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Blended/hybrid learning, a combination of face to face and online learning to deliver instruction, is growing in popularity at institutions of higher education, and may lead to many benefits for students, faculty, and administrators. However, the implementation of blended learning (BL) is a complex process. Although the move towards BL adoption is generally accepted by faculty, questions still remain when it comes to adopting and implementing standards across institutions. Given this problem, this integrative literature review was conducted to identify possible factors that impact the process of implementing BL smoothly and successfully at higher education institutions. The purpose of this study was to identify related institutional factors from empirical studies published from 2000 to 2020. Findings from this study may offer institutions a guide to effectively create, execute, and assess BL programs and courses. The study provides recommendations that may be impactful for decision-makers at Saudi higher education institutions. / Doctor of Philosophy / Blended/hybrid learning, a combination of face to face and online learning to deliver instruction, has become popular at universities because it provides advantages for students, faculty members, and the university itself. However, the implementation of blended learning (BL) is a challenging process, and in many instances there is not enough guidance available to assist universities through the process. For this reason, this study has been conducted with the goal of identifying possible factors relating to implementing BL smoothly and successfully at universities. Findings from this study may offer institutions a guide to effectively create, execute, and assess BL programs and courses. The study provides recommendations that may be impactful for decision-makers at Saudi universities

L’objet de cette recherche porte sur l’évolution des dispositifs de formation avec l’introduction de technologies de réalité virtuelle dans des contextes industrialisés. Cette thèse Cifre s’appuie sur une intégration au sein du département « training » d’Airbus Helicopters. La démarche de recherche-action mise en œuvre permet d’observer et de participer à l’élaboration d’une technologie immersive pour la formation de pilotes. Cet outil est mis en situation avec des clients en formation et plusieurs démonstrations sont faites auprès d’acteurs de différents métiers. Nous mettons en avant des configurations hybrides dans le sens ou les situations de formation révèlent des aspects de la pratique et de la théorie telles qu’elles sont pensées dans la « langue de l’organisation ». Nous montrons alors que la mise en œuvre de telles technologies pourrait remettre en question les modèles rationalisés dans l’organisation. Ces éléments nous permettent d’envisager qu’une « approche par l’hybridation des dispositifs » amène l’organisation à interroger à chaque étape du projet ses propres modèles (objets structurés de partage d’information, organigramme, compétences et métiers des acteurs). C’est alors une remise en question en « profondeur » du projet de l’organisation apprenante qui est rendue possible, à partir de l’expérience des sujets. / The purpose of this research is to better understand how training devices evolve, with the introduction of virtual reality technology, in industrialized training situations. This work I based on an immersion in the "training" department of Airbus Helicopters. The research-action approach allows us to observe and participate in the emergence of a technology of reality for pilot’s training. The tool is put in situation with customers as part of their training and several demonstrations are made to actors of different trades around the training. We identify hybrid configurations in the sense that training situations are both practical and at the same time theoretical in the language of the organization. Then we show that the implementation of these technologies requires to rethink a traditional rationalization. These elements allow to suggest an "approach by the hybridization of systems" gives the organization the ability to reconsider its own project (structured objects of information, organization chart, skills and trades of actors). It is a depth questioning of the learning organization that is possible, from the experience of subjects.

