An Ontology Model for Building, Classifying and Using Learning Outcomes

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.

An automation of the course design based on mathematical modeling and genetic algorithms

“…However, the current weakness is that two problems are solved by one algorithm: selection of relevant objects and their ordering. Also, it does not yet include different criteria of path construction (for example, multidimensional difficulty as in work [3], or type of students' perception) so it can become universal and can be upgraded to the social sequencing method or to the individual sequencing method, or contain both approaches. To analyze the real needs of finding a learning path we designed a full-fledged example in the area of programming and computer graphics using resources such as [10].…”

“…According to this review, there are a number of approaches, including methods using evolutionary algorithms. Paper [3] describes the merging of two ontologies: learning outcomes and Bloom's taxonomy. It shows rules and reasoning mechanisms for identifying the position of learning outcomes relative to each other.…”

An Instructional Design Methodology for Building Distance Learning Courses

“…However, in order for that to be feasible, the design and development of the instructional designs' core elements (i.e. Knowledge domain Representation Model, Learning Outcomes, LOs) should follow the standards and meet the requirements that have been placed in (Kalou, Solomou, Pierrakeas, & Kameas, 2012) (Nikolopoulos, Solomou, Pierrakeas, & Kameas, 2012). At this point, it should be emphasized that the adaptability of the system should be controlled.…”

“…learning outcomes) that the learner should ideally acquire after the successful completion of the course. outcomes must meet the specifications described in (Kalou, Solomou, Pierrakeas, & Kameas, 2012). During this step, for each concept to be learned by the learners, the ID defines at least one learning outcome that implies the acquisition of this particular concept at one of the RBT levels.…”

An Ontological Approach for Domain Knowledge Modeling and Management in E-Learning Systems

“…The necessity for a formal representation of the educational content is crucial in the case of designing courses for intelligent tutoring systems. Firstly, an efficient, formal representation of the cognitive domain will facilitate the tutors to define the learning strategies, techniques and outcomes for every cognitive domain [2]. Moreover, the conceptual representation will make easier the selection of the appropriate educational material (learning objects) so as to support the teaching of the specific domain of knowledge.…”