Blended learning could be seen as the solution to learning resources accessibility especially when the indicators of measure are limited to distance and time. Distance and time could be said to be the generic indicators for the measure of blended learning, however, these do not solve the problem for everyone in the society. For Inclusive Blended Learning (IBL), different types of users in society should be considered in its design. This is exactly what has provoked the focus of this chapter, to investigate the position of blended learning with respect to people with disability. The chapter's investigation is centered on selected secondary schools in Cameroon and Nigeria.
Nganji, J.T. and Nggada, S. H. (2014). Adoption of Blended Learning Technologies in Selected Secondary Schools in Cameroon and Nigeria: Challenges in Disability Inclusion. In N. Ololube (Ed.), Advancing Technology and Educational Development through Blended Learning in Emerging Economies (pp. 159-173). Hershey, PA: Information Science Reference. doi:10.4018/978-1-4666-4574-5.ch009. [Link to Book Chapter]
The increasing use of technology to enhance learning means both disabled students and higher education institutions face the challenge of adapting technology to meet the educational and special needs of students. As most e-learning systems are not designed to meet special needs, it is imperative to look for newer ways of designing e-learning systems to ensure that they are disability-aware and meet their assistive technology needs. In this light, this paper summarizes the result of research to seek better ways of enhancing learning for disabled students. Here, the resultant ONTODAPS system is introduced, including the methodology developed to design the system, its architecture and evaluation by 30 disabled students. The results of the usability evaluation are presented and discussed. It is hoped that researchers, instructional designers and developers of e-learning systems would look to this paper to gain insight into the design and development of disability-aware e-learning systems that will ensure that they are both accessible and usable to disabled students.
Nganji, J.T. and Brayshaw, M. (2014). Designing and reflecting on disability-aware e-learning systems: the case of ONTODAPS. The 14th IEEE International Conference on Advanced Learning Technologies- ICALT2014, July 7-9, Athens, Greece, pp.571-575.[Link to article] [Link to PDF]
Disabled students in higher education are faced with a lot of difficulties accessing learning resources when e-learning systems are inaccessible. When instructional designers and developers of e-learning systems overlook the needs of disabled students, this leads to exclusion in what is termed disability divide. This paper reviews some disabilities encountered in higher education and assistive technologies used in accessing e-learning environments and presents disabled students’ recommendations on designing inclusive e-learning systems, obtained during the user evaluation of a disability-aware e-learning software. It is hoped that these recommendations would be adopted by designers and developers of e-learning and web-based systems so that they can meet the needs of disabled students.
Nganji, J.T. (2012). Designing Disability-Aware E-Learning Systems: Disabled Students’ Recommendations. International Journal of Advanced Science and Technology, Volume 48, pp. 61-70. [Link to article]
Purpose: The purpose of this paper is to address how virtual learning environments (VLEs) can be designed to include the needs of learners with multiple disabilities. Specifically, it employs AI to show how specific learning materials from a huge repository of learning materials can be recommended to learners with various disabilities. This is made possible through employing semantic web technology to model the learner and their needs.
Design/methodology/approach: The paper reviews personalised learning for students with disabilities, revealing the shortcomings of existing e-learning environments with respect to students with multiple disabilities. It then proceeds to show how the needs of a student with multiple disabilities can be analysed and then simple logical operators and knowledge-based rules used to personalise learning materials in order to meet the needs of such students.
Findings: It has been acknowledged in literature that designing for cases of multiple disabilities is difficult. This paper shows that existing learning environments do not consider the needs of students with multiple disabilities. As they are not flexibly designed and hence not adaptable, they cannot meet the needs of such students. Nevertheless, it is possible to anticipate that students with multiple disabilities would use learning environments, and then design learning environments to meet their needs.
Practical implications: This paper, by presenting various combination rules to present specific learning materials to students with multiple disabilities, lays the foundation for the design and development of learning environments that are inclusive of all learners, regardless of their abilities or disabilities. This could potentially stimulate designers of such systems to produce such inclusive environments. Hopefully, future learning environments will be adaptive enough to meet the needs of learners with multiple disabilities.
Social implications: This paper, by proposing a solution towards developing inclusive learning environments, is a step towards inclusion of students with multiple disabilities in VLEs. When these students are able to access these environments with little or no barrier, they will be included in the learning community and also make valuable contributions.
