Case-based reasoning approach for utilisation of past remarks as advice for collaborative learning
Author(s) -
Tomoko Kojiri,
Shuto Ohata,
Yuki Hayashi
Publication year - 2014
Publication title -
international journal of knowledge and web intelligence
Language(s) - English
Resource type - Journals
eISSN - 1755-8263
pISSN - 1755-8255
DOI - 10.1504/ijkwi.2014.065064
Subject(s) - computer science , advice (programming) , case based reasoning , artificial intelligence , human–computer interaction , programming language
The collaborative learning remarks that were triggers of the past active discussion, which is called discussion promotion remark, can also be effective in the current discussion situation whose speech patterns are similar. The objective of this research is to construct the advising system for the collaborative learning which utilises discussion promotion remarks of the past collaborative learning as advice to solve current inappropriate situation. Discussion consists of various characteristics, so it is difficult to define appropriate speech pattern for each type of discussion promotion remark. This research introduces case-based reasoning approach to extract past discussion promotion remark which can solve current inappropriate situation. This paper describes two of the steps to accomplish the case-based reasoning system. First, several parameters that characterise the discussion situation are introduced and attached to past discussion promotion remarks. Second, discussion promotion remark database is constructed as a decision tree based on the attached parameters.
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