Project Y: Outcomes and Reflections on 5 Years of Elementary School Computational Thinking Interventions

• In Event: STEM Interventions for Talent Development: An Interactive Symposium on Evidence-Based Models Developed Through Javits Projects

Abstract

1. Objectives

Objectives include to summarize effects of curricular, pedagogical, and professional learning (PL) interventions on teacher outcomes across multiple years, explore successes, modifications, and future directions for supporting STEM talented students in rural, low SES communities.
2. Perspective(s)
Project Y aimed to enhance teacher self-efficacy and student engagement in computer science (CS) within a low socioeconomic status (SES) community. Guided by research on best practices in PL, CS, and gifted education (GT), we fostered a structured, sustainable approach to teaching computational thinking (CT). Challenges included preparing teachers to teach CT, maintaining student engagement, and implementing effective curriculum and pedagogy.

We utilized Code.org® curriculum to enhance problem-solving, higher-order thinking, and STEM identity (Perez et al., 2014). Our PL was content-focused, active, sustained, coherent, collaborative (Garet et al., 2001), and aligned with school priorities (Desimone, 2009), promoting teacher leadership (Desimone et al., 2002) and emphasizing content and pedagogies (Kong et al., 2020).

To support gifted students’ advanced needs and interests, (e.g., Rimm et al., 2017; Subotnik et al., 2023; VanTassel-Baska & Baska, 2021; Kaplan, 2009) we included components of Type II Enrichment and Enrichment Clusters (Renzulli & Reis, 2014).

3. Methods

This study was conducted in a rural community serving ~1250 students, 65% FARM-eligible (NCES, 2023). Participants were 75 elementary school teachers; 77.33% female; 6.67% male; 1.33% other; 14.67% unreported.

We employed a concurrent triangulation mixed methods design (Creswell et al., 2003). Interventions included comprehensive PL (Desimone, 2009), Code.org curriculum, pedagogies from GT and CS (Renzulli & Reis, 2014; Kong et al., 2020), and Enrichment Clusters (Renzulli & Reis, 2014). Comprehensive PL included workshops, PLCs, instructional videos, and teacher leaders.




4. Data

Data included surveys (Teaching Beliefs about Coding and Computational Thinking; Rich et al., 2021), classroom observations (Technology Observation Protocol for Science; Parker et al., 2019), and focus group interviews. We assessed changes in teachers’ value beliefs about coding, self-efficacy for coding, self-efficacy for teaching CT, and classroom practice (see Figure 1). Student achievement measures included the Phonological Awareness Literacy screening, i-Ready reading and mathematics, the Competent Computational Thinking Test (El-Hamamsy et al., 2022), the TechCheck (Relkin et al., 2020), and the West Virginia General Summative Assessment Test. Analysis of student-level data is in progress.

5. Results

• Teachers demonstrated notable increases in coding self-efficacy and self-efficacy for teaching CT after workshop 1 (see Table 1) and again after workshop 2 (see Table 2).
• Observations showed improvements in classroom instruction related to CT concepts and practices (see Table 3).
• Teachers reported positive feedback on PL components such as workshops, PLC instructional videos, and support from teacher leaders (see Table 4).
• Gifted referrals and identifications increased from 10 students in 2019 to 19 in 2022; of these, 13 were formally identified, indicating increasing awareness among teachers in identifying gifted students in coding.
6. Scholarly significance
This study advances understanding of effective strategies for enhancing CS education in underserved communities, contributing to educational equity and excellence in STEM fields, particularly for students with academic aptitude. Insights offer valuable guidance for future research and educational practice.

Authors

• Carla Brigandi, West Virginia University

• Jiangmei May Yuan, West Virginia University

• Karen E. Rambo-Hernandez, Texas A&M University

• Maryann R. Hebda