La evaluación de los aprendizajes en los sMOOC. Estudio de caso en el Proyecto Europeo ECO

El siguiente artículo hace una reflexión crítica sobre los MOOC, prestando especial atención al análisis de los nuevos sistemas de evaluación; en concreto, el método peer to peer, y cómo esto afecta al rol de docentes y estudiantes. El estudio se ha llevado a cabo tomando como referencia dos sMOOC liderados por el Proyecto Europeo ECO (Elearning, Communication and Open-data: Massive Mobile, Ubiquitous and Open Learning). Los resultados que se presentan han sido analizados desde una perspectiva cuantitativa, utilizando como muestra a los miembros de la comunidad de aprendizaje que han participado en ambos cursos. A través de la utilización de un cuestionario se ha podido conocer cómo han valorado su experiencia formativa y su grado de satisfacción. La mitad de los sujetos encuestados ha considerado adecuado y justo el nuevo sistema evaluativo, sin embargo existe otra mitad que lo considera injusto y que tiene lagunas. Se ha abordado la evaluación como una parte intrínseca del proceso educativo y por ello se ha enfatizado en aspectos como el empoderamiento del alumnado, la cultura de la participación y la interacción social, conceptos que nos acercan a nuevos modelos de aprendizaje que potencian el intelecto colectivo y dejan atrás sistemas transmisivos de conocimiento.

Linguistic Systems and Knowledge of Reality

Linguistic systems are the human tools to understand reality. But is it possible to attain this reality? The reality that we perceive, is it just a fragmented reality of which we are part? In this paper the authors present is an attempt to address this question from an epistemological and philosophic linguistic point of view.

An authoring tool for decision support systems in context questions of ecological knowledge

Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.