Originality/value: So far, no study has proposed a solution to the difficulties faced by students with multiple disabilities in existing learning environments. This study is the first to raise this issue and propose a solution to designing for multiple disabilities. This will hopefully encourage other researchers to delve into researching the educational needs of students with multiple disabilities.
Julius T. Nganji, Mike Brayshaw, (2017) "Disability-aware adaptive and personalised learning for students with multiple disabilities", The International Journal of Information and Learning Technology, Vol. 34 Issue: 4, pp.307-321, https://doi.org/10.1108/IJILT-08-2016-0027
The number of students with disabilities in UK higher education institutions increases every year. Delivering education online is becoming increasingly challenging as institutions encounter some disabilities requiring adjustments of learning environments. The law requires that people with disabilities be given equivalent learning experiences to their non-disabled peers through “reasonable adjustments”. Educational institutions have thus utilised assistive technologies to assist disabled students in their learning, but some of these technologies are incompatible with some learning environments, hence excluding some disabled students and resulting in a disability divide. To solve this problem, amongst other solutions, e-learning personalisation has been used and more recently, this is also achieved using Semantic Web technologies such as ontologies. Nevertheless, as ontologies are incorporated into learning environments little seems to be done to personalise learning for some disabled students. This study, in order to bridge the gap, proposes a personalisation approach based on a disability ontology containing information on various disabilities encountered in higher education, which can be used to present disabled students with learning resources relevant and suitable for their specific needs.
Nganji, J.T., Brayshaw, M. and Tompsett, B. (2011). Ontology-Based E-Learning Personalisation for Disabled Students in Higher Education. Innovation in Teaching and Learning in Information and Computer Sciences, Volume 10, Issue 1, pp. 1-11. [Link to article]
Purpose - The 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 the ONTODAPS e-learning system which has the mechanism for such personalisation.Design/methodology/approach - This 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 is an ontology-driven and disability-aware e-learning system which personalises learning resources and services to students. Three case studies are considered to show how personalisation is achieved using ONTODAPS.Findings - This 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/implications - This 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 to students with disabilities.
Nganji, J.T., Brayshaw, M. and Tompsett, B. (2013). Ontology-Driven Disability-Aware E-Learning Personalisation with ONTODAPS. Campus Wide Information Systems, Volume 30, Issue 1, pp. 17-34. [Link to article] [Link to PDF]
Current efforts towards including students with disabilities in web-based higher education are well established. However, existing learning environments are not fully inclusive, particularly for those with multiple disabilities. Most learning environments built for students with disabilities limit themselves to meeting the needs of specific disabilities and do not attempt to scale up to the difficulties of designing for those with multiple disabilities. This paper seeks to address how virtual learning environments (VLEs) can be designed to include the needs of learners with multiple disabilities. Specifically, it employs AI to show how specific learning materials from a huge repository of learning materials can be recommended to learners with various disabilities. This is made possible through employing semantic web technology to model the learner and their needs. Three techniques are discussed to combine requirements. Simple logical operators, knowledge based rules, and machine learning based rule induction are combined in this integrated approach. It is hoped that developers of e-learning systems will be encouraged from this approach to design fully inclusive virtual learning environments.
Nganji, J.T. and Brayshaw, M. (2015). Personalizing Learning Materials for Students with Multiple Disabilities in Virtual Learning Environments. Science and Information Conference 2015- SAI2015, July 28-30, London, UK, pp. 69-76. [Link to article]
Whilst a lot of research has been carried out on designing learning environments to meet the needs of learners, much of such research has focused on producing less flexible ready-made environments for learners to interact with. However, e-learning design and development could benefit from the lessons of the interaction of users with mobile devices, where users interact by selecting applications (Apps) they are interested in and hence engage with the device in an addictive way. By transposing the same interaction idea to the e-learning environment, if given the opportunity, learners will construct an environment that meets their needs with the tools that are available and hence will be motivated to engage more with such environment, possibly leading to improved performance. This article proposes FAUCLE (Flexible and Accessible User Constructed Learning Environment), a learner-centred model for a learner-constructed learning environment. It is hoped that this paper will encourage research interest on innovative ways of designing learner-centred learning environments that encourage active and inclusive learning.
Julius T. Nganji (2018) Towards learner-constructed e-learning environments for effective personal learning experiences, Behaviour & Information Technology, 37:7, 647-657, DOI: 10.1080/0144929X.2018.1470673