Statistics

This webinar provided early career data science education researchers with information on the state of the field; tools, curricula, and other resources for researchers; and insight into funding opportunities and proposal development. Participants explore topics, research interests, and problems of practice in more depth in breakout rooms with session leaders.

Civic Statistics by its nature is highly interdisciplinary. From a cross-curricular perspective, teaching and learning Civic Statistics faces specific challenges related to the preparation of teachers and the design of instruction. This chapter presents examples of how Civic Statistics resources and concepts can be used in different courses and subject areas. Because topical issues and current data are central to these resources, we recognise that the original ProCivicStat resources will become outdated in time.

To promote understanding of and interest in working with data among diverse student populations, we developed and studied a high school mathematics curriculum module that examines income inequality in the United States. Designed as a multi-week set of applied data investigations, the module supports student analyses of income inequality using U.S. Census Bureau microdata and the online data analysis tool the Common Online Data Analysis Platform (CODAP).

Data literacy is important for supporting individuals to incorporate information from research studies into their own perspectives and decision-making processes. However, it can be challenging for students to read, understand, and relate to data. Students have to be able to traverse the representational forms that data takes on (i.e., numerical, graphical, etc.) and connect it to their understanding of a topic.

Data literacy is important for supporting individuals to incorporate information from research studies into their own perspectives and decision-making processes. However, it can be challenging for students to read, understand, and relate to data. Students have to be able to traverse the representational forms that data takes on (i.e., numerical, graphical, etc.) and connect it to their understanding of a topic.

Data literacy is important for supporting individuals to incorporate information from research studies into their own perspectives and decision-making processes. However, it can be challenging for students to read, understand, and relate to data. Students have to be able to traverse the representational forms that data takes on (i.e., numerical, graphical, etc.) and connect it to their understanding of a topic.

Effective data literacy instruction requires that learners move beyond understanding statistics to being able to humanize data through a contextual understanding of argumentation and reasoning in the real-world. In this paper, we explore the implementation of a co-designed data comic unit about adolescent friendships. The 7th grade unit involved students analyzing data graphs about adolescent friendships and crafting comic narratives to convey perspectives on that data.

Effective data literacy instruction requires that learners move beyond understanding statistics to being able to humanize data through a contextual understanding of argumentation and reasoning in the real-world. In this paper, we explore the implementation of a co-designed data comic unit about adolescent friendships. The 7th grade unit involved students analyzing data graphs about adolescent friendships and crafting comic narratives to convey perspectives on that data.

Effective data literacy instruction requires that learners move beyond understanding statistics to being able to humanize data through a contextual understanding of argumentation and reasoning in the real-world. In this paper, we explore the implementation of a co-designed data comic unit about adolescent friendships. The 7th grade unit involved students analyzing data graphs about adolescent friendships and crafting comic narratives to convey perspectives on that data.