Learning and performance are not always commensurable. Conditions that maximize performance in the initial learning may not maximize learning in the longer term. I exploit this incommensurability to theoretically and empirically interrogate four possibilities for design: productive success, productive failure, unproductive success, and unproductive failure. Instead of only looking at extreme comparisons between discovery learning and direct instruction, an analysis of the four design possibilities suggests a vast design space in between the two extremes that may be more productive for learning than the extremes. I show that even though direct instruction can be conceived as a productive success compared to discovery learning, theoretical and empirical analyses suggests that it may well be an unproductive success compared with examples of productive failure and productive success. Implications for theory and the design of instruction are discussed.

This article proposes a conceptual framework of learning based on perspectives and methodologies being employed in the study of complex physical and social systems to inform educational research. We argue that the contexts in which learning occurs are complex systems with elements or agents at different levels—including neuronal, cognitive, intrapersonal, interpersonal, cultural—in which there are feedback interactions within and across levels of the systems so that collective properties arise (i.e., emerge) from the behaviors of the parts, often with properties that are not individually exhibited by those parts. We analyze the long-running cognitive versus situative learning debate and propose that a complex systems conceptual framework of learning (CSCFL) provides a principled way to achieve a theoretical rapprochement. We conclude with a consideration of more general implications of the CSCFL for educational research.

The current levels of enthusiasm for flipped learning are not commensurate with and far exceed the vast variability of scientific evidence in its favor. We examined 46 meta-analyses only to find remarkably different overall effects, raising the question about possible moderators and confounds, showing the need to control for the nature of the intervention. We then conducted a meta-analysis of 173 studies specifically coding the nature of the flipped implementation. In contrast to many claims, most in-class sessions are not modified based on the flipped implementation. Furthermore, it was flipping followed by a more traditional class and not active learning that was more effective. Drawing on related research, we proposed a more specific model for flipping, “Fail, Flip, Fix, and Feed” whereby students are asked to first engage in generating solutions to novel problems even if they fail to generate the correct solutions, before receiving instructions.

With the fast evolution of Virtual Reality (vr) technology, new prospects opened for embodied learning. Learners can now manipulate digital representations of abstract concepts and make sense of them through sensorimotor stimulation. However, in research, embodiment is explored from several perspectives, which, we argue, should be considered within a same framework. In this paper, we describe three major perspectives relevant for embodied learning in Virtual Reality (vr): embodied cognition, embodied interaction, and avatar embodiment. We organize these perspectives within one common interdisciplinary framework, and discuss resulting design opportunities for vr embodied learning interactions. Specifically, we show that embodied interaction does not necessarily support embodied cognition, and that breaking recommendations of avatar embodiment can actually support meaning-making. We believe our work offers novel avenues for future research and will foster interesting conversations in the hci community.