Restructure This: Using AI to Restructure Onboarding Documents to Reduce Cognitive Overload

2026-05-18

AI Summary

This study addresses the challenge of cognitive overload experienced by newcomers to open-source software, often caused by disorganized structure, redundant content, and fragmented information in onboarding documentation. To mitigate this barrier to participation, the work proposes a generative AI–driven optimization framework that systematically applies Cognitive Theory of Multimedia Learning (CTML) to documentation redesign. The framework employs semantic segmentation to extract discrete task units, infers implicit workflows, removes redundancies, and generates multimodal explanations to enhance comprehensibility. Expert evaluations confirm the approach’s completeness and feasibility, while user studies demonstrate that it significantly reduces cognitive load for novices, leading to higher task success rates and improved perceived usability.

Abstract

Onboarding documentation is critical for attracting and retaining newcomers in open source software (OSS). However, it is often presented as dense, inconsistently structured, and fragmented presentations that are difficult to understand, which creates cognitive overload leading to frustration, errors, and abandonment. Here, we investigate how Cognitive Theory of Multimedia Learning (CTML) strategies can be used to restructure OSS documentation. We use a GenAI-based pipeline to operationalize these strategies to restructure OSS documentation through our prototype VisDoc. VisDoc segments documentation into task-based units, infers workflows, removes redundancy, and generates multimodal explanations. An expert evaluation (N=4) affirmed VisDoc's completeness, accuracy, and adoptability; A between-subjects evaluation (N=14) with newcomers found that VisDoc participants achieved higher task success, had significantly lower cognitive load, and perceived higher usability. The contributions of this work include a CTML-grounded analysis of onboarding challenges, a GenAI-based documentation restructuring pipeline, and empirical evidence that cognitively informed documentation restructuring reduces cognitive load and improves usability and task performance in OSS.

Problem

• onboarding documentation
• cognitive overload
• open source software
• documentation structure
• newcomer retention

Innovation

• GenAI
• Cognitive Load Reduction
• Documentation Restructuring
• Multimodal Explanation
• Onboarding