Screening dyslexia for English using HCI measures and machine learning

More than 10% of the population has dyslexia, and most are diagnosed only after they fail in school. This work seeks to change this through early detection via machine learning models that predict dyslexia by observing how people interact with a linguistic computer-based game. We designed items of the game taking into account (i) the empirical linguistic analysis of the errors that people with dyslexia make, and (ii) specific cognitive skills related to dyslexia: Language Skills, Working Memory, Executive Functions, and Perceptual Processes. . Using measures derived from the game, we conducted an experiment with 267 children and adults in order to train a statistical model that predicts readers with and without dyslexia using measures derived from the game. The model was trained and evaluated in a 10-fold cross experiment, reaching 84.62% accuracy using the most informative features.Peer ReviewedPostprint (author's final draft

The Role of the Lateral Geniculate Nucleus in Developmental Dyslexia: Evidence From Multi-Modal Magnetic Resonance Imaging

The ability to read proficiently is key to social participation and an important premise for individual well-being and vocational success. Individuals with developmental dyslexia, a highly prevalent neurodevelopmental disorder affecting hundreds of millions of children and adults worldwide, face severe and persistent difficulties in attaining adequate reading levels. Despite years of extensive research efforts to elucidate the neurobiological origin of this disorder, its exact etiology remains unclear to date. In this context, most neuroimaging research on dyslexia in humans has focused on the cerebral cortex and has identified alterations in a distributed left-lateralized cortical language network. However, pioneering post-mortem human studies and animal models suggest that dyslexia might also be associated with alterations in subcortical sensory thalami and early sensory pathways. The largely cortico-centric view of dyslexia is due in part to considerable technical challenges in assessing the human sensory thalami non-invasively using conventional magnetic resonance imaging (MRI). As a result, the role that sensory thalami may play in dyslexia has been largely unaddressed. In this dissertation, I leveraged recent advances in high-field MRI to investigate the role of the human lateral geniculate nucleus (LGN) of the visual thalamus in adults with dyslexia in-vivo. In three multi-modal high-field MRI studies, I show that (i) dyslexia is associated with structural alterations in the direct V1-bypassing white matter pathway connecting the LGN with cortical motion-sensitive area V5/MT in the left hemisphere; (ii) the connectivity strength of which predicts a core symptom of the disorder, i.e., rapid naming ability. I further demonstrate that (iii) the two major functional subdivisions of the LGN can be distinguished non-invasively based on differences in tissue microstructure; and that (iv) adults with dyslexia show functional response alterations specifically in the magnocellular subdivision of the LGN. I also demonstrate that this subdivision deficit (v) is more pronounced in male than female dyslexics; and (vi) predicts rapid naming ability in male dyslexics only. The results of this doctoral thesis are the first to confirm previous post-mortem evidence of LGN alterations in dyslexia in-vivo and point to their relevance to key symptoms of the disorder. In synergy, our research findings offer new perspectives on explanatory models of dyslexia and bear potential implications also for prospective treatment strategies.:Contribution Statement i Acknowledgments iii Abstract v Table of Contents vii 1 General Introduction 1 1.1 Developmental Dyslexia 1 1.1.1 Diagnostic Criteria 1 1.1.2 Prevalence and Etiology 2 1.1.3 Cognitive and Behavioral Symptoms 3 1.1.4 Explanatory Models in Cognitive Neuroscience 4 1.2 Lateral Geniculate Nucleus 7 1.2.1 Anatomy and Function 7 1.2.2 Technical Challenges in Conventional MRI 8 1.2.3 High-Field MRI 9 1.3 Research Aim and Chapter Outline 10 2 Altered Structural Connectivity of the Left Visual Thalamus in Developmental Dyslexia 13 2.1 Summary 14 2.2 Results and Discussion 15 2.3 Conclusions 22 2.4 Materials and Methods 23 2.4.1 Subject Details 23 2.4.2 High-Resolution MRI Acquisition and Preprocessing 23 2.4.3 Lateral Geniculate Nucleus Definition 24 2.4.4 Cortical Region of Interest Definition 26 2.4.5 Probabilistic Tractography 27 2.4.6 Quantification and Statistical Analysis 29 2.5 Supplementary Information 30 3 Mapping the Human Lateral Geniculate Nucleus and its Cytoarchitectonic Subdivisions Using Quantitative MRI 33 3.1 Abstract 34 3.2 Introduction 35 3.3 Materials and Methods 37 3.3.1 In-Vivo MRI 37 3.3.2 Post-Mortem MRI and Histology 41 3.4 Results 44 3.4.1 Lateral Geniculate Nucleus Subdivisions in In-Vivo MRI 44 3.4.2 Lateral Geniculate Nucleus Subdivisions in Post-Mortem MRI 46 3.5 Discussion 50 3.6 Supplementary Information 54 3.6.1 In-Vivo MRI 54 3.6.2 Post-Mortem MRI and Histology 58 3.6.3 Data and Code Availability 60 4 Dysfunction of the Visual Sensory Thalamus in Developmental Dyslexia 61 4.1 Abstract 62 4.2 Introduction 63 4.3 Materials and Methods 66 4.3.1 Subject Details 66 4.3.2 High-Resolution MRI Experiments 66 4.3.3 High-Resolution MRI Acquisition and Preprocessing 67 4.3.4 Lateral Geniculate Nucleus Definition 68 4.3.5 Quantification and Statistical Analysis 69 4.4 Results 70 4.5 Discussion 75 4.6 Supplementary Information 77 4.6.1 Supporting Methods 77 4.6.2 Supporting Results 81 4.6.3 Data and Code Availability 82 5 General Conclusion 83 5.1 Summary of Research Findings 83 5.2 Implications for Dyslexia Models 84 5.2.1 Phonological Deficit Hypothesis 84 5.2.2 Magnocellular Theory 84 5.2.3 Model According to Ramus 85 5.2.4 Need for Revised Model 86 5.3 Implications for Remediation 87 5.4 Research Prospects 88 5.5 Brief Concluding Remarks 90 6 Bibliography 91 7 List of Tables 113 8 List of Figures 115 9 Selbstständigkeitserklärung 11