Neuro-fuzzy modeling is an efficient computing paradigm for system modeling problems. It mainly integrates two well-known approaches, neural networks and fuzzy systems, and therefore possesses advantages of them, i.e., learning capability, robustness, human-like reasoning, and high understandability. Up to now, many approaches have been proposed for neuro-fuzzy modeling. However, it still exists many problems need to be solved. We propose in this thesis two self-constructing rule generation methods, i.e., similarity-based rule generation (SRG) and similarity-and-merge-based rule generation (SMRG), and one hybrid learning algorithm (HLA) for structure identification and parameter identification, respectively, of neuro-fuzzy modeling. SRG and SMRG group the input-output training data into a set of fuzzy clusters incrementally based on similarity tests on the input and output spaces. Membership functions associated with each cluster are defined according to statistical means and deviations of the data points included in the cluster. Additionally, SMRG employs a merging mechanism to merge similar clusters dynamically. Then a zero-order or first-order TSK-type fuzzy IF-THEN rule is extracted from each cluster to form an initial fuzzy rule-base which can be directly employed for fuzzy reasoning or be further refined in the next phase of parameter identification. Compared with other methods, both our SRG and SMRG have advantages of generating fuzzy rules quickly, matching membership functions closely with the real distribution of the training data points, and avoiding the generation of the whole set of clusters from the scratch when new training data are considered. Besides, SMRG supports a more reasonable and quick mechanism for cluster merging to alleviate the problems of data-input-order bias and redundant clusters, which are encountered in SRG and other incremental clustering approaches. To refine the fuzzy rules obtained in the structure identification phase, a zero-order or first-order TSK-type fuzzy neural network is constructed accordingly in the parameter identification phase. Then, we develop a HLA composed by a recursive SVD-based least squares estimator and the gradient descent method to train the network. Our HLA has the advantage of alleviating the local minimal problem. Besides, it learns faster, consumes less memory, and produces lower approximation errors than other methods. To verify the practicability of our approaches, we apply them to the applications of function approximation and classification. For function approximation, we apply our approaches to model several nonlinear functions and real cases from measured input-output datasets. For classification, our approaches are applied to a problem of human object segmentation. A fuzzy self-clustering algorithm is used to divide the base frame of a video stream into a set of segments which are then categorized as foreground or background based on a combination of multiple criteria. Then, human objects in the base frame and the remaining frames of the video stream are precisely located by a fuzzy neural network which is constructed with the fuzzy rules previously obtained and is trained by our proposed HLA. Experimental results show that our approaches can improve the accuracy of human object identification in video streams and work well even when the human object presents no significant motion in an image sequence.

The replication of human intelligence, learning and reasoning by means of computer algorithms is termed Artificial Intelligence (Al) and the interaction of such algorithms with the physical world can be achieved using robotics. The work described in this thesis investigates the applications of concept learning (an approach which takes its inspiration from biological motivations and from survival instincts in particular) to robot control and path planning. The methodology of concept learning has been applied using learning decision trees (DTs) which induce domain knowledge from a finite set of training vectors which in turn describe systematically a physical entity and are used to train a robot to learn new concepts and to adapt its behaviour. To achieve behaviour learning, this work introduces the novel approach of hierarchical learning and knowledge decomposition to the frame of the reactive robot architecture. Following the analogy with survival instincts, the robot is first taught how to survive in very simple and homogeneous environments, namely a world without any disturbances or any kind of "hostility". Once this simple behaviour, named a primitive, has been established, the robot is trained to adapt new knowledge to cope with increasingly complex environments by adding further worlds to its existing knowledge. The repertoire of the robot behaviours in the form of symbolic knowledge is retained in a hierarchy of clustered decision trees (DTs) accommodating a number of primitives. To classify robot perceptions, control rules are synthesised using symbolic knowledge derived from searching the hierarchy of DTs. A second novel concept is introduced, namely that of multi-dimensional fuzzy associative memories (MDFAMs). These are clustered fuzzy decision trees (FDTs) which are trained locally and accommodate specific perceptual knowledge. Fuzzy logic is incorporated to deal with inherent noise in sensory data and to merge conflicting behaviours of the DTs. In this thesis, the feasibility of the developed techniques is illustrated in the robot applications, their benefits and drawbacks are discussed.

