Bayesian network student modeling of novice C programmers
Intelligent Tutoring Systems must make use of student models to represent the knowledge of their users. Although there are currently several different implementations of Bayesian network student models in existence, they all model the students current state of knowledge only. They do not address the...
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| Format: | text |
| Language: | English |
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Animo Repository
2005
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_masteral/3341 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=10179&context=etd_masteral |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | Intelligent Tutoring Systems must make use of student models to represent the knowledge of their users. Although there are currently several different implementations of Bayesian network student models in existence, they all model the students current state of knowledge only. They do not address the need to come up with a way to integrate the representation of misconceptions that may exist in a students mind into their network. Because the presence of misconceptions can affect the thought processes of students, the ability to model them in a Bayesian network student model should improve that models ability to make approximations about the user. The aim of this research is to design a Bayesian network student model for Novice C Programmers.
Keywords: Intelligent Tutoring System, Bayesian network, Student Model, Misconception |
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