Not Another Boot Camp: Toward an Inclusive Computational Pedagogy

abstract: This article explores inclusive approaches to data literacy in academic libraries through a case study of Python Camp, a four-day introductory programming workshop offered by George Washington University Libraries and Academic Innovation. We position computational literacy as a dimension of data literacy, emphasizing the ability to engage with data through code, modeling, and algorithmic reasoning. Unlike traditional boot camps that prioritize technical skill acquisition, Python Camp fosters collaborative learning, frames computation as a communicative and exploratory act, and embeds coding within interdisciplinary, context-rich problems. Drawing on facilitator reflections and semistructured interviews with participants, we argue that academic libraries are uniquely positioned to challenge exclusionary norms in data education. Our pedagogical approach centers relevance, learner agency, and ethical engagement with data, aligning with broader library trends toward inclusive, user-centered instruction. We describe how our team-based model supports a growth mindset and inclusive learning culture through varied lesson structures, reduced educator bias, and peer communication. We conclude by framing computational literacy as a social, situated practice. More than acquiring syntax, it is a process of building fluency, confidence, and relevance. Library-based data literacy programs that foreground ethical, critical, and user-centered approaches can broaden access to computational tools while modeling inclusive pedagogy. Reflection by both participants and facilitators is essential, not only for assessing program effectiveness but as a core practice of inclusion itself.