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How Does an Interactive Knowledge Platform Influence Decision-making of Novice Researchers in Engineering Education Research?

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2012 ASEE Annual Conference & Exposition


San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012



Conference Session

Best of Computers in Education Division

Tagged Division

Computers in Education

Page Count


Page Numbers

25.699.1 - 25.699.17



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Paper Authors


Xin Chen Purdue University, West Lafayette

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Xin Chen is a Ph.D. student in the School of Engineering Education at Purdue University. Her research focuses on social media analytics in the context of engineering education and engineering education research, and web personalization.

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Adithya Raghavan


Ji Soo Yi Purdue University

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Ji Soo Yi is an Assistant Professor specializing in human factors in the School of Industrial Engineering at Purdue University. He founded the Healthcare and Information Visualization Engineering (HIVE) Lab in March 2009. He received a B.S. degree in industrial engineering from Seoul National University in 1998. After graduation, he worked in industry for five years as a consultant and as an embedded software engineer in Seoul and Boston, where he became interested in human-computer interaction (HCI) research. He received his Ph.D. degree from the School of Industrial and Systems Engineering at Georgia Institute of Technology in Aug. 2008. His research topics include human-computer interaction, information visualization, and decision science, and he has focused on applying these techniques on improving healthcare services.

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Krishna Madhavan Purdue University, West Lafayette

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How does an Interactive Knowledge Platform Facilitate Decision-Making of Novice Researchers in Engineering Education Research?Background: Engineering Education Research (EER) is a newly emerging and highlyinterdisciplinary field of research. Many first-year PhD students in the EER community comefrom an engineering background. They usually have difficulties of shifting mindset from solvingspecific engineering problems to conducting rigorous educational research (Borrego, 2007).They are concerned with how they would fit their research interests to the larger knowledgebody, what other related work has been done, and what questions are worth asking in this field.Given the great demand for understanding the emerging field of EER, an interactive visualizationplatform iKNEER (Interactive Knowledge Network for Engineering Education Research, was developed with the goal of supporting researchers in the EERcommunity (Madhavan et. al, 2011). iKNEER is potentially helpful for first-year PhD students’research process by providing a comprehensive overview of the current state of the field, and theinsights about academic trends related to topical areas and who to follow on certain topics.Research Questions: There are many other computational tools developed aiming at helpingresearchers to characterize their respective research fields and identify patterns and trends in theliterature, such as CiteSeerx (Li, Councill, Lee, & Giles, 2006) and Apolo (Chau, Kittur, Hong,& Faloutsos, 2011). These tools often employ sophisticated data-mining algorithms andadvanced information visualization techniques. They are usually tested as effective under limitedcontext. For example, one tool may help users to locate references related to certain topics fasterthan others. However, little research has been found investigating novice researchers’ researchactivities in a realistic context, such as how researchers use these tools and why they feel thesetools are useful or not. The goal of this paper is to answer the following questions: (1) How doesiKNEER potentially facilitate decision-making of novice researchers with the research directionsthey choose? (2) What is the perceived usefulness of this tool among novice researchers? (3)What are the issues identified during the use of iKNEER and how these insights inform futuredevelopment of such tools?Methods: In this paper, we employ a qualitative approach to answer those questions. We presentresults from semi-structured interviews with first-year PhD students in Engineering Education.The participants are recruited among first-year PhD students registered in an introductoryresearch methods class. Students write a research proposal as the class final assignment whileusing iKNEER as an assistive tool. The data is analyzed using qualitative thematic analysis tolook for emerging common themes and patterns in order to address our research questions. Theresults of this study bring insight into human perceptions of the research tool, and could informfuture development of such tools.Borrego, M. (2007). Conceptual Difficulties Experienced by Trained Engineers Learning Educational Research Methods. Journal of Engineering Education, 96(2), 91–102.Chau, D. H., Kittur, A., Hong, J. I., & Faloutsos, C. (2011). Apolo: making sense of large network data by combining rich user interaction and machine learning. Proceedings of the 2011 annual conference on Human factors in computing systems (pp. 167–176).Li, H., Councill, I., Lee, W. C., & Giles, C. L. (2006). CiteSeerx: an architecture and web service design for an academic document search engine. Proceedings of the 15th international conference on World Wide Web (pp. 883–884).

Chen, X., & Raghavan, A., & Yi, J. S., & Madhavan, K. (2012, June), How Does an Interactive Knowledge Platform Influence Decision-making of Novice Researchers in Engineering Education Research? Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--21456

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