Light-weight ontologies for scrutable user modelling

This thesis is concerned with the ways light-weight ontologies can support scrutability for large user models and the user modelling process. It explores the role that light-weight ontologies can play, and how they can be exploited, for the purpose of creating and maintaining large, scrutable user models consisting of hundreds of components. We address problems in four key areas: ontology creation, metadata annotation, creation and maintenance of large user models, and user model visualisation, with a goal to provide a simple and adaptable approach that maintains scrutability. Each of these key areas presents a number of challenges that we address. Our solution is the development of a toolkit, LOSUM, which consists of a number of tools to support the user modelling process. It incorporates light-weight ontologies to fulfill a number of roles: aiding in metadata creation, providing structure for large user model visualisation, and as a means to reason across granularities in the user model. In conjunction with this, LOSUM also features a novel visualisation tool, SIV, which performs a dual role of ontology and user model visualisation, supporting the process of ontology creation, metadata annotation, and user model visualisation. We evaluated our approach at each stage with small user studies, and conducted a large scale integrative evaluation of these approaches together in an authentic learning context with 114 students, of whom 77 had exposure to their learner models through SIV. The results showed that students could use the interface and understand the process of user model construction. The flexibility and adaptability of the toolkit has also been demonstrated in its deployment in several other application areas

Exploring participative learner modelling and its effects on learner behaviour

scholarship 64999/111091The educational benefits of involving learners as active players in the learner modelling process have been an important motivation for research on this form of learner modelling, henceforth referred to as participative learner modelling. Such benefits, conceived as the promotion of learners' reflection on and awareness of their own knowledge, have in most cases been asserted on the grounds of system design and supported only by anecdotal evidence. This dissertation explores the issue of whether participative learner modelling actually promotes learners' reflection and awareness. It does so by firstly interpreting 'reflection' and 'awareness' in light of "classical" theories of human cognitive architecture, skill acquisition and meta-cognition, in order to infer changes in learner abilities (and therefore behaviour) amenable to empirical corroboration. The occurrence of such changes is then tested for an implementation of a paradigmatic form of participative learner modelling: allowing learners to inspect and modify their learner models. The domain of application centres on the sensorimotor skill of controlling a pole on a cart and represents a novel type of domain for participative learner modelling. Special attention is paid to evaluating the method developed for constructing learner models and the form of presenting them to learners: the former is based on a method known as behavioural cloning for acquiring expert knowledge by means of machine learning; the latter deals with the modularity of the learner models and the modality and interactivity of their presentation. The outcome of this research suggests that participative learner modelling may increase the abilities of learners to report accurately their problem-solving knowledge and to carry out novel tasks in the same domain—the sort of behavioural changes expected from increased learners' awareness and reflection. More importantly perhaps, the research suggests a viable methodology for examining the educational benefits of participative learner modelling. It also exemplifies the difficulties that such endeavours will face

User modeling for exploratory search on the Social Web. Exploiting social bookmarking systems for user model extraction, evaluation and integration

Exploratory search is an information seeking strategy that extends be- yond the query-and-response paradigm of traditional Information Retrieval models. Users browse through information to discover novel content and to learn more about the newly discovered things. Social bookmarking systems integrate well with exploratory search, because they allow one to search, browse, and filter social bookmarks. Our contribution is an exploratory tag search engine that merges social bookmarking with exploratory search. For this purpose, we have applied collaborative filtering to recommend tags to users. User models are an im- portant prerequisite for recommender systems. We have produced a method to algorithmically extract user models from folksonomies, and an evaluation method to measure the viability of these user models for exploratory search. According to our evaluation web-scale user modeling, which integrates user models from various services across the Social Web, can improve exploratory search. Within this thesis we also provide a method for user model integra- tion. Our exploratory tag search engine implements the findings of our user model extraction, evaluation, and integration methods. It facilitates ex- ploratory search on social bookmarks from Delicious and Connotea and pub- lishes extracted user models as Linked Data

Modélisation de l'apprenant dans le cadre d'un environnement informatique pour l'apprentissage humain offrant des conseils personnalisés

Nous avons élaboré un Modèle de l’Apprenant (MA) dans le but de donner des conseils personnalisés en fonction des connaissances de l’apprenant dans le cadre des Environnements Informatiques pour l’Apprentissage Humain (EIAH) à partir d’exemples. Le MA proposé contient cinq catégories de paramètres : les données personnelles, les caractéristiques de l'apprenant, l'état d'apprentissage, les interactions entre l'environnement et l'apprenant et les connaissances de l'apprenant. Notre travail a été effectué à l’aide de la méthode CommonKADS. Un prototype montre notamment sa représentation et l'algorithme de l'évaluation des connaissances de l'apprenant. Une valildation de cette évaluation a permis de vérifier le bon fonctionnement du prototype. Un cadre générique pour modéliser les connaissances de l’apprenant pour un EIAH en général a aussi été développé. Ce modèle pourrait servir d’un guide pour faciliter le développement de MA qui aident à améliorer l’intelligence des EIAH.We elaborated a Learner Model (LM) that allows the environment to give personalized advices according to a learner’s knowledge. The elaboration is regarding to the learning-by-examples environments. The LM we proposed contains five categories of parameters: personal data, learner’s characteristics, learning state, learner’s interactions with the system, and learner’s knowledge. Our model was designed based on CommonKADS. A prototype demonstrates especially its representation and the algorithm of assessing the learner’s knowledge. A validation on this assessment alowed to verify the good functioning of the prototype. A generic framework for modeling learner’s knowledge in a general learning environment is also developed. The model could serve as a guideline to facilitate developments of LM, which help to improve the intelligence of the environments

