Ontology‐driven disability‐aware e‐learning personalisation with ONTODAPS

Abstract

PurposeThe purpose of this paper is to show how personalisation of learning resources and services can be achieved for students with and without disabilities, particularly responding to the needs of those with multiple disabilities in e‐learning systems. The paper aims to introduce ONTODAPS, the Ontology‐Driven Disability‐Aware Personalised E‐Learning System, which has the mechanism for such personalisation.Design/methodology/approachThis paper reviews current e‐learning systems that provide personalisation for students, including their strengths and weaknesses. The paper presents personalisation and its techniques and then presents ONTODAPS, which personalises learning resources and services to students. In total, three case studies are considered to show how personalisation is achieved using ONTODAPS.FindingsThis paper shows that it is possible to use automated ontology‐based agents intercommunicating to provide an effective personalisation for disabled students. The results reveal that ONTODAPS is flexible enough to provide enough control and freedom to drive their learning. The results also suggest that ONTODAPS has the ability to provide appropriate levels of learner control by allowing them to self‐direct learning through personalising learning resources and then allowing them to choose which resources they wish to access. This thus gives them a sense of ownership and control.Research limitations/implicationsThis research reveals that it is possible for e‐learning systems to personalise learning for users with multiple disabilities. Thus, by considering the needs of such users and consulting them in the design and development process, developers of e‐learning systems can produce systems that are both accessible and usable by students with disabilities.Practical implicationsThe inclusion of multiple formats of learning resources and personalisation of their presentation to students means students will have increased access to such resources, with the potential of consuming and assimilating the information. This also has the potential of improving understanding and hence and improvement in results.Social implicationsThis research shows that ONTODAPS is a medium where disabled students can have equivalent learning experience with their non‐disabled peers. This could potentially increase access to learning for disabled students and possibly help improve their results due to an increase in accessibility of learning resources and usability of the system. This system thus complies with contemporary legislation which requires “reasonable adjustments” or “reasonable accommodations” to be made to meet the needs of disabled people.Originality/valueAlthough personalisation has been applied in e‐commerce systems, making them very successful, such personalisation is still a wish for e‐learning systems which struggle to catch up. This research proposes a solution in the e‐learning domain and its novelty is in its application to disabled students, including those with multiple disabilities.

The Portable Document Format (PDF) accessibility practice of four journal publishers

“…There are efforts being made through research to improve access to learning materials for students with disabilities (Nganji et al, 2013b). However, although much of the material needed for courses is usually located in the learning management systems, students may be referred to materials available elsewhere, including journal articles published in PDF.…”

Learning Pattern Discovery: Impact of User-Centric Design Approach towards Enhancement of E-learning Systems

“…prior knowledge of learners background, learning behaviour and actions when using the system. The system should also be capable to dynamically updat e the representation of users performance taking into account the changing state of the leaners and the variations in information that is relevant to each user considering the fact that there is an additional task of matching such learners (user profiles) with solutions that best fits their particular learning needs/requirement (Nganji et al, 2013). According to (Huang and Shiu, 2012;Nganji et al, 2011) the key challenge in developing automated system for learning is to build effectively represented user profile, learning styles and goal to help support reasoning about each learner.…”

Using Students’ Performance to Improve Ontologies for Intelligent E-Learning System

“…That being said, this simple test indicated that recommendations individualized for each student did help him or her to increase their knowledge and guide them through their learning process. Similar to patient-prescription-healing relation, the designed system offer student-personal recommendation-learning model (Kumaran & Sankar, 2013;Nganji et al, 2011). …”

“…A personalized E-learning system should: measure the student's knowledge on a subject, determine the concepts that need to be learned or reviewed, and provide essential content to the student. Supporting personalization in E-learning systems is one of the major benefits of using ontologies (Gaeta et al, 2009;Nganji, Brayshaw, & Tompsett, 2011;Ongenae et al, 2013;Yalcinalp & Gulbahar, 2010). There are adaptive systems designed to make personal recommendations by acquiring user's knowledge.…”