The changing environment during the COVID-19 pandemic has led to an increased demand for hybrid work formats. However, the research field merely focuses on hybrid work formats that were planned for. Generating knowledge regarding hybrid learning and how it can help those who intend to integrate it into their organizational settings is the purpose of this study. With this qualitative study we aim to make contributions to this research gap by exploring the research question “How are digital tools used for hybrid learning in higher education environments and how does it change the conditions for learning?”. The method used is a case study, in which we interview five respondents with differentiating experience of conducting hybrid learning. We found that digital tools are used similarly in both hybrid and non-hybrid higher education environments and that there had hardly been any kind of investments made towards hybrid work methods. We also found that hybrid learning works well for the traditional one-way communication lecture form but not as well for interactive lecture forms. Because this lecture form is important for deeper learning, in the context of this study hybrid learning is not perceived as an adequate lecture form. In addition to contributions to this research field, we aim to contribute to the practical usage of digital tools within hybrid work models.

School librarians create an atmosphere where learners feel empowered. Moreover, school library programming should support diversity, equity, and inclusive learning opportunities to facilitate student success. Thus, school librarians are expected to model and advocate for equitable learning spaces while considering the universal design for learning approach to improving accessibility, utilization, and relevance for all library patrons. Although it has been established that school library standards support diversity, equity, and inclusion (DEI), more is needed to know about the impact of a crisis on school library programming and services. In addition, extensive research has not been conducted to determine school librarians' responsiveness and strategies to provide services for their school communities during disruptive times. This study examines school librarians' perceptions of the opportunities and challenges encountered while endeavoring to engage in DEI practices during crises.

Muitas instituições de ensino superior (IES) buscam novas formas de aperfeiçoarem o processo ensino-aprendizagem visando adequarem as aulas tradicionais às tecnologias emergentes advindas da Web 2.0, como as mídias sociais. Nesse processo de reinvenção, o docente deve capacitar-se a ministrar aulas não apenas com o intuito de disseminar conhecimentos tácitos e explícitos, mas também de liderar os estudantes na sala de aula presencial e nos ambientes virtuais de aprendizagem, conduzindo-os a superarem suas expectativas quanto ao aprendizado. Analisando perfis de liderança existentes, a presente dissertação, focada em um Estudo de Caso, busca identificar qual o perfil ideal de liderança do docente em ambientes híbridos, utilizando-se para tal do Índice de Satisfação de Grupo, análise de gráficos e do discurso dos estudantes. O método de ensino adotado pelo docente foi o PBL (Problem Based Learning), dando-se ênfase ao desenvolvimento do pensamento critico. A pesquisa realizou-se junto a disciplinas do Departamento de Engenharia de Produção da EESC-USP, onde estudantes de graduação e pós-graduação foram desafiados pelo método PBL a pensarem de forma crítica na construção do próprio conhecimento. Os resultados obtidos por meio de questionários aplicados ao final dos semestres de 2011 e 2012 mostram que a liderança Laissez-faire não é indicada na fase de implantação do PBL, necessitando maior interferência do docente para a quebra do paradigma entre o modelo de ensino tradicional e o novo. Conclui-se que a conexão entre o processo ensino-aprendizagem tradicional e o novo possa ser feita por meio da liderança situacional, alternando a liderança transformacional e a transacional de acordo com o contexto, excluindo-se a Laissez-faire. / Many institutions have developed new ways to improve the teaching-learning process, trying to adequate the classes to the emerging new technologies based on Web 2.0, as in the case of social media. In this re-inventing process teachers must have the leadership skills both in classrooms and virtual learning environments, allowing the students to overcome their expectations of the learning process. This dissertation is focused on a case study that seeks to identify what is the ideal leadership profile into hybrid environments, using a group satisfaction index, graphical analysis and student speeching skills. The teaching methodology used by the teacher was the PBL (Problem-Based Learning) that emphasizes the critical mindset. The research was carried out during the disciplines into the Manufacturing Engineering graduation and post-graduation program of Universidade de São Paulo (USP) EESC department. The students were challenged by the PBL methodology to think about the best way to build their own know how. The data obtained with the application of questionaries in the 2011 and 2012 semesters showed that the \"Laissez-Faire\" leadership is not recommended during the PBL methodology implementation, requiring more interferences and attention from the teacher to break the paradigm of the traditional teaching models. The conclusion is that the connection between the traditional and the new teaching-learning processes can be built using situational leadership, alternating between transformational leadership and transactional models, contextually, excluding the Laissez-faire.

Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-09-22T18:42:19Z No. of bitstreams: 1 AdrianaCosta.pdf: 3838428 bytes, checksum: 2c98d9d837cb8ba187aa038e80b2d304 (MD5) / Made available in DSpace on 2017-09-22T18:42:19Z (GMT). No. of bitstreams: 1 AdrianaCosta.pdf: 3838428 bytes, checksum: 2c98d9d837cb8ba187aa038e80b2d304 (MD5) Previous issue date: 2017-08-14 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão / Software agents represent an evolution of traditional software entities, having the ability to control their own behavior and acting with autonomy. Typically, software agents act reactively, where actions and perceptions are predefined at design time, or in a deliberative way, where the corresponding action for a given perception is found at run time through reasoning. Deliberative agents do not need all knowledge to be predefined; on the contrary, from an initial knowledge they can infer new knowledge. However, to find an action appropriate to a particular perception, they take a long time, generating a high computational cost. As a solution to this problem, a hybrid architecture with learning for the development of hybrid software agents is presented in this work. Hybrid agents combine reactive and deliberative behavior taking advantage of the speed of reactive behavior and the reasoning capability of the deliberative one are a better option for structuring software agents. The main advantages of the proposed architecture are learning of the reactive behavior, faster and more efficient, through the interactions of the agent with its environment and its consequent adaptability to the environment. The agent adapts to the environment as it learns new reactive behavior from frequent deliberative behavior. The proposed architecture was evaluated through the development of case studies in the information security domain using case-based reasoning, ontologies for the representation of domain knowledge and supervised learning for automatic generation of reactive rules. Results obtained with the case studies performed confirmed a greater effectiveness and a shorter response time of the hybrid agent with learning regarding both the reactive or deliberative agent as well as a hybrid agent without learning in the intrusion detection in computer networks domain. From the specification and evaluation of the hybrid architecture with supervised learning in the Information Security domain, a reference architecture for the development of hybrid agents with learning was generalized. In future works, we intend to evaluate this reference architecture in other domains, with other types of reasoning and learning techniques to evaluate its impact on the productivity and quality of the development of hybrid software agents. / Os agentes de software representam uma evolução do software tradicional, tendo a capacidade de controlar seu próprio comportamento e agir com autonomia. Tipicamente, os agentes de software agem de forma reativa, onde as percepções e ações são predefinidas no momento da sua concepção, ou de forma deliberativa, onde a ação correspondente para uma determinada percepção é encontrada em tempo de execução através de um processo de raciocínio. Os agentes deliberativos não necessitam que todo o conhecimento seja predefinido, ao contrário, a partir de um conhecimento inicial eles conseguem inferir novo conhecimento. Todavia, em muitos casos, para encontrar uma ação apropriada a uma determinada percepção eles levam muito tempo, gerando um alto custo computacional. Como solução a esse problema, apresentamos neste trabalho uma arquitetura híbrida com aprendizagem para o desenvolvimento de agentes de software híbridos. Os agentes híbridos, que combinam comportamento reativo e deliberativo, são uma opção melhor para estruturar os agentes de software. As principais vantagens da arquitetura tese é o aprendizado do comportamento reativo, mais rápido e eficiente, através de interações do agente com o seu ambiente e a sua consequente adaptabilidade ao ambiente. O agente se adapta ao ambiente na medida em que aprende novo comportamento reativo a partir de comportamento deliberativo frequente. A arquitetura tese foi avaliada através do desenvolvimento de estudos de casos no domínio da segurança da informação utilizando o raciocínio baseado em casos, ontologias para a representação do conhecimento do domínio de estudo e aprendizagem supervisionada para geração automática de regras reativas. Os resultados obtidos com os estudos de casos realizados confirmaram uma efetividade maior e um menor tempo de resposta do agente híbrido com aprendizagem em relação tanto ao comportamento isolado de um agente reativo ou deliberativo bem como de um agente híbrido sem aprendizagem no domínio da detecção de intrusões em redes de computadores. A partir da especificação e avaliação da arquitetura híbrida com aprendizagem supervisionada no domínio da Segurança da Informação, foi generalizada uma arquitetura de referência para o desenvolvimento de agentes híbridos com aprendizagem. Em trabalhos futuros, pretende-se avaliar esta arquitetura de referência em outros domínios, com outros tipos de raciocínio e técnicas de aprendizagem para avaliar o seu impacto na produtividade e qualidade do desenvolvimento de agentes de software híbridos.

