Modeling the “Learning Process” of the Teacher in a Tutorial-Like System Using Learning Automata | IEEE Journals & Magazine | IEEE Xplore

Modeling the “Learning Process” of the Teacher in a Tutorial-Like System Using Learning Automata


Abstract:

Unlike the field of tutorial systems, where a real-life student interacts and learns from a software system, our research focuses on a new philosophy in which no entity n...Show More

Abstract:

Unlike the field of tutorial systems, where a real-life student interacts and learns from a software system, our research focuses on a new philosophy in which no entity needs to be a real-life individual. Such systems are termed as tutorial-like systems, and research in this field endeavors to model every component of the system using an appropriate learning model [in our case, a learning automaton (LA)]. While models for the student, the domain, the teacher, etc., have been presented elsewhere, the aim of this paper is to present a new approach to model how the teacher, in this paradigm, of our tutorial- like system “learns” and improves his “teaching skills” while being himself an integral component of the system. We propose to model the “learning process” of the teacher by using a higher level LA, referred to as the metateacher, whose task is to assist the teacher himself. Ultimately, the intention is that the latter can communicate the teaching material to the student(s) in a manner customized to the particular student's ability and progress. In short, the teacher will infer the progress of the student and initiate a strategy by which he can “custom-communicate” the material to each individual student. The results that we present in a simulated environment validate the model for the teacher and for the metateacher . The use of the latter can be seen to significantly improve the teaching abilities of the teacher.
Published in: IEEE Transactions on Cybernetics ( Volume: 43, Issue: 6, December 2013)
Page(s): 2020 - 2031
Date of Publication: 15 February 2013

ISSN Information:

PubMed ID: 23757589

References

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