Title :
Measuring Learning Difficulty Level by Comparing Ontologies
Author :
Zhang, Dehai ; Zhu, Yao
Abstract :
It is a common practice that learners (human beings or intelligent agent) estimate the difficulty level of their learning tasks. In this paper, we present an ontology comparison based method to measure the difficulty level by comparing target knowledge the learner wants to learn and the knowledge the learner already has. Our method proposes a set of measures that compare the differences of ontologies from two perspectives, the structural and the conceptual. Based on the result of comparing two ontologies, we defined the learning difficulty formally, and gave an algorithm to compute it.
Keywords :
learning (artificial intelligence); ontologies (artificial intelligence); intelligent agent; learning difficulty level measurement; ontologies; Birds; Computers; Electronic learning; Humans; Information processing; Intelligent agent; Knowledge representation; Laboratories; Ontologies; Software measurement;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.391