The DataSquad Experiment: Lessons for Preparing Data and Computer Scientists for Work

TL;DR

The DataSquad program at Carleton College trains undergraduates in data analysis and software development through peer mentorship and real projects, enhancing data skills and institutional data services.

Contribution

This paper introduces a scalable peer mentorship model for data education that improves student skills and institutional data capabilities at small colleges.

Findings

Students gain practical data and software skills.

Peer mentorship enhances student confidence and professional development.

The model is adaptable and has been adopted by other institutions.

Abstract

The DataSquad at Carleton College addresses a common problem at small liberal arts colleges: limited capacity for data services and few opportunities for students to gain practical experience with data and software development. Academic Technologist Paula Lackie designed the program as a work-study position that trains undergraduates through structured peer mentorship and real client projects. Students tackle data problems of increasing complexity-from basic data analysis to software development-while learning FAIR data principles and open science practices. The model's core components (peer mentorship structure, project-based learning, and communication training) make it adaptable to other institutions. UCLA and other colleges have adopted the model using openly shared materials through "DataSquad International." This paper describes the program's implementation at Carleton College and examines how structured peer mentorship can simultaneously improve institutional data services and provide students with professional skills and confidence.