A multiplatform e-learning system is an e-learning system that can deliver learning content to different accessing devices such as PCs, PDAs and mobile phones. The main objective of the research is to formulate a framework for multiplatform e-learning systems. This thesis focuses on the formulation, competency and constitution of the multiplatform e-learning systems framework and the implementation of a multiplatform e-learning system. In conjunction with the main objective, the research also addresses the factors that influence learner satisfaction during their engagement with a multiplatform e-learning system. In addition, the research investigates the relationships between these factors in influencing learner satisfaction. The research also intends to validate the assertion that multiplatform e-learning systems are better than non-adaptive e-learning systems. A comparative evaluation between a traditional e-learning system and a multiplatform e-learning system from end user (learner) perspective was conducted. The evaluation instrument is based on multiplatform e-learning system questionnaires (MELQ). A total of forty participants took part in the evaluation. Four participants took part in the initial pilot evaluation while thirty six participants took part in the final evaluation. Data analysis and statistical results indicate that there are potential gains in learner satisfaction score in multiplatform e-learning systems over traditional e-learning systems. The results also show that the gain is most significant in mobile devices than in desktop PCs. Statistical analysis reveals that all the factors that influence the learner satisfaction are significant and they have different levels of influence over learner satisfaction. These factors can be further organized into primary factors and secondary factors. These findings and the methodology of evaluation can play an important role for e-learning systems designer to improve the adaptation process and to enhance the level of learner satisfaction in multiplatform e-learning systems.

The focus of this research is to investigate the potential of user interface (UI) pattern languages in assisting students of Human Computer Interaction (HCI) to learn the principles of UI design. A graphical representation named a UI-pattern model was developed. It arose from the evaluation of four existing pattern languages. The UI-pattern model is an enhanced form of UI pattern list that represents a specific UI. It was recognised that the UI-pattern model has the potential to help students learn about pattern language structure. It was also realised that UI-pattern modelling can be used to incrementally improve pattern languages through the generative process proposed by Alexander (1979). A UI pattern language Maturity Model (UMM) has been developed. This model can be used by educators when selecting and/or modifying existing UI pattern languages so that they are more appropriate for student use. A method for developing detailed UI designs that utilises a UI pattern language has been developed with the aim of providing students with an ‘authentic’ real-world UI design experience, as envisaged by constructivist educational theory (Jonassen 1999). This UI design method (TUIPL) guides the students’ development of user interface conceptual models. To establish the authenticity of TUIPL three case studies were undertaken out with developers who had differing levels of UI design experience. A series of studies investigated how HCI students used TUIPL to guide the development of UI-pattern models and canonical abstract prototypes. The studies also ascertained the students’ views on using three different forms of UI pattern (illustrated, narrative and diagrammed). Data was collected by observation, questionnaires and completed exercises. The results indicate that the students developed an understanding of pattern language structure, were positive about their experience building UI-pattern models and canonical abstract prototypes, and that patterns aided communication. The learning outcomes were encouraging and students responded positively to using a UI pattern language.

Among student modelling researches, domain-independent student models have usually been a rarity. They are valued because of reusability and economy. The demand on domain-independent student models is further increased by the need to stay competitive in the so-called knowledge economy nowadays and the widespread practice of lifelong learning. On the other hand, the popularity of student-oriented pedagogy triggers the need to provide cognitive support in virtual learning environments which in turn requires student models that create cognitive profiles of students. This study offers an innovative student modelling approach called cognitive trait model (CTM) to address both the needs mentioned above. CTM is a domain-independent and persistent student model that goes beyond traditional concept of student model. It is capable of taking the role of a learning companion who knows about the cognitive traits of the student and can supply this information when the student first starts using a new learning system. The behaviour of the students in the learning systems can then be used to update CTM. Three cognitive traits are included in the CTM in this study, they are working memory capacity, inductive reasoning ability and divergent associative learning. For the three cognitive traits, their domain-independence and persistence are studied and defined, their characteristics are examined, and behaviour patterns that can be used to indicate them are extracted. In this study, a learning system is developed to gather behaviour data of students. Several web-based psychometric tools are also developed to gather the psychometric data about the three cognitive traits of students. In the evaluations, Cognitive trait modelling is then applied on the behaviour data and the results are compared with the psychometric data. The findings prove the effectiveness of CTM and reveal important insights about the three cognitive traits.