Exploring the Acceptability of Graphical Passwords for People with Dyslexia

Alphanumeric passwords are still the most common form of user authentication despite well-known usability issues. These issues, including weak composition and poor memorability, have been well-established across different user groups, yet users with dyslexia have not been studied despite making up approximately 10% of the population. In this paper, we focus on understanding the user authentication experiences of people with dyslexia (PwD) in order to better understanding their attitudes towards a graphical password system that may provide a more inclusive experience. Through interactive interviews, participants were encouraged to try three different knowledge-based authentication systems (PIN, password, and graphical password) and then discuss their strategies behind code composition. We found that PwD employed potentially dangerous workarounds when composing passwords, in particular an over-reliance on pattern-based composition. We report on how PwD do not immediately see the benefits of graphical passwords, but upon experiencing the mechanism we see opportunities for more inclusive authentication

What is the influence of morphological knowledge in the early stages of reading acquisition among low SES children? A graphical modeling approach

Children from low-SES families are known to show delays in aspects of language development which underpin reading acquisition such as vocabulary and listening comprehension. Research on the development of morphological skills in this group is scarce, and no studies exist in French. The present study investigated the involvement of morphological knowledge in the very early stages of reading acquisition (decoding), before reading comprehension can be reliably assessed. We assessed listening comprehension, receptive vocabulary, phoneme awareness, morphological awareness as well as decoding, word reading and non-verbal IQ in 703 French first-graders from low-SES families after 3 months of formal schooling (November). Awareness of derivational morphology was assessed using three oral tasks: Relationship Judgment (e.g., do these words belong to the same family or not? heat-heater … ham-hammer); Lexical Sentence Completion [e.g., Someone who runs is a …? (runner)]; and Non-lexical Sentence Completion [e.g., Someone who lums is a…? (lummer)]. The tasks differ on implicit/explicit demands and also tap different kinds of morphological knowledge. The Judgement task measures the phonological and semantic properties of the morphological relationship and the Sentence Completion tasks measure knowledge of morphological production rules. Data were processed using a graphical modeling approach which offers key information about how skills known to be involved in learning to read are organized in memory. This modeling approach was therefore useful in revealing a potential network which expresses the conditional dependence structure between skills, after which recursive structural equation modeling was applied to test specific hypotheses. Six main conclusions can be drawn from these analyses about low SES reading acquisition: (1) listening comprehension is at the heart of the reading acquisition process; (2) word reading depends directly on phonemic awareness and indirectly on listening comprehension; (3) decoding depends on word reading; (4) Morphological awareness and vocabulary have an indirect influence on word reading via both listening comprehension and phoneme awareness; (5) the components of morphological awareness assessed by our tasks have independent relationships with listening comprehension; and (6) neither phonemic nor morphological awareness influence vocabulary directly. The implications of these results with regard to early reading acquisition among low SES groups are discussed

