Open AccessDesigning an expert system for determining student learning styles using forward chaining in engineering education
Author(s) -
Muhammad Anwar
Publication year - 2021
Publication title -
jkp: jurnal konseling pendidikan/jurnal konseling dan pendidikan
Language(s) - English
Resource type - Journals
eISSN - 2337-6880
pISSN - 2337-6740
DOI - 10.29210/159000
Subject(s) - chaining , forward chaining , learning styles , quality (philosophy) , computer science , active learning (machine learning) , engineering education , style (visual arts) , process (computing) , knowledge management , work (physics) , expert system , backward chaining , mathematics education , engineering management , engineering , artificial intelligence , psychology , mechanical engineering , philosophy , archaeology , epistemology , psychotherapist , history , inference engine , operating system
Engineering education prepares its graduates able to work in the community and entrepreneurship, the quality of graduates is highly determined by the quality of the learning process is no exception for student learning styles. The purpose of this study was to describe the design of the expert system to determine the student learning style, the method used was forward chaining. The results of the design of this application have been able to diagnose student learning styles efficiently and provide the best solutions for their learning.