Orientadores: João Vilhete Viegas D'Abreu, , Heloisa Vieira da Rocha / Dissertação (mestrado profissional) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-05T14:50:46Z (GMT). No. of bitstreams: 1 Boer_MariaBetaniaRicci_M.pdf: 20921183 bytes, checksum: 63fb3b64820b3b1061c4dcbd9a84223b (MD5) Previous issue date: 2005 / Resumo: Uma parcela significativa da população brasileira possui algum tipo de deficiência visual, total ou parcial, e os softwares existentes no mercado só se preocupam em incluir digitalmente as pessoas com perda total de visão, enquanto as pessoas com baixa visão, às vezes, são consideradas pessoas normais ou com perda total de visão, portanto não se beneficiando desse tipo de ação. Esta dissertação descreve o desenvolvimento de uma ferramenta de software com uma interface que deve auxiliar os portadores de baixa visão em geral, incluindo alunos no processo educacional. A ferramenta em questão objetiva amenizar as dificuldades dos alunos com baixa visão no processo de interação com o computador buscando superar suas necessidades especiais, contribuindo para sua inclusão no processo educacional e, conseqüentemente, na sociedade. A ferramenta de software, que é apresentada neste trabalho, denominada Quatro Estações, quando executada em computador com uma mesa digitalizadora a ele acoplada, permite que os movimentos realizados na mesa por uma caneta especial sejam reproduzidos na forma de traços na tela do computador em tamanho maior, passíveis de serem visualizados por uma pessoa com baixa visão. A ferramenta Quatro Estações foi construída gradativamente tendo como base o estudo dos resultados de experimentos realizados na pesquisa de campo empreendida na EMIEE "Maria Ap. Muniz Michelin-José Benedito Carneiro" e na Associação dos Deficientes Visuais de Femandópolis, no período de agosto de 2004 a novembro de 2004. Essas entidades atendem pessoas com baixa visão, exatamente aquelas às quais se destina a referida ferramenta. Os resultados obtidos, além de servirem para a construção da ferramenta Quatro Estações, demonstraram ser esta eficaz para amenizar as dificuldades das pessoas com baixa visão / Abstract: A number of Brazilians have some sort of whole or partial visual deficiency and the softwares available currently are found to help those with complete loss of sight, while people with short sighted vision, at times, are considered normal or with complete loss of sight. Thus taking no benefits from this kind of action. This abstract describes the development of a software tool with an interface that should help out the ones bearing short sighted vision in general, including students in the educational process. The tool is handy for those bearing short sightedness who have difticulties in the interaction process with computers, trying to overcome their special needs, plus fostering their inc1usion in the educational process and, eventually, set them into the society they live in. The software tool that is shown in this work "Four Season", when executed in the computer with digitalizing table attached to it allows the moves to be performed by a special pen that allows trace shapes to be reproduced on the computer screen having a larger size, enough to be seen by a short sighted person. The "Four Seasons Tool" was gradually built based upon the experiment results study made at the seach field at a middle school " Maria Ap. Muniz Michelin-José Benedito Carneiro" and the Association for People with Eye Problems of Fernandopolis, from August to November 2004. Those organizations wait on beares of short sighted vision only. The outcomes besides fitting to the making of the Four Seasons tool, not only have demonstrated to be effective but also rendered pleasant to those with short sightedness / Mestrado / Engenharia de Software / Mestre em Engenharia Elétrica