Ontology-based personalisation of e-learning resources for disabled students

Students with disabilities are often expected to use e-learning systems to access learning materials but most systems do not provide appropriate adaptation or personalisation to meet their needs.The difficulties related to inadaptability of current learning environments can now be resolved using semantic web technologies such as web ontologies which have been successfully used to drive e-learning personalisation. Nevertheless, e-learning personalisation for students with disabilities has mainly targeted those with single disabilities such as dyslexia or visual impairment, often neglecting those with multiple disabilities due to the difficulty of designing for a combination of disabilities.This thesis argues that it is possible to personalise learning materials for learners with disabilities, including those with multiple disabilities. This is achieved by developing a model that allows the learning environment to present the student with learning materials in suitable formats while considering their disability and learning needs through an ontology-driven and disability-aware personalised e-learning system model (ONTODAPS). A disability ontology known as the Abilities and Disabilities Ontology for Online LEarning and Services (ADOOLES) is developed and used to drive this model. To test the above hypothesis, some case studies are employed to show how the model functions for various individuals with and without disabilities and then the implemented visual interface is experimentally evaluated by eighteen students with disabilities and heuristically by ten lecturers. The results are collected and statistically analysed.The results obtained confirm the above hypothesis and suggest that ONTODAPS can be effectively employed to personalise learning and to manage learning resources. The student participants found that ONTODAPS could aid their learning experience and all agreed that they would like to use this functionality in an existing learning environment. The results also suggest that ONTODAPS provides a platform where students with disabilities can have equivalent learning experience with their peers without disabilities. For the results to be generalised, this study could be extended through further experiments with more diverse groups of students with disabilities and across multiple educational institutions

Invented spelling and perspectives on spelling development: The necessity of an integrated cognitive model

There are several models about the mechanism that make pre-school children evolve regarding the quality of their invented spelling. Ehri's teorical perspective (1997) describes the development of children's spelling skills in terms of their increasing ability to map sounds of words to phonetically appropriate letters. According to this perspective, written language is conceived as an instrument for translating oral language and phonological awareness determines the precision of invented spelling. This model neglects linguistic variables that might influence children ability to analyse the oral and written language and also does not conceive children's reflection about written code as a factor of evolution. The constructivist perspective from Ferreiro (1988), emphasizes the importance of internal conflict between different criterion about the organization of the alphabetic code. For instance, the repetition of the same vowel in syllabic phonetised writing might cause a conflict in children's thinking with another criterion that they attaint, related with the variation of letters within the written word (e.g. Nunes Carraher and Rego (1984) cited a Portuguese-speaking child who spelled urubu 'vulture' as UUU). This conflict might lead children to analyse syllables in their phonemes and became a source for an alphabetic approach of writing. This and other conflicts are the main factor, from the point of view of this theory, for the evolution of children's conceptions about written language. However those mechanisms are described independently of children ability to analyse oral words or the frequency of words and the articulatory properties of phonemes that integrate those words. On the other hand, Polo, Kessler and Treiman (2005), think that that statistical learning skills exists from an early age. These skills are applied in learning to spell, as in other tasks. This perspective emphasizes that children's writing reflects the characteristics of the input to which they have been exposed as they try to find meaningful patterns in regularities of written language. These regularities give children information about graphical as well as phonological patterns of the language in which they reflected their very early spellings. However, this perspective never analyses the nature of children thinking and how that reflects their approach to written language. It is quite important to create a model that integrates these several contribution. © 2011 by Nova Science Publishers, Inc. All rights reserved.N/

Invented spelling and perspectives on spelling development : the necessity of an integrated cognitive model

There are several models about the mechanism that make pre-school children evolve regarding the quality of their invented spelling. Ehri's teorical perspective (1997) describes the development of children's spelling skills in terms of their increasing ability to map sounds of words to phonetically appropriate letters. According to this perspective, written language is conceived as an instrument for translating oral language and phonological awareness determines the precision of invented spelling. This model neglects linguistic variables that might influence children ability to analyse the oral and written language and also does not conceive children's reflection about written code as a factor of evolution. The constructivist perspective from Ferreiro (1988), emphasizes the importance of internal conflict between different criterion about the organization of the alphabetic code. For instance, the repetition of the same vowel in syllabic phonetised writing might cause a conflict in children's thinking with another criterion that they attaint, related with the variation of letters within the written word (e.g. Nunes Carraher and Rego (1984) cited a Portuguese-speaking child who spelled urubu 'vulture' as UUU). This conflict might lead children to analyse syllables in their phonemes and became a source for an alphabetic approach of writing. This and other conflicts are the main factor, from the point of view of this theory, for the evolution of children's conceptions about written language. However those mechanisms are described independently of children ability to analyse oral words or the frequency of words and the articulatory properties of phonemes that integrate those words. On the other hand, Polo, Kessler and Treiman (2005), think that that statistical learning skills exists from an early age. These skills are applied in learning to spell, as in other tasks. This perspective emphasizes that children's writing reflects the characteristics of the input to which they have been exposed as they try to find meaningful patterns in regularities of written language. These regularities give children information about graphical as well as phonological patterns of the language in which they reflected their very early spellings. However, this perspective never analyses the nature of children thinking and how that reflects their approach to written language. It is quite important to create a model that integrates these several contribution. © 2011 by Nova Science Publishers, Inc. All rights reserved.info:eu-repo/semantics/publishedVersio

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