Empowering Students to Harness the Data that Surrounds Them

• In Event: Empowerment-Focused Computing in Constructionist Learning Environments

Abstract

Objectives
Data shapes the way today’s students interact with the world. Data science plays a key role in helping students navigate this data-driven world, and critically, can empower them to use the data that surrounds them in purposeful and personally meaningful ways. This poster presents findings from an interest-driven high school data science curriculum designed to situate data science concepts and practices in students’ lived experiences. In particular, we highlight how the curriculum connected with students' lives and how students saw connections between the content and their lives beyond the classroom.

Theoretical Framework
This work builds on emerging work on K-12 data science (Dorsey et al., 2025; IDSSP, 2019; LaMar & Boaler, 2021; Lee & Delaney, 2021). It draws on Interest Development Theory (Renninger & Hidi, 2015) and the Integrated Interest Development for Computing Education Framework (Michaelis & Weintrop, 2022), which provides a model for designing learning experiences that cultivate interest in computing. The work also uses Shaffer & Resnick’s (1999) construct of “thick authenticity” to inform its design. The result is an interest-driven data science curriculum, called API Can Code (Weintrop & Israel-Fishelson, 2024).

Methods & Data Sources
The API Can Code curriculum was implemented in a public charter high school in the US. Thirty-five students consented to our study, where they completed the 3-unit, 18-lesson curriculum. The curriculum concluded with a summative data science final project that had students complete a full data science cycle to answer a question on a topic of their choice. For this work, we collected student artifacts over the course of the curriculum, including daily exit tickets and interviews. We also collected and analyzed students’ final presentations, final project artifacts, and post-survey responses.

Results
The poster will present a series of qualitative and quantitative results from the project on how the curriculum succeeded in increasing students' confidence with data and providing a sense of empowerment to use data and data science in their lives. The poster will explore various ways this was accomplished, including authentic tools, real data sets, investigations related to students' interests, and agency so the students could pursue topics based on their own interests and ideas. When asked to reflect on the curriculum, and whether or not they felt the curriculum would help them, one student responded “I could see how it will become useful. Even though it is not particularly hand-in-hand with what I’m doing, I’m going to handle a lot of data; it helps me learn how to analyze the data”. Another student added: “It felt like what we were doing could actually be used outside of school.” As for what contributed to these feelings, after the third unit, one student reflected, “The topics were real situations. We used a lot of real data from around the world. It was not made up!”

Scholarly Significance
This work contributes to a growing body of work on the importance of data science in K-12 education. In particular, it highlights how developing foundational data science competencies can empower students to succeed in the data-driven world that awaits them.

Authors

• David Weintrop, University of Maryland

• Rotem Israel-Fishelson, University of Maryland