Learners' self-assessment and metacognition when using an open learner model with drill down

Metacognition is ‘thinking on thinking’. It is important to educational practices for learners/teachers, and in activities such as formative-assessment and self-directed learning. The ability to perform metacognition is not innate and requires fostering, and self-assessment contributes to this. Literature suggests proven practices for promoting metacognitive opportunities and ongoing enquiry about how technology best supports these. This thesis considers an open learner model (OLM) with a drill-down approach as a method to investigate support for metacognition and self-assessment. Measuring aspects of metacognition without unduly influencing it is challenging. Direct measures (e.g. learners ‘thinking-aloud’) could distort/disrupt/encourage/effect metacognition. The thesis develops methods to evaluate aspects of metacognition without directly affecting it, relevant to future learning-analytics research/OLM design. It proposes a technology specification/implementation for supporting metacognition research and highlights the relevance of using a drill-down approach. Using measures that correspond to post-hoc learner accounts, this thesis identifies a baseline of student activity that is consistent with important regulation of cognition tasks and students’ specific interest in problems. Whilst this does not always influence self-assessment accuracy, students indicating their self-assessment ability can be used as a proxy measure to identify those who will improve. Evidence supports claims that OLMs remain relevant in metacognition research

Modélisation probabiliste du style d'apprentissage et application à l'adaptation de contenus pédagogiques indexés par une ontologie

Cette thèse s'inscrit dans le cadre général des systèmes d'enseignement adaptatifs. La problématique traitée est l'adaptation de l'activité pédagogique au mode d'apprentissage préféré de l'élève. Les travaux réalisés ont eu pour objectifs de : modéliser les préférences d'apprentissage de l'élève ; modéliser les contenus pédagogiques du domaine à enseigner ; proposer une stratégie d'adaptation qui rapproche les préférences des contenus afin de proposer une méthode pédagogique appropriée. Pour atteindre le premier objectif, la thèse étudie le style d'apprentissage de Felder. Une étude empirique pour établir un modèle de dépendance entre style, pédagogie, et comportement de l'élève a été réalisée. Les résultats ont permis d'établir un modèle de préférences probabiliste. Une méthode en deux étapes pour apprendre ce odèle puis le renforcer est développée. Deux implantations sont proposées : un réseau bayésien et une machine à vecteurs de support. Le contenu quant à lui est modélisé en utilisant une ontologie combinant le domaine, la pédagogie, ainsi que les ressources physiques. Une stratégie d'adaptation structurée sur quatre dimensions est présentée. Celle-ci consiste à rechercher dans le contenu la séquence pédagogique sémantiquement pertinente pour les préférences de l'élève. La recherche s'appuie sur une mesure de similarité sémantique qui est établie. Ce travail a eu un impact sur deux projets européens. En effet, la méthode de production et structuration des contenus, basée sur SCORM, qui est proposée a servi pour le projet UP2UML. L'approche de modélisation de l'élève sert aux recherches sur le profilage dans le projet KPLAB. ABSTRACT : This thesis deals with adaptive teaching systems. The research question is how to adapt pedagogical activities to the prefered learning mode of a student. The scientific objectives are: modelisation of student's learning preferences ; modelisation of adaptive learning contents of a given domain ; establishing an adaptation strategy that maps preferences to contents in order to recommend an appropriate teaching method In order to reach the first objective, the thesis studies the learning style of Felder. An empirical study to derive a dependency model between the style, the pedagogy, and the student behaviour has been conducted. Results led to creating a probabilistic preference model. A two-stage method to learn and reinforce the model is developed. Two implementations are proposed: a bayesian network and an SVM classifier. The content is represented using an ontology that combines the domain, the pedagogy, and the physical resources. An adaptation strategy centered around four dimensions is presented. This consists of searching the content to retrieve the most semantically pertinent pedagogical sequence given the student preferences. The search implements an original semantic similarity measure. This work significantly impacted two European research projects. The production and structuration method designed in this thesis and based on SCORM has been applied in the Leonardo Da Vinci project called UP2UML. The student modeling approche serves currently our research on user profiling in the KPLAB projec

Disciplinde With Holesome Reede: Edmund Spenser, Robert Burton, and the Profits of Reading

