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

Poornima Meegammana, Hussel Suriyaarachchi, Paul Denny, Suranga Nanayakkara

TL;DR

The paper investigates whether sensor-based, hands-on Scratch programming workshops can broaden participation in computing among rural Sri Lankan students, testing replication of prior findings from New Zealand. Using a between-group design with sensor vs non-sensor conditions (n=122 total), the study measures changes in programming confidence, self-efficacy, and outcome expectancy via pre/post surveys and analyzes open-ended responses. Results show significant gains in programming confidence for all students and greater improvements in self-efficacy for the sensor group, with qualitative data indicating enhanced creativity and interest in ICT careers when sensors are used. The findings support the value of sensor-enabled activities for engaging under-represented groups in resource-constrained settings and highlight replication's role in validating broad applicability of sensor-based pedagogy.

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.

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

TL;DR

The paper investigates whether sensor-based, hands-on Scratch programming workshops can broaden participation in computing among rural Sri Lankan students, testing replication of prior findings from New Zealand. Using a between-group design with sensor vs non-sensor conditions (n=122 total), the study measures changes in programming confidence, self-efficacy, and outcome expectancy via pre/post surveys and analyzes open-ended responses. Results show significant gains in programming confidence for all students and greater improvements in self-efficacy for the sensor group, with qualitative data indicating enhanced creativity and interest in ICT careers when sensors are used. The findings support the value of sensor-enabled activities for engaging under-represented groups in resource-constrained settings and highlight replication's role in validating broad applicability of sensor-based pedagogy.

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.

Paper Structure

This paper contains 21 sections, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Sensors, Self-efficacy and Expectations
  4. Sensor use in programming education
  5. Under-represented groups in computing
  6. Methodology
  7. Participants
  8. Programming environment and sensors
  9. Study Procedure
  10. Introduction to Programming
  11. Programming Activity
  12. Data Collection
  13. Data Analysis
  14. RESULTS & DISCUSSION
  15. Student Attitudes and Perceptions
  16. ...and 6 more sections

Figures (4)

  • Figure 1: Students in the sensor group using the sensor toolkit during a hands-on programming workshop. Permission to use these images has been granted.
  • Figure 2: The Sample Scratch program for the non-sensor group. The sprite is controlled by keyboard input and it moves to the right when the right arrow key is pressed
  • Figure 3: The Sample Scratch program for the sensor group. The sprite is controlled by the visible light sensor and moves to the right when light intensity is greater than 5.
  • Figure 4: A Sample of Student Projects from the Workshop.