Mauro Coccoli

University of Genova, DIBRIS Department of Informatics, Bioengineering, Robotics, and Systems Engineering, Faculty Member

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Smart e-Learning Systems with Big Data

International Journal of Electronics and Telecommunications

Nowadays, the Internet connects people, multimedia and physical objects leading to a new-wave of ... more Nowadays, the Internet connects people, multimedia and physical objects leading to a new-wave of services. This includes learning applications, which require to manage huge and mixed volumes of information coming from Web and social media, smart-cities and Internet of Things nodes. Unfortunately, designing smart e-learning systems able to take advantage of such a complex technological space raises different challenges. In this perspective, this paper introduces a reference architecture for the development of future and big-data-capable e-learning platforms. Also, it showcases how data can be used to enrich the learning process.

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Esercizio di Knowledge society: insegnare e imparare nell’ambiente di apprendimento EifFE-L

DIDAMATICA 2006, 2006

Analisi e progettazione di un ambiente user-friendly per la realizzazione di oggetti didattici fruibili in rete

IV Congresso della Società Italiana di eLearning, 2007

Smart Learning in Smart Cities

DOAJ (DOAJ: Directory of Open Access Journals), May 1, 2020

Commonly, the term smart learning is connected to the use of smart learning environments, with re... more Commonly, the term smart learning is connected to the use of smart learning environments, with reference to the combination of software and hardware used for education and training by universities, schools, institutions and industries. In this field of application, in recent years, we have observed a never-ending succession of innovations in support of learning and instruction where instructional designers and developers run-after every new technology, to create innovative applications based on what they believe more effective, efficient, and engaging for both learners and teachers (Spector, 2014). Then, such software environments can be more or less smart, depending on the number and the quality of services offered and the capability of interacting with other systems. Another possible interpretation is to consider smart learning as learning in smart environments and, in this respect, Koper (2014) defines smart learning environments as physical places enriched with digital, context-aware and adaptive devices, which promote better and faster learning. For what concerns smart cities, we observe that they should be considered the most advanced implementations of smart environments, since they are plenty of physical devices and systems, used to provide citizens with highly effective services, to the aim of improving their quality of life. In fact, cities are smart when they fully exploit newly available smart technologies and smart solutions, which rely on most recent advancements in, e.g., big data, analytics, cloud architectures, artificial intelligence and cognitive computing. Moreover, recent modifications in both laws and policy, also driven by economics and market trends, are dramatically changing learning processes and environments in the universities so that students are regarded as customers and, consequently, the objective is enhancing their satisfaction, which can be achieved by improving the overall quality of services. Since the main task of schools and universities is education, we observe that their role in forming smart citizens, also contributing to enhance the individuals' quality of life, is of paramount importance. In conclusion, smart learning environments and smart cities adopt the same set of technologies and pursue the same objective of empowering people, thus, a new powerful educational ecosystem has to be considered, where learning involves students and teachers, which are primarily citizens.

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On Social Network Engineering for Secure Web Data and Services

IGI Global eBooks, Apr 1, 2013

Looking Beyond E-Learning: The Impact of Cognitive Computing

ICERI proceedings, Nov 1, 2018

In the past years, a continuous innovation process characterized the field of Technology-Enhanced... more In the past years, a continuous innovation process characterized the field of Technology-Enhanced Learning (TEL), to the aim of implementing any newly emerged technology inside the different facets of teaching and learning tasks. Currently, something different is happening, mainly related to the so- called exponential learning, due to the exponential growth of training demand. In fact, new knowledge and skills must be delivered at a speed never seen before, pushed by, e.g., Industry 4.0 and other European Community programs, as well as by the new wave of cognitive computing technology (i.e., cognitive managers, cognitive architecture engineers, cognitive system programming, etc.). The authors believe that this paradigm must be extended, causing the shift from classrooms to communities where we can speak of men and machines, rather than men or machines, thus enhancing humans\u2019 faculties and assisting them in the transformation of skills. Such a revolutionary approach requires that the next generation of TEL platforms include a variety of novel cognitive services to enable storing and using big data. To achieve such results, we will be forced to respect two fundamental constraints: time and content, with contents that will have to be ready within the time learners will need them. Besides, the services will be profiled for different users\u2019 levels, such as learning professional and learning business consumer. Also interfaces will be completely different from those we are used today, because we will be able to talk with machines, whose answers will result from a very quick and effective natural language processing and decision-making methods. We are on a turning point of training processes, a very challenging and important moment in which the cognitive approach will lead to a transformation, and e-learning and platforms are not excluded. The paper presents the general vision of authors about this new scenario and some preliminary applications to a virtual community platform where a big data-enabled architecture and some prototypes of cognitive services are under experimentation

