Resources for JEDI-Informed Teaching of Statistics
Pedagogy, research, and professional development
This plugin created for CODAP links to data from the Fatal Encounters website. This website was created as an effort to document people in the United States who were killed during interactions with the police. The data ranges from 2000-2021. The plugin opens in CODAP. Users can subset the data by choosing states they are interested in as well as years. The original dataset has over 35,000 people included in it. Students who open the data via CODAP can quickly make graphs to explore variables of interest.
Engaging and motivating students in undergraduate statistics courses can be enhanced by using topical peer-reviewed publications for analyses as part of course assignments. Given the popularity of on-campus therapy dog stress-reduction programs, this topic fosters buy-in from students whilst providing information regarding the importance of mental health and well-being as it impacts learning. This paper describes how instructors can use a study on the benefits of human–dog interactions to teach students about study design, data collection and ethics, and hypothesis testing. The data and research questions are accessible to students without requiring detailed subject-area knowledge. Students can think carefully about how to collect and analyze data from a randomized controlled trial with two-sample hypothesis tests. Instructors can use these data for short in-class examples or longer assignments and assessments, and throughout this article, we suggest activities and discussion questions.
Some research has suggested that groups of people working on a task can do better if the group is more diverse, since diverse group members can suggest more creative ideas and make better decisions. At the same time, diverse groups can have more conflict than less diverse groups, possibly eliminating those benefits. This dataset is from a study that attempted to understand these factors and how they relate to the testosterone levels of members of the group.
Researchers and organizations can increase privacy in datasets through methods such as aggregating, suppressing, or substituting random values. But these means of protecting individuals' information do not always equally affect the groups of people represented in the data. A published dataset might ensure the privacy of people who make up the majority of the dataset but fail to ensure the privacy of those in smaller groups. Or, after undergoing alterations, the data may be more useful for learning about some groups more than others. How entities protect data can have varying effects on marginalized and underrepresented groups of people.
To understand the current state of ideas, we completed a literature review of equity-focused work in statistical data privacy (SDP) and conducted interviews with nine experts on privacy preserving methods and data sharing. These experts include researchers and practitioners from academia, government, and industry sectors with diverse technical backgrounds. We offer an illustrative example to highlight potential disparities that can result from applying SDP methods. We develop an equitable statistical data privacy workflow that privacy practitioners and decisionmakers can utilize to explicitly make equity part of the standard data privacy process.
In the spirit of Gutiérrez (2009), access represents all of the opportunities available for student learning. These slides are a collection of resources for thinking about all of the dimensions of access. There is a particular emphasis on metacognition and unveiling the hidden curriculum.
Dr. Rochelle Gutierrez (2002) stated "equity is ultimately about the distribution of power - power in the classroom, power in future schooling, power in one's everyday life, and power in a global society." This presentation unpacks ways in which statistics classrooms can put power in students' hands.