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Published Articles >> Table of Contents >> Abstract
International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1
p. 192
Assessing Distance Learning Student's Performance: A Natural Language Processing Approach to Analyzing Class Discussion Messages
Yi-fang Brook Wu, New Jersey Institute of Technology
Xin Chen, New Jersey Institute of Technology
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ITCC.2004.1286449
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| Abstract |
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In classes supported by electronic messaging
systems, students are required or encouraged to
discuss the class topics and share their knowledge
by posting text messages and replying to others.
When the amount of messages is large, it is
difficult for the instructor to read through all
messages and evaluate student's performance.
We apply natural language processing techniques
to analyze the course messages to assess student's
performance. Students are evaluated from three
aspects: knowledge learned from the class, effort
devoted to the class, and the activeness of their
participation; three measures - keyword density
(KD), message length (ML), and message count
(MC), are derived from the text messages for each
evaluation aspect respectively. The three
measures are then combined to compute an
overall performance indicator (PI) score for each
student. The experiment shows that there is a high
correlation between the PI scores and the actual
grades; the rank order of students by the PI
scores and that by the actual grades are highly
correlated as well.
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 Additional Information
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Index Terms- Natural Language Processing, Automated Grading, Education Technology, Keyword Density
Citation:
Yi-fang Brook Wu, Xin Chen,
"Assessing Distance Learning Student's Performance: A Natural Language Processing Approach to Analyzing Class Discussion Messages,"
itcc,
p. 192,
International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1,
2004
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