, lpoirier@smith.edu, Presentation Title: "Data Ethnography: Cultivating Reflexive Sensibilities through the Cultural Analysis of Datasets"
(Discussant) Nick Horton, Amherst College, nhorton@amherst.edu
Sponsors:
Justice Equity Diversity and Inclusion Outreach Group 3
Section on Statistics and Data Science Education 1
Section on Teaching of Statistics in the Health Sciences 2
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
Yes
Applied
Yes
Estimated Audience Size
Medium (80-150)
I have read and understand that JSM participants must abide by the Participant Guidelines.
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I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
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