scholarly journals Student Modeling: Supporting Personalized Instruction, from Problem Solving to Exploratory Open Ended Activities

AI Magazine ◽  
2013 ◽  
Vol 34 (3) ◽  
pp. 13-26 ◽  
Author(s):  
Cristina Conati ◽  
Samad Kardan
Keyword(s):  
Problem Solving ◽  
Intelligent Tutoring Systems ◽  
Educational Games ◽  
Student Modeling ◽  
Student Needs ◽  
Personalized Instruction ◽  
Tutoring Systems ◽  
Student Models ◽  
Target Skills ◽  
Interactive Simulations

The field of intelligent tutoring systems has successfully delivered techniques and applications to provide personalized coaching and feedback for problem solving in a variety of domains. The core of this personalized instruction is a student model; the ITS component in charge of assessing student traits and states relevant to tailor the tutorial interaction to specific student needs during problem solving. There are however, other educational activities that can help learners acquire the target skills and abilities at different stages of learning including, among others, exploring interactive simulations and playing educational games. This article describes research on creating student models that support personalization for these novel types of interactions, their unique challenges, and how AI and machine learning can help.

scholarly journals Conceptual clustering: a new approach to student modeling in Intelligent Tutoring Systems

2018 ◽  
pp. 70-76 ◽  
Author(s):  
Yunia Reyes-González ◽  
◽  
Natalia Martínez-Sánchez ◽  
Adolfo Díaz-Sardiñas ◽  
Marisol de la Caridad Patterson-Peña ◽  
...  
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Student Modeling ◽  
Conceptual Clustering ◽  
New Approach ◽  
Tutoring Systems

Student Modeling in an Intelligent Tutoring System

2011 ◽  
pp. 208-236 ◽  
Author(s):  
Mingyu Feng ◽  
Neil Heffernan ◽  
Kenneth Koedinger
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Student Modeling ◽  
Tutoring System ◽  
Tutoring Systems ◽  
Fine Grained ◽  
Knowledge States ◽  
Complex Models ◽  
Cognitively Diagnostic

Student modeling and cognitively diagnostic assessment are important issues that need to be addressed for the development and successful application of intelligent tutoring systems (its). Its needs the construction of complex models to represent the skills that students are using and their knowledge states, and practitioners want cognitively diagnostic information at a finer grained level. This chapter reviews our effort on modeling student’s knowledge in the ASSISTment project. Intelligent tutors have been mainly used to teach students. In the ASSISTment project, we have emphasized using the intelligent tutoring system as an assessment system that provides instructional assistance during the test. Usually it is believed that assessment get harder if students are allowed to learn during the test, as its then like try to hit a moving target. So our results are surprising that by providing tutoring to students while they are assessed we actually prove the assessment of students’ knowledge. Additionally, in this article, we present encouraging results about a fine-grained skill model with that system that is able to predict state test scores. We conclude that using intelligent tutoring systems to do assessment seems like a reasonable way of dealing with the dilemma that every minute spent testing students takes time away from instruction.

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