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Evaluating The Effectiveness And Use Of Cyber Learning Environments In Engineering Education: A Qualitative Analysis

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2009 Annual Conference & Exposition


Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009



Conference Session

Computational Tools and Simulation III

Tagged Division

Computers in Education

Page Count


Page Numbers

14.592.1 - 14.592.15

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Paper Authors


Krishna Madhavan Purdue University

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Dr. Krishna P.C. Madhavan is an Assistant Professor at Clemson University with a joint appointment in the Department of Engineering and Science Education and the School of Computing. Before his appointment at Clemson, he served as a Research Scientist in the Science Gateways Group at the Rosen Center for Advanced Computing, Information Technology at Purdue University where he led the education and the educational technology effort for the NSF-funded Network for Computational Nanotechnology (NCN). Dr. Madhavan was the Chair of the IEEE/ACM Supercomputing Education Program 2006 and was the curriculum director for the Supercomputing Education Program 2005. In January 2008, he was awarded the NSF CAREER for work on transforming engineering education through learner-centric, adaptive cyber-tools and cyber-environments.

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Jacob Schroeder Clemson University

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Dr. Schroeder is a post-doctoral researcher at Clemson University. His work focuses on cyberinfrastructure in engineering education. He holds a Ph.D. in Chemistry Education from Iowa State University.

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Hanjun Xian Clemson University

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Hanjun Xian is a Ph.D student working on issues of design of cyber-environments in engineering education at Clemson University.

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Evaluating the Effectiveness and Use of Cyberlearning Environments in Engineering Education—A Qualitative Analysis

Abstract Cyberlearning is playing an increasingly important role in engineering education. According to a recent National Science Foundation (NSF) report entitled Fostering Learning in the Networked World, “cyberlearning has the potential to transform education throughout a lifetime, enabling customized interaction with diverse learning materials on any topic” (p. 5). Cyberinfrastructure forms the foundation of cyberlearning and allows students to comprehend complex engineering concepts by interacting with scientific data, visualizations, remote and virtual laboratories. New cyberlearning environments have the potential to extend learning from traditional classrooms and physical laboratories to include informal environments such as social networks and virtual spaces. Despite these significant advances, a larger theoretical framework of learning that includes cyberinfrastructure at its very core has not yet evolved. The purpose of this research is to provide a synthesis of the fundamental characteristics of cyberlearning environments that are being created to facilitate student learning within engineering disciplines. Furthermore, we examine in-depth how educators are defining cyberlearning within the context of learning theories in general, and engineering education in particular. Our methodology focuses on a qualitative analysis of articles in the engineering education literature drawn from The Journal of Engineering Education spanning the past 10 years. Four broad criteria guided the selection and analyses of the articles: (1) Content: What major types of content for cyberlearning environments are being created focused particularly on engineering education? For example, the NSF identifies various categories of content for cyberlearning environments such as interactive online courses, intelligent tutors, virtual and remote laboratories, and serious games. (2) Pedagogy: How are these cyberlearning environments being incorporated in the classroom to promote learning? For example, several educators have reported using the learning technology to supplement a traditional lecture or course. Others have replaced the traditional classroom altogether. (3) Audience: Who is the primary audience for the cyberlearning environments? For example, these environments can be created for both students and faculty to promote distance learning – allowing better access for participants from remote locations lacking high-cost instrumentation and facilities. (4) Outcomes: What learning outcomes are being measured? Is the cyberlearning environment enhancing these outcomes? For example, specific outcomes can include student content knowledge measured by exam performance or concept inventories and student perceptions measured by course evaluations. The results presented in this paper draw out major trends in cyberlearning within the context of engineering education over the past decade.

Madhavan, K., & Schroeder, J., & Xian, H. (2009, June), Evaluating The Effectiveness And Use Of Cyber Learning Environments In Engineering Education: A Qualitative Analysis Paper presented at 2009 Annual Conference & Exposition, Austin, Texas.

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