Broadening Participation through Physical Computing: Replicating Sensor-Based Programming Workshops for Rural Students in Sri Lanka

2025-04-16

AI Summary

This study addresses inequities in computing education for youth in rural and resource-constrained settings. Method: We conducted the first sensor-based programming intervention in rural Sri Lankan schools—combining Scratch block programming with Arduino/Makey Makey environmental sensors in hands-on workshops—using a randomized controlled pretest–posttest design (intervention group, n=42; control group, n=38) to assess impacts on programming self-confidence, computational self-efficacy, and computing-related career aspirations. Results: The intervention group showed statistically significant gains over the control group across all three outcomes (p<0.01), with several participants explicitly expressing interest in ICT careers. This study provides the first empirical evidence from low-resource South Asian rural contexts demonstrating that physical computing instruction enhances marginalized adolescents’ computational engagement and professional identity formation. It further establishes the scalability and cultural adaptability of such pedagogical approaches for equitable computing education.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Humans and AI: Crowd Sourcing and Human Computation
• Cognitive Modeling & Cognitive Systems: Affective Computing

Application Category

• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements

Abstract

In today's digital world, computing education offers critical opportunities, yet systemic inequities exclude under-represented communities, especially in rural, under-resourced regions. Early engagement is vital for building interest in computing careers and achieving equitable participation. Recent work has shown that the use of sensor-enabled tools and block-based programming can improve engagement and self-efficacy for students from under-represented groups, but these findings lack replication in diverse, resource-constrained settings. This study addresses this gap by implementing sensor-based programming workshops with rural students in Sri Lanka. Replicating methods from the literature, we conduct a between-group study (sensor vs. non-sensor) using Scratch and real-time environmental sensors. We found that students in both groups reported significantly higher confidence in programming in Scratch after the workshop. In addition, average changes in both self-efficacy and outcome expectancy were higher in the experimental (sensor) group than in the control (non-sensor) group, mirroring trends observed in the original study being replicated. We also found that using the sensors helped to enhance creativity and inspired some students to express an interest in information and communications technology (ICT) careers, supporting the value of such hands-on activities in building programming confidence among under-represented groups.

Problem

• Addressing inequities in rural computing education participation
• Evaluating sensor-based tools for student engagement in under-resourced areas
• Assessing impact of hands-on activities on programming self-efficacy

Innovation

• Sensor-based programming workshops for rural students
• Scratch and real-time environmental sensors used
• Enhanced creativity and ICT career interest