Originally funded by the National Science Foundation
Current Research Endeavors
Studying Robust-Design Strategies for Developing Innovations Effective and Scalable in Challenging Classroom Settings
This project studied the extent to which The River City MUVE, a technology-based curricular innovation, developed through "robust-design" strategies is effective in increasing students' educational outcomes across a range of challenging classroom settings. Evolving an intervention for extreme scalability - even into contexts in which some of its conditions for success are attenuated or lacking - requires "ruggedizing" its efficacy when parts of its intended enactment are absent.
Developing an innovation capable of adaptation into most school sites involves designing interventions that retain a substantial proportion of their effectiveness despite relatively barren settings, such as many urban districts, in which some of the innovation's important conditions for success (e.g., a supportive administration, qualified and enthusiastic teachers, a well maintained technology infrastructure) are missing or attenuated. Under these circumstances, major intended aspects of an innovation's design will not be enacted as intended by its developers, so evolving robust-design strategies and studying the efficacy under inhospitable conditions of interventions produced using these ruggedized strategies is important. This project will assess such a strategy for extreme scalability through design-based research on large-scale implementations of a multi-user virtual environment curriculum across a spectrum of contexts.
Recently, the River City team began exploring the use of data mining techniques to harvest information from the data beyond the articulated research questions of the study. This work culminated in the development of the Avatar Log Visualizer (AVL), freely available here.
- Museum-Related Multimedia and Virtual Environments for Teaching and Learning Science » NSF Grants 9980464, 0296001, 0202543
- Studying Situated Learning and Knowledge Transfer in a Multi-User Virtual Environment » NSF Grant 0310188