Definição do conceito de blended learning. Proposta metodológica no quadro da terminologia de base conceptual

Sustentado numa abordagem conceptual da Terminologia, o trabalho de investigação que a seguir se desenvolve visa propor um cenário de resposta à questão: como se define o blended learning no contexto educativo de Ensino Superior Pós-Bolonha? A necessidade de compreender, delimitar e harmonizar o conceito de blended learning no panorama actual do Ensino Superior, resulta do pressuposto de que muito embora proliferem descrições de práticas e modelos para a sua operacionalização de reconhecida qualidade - tal como sucede com outros conceitos sob alçada da educação a distância - a reflexão teórica é ainda insuficiente. Com efeito, para responder à questão supra-colocada, propõe-se o desenho de uma metodologia para construção de uma definição intensional do conceito de blended learning que herde, subsuma e melhore o conhecimento existente, identificado através da análise de texto para fins onomasiológicos e de um processo de elicitação de conhecimento tácito e de negociação discursiva junto de sujeitos especializados. A proposta de desenho metodológico que neste trabalho de esboça escora-se globalmente em três etapas: (1) etapa exploratória do domínio-objecto de estudo; (2) etapa de análise onamasiológica de evidência textual e discursiva; (3) etapa de modelização e de validação de resultados. Pretende-se, em primeiro lugar, através do estudo do espaço conceptual das modalidades de educação que se situam no continuum presença-distância sistematizar e ordenar as visões analisadas, propondo representações de educação presencial, educação a distância, e-learning, educação online, aprendizagem enriquecida por tecnologias e ainda de outras modalidades emergentes. As representações assumem o carácter de proposta aberta e decorrem da necessidade de uma primeira ordenação no sentido de topografrar, delineando - a um nível macro - o possível lugar do conceito de blended learning naquele cenário. Num segundo momento, aprofunda-se e circunscreve-se a análise, depurando a evidência observada, agora reduzida a um conjunto de contextos ricos em informação conceptual – um corpus escrito e oral de definições e descrições de blended learning – identificando candidatas a características essenciais e candidatas a características acidentais. Num terceiro momento, procede-se à modelização do conhecimento, encapsulando-a numa proposta de definição sujeita a um processo iterativo e reflexivo, constituído por um conjunto de ciclos de investigação-acção, os quais reflectem a sequência de interacções entre o terminólogo e sujeitos especializados. Defender-se-á que a experimentação deste desenho revela a produtividade de uma sequência cíclica entre a análise textual e discursiva para fins onomasiológicos, a interacção colaborativa e a introspecção. Por outras palavras, embora a natureza do estudo realizado não permita a generalização, para além da relação diádica de mediação que o terminológo estabelece com o especialista, defende-se a produtividade de um procedimento de acção-reflexão autónomo, solitário e introspectivo, no âmbito da qual o terminólogo se afirma como sujeito conceptualizador, decisor e interventor. Resultam deste percurso uma proposta de definição e de descrição de blended learning em língua portuguesa que acreditamos poder servir diferentes actores da comunidade académica envolvida neste domínio de especialidade.

A conceptual model for grid learning services automatic composition

Peer-reviewed

Learning across business sectors: context, embeddedness and conceptual chasms

While the construction industry is frequently encouraged to learn from other business sectors, the difficulties of transferring knowledge from one context to another are rarely acknowledged. The problematic nature of knowledge is addressed with particular emphasis on the concept of contextual embeddedness. From this point of view, the process of 'knowledge transfer' depends upon a prolonged process of socialization between actors from both the 'receiving' and 'sending' contexts networking. It is contended that a significant conceptual chasm exists between the exhortations of industry leaders to learn from other sectors and the theoretical complexities associated with knowledge transfer. An ongoing research project is described that seeks to facilitate knowledge sharing between construction and aerospace. A novel approach to knowledge sharing based upon soft systems methodology (SSM) (Mode 2) is described and justified. Initial findings from the first cycle of the research are discussed and used to highlight the importance of context in the implementation of supply chain management.

A conceptual framework for aligning business and information systems from organisational learning perspective

The three decades of on-going executives’ concerns of how to achieve successful alignment between business and information technology shows the complexity of such a vital process. Most of the challenges of alignment are related to knowledge and organisational change and several researchers have introduced a number of mechanisms to address some of these challenges. However, these mechanisms pay less attention to multi-level effects, which results in a limited un-derstanding of alignment across levels. Therefore, we reviewed these challenges from a multi-level learning perspective and found that business and IT alignment is related to the balance of exploitation and exploration strategies with the intellec-tual content of individual, group and organisational levels.

Incidental task sequence learning: perceptual rather than conceptual?

