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Cognitive Interviewing within a Mixed Methods Practice: Utilization and Methodological Exploration of Cognitive Interviewing

Year: 2024
Type: article
Abstract: Cognitive interviewing (CI) is a memory-enhancing technique used to extract more valid data from participants by addressing cognitive needs. Present research applied CI to program evaluation, theorizing that more quality data would be retrieved, especially when utilizing a mixed methods approach. The program chosen to further explore this technique and provide potentially invaluable evaluation data was the Educational Psychology Department at the University of Nebraska-Lincoln (EDPS). The sample consisted of 32 individuals, consisting of graduate students and faculty across all programs. The overall evaluation focused on inter-program and inner program understanding which is operationalized as the ability to relay how accurately they interpret program roles and contributions to the department. Current research added additional processes to increase researcher transparency and maximize quality results. “Capability and Complexity of Question Responses” approach was introduced to improve transparency and quality. “Cognitive pathways” were introduced as a triangulation process through probability-based analyses that addressed response consistency and probability. Analyses looked within and between programs to capture the fullest picture. Findings showed that students and faculty within their programs had very consistent inner program understanding. The more prominent result was the inter-program understanding, which revealed that there was low consistency between response patterns between programs and the narratives expressed between programs, demonstrating very little awareness of the contributions of other programs. With these steps in hand the methodological process can assist in obtaining results that are capable of revealing narratives that can reflect varying levels of response patterns within and between groups. Advisor: Wayne A. Babchuk
Author: Hebner, Jack Riley
Language: English
Open Access status: green
OpenAlex ID: W7046068323
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