Orientador: Gilmar Barreto / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-15T23:37:59Z (GMT). No. of bitstreams: 1 Souza_CristianoRobertode_M.pdf: 1062354 bytes, checksum: 8217be7daba7d7fd194700fdacfc5b03 (MD5) Previous issue date: 2010 / Resumo: Os modelos computacionais para previsão do risco financeiro têm ganhado grande importância desde 1970. Com a atual crise financeira os governos tem discutido formas de regular o setor financeiro e a mais conhecida e adotada é a de Basiléia I e II, que é fortemente suportada por modelo de previsão de risco de crédito. Assim este tipo de modelo pode ajudar os governos e as instituições financeiras a conhecerem melhor suas carteiras para assim criarem controle sobre os riscos envolvidos. Para se ter uma idéia da importância destes modelos para as instituições financeiras a avaliação de risco dada pelo modelo é utilizada como forma de mostrar ao Banco Central a qualidade da carteira de crédito. Através desta medida de qualidade o Banco Central exige que os acionistas do banco deixem depositados um percentual do dinheiro emprestado como garantia dos empréstimos duvidosos criando assim o Índice de Basiléia. Com o objetivo de estudar as ferramentas que atualmente auxiliam no desenvolvimento dos modelos de risco de crédito iremos abordar: 1. Técnicas tradicionais Estatísticas, 2. Técnicas Não Paramétricas, 3. Técnicas Computação Natural / Abstract: The computer models to forecast financial risk have gained great importance since 1970 [1]. With the current crisis Financial government has discussed ways to regulate the financial sector, and the most widely known and adopted form is Basel I and II, which is strongly supported by the forecasting models of credit risk. This type of model can help governments and financial institutions to better understand their portfolios so they can establish control over the risks involved. To get an idea of the importance of this models for financial institutions, the risk assessment given by the model is used as a way of showing the central bank quality of credit portfolio. This measure of quality the Central Bank requires that the shareholders of the bank no longer paid a percentage of the borrowed money as collateral in problem loans and thus creating the index of Basel. In order to study the tools that actually support the development to models of credit risk we will cover: 1. Statistics techniques, 2. Non-Parametric Techniques, 3. Natural Computation Techniques / Mestrado / Automação / Mestre em Engenharia Elétrica

The onset of Industry 4.0 has provided considerable benefits to Intelligent Cyber-Physical Systems (ICPS), with technologies such as internet of things, wireless sensing, cognitive computing and artificial intelligence to improve automation and control. However, with increasing automation, the “human” element in industrial systems is often overlooked for the sake of standardization. While automation aims to redirect the workload of human to standardized and programmable entities, humans possess qualities such as cognitive awareness, perception and intuition which cannot be automated (or programmatically replicated) but can provide automated systems with much needed robustness and sustainability, especially in unstructured and dynamic environments. Incorporating tangible human skills and knowledge within industrial environments is an essential function of “Human-in-the-loop” (HITL) Systems, a term for systems powerfully augmented by different qualities of human agents. The primary challenge, however, lies in the realistic modelling and application of these qualities; an accurate human model must be developed, integrated and tested within different cyber-physical workflows to 1) validate the assumed advantages, investments and 2) ensure optimized collaboration between entities. Agricultural Robotic Systems (ARS) are an example of such cyber-physical systems (CPS) which, in order to reduce reliance on traditional human-intensive approaches, leverage sensor networks, autonomous robotics and vision systems and for the early detection of diseases in greenhouse plants. Complete elimination of humans from such environments can prove sub-optimal given that greenhouses present a host of dynamic conditions and interactions which cannot be explicitly defined or managed automatically. Supported by efficient algorithms for sampling, routing and search, HITL augmentation into ARS can provide improved detection capabilities, system performance and stability, while also reducing the workload of humans as compared to traditional methods. This research thus studies the modelling and integration of humans into the loop of ARS, using simulation techniques and employing intelligent protocols for optimized interactions. Human qualities are modelled in human “classes” within an event-based, discrete time simulation developed in Python. A logic controller based on collaborative intelligence (HUB-CI) efficiently dictates workflow logic, owing to the multi-agent and multi-algorithm nature of the system. Two integration hierarchies are simulated to study different types of integrations of HITL: Sequential, and Shared Integration. System performance metrics such as costs, number of tasks and classification accuracy are measured and compared for different collaboration protocols within each hierarchy, to verify the impact of chosen sampling and search algorithms. The experiments performed show the statistically significant advantages of HUB-CI based protocol over traditional protocols in terms of collaborative task performance and disease detectability, thus justifying added investment due to the inclusion of HITL. The results also discuss the competitive factors between both integrations, laying out the relative advantages and disadvantages and the scope for further research. Improving human modelling and expanding the range of human activities within the loop can help to improve the practicality and accuracy of the simulation in replicating an HITL-ARS. Finally, the research also discusses the development of a user-interface software based on ARS methodologies to test the system in the real-world.<br>

