D2.1 Analysis of existing MOOC platforms and services

The main objective of this task is to analyze features and services of MOOC platforms that are used in ECO and, secondly, in other commonly used MOOC platforms. This task takes into account the functionality that is required by the different pilots from two viewpoints: technological and pedagogical aspects. Firstly, to ensure this objective, this task performed a state-of-the-art review, mainly research papers and all annotated scientific literature. Secondly, we elaborate a Competitive Analysis Checklist for MOOC platforms. An approach based on technological and pedagogical items is suggested to define specific dimensions for this task. This Checklist will be a useful tool for evaluating MOOC platforms. Thirdly, five of the ECO platforms have been evaluated by using the authoring and delivery environment to check for the availability of features that are essential for the implementation of the pedagogical model as described in D2.1. It became clear that these platforms are not very suitable for the pedagogical model. Finally, a Guide for the Effective Creation of MOOCs has been drawn up indicating to assist course designers to compare the functionality, features, pedagogical and instructional advantages so they can choose the most suitable one for their areas of interest and needs.Part of the work carried out has been funded with support from the European Commission, under the ICT Policy Support Programme, as part of the Competitiveness and Innovation Framework Programme (CIP) in the ECO project under grant agreement n° 21127

Preference extraction and reasoning in negotiation dialogues

Modéliser les préférences des utilisateurs est incontournable dans de nombreux problèmes de la vie courante, que ce soit pour la prise de décision individuelle ou collective ou le raisonnement stratégique par exemple. Cependant, il n'est pas facile de travailler avec les préférences. Comme les agents ne connaissent pas complètement leurs préférences à l'avance, nous avons seulement deux moyens de les déterminer pour pouvoir raisonner ensuite : nous pouvons les inférer soit de ce que les agents disent, soit de leurs actions non-linguistiques. Plusieurs méthodes ont été proposées en Intelligence Artificielle pour apprendre les préférences à partir d'actions non-linguistiques mais à notre connaissance très peu de travaux ont étudié comment éliciter efficacement les préférences verbalisées par les utilisateurs grâce à des méthodes de Traitement Automatique des Langues (TAL).Dans ce travail, nous proposons une nouvelle approche pour extraire et raisonner sur les préférences exprimées dans des dialogues de négociation. Après avoir extrait les préférences de chaque tour de dialogue, nous utilisons la structure discursive pour suivre leur évolution au fur et à mesure de la conversation. Nous utilisons les CP-nets, un modèle de représentation des préférences, pour formaliser et raisonner sur ces préférences extraites. Cette méthode est d'abord évaluée sur différents corpus de négociation pour lesquels les résultats montrent que la méthode est prometteuse. Nous l'appliquons ensuite dans sa globalité avec des raisonnements issus de la Théorie des Jeux pour prédire les échanges effectués, ou non, dans le jeu de marchandage Les Colons de Catane. Les résultats obtenus montrent des prédictions significativement meilleures que celles de quatre baselines qui ne gèrent pas correctement le raisonnement stratégique. Cette thèse présente donc une nouvelle approche à la croisée de plusieurs domaines : le Traitement Automatique des Langues (pour l'extraction automatique des préférences et le raisonnement sur leur verbalisation), l'Intelligence Artificielle (pour la modélisation et le raisonnement sur les préférences extraites) et la Théorie des Jeux (pour la prédiction des actions stratégiques dans un jeu de marchandage)Modelling user preferences is crucial in many real-life problems, ranging from individual and collective decision-making to strategic interactions between agents for example. But handling preferences is not easy. Since agents don't come with their preferences transparently given in advance, we have only two means to determine what they are if we wish to exploit them in reasoning: we can infer them from what an agent says or from his nonlinguistic actions. Preference acquisition from nonlinguistic actions has been wildly studied within the Artificial Intelligence community. However, to our knowledge, there has been little work that has so far investigated how preferences can be efficiently elicited from users using Natural Language Processing (NLP) techniques. In this work, we propose a new approach to extract and reason on preferences expressed in negotiation dialogues. After having extracted the preferences expressed in each dialogue turn, we use the discursive structure to follow their evolution as the dialogue progresses. We use CP-nets, a model used for the representation of preferences, to formalize and reason about these extracted preferences. The method is first evaluated on different negotiation corpora for which we obtain promising results. We then apply the end-to-end method with principles from Game Theory to predict trades in the win-lose game The Settlers of Catan. Our method shows good results, beating baselines that don't adequately track or reason about preferences. This work thus presents a new approach at the intersection of several research domains: Natural Language Processing (for the automatic preference extraction and the reasoning on their verbalisation), Artificial Intelligence (for the modelling and reasoning on the extracted preferences) and Game Theory (for strategic action prediction in a bargaining game

Collaborative Learning and New Media

This book is an essential resource for researchers in the field of applied linguistics as well as practising teachers and teacher trainees in secondary and higher education. It explores collaboration in the foreign language classroom through the use of new media. Combining theoretical, empirical and practical insights into this intricate area of research, the contributions take different approaches across a wide range of international contexts

Cadenland: An Ethnographic Case Study Exploring a Male's Videogaming Literacies on Crayta Within the Larger Stadia Culture

As content creation becomes more accessible and social through gaming, defying hardware barriers, not deterred by software interfaces, moving gaming into the cloud has made it a massive multiplier for players to explore their literacies and creativity without the clutter of the physical space. Videogaming's popularity has sparked controversy, especially the perception of videogames as violent and having a negative influence on players or having no social value in it. Hence, the need to create a balance by focusing on the merits inherent in videogames. This virtual ethnographic case study explored the literacies found in a 26-year-old male gamer's videogaming on Crayta within a larger Stadia cloud gaming community. The methodology included observations, semistructured and unstructured interviews, in-game chats, game-based artifacts, and thematic analysis to analyze the data gathered from the participant. Findings reveal how videogaming experience enhanced the participant's engagement, resulting in four significant literacy outcomes. Results are discussed regarding implications for collaboration, creativity and innovation, critical strategic thinking, and social skills. Included is a hybrid theoretical framework of layered literacies and the feedback loop for examining the lived-in experiences of the participant

Middle School Students Experiences with Personal Learning Devices as it Relates to Reading Motivation: A Case Study

The purpose of this collective case study was to understand the experiences of middle grades students as they relate to reading motivation with personal learning devices. The guiding question was, how do middle school students describe their experiences with personal learning devices as it relates to their motivation to read? The sample population included a total of 15 students from grades sixth, seventh and eighth from a North Georgia middle school. The psychological needs aspect of Deci and Ryan’s self-determination relevant to reading motivation and Rosenblatt’s transactional reading theory in regard to efferent and aesthetic reading transactions served as the theoretical basis for the research. Data was collected from multiple sources including individual interviews, ELA journals, reports from the reading platform myON® and focus group interviews. Data analysis consisted of coding and categorizing information that was then used to conduct a cross case synthesis. The themes of tools, focus, purpose, choice, voice and nonlinear reading were extrapolated and used to inform the naturalistic generalization that technology does not encourage students to read of their own volition. Instead, middle grade students are inclined to read with devices because the tools and features allow differentiation of the reading process on many levels. The results of this study substantiated the notion that technology is best utilized within the context of well-planned engaging instruction that takes into consideration the individual needs, capabilities, and preferences of each learner