Motivation Modelling and Computation for Personalised Learning of People with Dyslexia

The increasing development of e-learning systems in recent decades has benefited ubiquitous computing and education by providing freedom of choice to satisfy various needs and preferences about learning places and paces. Automatic recognition of learners’ states is necessary for personalised services or intervention to be provided in e-learning environments. In current literature, assessment of learners’ motivation for personalised learning based on the motivational states is lacking. An effective learning environment needs to address learners’ motivational needs, particularly, for those with dyslexia. Dyslexia or other learning difficulties can cause young people not to engage fully with the education system or to drop out due to complex reasons: in addition to the learning difficulties related to reading, writing or spelling, psychological difficulties are more likely to be ignored such as lower academic self-worth and lack of learning motivation caused by the unavoidable learning difficulties. Associated with both cognitive processes and emotional states, motivation is a multi-facet concept that consequences in the continued intention to use an e-learning system and thus a better chance of learning effectiveness and success. It consists of factors from intrinsic motivation driven by learners’ inner feeling of interest or challenges and those from extrinsic motivation associated with external reward or compliments. These factors represent learners’ various motivational needs; thus, understanding this requires a multidisciplinary approach. Combining different perspectives of knowledge on psychological theories and technology acceptance models with the empirical findings from a qualitative study with dyslexic students conducted in the present research project, motivation modelling for people with dyslexia using a hybrid approach is the main focus of this thesis. Specifically, in addition to the contribution to the qualitative conceptual motivation model and ontology-based computational model that formally expresses the motivational factors affecting users’ continued intention to use e-learning systems, this thesis also conceives a quantitative approach to motivation modelling. A multi-item motivation questionnaire is designed and employed in a quantitative study with dyslexic students, and structural equation modelling techniques are used to quantify the influences of the motivational factors on continued use intention and their interrelationships in the model. In addition to the traditional approach to motivation computation that relies on learners’ self-reported data, this thesis also employs dynamic sensor data and develops classification models using logistic regression for real-time assessment of motivational states. The rule-based reasoning mechanism for personalising motivational strategies and a framework of motivationally personalised e-learning systems are introduced to apply the research findings to e-learning systems in real-world scenarios. The motivation model, sensor-based computation and rule-based personalisation have been applied to a practical scenario with an essential part incorporated in the prototype of a gaze-based learning application that can output personalised motivational strategies during the learning process according to the real-time assessment of learners’ motivational states based on both the eye-tracking data in addition to users’ self-reported data. Evaluation results have indicated the advantage of the application implemented compared to the traditional one without incorporating the present research findings for monitoring learners’ motivation states with gaze data and generating personalised feedback. In summary, the present research project has: 1) developed a conceptual motivation model for students with dyslexia defining the motivational factors that influence their continued intention to use e-learning systems based on both a qualitative empirical study and prior research and theories; 2) developed an ontology-based motivation model in which user profiles, factors in the motivation model and personalisation options are structured as a hierarchy of classes; 3) designed a multi-item questionnaire, conducted a quantitative empirical study, used structural equation modelling to further explore and confirm the quantified impacts of motivational factors on continued use intention and the quantified relationships between the factors; 4) conducted an experiment to exploit sensors for motivation computation, and developed classification models for real-time assessment of the motivational states pertaining to each factor in the motivation model based on empirical sensor data including eye gaze data and EEG data; 5) proposed a sensor-based motivation assessment system architecture with emphasis on the use of ontologies for a computational representation of the sensor features used for motivation assessment in addition to the representation of the motivation model, and described the semantic rule-based personalisation of motivational strategies; 6) proposed a framework of motivationally personalised e-learning systems based on the present research, with the prototype of a gaze-based learning application designed, implemented and evaluated to guide future work

Mathematics learning support and dyslexia

This research identifies, through an extensive series of exploratory and explanatory case studies, the mathematical difficulties that might be encountered by dyslexic engineering students. It details support mechanisms that may be put in place to help these students reach their full potential and makes suggestions for the introduction of measures at institutional level to ensure compliance with current legislation. This is an area, identified from the literature search, that has not, until now, been the focus of any substantial research activity and thus the findings form an original and significant contribution to knowledge in this field. The findings are not only intrinsically interesting but will also be of use to practitioners of mathematics, support staff, staff developers and policy makers in higher education. A literature review gives historical background on the development of education in general, and mathematics in particular, in the UK. The main theories and problems associated with developmental dyslexia are also given. Surveys were undertaken to determine the extent of mathematics learning support in UK universities and also to determine the extent of the provision of mathematics support to dyslexic students. Using case study research and by providing one-to-one mathematics support, the difficulties encountered by dyslexic students were investigated. Related work is an exploratory study into the use of different media combinations in Computer Assisted Assessment. Additionally, an in-depth case study of the Mathematics Learning Support Centre at Loughborough University has been undertaken and is reported in detail with recommendations for changes suggested. The results of this research show that mathematics learning support is widespread and often essential to bridge the gap between school mathematics and university level mathematics but specialist mathematical support for dyslexic students is rarely available. It is determined that dyslexic students can be impeded in their learning and understanding of mathematics as a direct result of their dyslexia. Recommendations for further study in some areas and future lines of inquiry in others are suggested

