Paper Info
Title
Fuzzy Grading for Adaptability in a Learning Platform.
Abstract
Due to the increasing global competition and technology's constant progress, the usage of online training platforms has grown rapidly. One of the problems that these platforms face is the lack of a physical evaluator. Given that flexible evaluating methods are considered necessary in training platforms this is an obstacle we must overcome. In this paper we describe the implementation of a fuzzy grading system that is going to be used in the Competence Oriented Multilingual Adaptive Language Assessment and Training (COMALAT) system as an intelligent evaluating system of the platform. First, we present a literature review on fuzzy evaluation methods and afterwards we describe the technique that we used in order to apply it in the COMALAT platform. Aside from the COMALAT platform, the fuzzy grading system is an innovative evaluation method that can be deployed in other online learning platforms as well, due to its adaptability and capability to automatically set the difficulty of a quiz, based on the learners' performance.
Year
DOI
Venue
2016
10.1145/3003733.3003766
PCI
Keywords
Field
DocType
Fuzzy grading, Membership functions, Evaluation method, Adaptability, Learning platforms
Adaptability,Online learning,Obstacle,Data mining,Virtual learning environment,Software engineering,Grading (education),Computer science,Fuzzy logic,Artificial intelligence,Language assessment,Aside
Conference
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
Kyriaki Chatzistavrou100.34
George Kakarontzas28012.72
Lefteris Angelis3129682.51