Chapter 7: Captured Matter: Using Web-Based Informatics for Evaluation of Educational Projects
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Published:2010
Matthew J. Stuve, Jerrell C. Cassady, Laurie J. Mullen, Jody S. Britten, 2010. "Captured Matter: Using Web-Based Informatics for Evaluation of Educational Projects", Evaluating Technology in Teacher Education: Lessons from the Preparing Tomorrow’s Teachers for Technology (Pt3) Program, Walt Heinecke, Pete Adamy
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In this chapter we will discuss Web-based models for distributed evaluation of multidimensional educational projects for K-12 and teacher education institutions. Many Preparing Tomorrow’s Teachers to Use Technology projects involved large numbers of distributed participants and personnel, working on numerous initiatives, for numerous stakeholders, all within multiple evaluative lenses. The shear volume of activity involves management of data requiring technical and organizational capacities that teacher education institutions traditionally lack. Furthermore, and perhaps more importantly, K-12 and teacher education institutions traditionally lack systems for large-scale data acquisition, management and representation in digital form.
We approach informatics as the application of computer science and data systems to decision-making to support a line of inquiry. This model not only facilitated the evaluation of our PT3 project, but also demonstrated the plausibility of future roles for universities in providing outreach to K-12 schools and supporting K-12 efforts to develop and employ data-driven decision-making systems. The systems of data capture, organization, and access that we will discuss in this chapter will become increasingly useful as evaluation projects become progressively more stringent in their access of varied relevant sources of data from diverse settings. As federal guidelines have developed in recent years, it is increasingly important to be able to gather and maintain performancebased data from multiple locations. Our model allows us to meet the challenge of maintaining high standards in evaluation design while capturing contextually rich data across a widespread network of stakeholders.
