Optimizing Data Input Interfaces Through User Error Analysis: A Statistical and HCI-Driven Approach

چکیده

Accurate and efficient data input interfaces are essential for user interaction in a wide range of digital systems, from online forms to enterprise software. However, poorly designed input forms often lead to high error rates, increased cognitive load, and inefficiencies in task completion. This paper presents a comprehensive approach to optimizing data input interfaces by integrating Human-Computer Interaction (HCI) principles with statistical analysis techniques. The study compares three types of input form designs—simple, complex, and optimized layouts—focusing on their impact on user performance, including task completion time, error rates, and interaction counts (such as clicks and screen changes). By utilizing synthetic and real-world user data, we employ statistical methods to analyze how interface design choices influence user behavior, revealing patterns in error frequency and task inefficiency. Through iterative testing and user-centered redesign, the research aims to demonstrate how optimizing layout structure, minimizing unnecessary interactions, and improving input validation can reduce cognitive load and enhance user accuracy. The findings underscore the value of a data-driven approach to interface design, with results showing significant reductions in error rates and task times when optimized interfaces are implemented. This research offers an innovative framework for combining HCI insights and statistical analysis, providing a replicable methodology for improving the usability of data input systems across various industries. The proposed approach not only identifies specific design flaws but also delivers practical, evidence-based solutions for creating more intuitive and user-friendly interfaces, ultimately enhancing user experience and system efficiency.