Equity of Access: Adaptive Technology

In this age of information technology, it is morally imperative that equal access to information via computer systems be afforded to people with disabilities. This paper addresses the problems that computer technology poses for students with disabilities and discusses what is needed to ensure equity of access, particularly in a university environment

Identifying Dyscalculia Symptoms Related to Magnocellular Reasoning using Smartphones

This thesis presents a research that has developed and evaluated a software application for smartphones, called MagnoMath. MagnoMath has been developed for assisting diagnosis of dyscalculia, a learning disability in mathematics, and for identifying dyscalculia symptoms possibly related to magnocellular reasoning. Typical software aids developed for individuals with learning disabilities are focused on both assisting diagnosis and teaching the material. The software developed in this project however maintains a specific focus on the former, while attempting to capture alleged correlations between dyscalculia symptoms and possible underlying causes of the condition. This was achieved by applying k-Nearest Neighbor algorithm classifying five parameters used in evaluating users' mathematical and magnocellular reasoning. Evaluation results were then utilized to support diagnosis and measure correlations between performances across the two task categories. To test MagnoMath's validity, an experiment involving seven dyscalculic and four non-dyscalculic volunteers was conducted. Results show that the software was able to reveal dyscalculic behavior. A strong correlation between deficiencies in arithmetic and spatial reasoning was identified, revealing a possible dependency valuable for detecting early signs of developmental dyscalculia. Learning disability experts at Linköping University, Sweden, University of Oslo, Norway and Dyslexia Norway have found the application to be appropriate and valuable for its intended purposes. Thus, results prove that mobile software is a suitable and valuable tool for assisting dyscalculia diagnosis and identifying possible root causes of developing the condition. Additional evaluation would be necessary to further test mobile softwares' ability to confirm the theory of magnocellular reasoning's involvement in developing mathematical deficiencies.INFO390MASV-INF

Learning Disabilities

Learning disabilities are a heterogeneous group of disorders characterized by failure to acquire, retrieve, and use information competently. These disorders have a multifactorial aetiology and are most common and severe in children, especially when comorbid with other chronic health conditions. This book provides current and comprehensive information about learning disorders, including information on neurobiology, assessment, clinical features, and treatment. Chapters cover such topics as historical research and hypotheses of learning disorders, neuropsychological assessment and counselling, characteristics of specific disorders such as autism and ADHD, evidence-based treatment strategies and assistive technologies, and much more

Transforming pedagogy using mobile Web 2.0

Blogs, wikis, podcasting, and a host of free, easy to use Web 2.0 social software provide opportunities for creating social constructivist learning environments focusing on student-centred learning and end-user content creation and sharing. Building on this foundation, mobile Web 2.0 has emerged as a viable teaching and learning tool, facilitating engaging learning environments that bridge multiple contexts. Today’s dual 3G and wifi-enabled smartphones provide a ubiquitous connection to mobile Web 2.0 social software and the ability to view, create, edit, upload, and share user generated Web 2.0 content. This article outlines how a Product Design course has moved from a traditional face-to-face, studio-based learning environment to one using mobile Web 2.0 technologies to enhance and engage students in a social constructivist learning paradigm. Keywords: m-learning; Web 2.0; pedagogy 2.0; social constructivism; product desig

Improving Legibility of User Interfaces for Low Vision Conditions with a Crowdsource Platform

The growing importance of inclusive design solutions has prompted this study examining typography legibility and its impact on accessibility for users with low vision conditions. Focusing on factors such as typographic form, letter spacing, and font size, this research seeks to understand the unique demands of low vision individuals and how typography and user interface design can be adapted to improve legibility and accessibility. Previous research has provided insights into various aspects of typography legibility, but a comprehensive approach addressing the specific needs of low vision users has been lacking. This study contributes to the existing body of knowledge by deconstructing user interfaces (UI) and analyze the fundamental elements affecting legibility. By examining various UI elements and their relationship to text, this research offers personalized, integrated solutions for individuals to tailor websites to their unique needs. The proposed platform differentiates itself from existing accessibility overlays (additional software that is intended to detect and address web accessibility issues on web sites) by emphasizing personalization based on individual preferences, leveraging crowdsourcing to create a variety of modification options. Although the proposal's primary focus is on low vision, it has the potential to assist a wide range of users with various needs. Despite some limitations and challenges faced during the project, this study provides insights into the factors contributing to the legibility of various typefaces, emphasizing the importance of customization to cater to specific needs. Future research should continue to explore these factors, further promoting a more inclusive approach to typography in diverse UI contexts