Designing Adaptive, Mixed-Mode HCI Research for Resilience

Nitin Verma

Kenneth R. Fleischmann

Kolina S. Koltai

We describe the design of a mixed-mode study that illustrates an adaptive approach to conducting HCI research. This mixed-mode approach is resilient to circumstances created by public health crises such as the COVID-19 pandemic. We based our study around a web-based survey instrument that was used both online (N = 205) and in an HCI lab (N = 29). Both modalities offer their respective advantages and limitations but complement each other to paint a picture that could not be obtained with either modality by itself. We believe that this approach may be timely and helpful for HCI researchers who moved to online data collection during the pandemic and are looking for ways to augment that data with lab data. This study design provides a potential template for mixed-mode research that can be resilient to future societal crises.

This publication uses Eye Tracking and Eye Tracking Screen Based which is fully integrated into iMotions Lab

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