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Realism and Control: Problem-Based Learning Programs as a Data Source for Work-Related Research

TitleRealism and Control: Problem-Based Learning Programs as a Data Source for Work-Related Research
Publication TypeWorking Paper
Year of Publication2002
AuthorsZolin, Rand Raymon, Fruchter, R, Levitt, RE
Date Published05/2002
Publication Languageeng
KeywordsCenter for Integrated Facility Engineering, CIFE, Cross-Functional, Distributed Work, Global Teams, Problem-Based Learning, Stanford University, Trust
AbstractProblem-based learning (PBL) is a pedagogical methodology that presents the learner with a problem to be solved to stimulate and situate learning. This paper presents key characteristics of a problem-based learning environment that determines its suitability as a data source for work-related research studies. To date, little has been written about the availability and validity of PBL environments as a data source and its suitability for work-related research. We describe problem-based learning and use a research project case study to illustrate the challenges associated with industry work samples. We then describe the PBL course used in our research case study and use this example to illustrate the key attributes of problem-based learning environments and show how the chosen PBL environment met the work-related research requirements of the research case study. We propose that the more realistic the PBL work context and work group composition, the better the PBL environment as a data source for a work-related research. The work context is more realistic when relevant and complex project-based problems are tackled in industry-like work conditions over longer time frames. Work group composition is more realistic when participants with industry-level education and experience enact specialized roles in different disciplines within a professional community.
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