Agenda
8:30 -9:00 Welcome and introductions
9:00 -10:30 Teaching Introductory Statistics and Assessing Learning
An interactive session providing an overview of the GAISE guidelines, why they exist, how they connect to other pedagogical recommendations, and how they can be applied to different programs (e.g., large and small class sizes and students of diverse backgrounds). We will present some model activities for immediate use in the classroom illustrating the GAISE principles as well as discuss how to assess students’ mastery of concepts highlighted in the GAISE principles.
10:30 - 10:45 Break
10:45 - 11:30 Teaching focused career opportunities
An information session on the wide variety of teaching focused career opportunities at teaching oriented institutions, professorships of teaching practice, and postdoc opportunities. The session will also discuss how departmental cultures vary between different disciplines that hire statistics teaching faculty and interdisciplinary opportunities for collaboration across departments as well as how “what’s valued” can vary across various home departments and institutions.
LUNCH BREAK 11:30 -12:30 Roundtable style
Participants will have the choice of four roundtable topics:
(1) Preparing a statement of teaching philosophy and plan for intellectual development
(2) Best practices for teaching introductory statistics and data science (discussion of morning sessions)
(3) NSF grant opportunities related to education research
(4) Preparing for a teaching-focused job search
12:30 -1:30 Teaching Introductory Data Science and Assessing Learning
An interactive session providing examples with complex datasets, technology resources, and common pitfalls to watch for. We will provide a repository of resources (lecture notes, assessments, assignments, etc.) to teach an introductory data science course as well as an overview of existing programs and how isolated faculty members can become involved. Open discussion will focus on how the teaching of statistics is likely to involve over the next decade.
1:30 - 1:45 Break
1:45 -2:30 Preparing to mentor undergraduate researchers
This session will focus on how to train next generation of statisticians whose research increasingly involves analysis of large and complex datasets. We will discuss best practices for project organization and dissemination of undergraduate research products.
2:30 -3:15 Opportunities for grants
This session will provide examples of research opportunities in the scholarship of teaching as well as strategies for enhancing discipline-specific proposals through inclusion of undergraduate researchers. A handbook for PIs will be distributed.
3:15 -3:45 Sharing resources and staying connected
During this session we will map out details for how participants will stay connected during the upcoming academic year. This includes identifying avenues for how to contribute content and share their work through existing blogs and webinars and by creating their own platforms . Several resources for staying connected (CIRTL network, Stat Ed Mentoring Program) will be discussed, and participants will be signed up on a Slack channel that is meant to keep the conversation between the cohort members going beyond the workshop. We will also explain the expectation that during the following year, participants will share and peer-review syllabi, teaching statements, and new/modified activities for use in the classroom and request participants to share assessment items created in the fall and assessment results in the spring. The Spring follow-up conversation will focus on how to use these assessment results to guide next steps of curriculum development.