Reducing Cognitive Load in Expert Interviews: Interface Design and Application of a Spreadsheet-based CASI System

Abstract

Traditional expert interviews in complex domains like kitchen cabinetry design often suffer from significant data collection errors and extraneous cognitive load for both the interviewer and interviewee. To address these bottlenecks, this study introduces a low-code Spreadsheet-native CASI (Computer-Assisted Structured Interview) tool. Developed under the principle of "Appropriate Design," the system leverages an End-User Development (EUD) approach to align functional requirements strictly with task objectives. By integrating real-time visual logic monitoring—such as immediate alerts for logical inconsistencies—and a unified interface, the tool shifts the researcher’s task from "recall" to "recognition" via preattentive processing. Validation through expert interviews confirmed that the tool achieved zero-error performance regarding data integrity and significantly reduced cognitive strain for both participants. Concurrently, the system successfully elicited a granular competency framework (seven competencies across five stages), revealing stage-wise shifts in professional requirements. These findings validate the efficacy of agile, researcher-led tool design in ensuring superior Task-Technology Fit without compromising methodological rigor. The study concludes by proposing a modular end-user development platform to build customizable, high-fidelity data acquisition tools for cross-disciplinary inquiry.

Keywords: Computer-assisted Structured Interviewing (CASI), Cognitive Load, Interface Design, Usability, Kitchen Cabinetry And Space Design

DOI: 10.54941/ahfe1008058