LogicDS: Virtual Data Science Learning for Rural High Schools

Interdisciplinary foundations in computing, math, and statistics are essential for students to solve everyday problems and prepare for future careers in data science or artificial intelligence. However, data science curricula are often inaccessible, particularly in rural communities, due to their interdisciplinary complexity and the limited local availability.

Purpose

In partnership with Texas Tech University, University of Florida, and Concord Consortium, WestEd is testing and evaluating LogicDS, a 12- to 16-week digital, self-paced data science course for high school students attending virtual schools. LogicDS offers a logic-based integration of interdisciplinary foundations in math, statistics, and computing, structured around the data investigation cycles framework.

Leveraging virtual learning, the project aims to enhance students’ understanding of data science and artificial intelligence, engage STEM students, explore data science careers that develop and implement artificial intelligence solutions, and improve the teaching and learning of statistics and data science for high school students.

Audiences Served

LogicDS will provide a digital, self-paced learning experience for high school students to learn interdisciplinary concepts in data science and artificial intelligence.

This evaluation project will provide practitioners, administrators, developers, and researchers with more insights about the promise of flexible, online instruction to support academic preparation and success for all students.

Project Activities

WestEd and its research partners will work with virtual school instructors to develop and refine a self-paced, logic-based data science course by conducting usability and feasibility testing in virtual schools. The quasi-experimental study will examine the impact of the intervention on high school students’ math and computational thinking outcomes and students’ interests in the data science career pathway.

Project Director

Linlin Li

Linlin Li is a Research Director on the Learning and Technology team. Li develops and directs research and evaluations with local, statewide, and national agencies.

Funder

This project is funded in full by the National Science Foundation (NSF) through award number 2201393.

Project Duration

4 Years (July 15, 2022 – June 30, 2026)