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.

EmotiBlog: a finer-grained and more precise learning of subjectivity expression models

The exponential growth of the subjective information in the framework of the Web 2.0 has led to the need to create Natural Language Processing tools able to analyse and process such data for multiple practical applications. They require training on specifically annotated corpora, whose level of detail must be fine enough to capture the phenomena involved. This paper presents EmotiBlog – a fine-grained annotation scheme for subjectivity. We show the manner in which it is built and demonstrate the benefits it brings to the systems using it for training, through the experiments we carried out on opinion mining and emotion detection. We employ corpora of different textual genres –a set of annotated reported speech extracted from news articles, the set of news titles annotated with polarity and emotion from the SemEval 2007 (Task 14) and ISEAR, a corpus of real-life self-expressed emotion. We also show how the model built from the EmotiBlog annotations can be enhanced with external resources. The results demonstrate that EmotiBlog, through its structure and annotation paradigm, offers high quality training data for systems dealing both with opinion mining, as well as emotion detection.

Complex learning: the role of knowledge, intelligence, motivation and learning strategies

This work presents the main theories and models formulated with the purpose of offering a global overview on the acquisition of knowledge and skills involved in the initial development of expert competence. Setting from this background, we developed an empirical work whose main purpose is to define those factors in a complex learning situation such as chapter-sized in a knowledge-rich domain. The results obtained in a sample of Master students reveal that the several variables intervening, such as the qualitative organization of knowledge, intellectual ability, motivation, the deliberate use of strategies, and a rich learning environment, contribute in an independent way to provide an explanation for the acquired knowledge.

An explanatory model of academic achievement based on aptitudes, goal orientations, self-concept and learning strategies

As a result of studies examining factors involved in the learning process, various structural models have been developed to explain the direct and indirect effects that occur between the variables in these models. The objective was to evaluate a structural model of cognitive and motivational variables predicting academic achievement, including general intelligence, academic self-concept, goal orientations, effort and learning strategies. The sample comprised of 341 Spanish students in the first year of compulsory secondary education. Different tests and questionnaires were used to evaluate each variable, and Structural Equation Modelling (SEM) was applied to contrast the relationships of the initial model. The model proposed had a satisfactory fit, and all the hypothesised relationships were significant. General intelligence was the variable most able to explain academic achievement. Also important was the direct influence of academic self-concept on achievement, goal orientations and effort, as well as the mediating ability of effort and learning strategies between academic goals and final achievement.