Call for paper - Vol.10, n.3, 2014
LEARNING IN SMART ENVIRONMENTS
Giuseppina Rita Mangione, University of Salerno, Italy
Paolo Maresca, University Napoli Federico II, Italy
August, 24th 2014: Initial manuscripts due
September, 14th 2014: Notification and Review Comments
September, 21st 2014: Camera Ready manuscript due
September, 2014: Special Issue published
- the boom of the degrees for adults (grown in the world from 19% to 29%),
- growth in the number of university enrollments, which are going to increase from 178 to 262 million,
- new regions of the world that are going to drive the global competition in the coming years. China plans to increase its research spending from 1.8% to 2.5% of GDP by 2020, and the President of India, Shri Praneb Mukherjee, has planned to place India among the first five scientific powers in the world by 2020.
- internationalization will always be wider and deeper.
The agents of change are already changing the way we teach. Among these we find:
- The universities are no longer the gatekeepers of knowledge, and university libraries have ceased to be the only repositories, sanctioning the "democratization of knowledge"
- Digitization is changing education in the same way in which has transformed media, retail, banking and entertainment: the digital delivery is going to replace the classroom for the large majority of learning situations.
- A globalized market is growing, in which competition between universities is becoming intense and students are equipping themselves to choose according to quality. Governments begin to "outsource" education programs, in order to more effectively use their resources in targeted spending.
- The relationship between universities and industry is becoming more continuous and extensive, and the influence of industry on research and teaching is growing. The universities should align more closely with businesses, if they want to be the drivers of innovation and growth.
- Access to universities is increasing, while the requirement to be physically present on campus is decreasing: the global competition intensifies in such a way that traditional education Importers seek to become exporters; universities need to re-invent their business model.
This premises produce a new, open, participatory, inclusive and shared learning model: This model will be supported by appropriate methods, techniques and tools, based on the data and their complex management. We define SMART the environments that underlie these methods of learning
A SMART environment is therefore an "open ecosystem", where processes and systems, interacting with the user in a natural way, give rise to the possibility of collaborative, continuous and contextual learning, with respect to various life situations.
Let's talk about living lab just to refer to the possibility that each context has to become a learning lab, in which the figure of the teacher becomes that of a coach.
A SMART environment is also a cognitive environment, where the new way in which we access resources and big data and we interact with people through applications, devices, and network, uses and maximizes disruptive technologies such as just (i) mobile (ii) social, (iii) cloud (iv) and the internet of things.
A learning environment can be considered SMART when it makes use of adaptive technologies and when it is designed to improve understanding opportunities and the learning performance of a subject in situation. Therefore, the institutions have undertaken efforts to take advantage of the data through detailed analysis to be used in order to improve, customize and adapt paths and devices (analytics).
A SMART environment can also be used to manage the acquisition of student’s "experience" through the student’s life cycle, following him from the stage of recruiting until his graduation, including his employment, and then following him during his work, when he may be useful to his institution of origin as an influencer.
A SMART environment presents features capable of supporting effective cooperation of the user, his emotional and affective involvement, in order to stimulate an easier access to the network data made public by peers (open data) and institutions (open government data) that allow an augmented vision of resources.
According to the IASLE (International Association of Smart Learning Environment), “Smart learning environments are neither pure technology-based systems nor a particular pedagogical approach. They encompass various contexts, in which students (and perhaps teachers) move from one context to another”. La “smartness” dimension of an environment is provided by “conversational support for learners, teachers and designers, dynamic updating of student profiles, resources and databases, and automatic [re-]configuration of interfaces to adjust to different learners and learning situations”.
The idea is to draw the attention of researchers and practitioners, both in terms of methodologies, techniques and tools for a smarter learning, both in terms of educational and social relationships, where people participation help to support the co-design and co-creation of innovative things (such as learning resources).
If the source of innovation is the collective intelligence, crowdsourcing will serve as an engine for innovation in mass. This is mass customization which may also involve learning resources. The problems related to the optimization of processes and to support learning in a personalized, seamless and cooperative manner are also of interest.
Recently, semi-automatic solutions to personalize learning begin to appear. They are characterized by classes of cognitive services for education. These classes of services will allow teachers, students and computers to interact in order to obtain problems understanding and learning personalization of. These are innovative solutions whose trial is due to new models and applied teaching strategies.
The merging of pedagogy and technology for the development of smart environment will result in the transformation of curricula, the redefinition of educational settings, creating new frameworks for testing and validation from the point of view of cultural and educational effectiveness.
The submitted papers focus preferably, but not exclusively, on the following topics:
- Architectures for smart learning environments
- Models of excellence in smart learning environments
- Smart Education and Cognitive computing
- Collaborative Learning in Smart Environments
- Smart Environments, sensing and disruptive technologies
- Eclipse Open Source ecosystem and smart learning
- Smart environments models for evaluation and validation
- Historical and pedagogical Perspective on Smart Learning Environments
- Mobile app for smarter learning
- Technologies and tools as teaching support in Smart Environments
- Game-based education with ubiquitous and smart learning
- Adaptive learning environments, smart and ubiquitous learning
All submitted papers will be subject to a selection mechanism based on a double blind review.
Language: all contributions/papers must be written in English
Author Guidelines: http://www.je-lks.org/ojs/index.php/Je-LKS_EN/about/submissions
The Journal of e-Learning and Knowledge Society (Je-LKS) (eISSN 1971-8829) is published by the Italian Society of e-Learning since 2005 and in 2013 is publishing its ninth volume, consisting of three numbers (their output is four months). Je-LKS is indexed, among other things, on AACE-EdITLib, Scopus, Elsevier, DOAJ, IET Inspec, CiteFactor and in 2013 reached a h-index of 13 compared to Google Scholar database.