Bayesian expert systems and multi-agent modeling for learner-centric Web-based education
Name
60686136-MIT.pdf
Description
Full printable version
Size
6.67 MB
Format
Adobe PDF
Checksum (MD5)
a7e4018940526c9ebac0bba263e25dca
Author(s)
Rabbat, Ralph R., 1978-
Advisor(s)
Steven R. Lerman.
Date Issued
2005
Publisher
Massachusetts Institute of Technology
Abstract
Online distance education provides students with a wealth of information. When students submit course-related search term queries, the search engine returns the search hits based on keyword and topic match. A student's particular learning style is not taken into consideration. For instance, a visually oriented student may benefit more than others from viewing videos and interacting with simulations. We address this problem by designing and developing a knowledge-based system for the initial assessment of students' learning styles. Each student's membership in a learning style dimension (e.g. visual or verbal) is estimated probabilistically. We reach this probability value by using a sequential Bayesian approach to administer a dynamic questionnaire that aims to attain a desired confidence level estimate with the minimal number of questions. A multi-agent online tutoring system uses this initial learning style model to start suggesting learning material matching the student's style. Each agent is an expert in a learning style dimension and can suggest the learning materials matching the student's style. In addition, these agents closely follow the student's evolving preferences and continuously update the stochastic model based on the student's online activities. When the student searches for course material, the multi-agent system delivers the search matches in a cycle-free preference order influenced by the students' multi-dimensional learning style model.
Description
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2005.
Includes bibliographical references (leaves 140-150).
Subjects
Civil and Environmental Engineering.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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