Rural Elementary Teachers’ Computational Thinking Self-Efficacy Through Community-Based Citizen Science

ABSTRACT

While both citizen science engagements and computational thinking practices can mutually support student ownership in the science classroom, both face similar challenges to adoption in that they require teachers to openly position themselves as learners alongside their students. This dual role—as a teacher and as a learner—poses self-efficacy challenges that may preclude teachers from exploring these important pedagogical tools and perspectives in their classrooms. We present a cross-case analysis of three experienced teachers in rural elementary and middle schools as they integrate computational thinking in a year-long, student-led community-based citizen science project. Drawing from interview data, we illustrate how teachers’ capacity to embrace their role of co-learners alongside their students redefined “mastery experiences” of teaching self-efficacy. Specifically, the case teachers evaluated their successful use of computational thinking within the community-based citizen science program in ways that valued student curiosity and discovery over mastery of content. In this way, their self-efficacy for using computational thinking developed when they saw and shared these activities in themselves and their students. We further illustrate how contextual contributors of the professional development program and their rural schools and districts contributed to their comfort in experimenting with new instructional approaches, which helped them to build the mastery experiences that fueled further exploration of computational thinking within their classroom’s community-based citizen science investigations.

KEYWORDS:

• Community-based citizen science
• computational thinking
• professional development
• rural
• self-efficacy

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ “Citizen science” has attracted scrutiny for its political connotations of citizenship as a criteria for engagement, leading some to favor “community science” (Cooper et al., 2021). However, “community science” is paradigmatically grounded in community needs and action for social change—a component that is often missing in projects described as “Citizen science” that serve the interests of organizations (Cooper et al., 2021). Thus, “Citizen science” may apply to public-engaged scientific research more broadly, while “community science” is community-centric. When we speak of the project that is the focus of this paper, we refer to “community-based citizen science” to reflect the community-grounded nature of the work, reserving the “community science” term for activism-oriented projects.

2 We recognize that data collection and analysis is a complex process that engages many more components than can be reported in a journal article. We rely on the APA journal article reporting standards for qualitative inquiry (Levitt et al., 2018) to select the content of this section.

³ We use brackets to indicate the data source of each quote. I1 and I3 refer to the first and third interviews, and GI refers to the second interview, which was a group interview.

Additional information

Funding

This work is supported by funding from the National Science Foundation [DRL 1933491].