TY - BOOK

T1 - An evaluative case study of the program debugging behaviour of the paired Software Development Technician Apprentice in a geographically distributed environment.

AU - Jolugbo, Olajide

PY - 2025

Y1 - 2025

N2 - This empirical study investigates the collective efforts of paired novice programmers working on rectifying Python code using technology-mediated tools. It aims to uncover: 1) the types of errors they encountered; 2) the debugging strategies and tactics employed by these apprentice pairs to locate and fix bugs within the Python code; 3) insights into how the pairs share the cognitive load; 4) the influence and efficacy of technological tools in the debugging process; and 5) the challenges faced by the pairs while working remotely to identify and resolve bugs, along with the underlying reasons for these challenges. It is methodically qualitative in nature and adopts a multi-case approach to closely examine each instance in its real-life context, utilising various data collection methods such as in-depth interviews, participant observations, code analysis, and focus groups. Furthermore, this study examines 15 dyads as they work collaboratively to debug Python code, showing the challenges they confront as well as their diverse debugging strategies and tactics. It also demonstrates the importance of integrating debugging tools, as well as how dyads strategically distribute cognitive tasks. By focusing on the relatively unexplored area of distributed pair debugging, this study offers a fresh perspective on collaborative problem-solving among novice programmers working in remote settings. It notably presents a conceptual framework for understanding dyad’s debugging in disparate settings, contributing significantly to computing education and integrating technology into educational practices. However, despite its contributions, the study acknowledges its limitations and suggests directions for further research to enhance the generalisability and applicability of its conclusions. Ultimately, this thesis advances our understanding of the debugging processes of paired novice programmers in remote settings, offering empirical insights and technical recommendations to improve computing education and practice.

AB - This empirical study investigates the collective efforts of paired novice programmers working on rectifying Python code using technology-mediated tools. It aims to uncover: 1) the types of errors they encountered; 2) the debugging strategies and tactics employed by these apprentice pairs to locate and fix bugs within the Python code; 3) insights into how the pairs share the cognitive load; 4) the influence and efficacy of technological tools in the debugging process; and 5) the challenges faced by the pairs while working remotely to identify and resolve bugs, along with the underlying reasons for these challenges. It is methodically qualitative in nature and adopts a multi-case approach to closely examine each instance in its real-life context, utilising various data collection methods such as in-depth interviews, participant observations, code analysis, and focus groups. Furthermore, this study examines 15 dyads as they work collaboratively to debug Python code, showing the challenges they confront as well as their diverse debugging strategies and tactics. It also demonstrates the importance of integrating debugging tools, as well as how dyads strategically distribute cognitive tasks. By focusing on the relatively unexplored area of distributed pair debugging, this study offers a fresh perspective on collaborative problem-solving among novice programmers working in remote settings. It notably presents a conceptual framework for understanding dyad’s debugging in disparate settings, contributing significantly to computing education and integrating technology into educational practices. However, despite its contributions, the study acknowledges its limitations and suggests directions for further research to enhance the generalisability and applicability of its conclusions. Ultimately, this thesis advances our understanding of the debugging processes of paired novice programmers in remote settings, offering empirical insights and technical recommendations to improve computing education and practice.

KW - Distributed Pair Debugging, Debugging Strategies

KW - Cognitive Load Management

KW - Remote Collaboration

KW - Computer Science Education

U2 - 10.17635/lancaster/thesis/2717

DO - 10.17635/lancaster/thesis/2717

M3 - Doctoral Thesis

PB - Lancaster University

ER -