Submitted by Livia Mello (liviacmello@yahoo.com.br) on 2016-10-03T20:31:27Z No. of bitstreams: 1 TeseLCC.pdf: 6299139 bytes, checksum: 5b78e4b3502f2dc005aa69b90a54ad55 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-10T19:14:08Z (GMT) No. of bitstreams: 1 TeseLCC.pdf: 6299139 bytes, checksum: 5b78e4b3502f2dc005aa69b90a54ad55 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-10T19:14:33Z (GMT) No. of bitstreams: 1 TeseLCC.pdf: 6299139 bytes, checksum: 5b78e4b3502f2dc005aa69b90a54ad55 (MD5) / Made available in DSpace on 2016-10-10T19:14:44Z (GMT). No. of bitstreams: 1 TeseLCC.pdf: 6299139 bytes, checksum: 5b78e4b3502f2dc005aa69b90a54ad55 (MD5) Previous issue date: 2016-02-26 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / This research aimed to analyze the limits and contributions of a hybrid space, the 3rd Space, understood as dialogue environment between students of Pedagogy - of distance learning programs -, experienced Elementary School teachers, mentors of the initial years of Middle School Education and University researchers / academic advisors, aiming at learning the teaching profession and the professional development of teachers. Specifically, the intent was to analyze construction processes of knowledge needed for the exercise of pedagogical practices in varied school contexts; to understand how knowledge and skills are integrated, providing the knowledge base for teaching; and to understand if a hybrid space supports the articulation of knowledge of various natures in favor of learning the teaching profession. The theoretical framework comprised: initial and continuing teacher training; learning the teaching profession and professional development; knowledge base; university-school partnership; hybrid spaces of training and written narratives, their main authors being Veenman, Shulman, Cavaco, Garcia, Mizukami, Zeichner, Vaughan, Penã and Allegretti. A constructive-collaborative approach was used (COLE; KNOWLES, 2003) for research and intervention. The data collection instruments were written narratives (VAZ; MENDES; MAUÉS, 2001) prepared by the participants, and the analysis took place in a procedural manner, based on the knowledge model for teaching as a main reference (SHULMAN, 1987, 2005), and the profession and professional teaching as categories that are both complementary and revealing of the specifics of the teacher's work (NÓVOA, 1999; CONTRERAS, 2002; ROLDÃO, 2007). The in-depth analyses were made from the study of multiple cases (EZPELETA, 1984; LUDKE; ANDRÉ 1986; MAZZOTTI, 2006), arising from professional apprenticeships of teaching three dyads (mentor / undergraduate student), one of which is active in the Early Years of Middle School, and the other two in Elementary School. Analyses indicated that learning to teach and being a teacher are processes that are enhanced throughout life, highly influenced by previous experiences - be they formal or informal - related to the teaching profession and the specific contexts of action. It was suggested that the formative demand for the teaching practice for Elementary School and Early Years of Middle School focused on the process involving the mastery of general pedagogical knowledge. Additionally, little ability to plan educational interventions consistent with the needs of children was identified, even when dealing with experienced teachers. As a training space, the virtual learning environment (VLE) created with the development of research and called 3rd Space revealed itself as a viable tool for the articulation between the knowledge derived from their participants (mentors, undergraduate students and researchers / academic advisors) and for strengthening the links between the university