Investigating Students' Behaviors, Patterns, and Learning in a Multi-User Virtual Environment Designed Around Inquiry

Document Type



American Educational Research Association (AERA)

Publication Date



The River City MUVE is a middle school science curriculum designed around national content and assessments in biology, ecology, and epidemiology. Students engage in scientific inquiry as they investigate a disease outbreak in an 18th century city. This problem-based curriculum is delivered with a multi-user virtual environment (MUVE) which enables multiple simultaneous participants to access virtual contexts (e.g. an historically accurate 18th century city), interact with digital artifacts and tools (e.g. virtual microscopes), represent themselves through avatars (graphical representations of participants), communicate with other participants and with computer-based agents, and enact collaborative learning activities of various types (e.g., inquiry).

We are collecting rich data-streams about individual learners via a server-side database and embedded assessments. MUVE makes use of a customized server that contains a database that records the movements, actions, and communication of each student as they explore the environment. All items in the world that students can interact with have been tagged with identification codes. Every time a student clicks on a virtual object (picture, resident, microscope, map, etc) or speaks to either a resident or teammate, a record of the interaction is stored in the database. These data allow us to record the trajectory of each student as they work through the curriculum. To date, we have worked with over 70 teachers and approximately 5000 students in 9 states, logging more than 50,000 curriculum hours.

We will present findings on how these technologies are enabling us to understand students data-gathering behaviors (Ketelhut, 2006) and trajectories of participation (Clarke, 2006) at a level rarely visible to researchers. In addition, we will discuss how these data-streams provide complementary methods to our pre-post measures for assessing student learning, and therefore enable greater confidence in research conclusions (Ketelhut et al, in press; Clarke, 2006).

This document is currently not available here.