UFRM: A User Feedback Reference Model for Managing Feedback in Dynamic Software Scenarios - Systematic Approach to Developing and Evaluating the UFRM in Dynamic Scenarios

Abstract

User feedback is essential for software improvement, shaping usability, functionality, and overall user experience. However, in Dynamic Scenarios, where users try to provide feedback under high cognitive load, stress, or mental pressure due to factors such as time sensitivity, environmental uncertainty, or task-focused workflows, significant challenges arise. These situations make it difficult for both feedback senders and receivers to effectively manage the feedback process. As a result, users may delay or skip giving feedback altogether, making it harder for receivers to collect and process valuable input, especially in dynamic scenarios.

This study develops a User Feedback Reference Model (UFRM) to improve feedback management under such conditions. We conducted 10 semi-structured interviews with feedback receivers (such as developers and product managers) and 30 semi-structured interviews with feedback senders (end users) to understand their current issues in collecting and processing feedback in dynamic scenarios. The results were analyzed using Thematic Analysis to identify key preferences and challenges of both sides and suggest solutions. These findings were then structured into a four-layer conceptual model for managing real-time feedback in dynamic scenarios, covering scenario detection, feedback collection, processing, and response.

UFRM was validated using three real-world inspired use cases covering smart navigation systems, autonomous autopilot driving, and digital healthcare platforms to ensure its effectiveness. These use cases were derived from real feedback contexts shared by users during interviews and were applied step-by-step to test the model’s adaptability and performance under realistic dynamic constraints. The findings provide insights into optimizing feedback mechanisms in dynamic scenarios, balancing the preferences of both feedback senders and receivers, and supporting better software adaptation and user experience.