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Improving Evaluations in Computer-Supported Learning Projects

Improving Evaluations in Computer-Supported Learning Projects
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Author(s): John B. Nash (Stanford University, USA), Christoph Richter (University of Hannover, Germany)and Heidrun Allert (University of Hannover, Germany)
Copyright: 2009
Pages: 6
Source title: Encyclopedia of Distance Learning, Second Edition
Source Author(s)/Editor(s): Patricia L. Rogers (Bemidji State University, USA), Gary A. Berg (California State University Channel Islands (Retired), USA), Judith V. Boettcher (Designing for Learning, USA), Caroline Howard (HC Consulting, USA), Lorraine Justice (Hong Kong Polytechnic University, Hong Kong)and Karen D. Schenk (K. D. Schenk and Associates Consulting, USA)
DOI: 10.4018/978-1-60566-198-8.ch162

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Abstract

The call for the integration of program evaluation into the development of computer-supported learning environments is ever-increasing. Pushed not only by demands from policy groups and grant makers who desire greater accountability in lean times, this trend is due also because outcomes of computer supported learning environment projects often fall short of the expectations held by the project teams. The discrepancy between the targets set by the project staff and the outcomes achieved suggests there is a need for formative evaluation approaches (vs. summative approaches) that derive information that can be used to improve a program while it is in its development stage (see Worthen, Sanders, & Fitzpatrick, 1997). And in spite of the known benefits of integrating evaluation into the project development process, we note a lack of theoretical frameworks that reflect the peculiarities of computer-supported learning projects and the ways they evolve (see Keil-Slawik, 1999). This is of crucial importance, as formative evaluation will only be an accepted and effective part of a project if it provides information useful for the project staff. The purpose of this chapter is to outline the obstacles to integrating evaluation in computer-supported learning projects and then discuss two promising approaches that can be used to address these challenges.

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