@proceedings{68,
title = {An Ontology Model for Building, Classifying and Using Learning Outcomes},
author = {Aikaterini Kalou and Georgia Solomou and Christos Pierrakeas and Achilles Kameas},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6268037},
year = {2012},
date = {2012-01-01},
journal = {12th IEEE International Conference on Advanced Learning Technologies (ICALT 2012)},
publisher = {IEEE Conference Publications},
address = {Rome, Italy},
abstract = {
Learning outcomes are statements that should accompany any type of educational material intended for lifelong learning. These statements deliver important information, which works as an indicator for students in the process of learning. However, in order for this information to be further utilizable within the context of intelligent e-learning applications, a more fine-grained definition and structure should be adopted. Having these in mind, we initially assign a strict and rather technical definition for the notion of learning outcomes, which is fully aligned, though, with their educational purpose. We then propose an ontological model for their representation and classification, which fully adheres to this definition. Our ultimate goal is to provide the mean for exploiting all aspects of knowledge implied by such statements within intelligent applications. To bear out this possibility, we apply our model to a selected piece of educational material provided by the Hellenic Open University.
<p style="text-align: justify;">Learning outcomes are statements that should accompany any type of educational material intended for lifelong learning. These statements deliver important information, which works as an indicator for students in the process of learning. However, in order for this information to be further utilizable within the context of intelligent e-learning applications, a more fine-grained definition and structure should be adopted. Having these in mind, we initially assign a strict and rather technical definition for the notion of learning outcomes, which is fully aligned, though, with their educational purpose. We then propose an ontological model for their representation and classification, which fully adheres to this definition. Our ultimate goal is to provide the mean for exploiting all aspects of knowledge implied by such statements within intelligent applications. To bear out this possibility, we apply our model to a selected piece of educational material provided by the Hellenic Open University.</p>
