Using Machine Learning advances to unravel patterns in subject areas and performances of university students with Special Educational Needs and Disabilities (MALSEND): A conceptual Approach

Drishty Sobnath, Sakirulai Isiaq, Ikram Rehman, Moustafa Nasralla

    Research output: Chapter in Book/Report/Published conference proceedingConference contributionpeer-review

    252 Downloads (Pure)

    Abstract

    Universities and colleges in the UK welcome about 30,000 students with special needs each year. Research shows that the dropout rate for disabled students is much higher at 31.5% when compared with about 12.3% for non-disabled students in the EU. Supporting young students with special educational needs while pursuing higher education is an ambitious and important role, which needs to be adopted by tertiary education providers worldwide. We propose, MALSEND, a conceptual platform based on human-machine intelligence (HMI), a collective intelligence of human and machine to understand patterns of learning of disabled students in higher education. This platform aims to accommodate and analyse data sets features of universities activities to discover trends in performances with regards to subject areas for autistic students, dyslexic students and students having attention deficit hyperactive disorder (ADHD), among others. Analysis of variables, such as students’ performances in modules, courses and other engagement-indices will give new insights into research questions, career advice and institutional policymaking. This paper describes the developmental activities of the MALSEND concept in phases.
    Original languageEnglish
    Title of host publicationFourth International Congress on Information and Communication Technology (ICICT 2019)
    PublisherSpringer Singapore
    Pages509-517
    Number of pages9
    Volume1027
    ISBN (Print)978-981-32-9342-7, 978-981-32-9343-4
    DOIs
    Publication statusPublished - 3 Jan 2020

    Publication series

    NameAdvances in Intelligent Systems and Computing (AISC)
    PublisherSpringer
    ISSN (Electronic)2194-5357

    Fingerprint

    Dive into the research topics of 'Using Machine Learning advances to unravel patterns in subject areas and performances of university students with Special Educational Needs and Disabilities (MALSEND): A conceptual Approach'. Together they form a unique fingerprint.

    Cite this