and teachers' work reality. While articulating relations between theory and practice, the hybrid space potentiated the reflective exercise, especially in the case of undergraduate students; however, it faced some difficulties due to the exclusive use of written narratives, predominantly in the case of experienced teachers (mentors). / A pesquisa teve como propósito analisar limites e contribuições de um espaço híbrido, o 3o Espaço, compreendido como ambiente de interlocução entre licenciandas em Pedagogia, na modalidade a distância, professoras experientes da Educação Infantil e dos Anos Iniciais do Ensino Fundamental (mentoras) e pesquisadoras-formadoras da universidade, visando à aprendizagem da docência e ao desenvolvimento profissional de professores. Especificamente, pretendeu-se analisar processos de construção de conhecimentos necessários para o exercício de práticas pedagógicas em contextos escolares variados; compreender como conhecimentos teóricos e práticos se integram, constituindo a base de conhecimento para o ensino; e entender se um espaço híbrido sustenta a articulação de conhecimentos de naturezas diversas em benefício da aprendizagem da docência. O referencial teórico englobou: formação inicial e continuada de professores; aprendizagem da docência e desenvolvimento profissional; base de conhecimento; parceria universidade-escola; espaços híbridos de formação e narrativas escritas, tendo como principais autores: Veenman, Shulman, Cavaco, Garcia, Mizukami, Zeichner, Vaughan, Penã e Allegretti. Adotou-se uma abordagem construtivo-colaborativa (COLE; KNOWLES, 2003) de pesquisa e intervenção. Os instrumentos de coleta de dados foram narrativas escritas (VAZ; MENDES; MAUÉS, 2001) elaboradas pelas participantes, e a análise se deu de modo processual, tendo o modelo de base de conhecimento para o ensino como referência principal (SHULMAN, 1987, 2005) e a profissão e a profissionalidade docente como categorias complementares e reveladoras das especificidades do trabalho do professor (NÓVOA, 1999; CONTRERAS, 2002; ROLDÃO, 2007). As análises em profundidade foram feitas a partir do estudo de casos múltiplos (EZPELETA, 1984; LUDKE; ANDRÉ 1986; MAZZOTTI, 2006), decorrentes das aprendizagens profissionais da docência de três díades (mentora/licencianda), uma delas atuante nos Anos Iniciais do Ensino Fundamental, e as outras duas na Educação Infantil. As análises indicaram que aprender a ensinar e ser professor são processos que se aprimoram ao longo da vida, altamente influenciados por experiências anteriores, formais ou informais, relativas ao exercício da docência e pelos contextos específicos de atuação. Sugeriram que a demanda formativa para a atuação docente na Educação Infantil e nos Anos Iniciais do Ensino Fundamental se centrou no processo que envolve o domínio do conhecimento pedagógico geral. Adicionalmente, identificou-se pouca habilidade para planejar intervenções pedagógicas coerentes com as necessidades das crianças, mesmo se tratando de professoras experientes. Enquanto espaço formativo, o ambiente virtual de aprendizagem (AVA), criado em função do desenvolvimento da pesquisa e denominado 3o Espaço, revelou-se como ferramenta viável para a articulação entre os conhecimentos advindos de suas participantes (mentoras, licenciandas e pesquisadoras-formadoras) e para aproximações entre a universidade e a realidade de trabalho das professoras. Enquanto articulador de relações entre teoria e prática, o espaço híbrido potencializou o exercício reflexivo, principalmente no caso das licenciandas, mas enfrentou algumas dificuldades em razão do uso exclusivo de narrativas escritas, sobretudo no caso das professoras experientes (mentoras). / FAPESP no 2014/11263-5