Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-05-09T17:24:59Z No. of bitstreams: 1 LENARDO CHAVES E SILVA - TESE PPGCC 2015..pdf: 9863003 bytes, checksum: b4ff7a7517f3ec159596b4b3c8730219 (MD5) / Made available in DSpace on 2018-05-09T17:24:59Z (GMT). No. of bitstreams: 1 LENARDO CHAVES E SILVA - TESE PPGCC 2015..pdf: 9863003 bytes, checksum: b4ff7a7517f3ec159596b4b3c8730219 (MD5) Previous issue date: 2015-11-12 / Capes / Sistemas Médicos Físico-Cibernéticos (SMFC) são sistemas críticos cientes de contexto que têm a segurança do paciente como principal requisito, demandando processos rigorosos de validação para garantir a conformidade com os requisitos do usuário e a corretude orientada à especificação. Neste trabalho é proposta uma arquitetura baseada em modelos para validação de SMFC, focando em promover a reúso e a produtividade. Tal abordagem permite que desenvolvedores de sistemas construam modelos formais de SMFC baseados em uma biblioteca de modelos de pacientes e dispositivos médicos, bem como simular o SMFC para identificar comportamentos indesejados em tempo de projeto. A abordagem proposta foi aplicada a três diferentes cenários clínicos para avaliar seu potencial de reúso para diferentes contextos. A abordagem foi também validada por meio de uma avaliação empírica com desenvolvedores para avaliar o reúso e a produtividade. Finalmente, os modelos foram formalmente verificados considerando os requisitos funcionais e de segurança, além da cobertura dos modelos. / Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different context. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage.

<p>Social presence positively influences the motivation, satisfaction, retention, and learning outcomes of online students. Although it is crucial for successful online learning experiences, little work has thoroughly examined the evolution of social presence over time and the influence of social presence on peer interaction. In other words, if social presence can be learned by interacting with others. This three-article dissertation study elucidates this gap by answering the overarching question: How does online students' social presence evolve over time to shape their online learning behaviors? Using stochastic-actor oriented models to reflect the dependence among learners in online collaborative learning communities, this dissertation investigated how learners' social presence evolved in learner-learner interaction resulting in two empirical studies and one conceptual framework. The first study explored social presence through clickstream interaction (e.g., number of replies received/sent in an online discussion) of 382 learners enrolled in a Massive Open Online Course. Three key findings from the study were: 1) dropout rates could be lowered if social presence affordances are used purposefully; 2) adding social media characteristics to online discussion boards, for example, "like" buttons, inhibits conversational behavior, and eventually, decreases achievement of learning outcomes; and 3) the "rich-get-richer" effect also applies to social presence, reinforcing highly active students' behavior and risking inactive online students to experience isolation. The second study used peer-nomination data (i.e., asking students who they interact with) and a scale to investigate the spread of social presence perceptions in online networks of students over three consecutive courses (n = 197). Although there was no evidence of social influence, online learners who nominated more peers are more likely to report higher social presence perceptions over time. Students were not more likely to share with those who showed similar levels of social presence. The "rich-get-richer effect" was observed in the incoming nominations of learners. The third study is a conceptual framework that integrates network theory and the online learning literature into a new perspective to analyze learners' online behaviors and interactions under the light of social presence theory. The proposed framework includes four main steps: 1) interaction, 2) social presence alignment, 3) unit of analysis definition, and 3) network statistics and inferential analysis selection. The findings of this dissertation improve educational practice by identifying behaviors that harm online social presence and providing specific actions for online instructors and instructional designers to promote social presence in online learning.  </p>