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The recent and rapid growth of data-driven applications, fostered by the advent of enhanced Information and Communication Technologies (ICTs) together with the broad availability of modern high-performance storage and computing infrastructures, has created a considerable gap of experts in this new field. The quick evolution of these technologies, their dissimilarities with traditional approaches, and the broad skills set required to master them, might prevent existing professionals working in industry to gain high quality knowledge and experience in Big Data related areas. Therefore, universities and teaching professionals must propose feasible and effective alternatives to train professionals and students in these topics. The purpose of this paper is to present the Master as a Service (MaaS) approach, that is currently being used to train students in Big Data- related areas (e.g., eHealth, Digital Transformation, etc.), following a multidisciplinary, Project Based Learning strategy. More specifically, students coming from different master's degrees and undergraduate backgrounds (ranging from management studies to computer engineering, including architects, social and physical sciences) are trained to address latent and future challenges in Big Data and High-Performance Computing technologies by combining their profiles, and exposing them to real-world challenges that require the very best of each different profile. The results obtained from the implementation of the MaaS approach during the last two years in terms of both student satisfaction and employability rate, confirm the benefits of this method and encourage practitioners to keep working in this direction.

There are numerous examples from recent years of the incorporation of all types of applications and technological systems into the classroom at all educational levels, with the aim to improve both student motivation and academic performance; we can group these initiatives under the term technology-enhanced learning, TEL. The TEL research field has been profoundly involved with the development and application of collaboration apps. Computers, mobile devices, and applications play diverse roles at different times along the project lifecycle. The most common lifecycle comprises four distinct phases: design, implementation, approval, and final assessment. In this chapter, the authors discuss key concepts of these TEL phases as well as some different approaches that can be defined as “good technological practices” and their main results in order to implement technologies in the formative process.

The configuration of urban projects using Information and Communication Technologies is an essential aspect in the education of future architects. Students must know the technologies that will facilitate their academic and professional development, as well as anticipating the needs of the citizens and the requirements of their designs. In this paper, a data mining approach was used to outline the strategic requirements for an urban design project in an architecture course using a Project-Based Learning strategy. Informal data related to an award-winning public space (Gillett Square in London, UK) was retrieved from two social networks (Flickr and Twitter), and from its official website. The analysis focused on semantic, temporal and spatial patterns, aspects generally overlooked in traditional approaches. Text-mining techniques were used to relate semantic and temporal data, focusing on seasonal and weekly (work-leisure) cycles, and the geographic patterns were extracted both from geotagged pictures and by geocoding user locations. The results showed that it is possible to obtain and extract valuable data and information in order to determine the different uses and architectural requirements of an urban space, but such data and information can be challenging to retrieve, structure, analyze and visualize. The main goal of the paper is to outline a strategy and present a visualization of the results, in a way designed to be attractive and informative for both students and professionals – even without a technical background – so the conducted analysis may be reproducible in other urban data contexts.

