Analyzing the efficacy of using digital ink devices in a learning environment |
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Authors: | Akila Varadarajan Nilesh Patel Bruce Maxim William I Grosky |
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Affiliation: | (1) The University of Michigan - Dearborn, 4901, Evergreen Road, Dearborn, MI 48080, USA;(2) Oakland University, 2200 N. Squirrel Road, Rochester, MI, USA |
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Abstract: | There has been increased interest on the impact of mobile devices such as PDAs and Tablet PCs in introducing new pedagogical
approaches and active learning experiences. We propose an intelligent system that efficiently addresses the inherent subjectivity
in student perception of note taking and information retrieval. We employ the idea of cross indexing the digital ink notes
with matching electronic documents in the repository. Latent Semantic Indexing is used to perform document and page level
indexing. Thus for each retrieved document, the user can go over to the relevant pages that match the query. Techniques to
handle problems such as polysemy (multiple meanings of a word) in large databases, document folding and no match for query
are discussed. We tested our system for its performance, usability and effectiveness in the learning process. The results
from the exploratory studies reveal that the proposed system provides a highly enhanced student learning experience, thereby
facilitating high test scores.
Akila Varadarajan
is a Senior Software Engineer at Motorola, IL with the Mobile devices division. Prior joining Motorola, she was a Software
development intern at Autodesk, MI and Graduate Research assistant at University of Michigan - Dearborn. She received her
MS in Computer Engineering from University of Michigan in 2006 and her BS in Computer Engineering from Madurai Kamaraj University,
India in 2003. She is interested in Mobile computing - specifically Human Factors of Mobile Computing, Information retrieval
and pattern recognition.
Nilesh Patel
is Assistant Professor in the department of Computer Science and Engineering at Oakland University, MI. He received his PhD
and MS in Computer Science from Wayne State University, MI in 1997 and 1993. He is interested in Multimedia Information Processing
- specifically audio and video indexing, retrieval and event detection, Pattern Recognition, Distributed Data Mining in a
heterogeneous environment, and Computer Vision with special interest in medical imaging. Dr. Patel has also served in the
automotive sector for several years and developed interest in Telematics and Mobile Computing.
Bruce Maxim
has worked as a software engineer for the past 31 years. He is a member of the Computer and Information Science faculty at
the University of Michigan-Dearborn since 1985. He serves as the computing laboratory supervisor and head of the undergraduate
programs in Computer Science, Software Engineering, and Information Systems. He has created more than 15 Computer and Information
Science courses dealing with software engineering, game design, artificial intelligence, user interface design, web engineering,
software quality, and computer programming. He has authored or co-authored four books on programming and software engineering.
He has most recently served on the pedagogy subcommittee for Software Engineering 2004 and contributed to the IDGA Game Curriculum
Framework 2008 guidelines.
William I. Grosky
is currently Professor and Chair of the Department of Computer and Information Science at University of Michigan - Dearborn,
Dearborn, Michigan. Prior to joining the University of Michigan in 2001, he was Professor and Chair of the Department of Computer
Science at Wayne State University, Detroit, Michigan. Before joining Wayne State University in 1976, he was an Assistant Professor
in the Department of Information and Computer Science at Georgia Tech, Atlanta, Georgia. He received his B.S. in Mathematics
from MIT in 1965, his M.S. in Applied Mathematics from Brown University in 1968, and his Ph.D. in Engineering and Applied
Science from Yale University in 1971.
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Keywords: | Pen-based computing Digital ink Latent semantic indexing Information retrieval Document cross indexing |
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