Design-Based Research Methods in CSCL: Calibrating our Epistemologies and Ontologies (original) (raw)

2020, International Handbook of Computer-Supported Collaborative Learning

Design-based research (DBR) methods are an important cornerstone in the methodological repertoire of the learning sciences, and they play a particularly important role in CSCL research and development. In this chapter, we first lay out some basic definitions of what DBR is and is not, and discuss some history of how this concept came to be part of the CSCL research landscape. We then attempt to describe the state-of-the-art by unpacking the contributions of DBR to both epistemology and ontology of CSCL. We describe a tension between two modes of inquiry-scientific and design-which we view as inherent to DBR, and explain why this has provoked ongoing critique of DBR as a methodology, and debates regarding the type of knowledge DBR should produce. Finally, we present a renewed approach for conducting a more methodologically-coherent DBR, which calibrates between these two modes of inquiry in CSCL research. Definition & Scope DBR is one of a cluster of terms used to describe various intersections between design and research, especially in the realm of academic research in either education or in human-computer interaction. In this section, we attempt to define what we mean by design-based research and contrast it with other definitions. DBR methods were originally defined (Design-Based Research Collective [DBRC], 2003; Hoadley, 2002), like the earlier concept of design experiments (Brown, 1992; Collins, 1990,1992), as a research method or related methodology which used a blended form of design activities and research activities to produce design-relevant, empirically supported knowledge. Designed interventions in DBR are tested iteratively in a context of use, and the iterations become settings to collect data that support or refute inferences about underlying theoretical claims. At the same time, the iterations are used for increasing the fit between the theory, the design, and the enactment or implementation so as to best test the theoretical conjectures. Unlike earlier definitions associated with design experiments (notably Brown's, 1992), DBR methods were claimed to be not merely related to hypothesis generation, but a scientific enterprise in their own right. This approach stemmed from a very practical problem described earlier by Simon (1969) in his seminal book-The Sciences of the Artificial-namely, that