Linda Castaneda1 , Nada Dabbagh2, Ricardo Torres-Kompen31University of Murcia, Spain {lindacq@um.es}2George Mason University, USA {ndabbagh@gmu.edu}3Universitat Ramon Llull - La Salle Barcelona Campus, Spain {ricardot@salleurl.edu}Received on 26 December 2016; revised on 28 December 2016; accepted on 29 December 2016; published on 15 January 2016DOI: 10.7821/naer.2017.1.229Personal Learning Environments (PLE), as a concept as well as an emerging practice, is not just one of the most innovative dimensions of technology-enabled student-centered learning, but also one of the most challenging disruptions to the institutional traditional conception of knowledge.A PLE is usually described as a structure and process that helps learners organize the influx of information, resources and interactions that they are faced with on a daily basis into a personalized learning space or experience. In a PLE, the learner develops an individualized digital identity through the perceptual cues and cognitive affordances that the personal learning environment provides, such as what information to share and when, who to share it with, and how to effectively merge formal and informal learning experiences (Castaneda, Cosgrave, Marin, Cronin, 2016).Events as the PLE Conference, which started in 2010, emerged as an answer to the need for showcasing, disseminating and sharing the novel and original research (and knowledge) specific to the PLE movement. Additionally, they were a departure from the traditional format of most conferences in that the attendees, who had developed individualized research-based PLE practice, came together in what we call the "spirit of PLEs": sharing, collaborating and creating together.This past decade has seen a dramatic increase in the quantity of research published on PLEs and most of it has been enriched by the papers presented in the successive PLE events that have formed part of special issues of a diversity of journals, including Digital Education Review, the International Journal of Virtual and Personal Learning Environments, and others (Hernandez, 2016).Thanks to the previous -and current- debate, experts are trying to understand what our relationship with the PLE concept is, and how it could help us improve the role of technology, people, communities, educational and information resources, cognitive mechanisms and so on, in learning. From these debates and discussions, witnessed at the PLE events and beyond, original discussions regarding institutional or non-institutional education have evolved into how to reconcile -pedagogically and technologically- learning inside and outside formal contexts.Other discussions about technological and pedagogical perspectives have evolved to sociomaterial visions of learning recognising the reciprocal, recursive, and transformative interaction between people and technology.The network, the impact -and training- of metacognition, the horizontal organisation, are emerging and ongoing topics that are enriching the learning debate and forcing new explorations in research and practice. Such investigations will focus more on people and their relationship with technology and less on the use of technology for automating the learning experience.On the one hand, it seems that PLE is no longer the centre of the discussion, at least not as a standalone construct. But, on the other hand, PLE is more than ever the paradigm for supporting new learning models for the digital times.PLEs have had direct implications on Massive Open Online Courses (MOOCs), adaptive learning, and learning analytics, to name a few new learning models and processes that have personalization of learning at their core. MOOCs have been characterised as PLE-type environments providing learners with the appropriate tools to engage in self-directed and personalised learning and integrating social media features to boost opportunistic interaction and informal exchanges between students (Gillet, 2013; Kop & Fournier, 2014). …

The concept of Personal Learning Environments (PLE) is, one of the concepts in the field of educational technology that has gained more attention in during the last decade. Those of us who do research on this topic assume —perhaps naively— that this is a disruptive, a fundamental concept, at the base of the emergent pedagogical approaches that characterize the techno-social age we live in, not only from the technological and instrumental perspective, but its roots in the very foundations of the educational process. Nevertheless, we know very little about the impact of this concept - and other associated topics - on other educational issues that are not necessarily linked to technology. By means of a systematized review of the available literature, we analyzed the impact of the PLE topic on three main themes of the scientific literature in education produced during the last decade: emerging pedagogical practices, self-regulated learning and professional teacher development. The analysis is focused on whether (and how) the PLE concept has impacted each of the topics, the level of importance of that impact in each one of the themes and the way in which the concept is "materialized" in them. The conclusions of this article intend to offer suggestions on the future of research and the applications in practice of a concept that, after more than ten years of its emergence in the educational field, continues to be considered as emergent.

[EN] This paper proposes a framework for context-aware assessment of out-ofclassroom subjects with the support of mobile technologies. The paper discusses: (a) the principles and implications of out-of-classroom activities, e.g. internships, outdoors practicals of topography, of agricultural or marine engineering, virtual university courses, etc.; and (b) context-aware assessment, in which some context elements (location, date and time, environmental circumstances) may be incorporated into the assessment by means of mobile technology. The aim of this framework is to provide the tools that will allow for an enhanced evaluation, by taking into account the context of the activities being carried out. Given the characteristics of the activities, the assessment will be based on submissions prepared by the students, which will automatically incorporate context information that can be relevant for the assessment. The framework will be tested with several groups of students participating in internships and/or international mobility programmes, from different universities (public, private, semi-public).