Blockchain-Driven Research in Personality-Based Distributed Pair Programming

TL;DR

This paper explores integrating blockchain technology into personality-based pair programming research to improve transparency, reproducibility, and motivation, demonstrating its effectiveness through distributed experiments and a custom web app.

Contribution

It introduces the ROMA framework linking personality traits to programming roles and utilizes blockchain for transparent data management in distributed pair programming research.

Findings

Blockchain enhances research transparency and reproducibility.

ROMA framework increases motivation and team productivity.

Distributed experiments validate personality-based pairing effectiveness.

Abstract

This study aims to integrate blockchain technology into personality-based pair programming research to enhance its generalizability and adaptability by offering built-in continuous, reproducible, and transparent research. In the developing Role-Optimization Motivation Alignment (ROMA) framework, human/AI programming roles align with individual Big Five personality traits, optimizing individual motivation and team productivity in Very Small Entities and undergraduate courses. Twelve quasi-experimental sessions were conducted to verify the personality-based pair programming in distributed settings. A mixed-methods approach was employed, combining intrinsic motivation inventories and qualitative insights. Data were stored transparently on the Solana blockchain, and a web-based application was developed in Rust and TypeScript languages to facilitate partner matching based on ROMA suggestions, expertise, and availability. The results suggest that blockchain can enhance research generalizability, reproducibility, and transparency, while ROMA can increase individual motivation and team performance. Future work can focus on integrating smart contracts for transparent and versioned data analysis.