<p><b><u>Introduction</u></b>: Mobile health applications (mHealth apps) have the potential to assist patients in adhering to their physician’s advice in chronic disease management through the use of persuasive nudge. However, systematically developing the persuasive features of a mHealth app for the major user demographic of older adults is challenging. The current usability engineering framework could ensure the user-friendliness of the app but not the persuasiveness. It is necessary to extend the current framework with appropriate measures to better understand the effectiveness of persuasive design elements in an iterative design process.</p><p> </p><p><b><u>Methods:</u></b> A pilot design project was run, a persuasive mHealth app for dietary management was developed using the user-centered design approach (persona, use scenario, task analysis, and cognitive walkthrough), the pilot testing result showed high potential of technology acceptance of older adults. To further evaluate persuasiveness, a food choice experimental protocol and human decision performance metrics based on Signal Detection Theory (SDT) were proposed. A mixed-methods, full factorial user testing study was conducted with twenty older adults aged over 60 and twenty students age 18-35. Critical persuasive User Interface (UI) design variables included decision paradigm (digital nudge), nutrition information format (information nudge), and the system default pre-selection (default nudge). The proposed SDT metrics to evaluate persuasiveness were then compared with confusion matrix metrics which are frequently used to validate system decision-making performance. The relationship between the human performance, subjective workload, and perceived usability of the proposed mHealth app was also investigated.</p><p> </p><p><b><u>Results:</u></b> The ‘Two Alternative Forced Choice’ layout significantly increased the d-prime and accuracy (persuasiveness), the system default pre-selection decreased persuasiveness. The interpretative FSA Nutri-scores label reduced time of response and workload, and increased perceived ease of use, perceived ease of learning, and satisfaction. Among older adults, results differed by age, computer proficiency, and health literacy.</p><p><b><u> </u></b></p><b><u>Conclusion:</u></b> The findings of this study imply the proposed framework is a valid persuasive design research approach. And digital nudge is an effective persuasive design for mHealth app, while default nudge may give rise to negative effects. A generalized human-centered digital nudge design framework along with ageing-centered guidelines were suggested for the similar research and design projects for persuasive technology performed in the future.

<p>With autonomous systems bringing greater demand for user data, in some applications, this also brings an opportunity to solicit data from users. To exploit this, a user interface will need to be designed to coax the user into achieving system goals, like data solicitation. One approach is to design a system to leverage an already present tendency for people to socially interact with technology. In this thesis, I argue that such an approach would involve incorporating interaction concepts that facilitate engagement into the design of recommender system interfaces that will improve the likelihood of obtaining data from users. To support this claim, I synthesize past work on human-computer interaction and recommender systems to derive a framework to guide scientific investigations into interface design concepts that will address the data solicitation problem.<br></p>

Enabling human understanding of high-dimensional (HD) data is critical for scientific research but highly challenging. To deal with large datasets, probabilistic-based non-linear DR models, like UMAP and t-SNE, lead the performance on reducing the high dimensionality. However, considering the trade-off between global and local structure preservation and the randomness initialized for computation, applying non-linear models in different parameter settings to unknown high-dimensional structure data may return different 2D visual forms. Much critical neighborhood relationship may be falsely imposed, and uncertainty may be introduced into the low-dimensional embedding visualizations, so-called distortion. In this work, a survey has been conducted to illustrate the most state-of-the-art layout enrichment works for interpreting dimensionality reduction methods and results. Responding to the lack of visual interpretation techniques to probabilistic-based DR methods, we propose a visualization technique called ManiGraph, which facilitates users to explore multi-view 2D embeddings via mesoscopic structure graphs. A dynamic mesoscopic structure first subsets HD data by a hexagonal grid in visual space from non-linear embedding (e.g., UMAP). Then, it measures the regional adapted trustworthiness/continuity and visualizes the restored missing and highlighted false connections between subsets from high-dimensional space to the low-dimensional in a node-linkage manner. The visualization helps users understand and interpret the distortion from both visualization and model stages. We further demonstrate the user cases tested on intuitive 3D toy datasets, fashion-MNIST, and single-cell RNA sequencing with domain experts in unsupervised scenarios. This work will potentially benefit the data science community, from toolkit users to DR algorithm developers.<br>

In this study, computer human interaction factors are examined as a possible source of information to aid in the operation and management of local area computer networks. Users' perceptions of computer performance and response time are evaluated in relation to specific modifications in the information organization of a file server in a local area network configuration running in Novell 3.11.