Disciplinde with Holesome Reede: Edmund Spenser, Robert Burton, and the Profits of Reading offers an extended comparative reading of Edmund Spenser’s The Faerie Queene (1590-96) and Robert Burton’s The Anatomy of Melancholy (1621-50), taking as its cue these texts’ shared claims to bibliotherapeutic possibilities: that Spenser’s is intended to ‘fashion a gentleman or noble person in vertuous and gentle discipline’, and that Burton hopes his writings will ‘medicinally worke upon the whole body [... and] not only recreate, but rectify the minde’. Reading these claims in light of medical, philosophical, and theological contexts, I explore how Spenser and Burton conceptualise the potentially profitable (and, conversely, pernicious) possibilities of reading in medicinal, economic, and recreative terms. Central to the thesis is the idea that such claims to reformative efficacy depend on the authors’ shaping and inculcation of certain kinds of readerly habits, and that, correlating to the contiguous nature of world and text, the fashioning of a reader constitutes the fashioning of an ethical and healthy subject: in short, the thesis follows early modern thought in eliding the hermeneutic and the therapeutic. As such, the thesis will throughout explore how both The Faerie Queene and the Anatomy encode, challenge, and frustrate their own interpretive practices. Shaping a readership trained in careful attention and profound memory constitutes the work of reading that is both laborious and edifying. At the same time, whilst celebrating each work’s complex particularity, the thesis demonstrates how comparative work on texts rarely – and only ever fleetingly – drawn into conversation might shed new light on the ways in which intellectual traditions span and develop across form, genre, and period

Fugitive Dust: How Dust Escapes Regulation and Remains Inscrutable

Dust carries consequences for public health, visibility, trade and transportation, and water insecurity, yet dust largely remains inscrutable. This dissertation focuses on the consequences and politics of how we measure, monitor, and manage environmental systems and the broader &ldquo;politics of inscrutability&rdquo; in environmental knowledge. I use a mixed-methods approach including interviews, participant observation, document analysis, a community survey, and spatial analysis to investigate the ways dust is left unknown. My research explores the &ldquo;politics of inscrutability&rdquo; in environmental knowledge and its multiple modes of production, specifically focusing on disciplinary, intentional, material and discursive types of inscrutability. My initial chapter explores basic definition questions about my focal object: dust. I found that experts&mdash;regulators and scientists&mdash;struggle to define dust and that there is an &ldquo;accepted ambiguity&rdquo; about the lack of a technical or common definition, which halts the production of dust science. Then, I focus on the role of data collection in inscrutability. I analyze Clean Air Act monitoring system to highlight biases and unquestioned assumptions that lead to large spatial gaps and instruments that are ill equipped to detect extreme events, resulting in incomplete data about dust. Last, I examine how the treatment of &ldquo;exceptional events&rdquo; leads to the intentional removal of dust data from the regulatory dataset, altering regulatory action and nonattainment status. My research findings contribute to scholarship on the politics of environmental knowledge, specifically political ecology and STS, as well as make policy-relevant recommendations for dust regulation and monitoring. Ultimately, this work shows how multiple inscrutabilities each with their own conditions and politics keep dust largely unknown: these same processes are at play with many other environmental systems and sectors of environmental knowledge.</p

Aftershocks: Globalism and the Future of Democracy [ISSEI – XVI International Conference]

This digital publication consists of a selection of 56 papers presented at the 16th International Conference of the International Society for the Study of European Ideas (ISSEI), held at the University of Zaragoza, 2-5 July 2019, the general theme of which was ‘Aftershocks: Globalism and the Future of Democracy’. Sponsored by The Aragonese Association of Sociology, the conference was well-attended – 170 participants from 28 countries met to discuss a wide variety of topics in 29 workshops. The feedback we received from participants confirmed that they had greatly enjoyed the venue of the conference, that they appreciated the warm welcome they had received and the congenial social atmosphere and opportunity to attend workshops on subjects that were not only in their own field of expertise. No one, of course, could have predicted that our world – our work and life as individuals, as communities and as nations – would change so suddenly and radically eighteen months after the conference, with the rapid and devastating spread of the Convid-19 pandemic. The current deepening global crisis along with the challenge of climate change and growing international tensions are a stark reminder of how vulnerable our societies, our civilization, and our species are. The shocks and aftershocks of these crises are felt today in every corner of the world and in every aspect of our global and local economies, and most obviously in the sociopolitical arena. As several of the conference workshops on the multiple crises Europe and the world face today – from the migrant crisis to the rise of populism and deepening inequality between rich and poor – showed – and as the Covid-19 pandemic has so cruelly brought home to us – we simply cannot take the achievements of human civilization for granted and must find ways to meet the fundamental social and political needs of human beings not only in our own neighborhoods, cities and countries, but ultimately in the world as a whole: their living conditions, livelihoods, social services, education and healthcare, human rights and political representation. Several of the workshops, as I mentioned, directly addressed these issues and emphasized the need for building social resilience based on tolerance, solidarity and equity. This too is why, as academics, we should continue to initiate and engage in collective reflection and debate on how to foster and strengthen human communities and human solidarity. Finally, I want to thank the participants and workshop chairs for their contribution to the success of the conference. It was a pleasure for me to work with the university organizing team and with ISSEI’s team in bringing this about, and I am particularly proud that my university and the city of Zaragoza hosted this conference