Are there purposeful ‘Lies’ we can tell our intro students to improve understanding?

Abstract Number:

1515 

Submission Type:

Topic-Contributed Panel Session 

Participants:

Beth Chance (1), Bradley Hartlaub (3), Stacey Hancock (4), Tisha Hooks (5), Jeffrey Witmer (6), Beth Chance (1), Allan Rossman (2)

Institutions:

(1) California Polytechnic State University, N/A, (2) Cal Poly - San Luis Obispo, N/A, (3) Kenyon College, N/A, (4) Montana State University, N/A, (5) Winona State University, N/A, (6) Oberlin College, N/A

Chair:

Allan Rossman  
Cal Poly - San Luis Obispo

Panelist(s):

Bradley Hartlaub  
Kenyon College
Stacey Hancock  
Montana State University
Tisha Hooks  
Winona State University
Jeffrey Witmer  
Oberlin College
Beth Chance  
California Polytechnic State University

Session Organizer:

Beth Chance  
California Polytechnic State University

Session Description:

With JSM 2024's theme of "countering misinformation," we thought of a panel/debate on whether some 'misinformation' was acceptable, and even helpful, in teaching introductory statistics. We have recruited a group of well-known educators, with experience in curriculum development, to share their thoughts on presenting some purposeful inaccuracies when introducing foundational ideas to see whether they believe any are helpful in improving student understanding and potentially making the material more accessible to a broader audience. As statisticians, we tend to get so overly concerned about small details (e.g., choice of multiple comparison procedures), that we often lose the interest of the novice learner. The goal of this panel is to help educators, especially beginning teachers, consider what ideas are most important to instill in students, even if this implies fewer details. While we don't really mean "lying" to students (instead "foregoing irrelevant details"), we thought it would be a catchy title. The discussion could also help educators learn how to recognize and provide feedback to AI-generated responses that don't understand the big picture, and enable educators to help teach our students to be story-tellers.

Sponsors:

Section on Statistical Consulting 1
Section on Statistics and Data Science Education 2
Section on Teaching of Statistics in the Health Sciences 3

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.

Yes

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.

I understand