<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Developing Student Model for Intelligent Tutoring System"^^ . "The effectiveness of an e-learning environment mainly encompasses on how efficiently the tutor presents the\r\nlearning content to the candidate based on their learning capability. It is therefore inevitable for the teaching\r\ncommunity to understand the learning style of their students and to cater for the needs of their students. One\r\nsuch system that can cater to the needs of the students is the Intelligent Tutoring System (ITS). To overcome\r\nthe challenges faced by the teachers and to cater to the needs of their students, e-learning experts in recent times\r\nhave focused in Intelligent Tutoring System (ITS). There is sufficient literature that suggested that meaningful,\r\nconstructive and adaptive feedback is the essential feature of ITSs, and it is such feedback that helps students\r\nachieve strong learning gains. At the same time, in an ITS, it is the student model that plays a main role in\r\nplanning the training path, supplying feedback information to the pedagogical module of the system. Added to\r\nit, the student model is the preliminary component, which stores the information to the specific individual\r\nlearner. In this study, Multiple-choice questions (MCQs) was administered to capture the student ability with\r\nrespect to three levels of difficulty, namely, low, medium and high in Physics domain to train the neural\r\nnetwork. Further, neural network and psychometric analysis were used for understanding the student\r\ncharacteristic and determining the student’s classification with respect to their ability. Thus, this study focused\r\non developing a student model by using the Multiple-Choice Questions (MCQ) for integrating it with an ITS\r\nby applying the neural network and psychometric analysis. The findings of this research showed that even\r\nthough the linear regression between real test scores and that of the Final exam scores were marginally weak\r\n(37%), still the success of the student classification to the extent of 80 percent (79.8%) makes this student model\r\na good fit for clustering students in groups according to their common characteristics. This finding is in line\r\nwith that of the findings discussed in the literature review of this study. Further, the outcome of this research is\r\nmost likely to generate a new dimension for cluster based student modelling approaches for an online learning\r\nenvironment that uses aptitude tests (MCQ’s) for learners using ITS. The use of psychometric analysis and\r\nneural network for student classification makes this study unique towards the development of a new student\r\nmodel for ITS in supporting online learning. Therefore, the student model developed in this study seems to be\r\na good model fit for all those who wish to infuse aptitude test based student modelling approach in an ITS\r\nsystem for an online learning environment. (Abstract by Author)"^^ . "2018" . . . . . "Open University Malaysia"^^ . . . "OUM Graduate Centre, Open University Malaysia"^^ . . . . . . . . ""^^ . "Purushothman Ravichandran"^^ . " Purushothman Ravichandran"^^ . . "Open University Malaysia"^^ . . . . . . . "Developing Student Model for Intelligent Tutoring System (Text)"^^ . . . . . "library-document-1213.pdf"^^ . . . "Developing Student Model for Intelligent Tutoring System (Text)"^^ . . . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "lightbox.jpg"^^ . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "preview.jpg"^^ . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "medium.jpg"^^ . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "small.jpg"^^ . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "indexcodes.txt"^^ . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . . "Developing Student Model for Intelligent Tutoring System (Other)"^^ . . . . . "HTML Summary of #1213 \n\nDeveloping Student Model for Intelligent Tutoring System\n\n" . "text/html" . . . "LB Theory and practice of education"@en . ""@en . . . "QA76 Computer software"@en . .