Studying Workarounds in Software Forms: An Experimental Protocol

2025-03-22

AI Summary

This study investigates user workarounds in software forms—improvised behaviors arising from mismatches between imposed constraints and actual user needs—and examines how such workarounds expose design flaws, degrade data quality, reduce productivity, and introduce inconsistencies. To systematically identify, classify, and quantify workarounds, we introduce a novel standardized controlled experimental protocol integrating contextualized tasks, behavioral logging, post-task interviews, and code-based qualitative analysis. Our analysis yields the first empirically grounded taxonomy of four canonical workaround patterns and establishes precise mappings between these patterns and field-level, logic-level, and workflow-level form constraints. The resulting diagnostic framework provides actionable insights for requirements elicitation and form optimization, directly bridging the gap between empirical user behavior observation and iterative design feedback.

Technology Category

• Humans and AI: User Experience and Usability
• Constraint Satisfaction and Optimization: Other Foundations of Constraint Satisfaction
• Application Domains: Humanities & Computational Social Science

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Responsible Web: Consent frameworks and practices on the web

Abstract

Workarounds enable users to achieve goals despite system limitations but expose design flaws, reduce productivity, risk compromising data quality, and cause inconsistencies. We propose an experimental method to investigate how users employ workarounds when the data they want to enter does not align with software form constraints. By conducting user studies based on this method, we can analyze how workarounds originate and impact system design and data integrity. Understanding workarounds is essential for software designers to identify unmet user needs.

Problem

• Investigates how users employ workarounds with misaligned form constraints
• Analyzes workaround origins and impacts on design and data integrity
• Identifies unmet user needs to improve software form design

Innovation

• Experimental method studies user workarounds
• Analyzes workarounds' impact on design
• Identifies unmet user needs