Check out these Birds of a Feather Sessions!
In Person BoF Sessions
Sunday, August 4
4:00-5:00 pm PDT
Topic: Students Interested in Statistics and Data Science Education
Discussion Leader: Alyssa Hu (awh70@psu.edu)
Abstract: This session is for current students interested in statistics and/or data science education! Our goal is for students across institutions to meet in a supportive environment - whether it’s getting to know a few friendly faces over a meal, building a network across institutions, or chatting with others about your education research, we want you to feel comfortable at a large conference like JSM. This will be an excellent opportunity to also share ideas and resources, from student communities (e.g., SEEDS - Statistics Education: Engagement and Development for Students) to opportunities for professional development (e.g., various Conferences on Teaching Statistics).
Monday, August 5
12:30-1:30 pm PDT
Topic: Teaching both philosophies of statistics in the introduction class
Discussion Leader: Yuan Ji (yji@bsd.uchicago.edu)
Abstract: The main objective is to advocate teaching both Frequentist and Bayesian philosophies to students who first learn statistics. Anyone who teaches statistical theory or inference classes might be interested.
4:00-5:00 pm PDT
Topic: Balancing the "why" and the "how" of Statistical education. Is technology taking over?
Discussion Leader: Evidence Matangi (matangievidence@gmail.com)
Abstract: We seek to discuss the burden of teaching introductory service Statistics courses in view of the role of technology. Seek solutions to handling overemphasis on technology, and learn from peers on navigating this reality and how technology is influencing the assessment for statistical competence. We hope to attract the attention of Data and Statistics educators, teaching assistants, and ASA leaders to champion the sustainability and scaling of the practice and profession of Statistics.
Tuesday, August 6
12:30-1:30 pm PDT
Topic: Resources for JEDI-Informed Teaching of Statistics
Discussion Leader: Jo Hardin (jo.hardin@pomona.edu)
Abstract: Are you a statistics or data science instructor who is looking for a single website repository for educational resources related to Justice, Equity, Diversity, and Inclusion (JEDI)? Or do you use and/or create JEDI resources, and want to share how and what you use in your classrooms or research with others? The CAUSE Resources for JEDI-Informed Teaching of Statistics website offers materials such as classroom activities, curricular design, datasets, and professional development guidance to help all instructors incorporate more JEDI in their teaching and be more JEDI-Informed themselves. In this poster we will highlight some great examples that are currently on the CAUSE-JEDI website, provide guidance, and answer any questions about submitting JEDI materials that you have used and/or created for use in the statistics classroom.
4:00-5:00 pm PDT
Topic: Revising the College GAISE report
Discussion Leader: Patti Frazer Lock (plock@stlawu.edu)
Abstract: Members of the Steering Committee on revising the College GAISE report will be available to share updates and invite input. We welcome anyone who is interested in learning more and discussing the next iteration of the College GAISE report. The College GAISE report, available on the ASA site, provides "Guidelines for Assessment and Instruction in Statistics Education." The original report was written in 2005 and revised in 2016. We are currently working on updating this report again, and will also be including issues in Data Science.
Wednesday, August 7
12:30-1:30 pm PDT
Topic: Statistical Inference: Population Inference and Causal Inference
Discussion Leader: Milo Schield (mschield@ncf.edu)
Abstract: Statistical educators use "statistical inference" to indicate "population inference". Most students taking statistics are interested in causal inference involving observationally-based statistics. Saying "Correlation does not imply causation" is true, but not helpful for those majoring in sociology, social work, social psychology, political science, journalism and large parts of business and education. What can we say as professionals to these students? Do we need a separate course? Is such a course (and textbook) currently available?
Co-host: Dan Kowalczyk.
4:00-5:00 pm PDT
Topic: Teaching Statistics for Biology and Pre-Med Students
Discussion Leader: Kelly Findley (kfindley@illinois.edu)
Abstract: This session will consider statistical topics and learning goals that may be particularly relevant for an introductory statistics course geared toward biology and pre-med students. This may include discussions about how to incorporate measures of risk (risk ratios, odds ratios, hazard ratios), experimental and observational design, and possibly some experience with coding. This discussion welcomes both novice instructors of these courses as well as more veteran biostatistics instructors who have resources and rich experience to contribute.
5:30-6:30 pm PDT
Topic: DataFest Discussion
Discussion Leader: Rob Gould (rgould@stat.ucla.edu)
Abstract: For those who participated in DataFest or those who want to consider. What worked, what didn't, what should happen in the future?
Virtual BoF Sessions
Monday, August 12
2:00-3:00 pm EST
Topic: Revising the College GAISE report
Zoom link: https://stlawu.zoom.us/my/pflock
Discussion Leader: Patti Frazer Lock (plock@stlawu.edu)
Abstract: Members of the Steering Committee on revising the College GAISE report will be available to share updates and invite input. We welcome anyone who is interested in learning more and discussing the next iteration of the College GAISE report. The College GAISE report, available on the ASA site, provides "Guidelines for Assessment and Instruction in Statistics Education." The original report was written in 2005 and revised in 2016. We are currently working on updating this report again, and will also be including issues in Data Science.
Tuesday, August 13
1:00-2:00 pm Eastern
Topic: Teaching both philosophies of statistics in the introduction class
Zoom Link: https://us02web.zoom.us/j/88394197611
Discussion Leader: Yuan Ji (yji@bsd.uchicago.edu)
Abstract: The main objective is to advocate teaching both Frequentist and Bayesian philosophies to students who first learn statistics. Anyone who teaches statistical theory or inference classes might be interested.
Wednesday, August 14
1:00-2:00 pm Eastern
Topic: Statistical Inference: Population Inference and Causal Inference
Discussion Leader: Milo Schield (mschield@ncf.edu)
Abstract: Statistical educators use "statistical inference" to indicate "population inference". Most students taking statistics are interested in causal inference involving observationally-based statistics. Saying "Correlation does not imply causation" is true, but not helpful for those majoring in sociology, social work, social psychology, political science, journalism and large parts of business and education. What can we say as professionals to these students? Do we need a separate course? Is such a course (and textbook) currently available?
Co-host: Dan Kowalczyk
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