In four experiments we investigated whether incidental task sequence learning occurs when no instructional task cues are available (i.e. with univalent stimuli). We manipulated task sequence by presenting three simple binary-choice tasks (colour, form or letter case decisions) in regular repeated or random order. Participants were required to use the same two response keys for each of the tasks. We manipulated response sequence by ordering the stimuli so as to produce either a regular or a random order of left versus right-hand key presses. When sequencing in both, or either, separate stream (i.e. task sequence and/or response sequence) was changed to random, only those participants who had processed both sequences together showed evidence of sequence learning in terms of significant response time disruption (Experiments 1-3). This effect disappeared when the sequences were uncorrelated (Experiment 4). The results indicate that only the correlated integration of task sequence and response sequence produced a reliable incidental learning effect. As this effect depends on the predictable ordering of stimulus categories, it suggests that task sequence learning is perceptual rather than conceptual in nature.

A Semantic Approach to Problem-Based Learning with Conceptual Models

El aprendizaje basado en problemas se lleva aplicando con éxito durante las últimas tres décadas en un amplio rango de entornos de aprendizaje. Este enfoque educacional consiste en proponer problemas a los estudiantes de forma que puedan aprender sobre un dominio particular mediante el desarrollo de soluciones a dichos problemas. Si esto se aplica al modelado de conocimiento, y en particular al basado en Razonamiento Cualitativo, las soluciones a los problemas pasan a ser modelos que representan el compotamiento del sistema dinámico propuesto. Por lo tanto, la tarea del estudiante en este caso es acercar su modelo inicial (su primer intento de representar el sistema) a los modelos objetivo que proporcionan soluciones al problema, a la vez que adquieren conocimiento sobre el dominio durante el proceso. En esta tesis proponemos KaiSem, un método que usa tecnologías y recursos semánticos para guiar a los estudiantes durante el proceso de modelado, ayudándoles a adquirir tanto conocimiento como sea posible sin la directa supervisión de un profesor. Dado que tanto estudiantes como profesores crean sus modelos de forma independiente, estos tendrán diferentes terminologías y estructuras, dando lugar a un conjunto de modelos altamente heterogéneo. Para lidiar con tal heterogeneidad, proporcionamos una técnica de anclaje semántico para determinar, de forma automática, enlaces entre la terminología libre usada por los estudiantes y algunos vocabularios disponibles en la Web de Datos, facilitando con ello la interoperabilidad y posterior alineación de modelos. Por último, proporcionamos una técnica de feedback semántico para comparar los modelos ya alineados y generar feedback basado en las posibles discrepancias entre ellos. Este feedback es comunicado en forma de sugerencias individualizadas que el estudiante puede utilizar para acercar su modelo a los modelos objetivos en cuanto a su terminología y estructura se refiere. ABSTRACT Problem-based learning has been successfully applied over the last three decades to a diverse range of learning environments. This educational approach consists of posing problems to learners, so they can learn about a particular domain by developing solutions to them. When applied to conceptual modeling, and particularly to Qualitative Reasoning, the solutions to problems are models that represent the behavior of a dynamic system. Therefore, the learner's task is to move from their initial model, as their first attempt to represent the system, to the target models that provide solutions to that problem while acquiring domain knowledge in the process. In this thesis we propose KaiSem, a method for using semantic technologies and resources to scaffold the modeling process, helping the learners to acquire as much domain knowledge as possible without direct supervision from the teacher. Since learners and experts create their models independently, these will have different terminologies and structure, giving rise to a pool of models highly heterogeneous. To deal with such heterogeneity, we provide a semantic grounding technique to automatically determine links between the unrestricted terminology used by learners and some online vocabularies of the Web of Data, thus facilitating the interoperability and later alignment of the models. Lastly, we provide a semantic-based feedback technique to compare the aligned models and generate feedback based on the possible discrepancies. This feedback is communicated in the form of individualized suggestions, which can be used by the learner to bring their model closer in terminology and structure to the target models.

A conceptual model of personalized virtual learning environments

The Virtual Learning Environment (VLE) is one of the fastest growing areas in educational technology research and development. In order to achieve learning effectiveness, ideal VLEs should be able to identify learning needs and customize solutions, with or without an instructor to supplement instruction. They are called Personalized VLEs (PVLEs). In order to achieve PVLEs success, comprehensive conceptual models corresponding to PVLEs are essential. Such conceptual modeling development is important because it facilitates early detection and correction of system development errors. Therefore, in order to capture the PVLEs knowledge explicitly, this paper focuses on the development of conceptual models for PVLEs, including models of knowledge primitives in terms of learner, curriculum, and situational models, models of VLEs in general pedagogical bases, and particularly, the definition of the ontology of PVLEs on the constructivist pedagogical principle. Based on those comprehensive conceptual models, a prototyped multiagent-based PVLE has been implemented. A field experiment was conducted to investigate the learning achievements by comparing personalized and non-personalized systems. The result indicates that the PVLE we developed under our comprehensive ontology successfully provides significant learning achievements. These comprehensive models also provide a solid knowledge representation framework for PVLEs development practice, guiding the analysis, design, and development of PVLEs. (c) 2005 Elsevier Ltd. All rights reserved.