scholarly journals Emulating Human Supervision in an Intelligent Tutoring System for Arithmetical Problem Solving

2014 ◽  
Vol 7 (2) ◽  
pp. 155-164 ◽  
Author(s):  
David Arnau ◽  
Miguel Arevalillo-Herraez ◽  
Jose Antonio Gonzalez-Calero
2014 ◽  
Vol 46 (6) ◽  
pp. 1189-1200 ◽  
Author(s):  
José Antonio González-Calero ◽  
David Arnau ◽  
Luis Puig ◽  
Miguel Arevalillo-Herráez

Author(s):  
Alla Anohina

The paper focuses on the issues of providing an adaptive support for learners in intelligent tutoring systems when learners solve practical problems. The results of the analysis of support policies of learners in the existing intelligent tutoring systems are given and the revealed problems are emphasized. The concept and the architectural parts of an intelligent tutoring system are defined. The approach which provides greater adaptive abilities of systems of such kind offering two modes of problem-solving and using a two-layer model of hints is described. It is being implemented in the intelligent tutoring system for the Minimax algorithm at present. In accordance with the proposed approach the learner solves problems in the mode which is the most appropriate for him/her and receives the most suitable hint.


Author(s):  
Yatao Li ◽  
Ke Zhao ◽  
Wei Xu

Intelligent tutoring systems (ITSs), which provide step-by-step guidance to students in problem-solving activities, have been shown to enhance student learning in a range of domains. However, they tend to be preestablished and cannot supply the tutoring function immediately from the diverse mathematical questions. The MITSAS (multiagent intelligent tutoring system after school) is a web-based ITS in algebra and geometry with a natural language interface which is designed to extract the hint and summarization from the detailed solving answer automatically. In this paper, its Design principles and functionality is analysed firstly. Then, the framework including the natural language understanding agent, automatic modelling agent and automatic problem-solving agent are discussed in the following in order to support the real-time problems solution. Next, the methods for automatically extracting tutoring function such as hint and summarization is given based on the difficulty of knowledge components and the type of problem acquired from the detailed answer. Finally, the effectiveness of MITSAS at improving the Chinese Students' learning gain is shown by an experiment conducted in junior school.


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