The design, experiment, analyse, and reproduce principle for experimentation in virtual reality

Abstract

Conducting experiments in virtual reality (VR) requires a complex setup of hardware, software, experiment design and implementation, and data collection which is supported by frameworks that provide pre-determined features for scientists to implement their experiment in VR. These VR frameworks have proliferated exponentially since the start of the millennia, and unfortunately, they both only differ slightly from one another and often miss one or more of the key features required by the researcher. Therefore, it has become less clear to researchers which framework to choose for what task and to what benefit. I introduce the design, experiment, analyse, and reproduce (DEAR) principle to develop a new perspective on VR frameworks through a holistic approach to experimentation (i.e., the process of conducting an experiment). The DEAR principle lays out the core components that future frameworks should entail. Most previous VR frameworks have focussed on the design phase and sometimes on the experiment phase to help researchers create and conduct experiments. However, being able to create an experiment with a framework is not sufficient for wide adoption. Ultimately, I argue that it is important to take reproducibility seriously to overcome the limitations of current frameworks. Once experiments are fully reproducible through automation, the adaptation of new experiments becomes easier. Hopefully, researchers can find ways to converge in the use of frameworks or else frameworks may become a hindrance instead of a help.