e-Learning for depth in the Semantic Web

Abstract

In this paper, we describe concept parsing algorithms, a novel semantic analysis methodology at the core of a new pedagogy that focuses learners' attention on deep comprehension of the conceptual content of learned material. Two new e-learning tools are described in some detail: interactive concept discovery learning and meaning equivalence reusable learning objects. These semantic technologies were developed at the Ontario Institute for Studies in Education and Adaptive Technology Resource Centre of Faculty of Information Studies (ATRC/FIS) at the University of Toronto; they were tested since 2001 in several academic institutions in Canada and at the Russian Academy of Sciences (patents pending: US patent 6,953,344 B2, USPO ♯20050149510; Copyright 2005, PARCEP Inc.). We describe the rationale for developing these instructional tools, their main characteristics and results of several evaluative implementations that show their potential to enhance learning outcomes and to provide authentic, credible, evidence-based formative assessments of learning processes.