Smart Learning Communities for Bridging the Gender Gap in STEM

2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI), Sep 6, 2021

This paper presents the results achieved in four years of activity within the NERD? project, whic... more This paper presents the results achieved in four years of activity within the NERD? project, which was created by IBM Italy and La Sapienza University of Rome and is carried on in collaboration with several universities and schools, in Italy. The long-term objective of the project is bridging the gender gap in the so-called STEM disciplines (science, technology, engineering and mathematics) starting from the secondary education. Specifically, we refer to the experience conducted in the field of informatics and computer engineering by the Federico II University of Naples, which empowered the original educational model of the NERD? project, introducing collaboration issues within a smart learning community. This involved people from industry, university and secondary schools, including both teachers and students at all the levels.

Computer Supported Collaborative Learning in software engineering

Computer Supported Collaborative Learning in Software Engineering (ETC - Enforcing Team Cooperation)

Video augmentation to support video-based learning

Proceedings of the 2022 International Conference on Advanced Visual Interfaces

Social Network Engineering for Secure Web Data and Services

User experience evaluation of Edurell interface for video augmentation

Multimedia Tools and Applications

This paper deals with the use of videos in education and describes an approach to improve the lea... more This paper deals with the use of videos in education and describes an approach to improve the learners’ experience in the first-watch and rewatch learning contexts. Actually, learning through videos raises challenging issues like non-linear navigation and poor structure of the video content. Hence, a novel application is presented, designed to address such issues. To this aim, the proposed Edurell environment enriches standard video lessons with new services based on the contents’ structure of the video, resulting in a new hypervideo educational application. The system extracts the concepts explained in a given video lesson, their prerequisite relations, and the segments of the video where they occur, together with other pieces of knowledge. The resulting knowledge graph allows creating augmented video lessons and enables learners to perform non-linear navigation and in-depth exploration of their learning contents. This idea was implemented in a custom web-based video player with in...

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EifFE-L: e-learning experiences with the platform of the University of Genoa

SIE-L 2005, 2005

Modeling and control of new elements of the AMADEUS gripper designed for fast manipulative tasks

by Vincenzo Arrichiello and Mauro Coccoli

IEEE Oceanic Engineering Society. OCEANS'98. Conference Proceedings (Cat. No.98CH36259)

The paper presents the definition of the characteristics of a new manipulator based on the elepha... more The paper presents the definition of the characteristics of a new manipulator based on the elephant trunk principle but with a special kind of large bandwidth actuators working with oil at low pressure, controlled by the sliding modes technique and with a new simplex-based approach for tracking trajectories. This work represents a point of convergence of two complementary activities. The

1997 Index IEEE Robotics And Automation Magazine Vol. 4

IEEE Robotics & Automation Magazine, 1997

Using Visual Feedbacks in an Augmented Video-based Learning Tool

International Conferences on Distributed Multimedia Systems

Advanced Visual Interfaces for Augmented Video

Proceedings of the 2022 International Conference on Advanced Visual Interfaces

Peer Reviewed Papers Big Data, Cognitive Computing and Innovative Teaching Models Cognitive Computing in Education

Cognitive computing is the new wave of Artificial Intelligence (AI), relying on traditional techn... more Cognitive computing is the new wave of Artificial Intelligence (AI), relying on traditional techniques based on expert systems and also exploiting statistics and mathematical models. In particular, cognitive computing systems can be regarded as a &quot; more human &quot; artificial intelligence. In fact, they mimic human reasoning methodologies, showing special capabilities in dealing with uncertainties and in solving problems that typically entail computation consuming processes. Moreover, they can evolve, exploiting the accumulated experience to learn from the past, both from errors and from successful findings. From a theoretical point of view, cognitive computing could replace existing calculators in many fields of application but hardware requirements are still high, even if the cloud infrastructure, which is expected to uphold its rapid growth in the very next future, can support their diffusion and ease the penetration of such a novel variety of systems, fostering new services as well as changes in many settled paradigms. In this paper, we focus on

Big Data, Cognitive Computing, and the Future of Learning Management Systems

Applied Degree Education and the Future of Work, 2020

Both technology and society are living a continuous evolution process, driving innovation and the... more Both technology and society are living a continuous evolution process, driving innovation and the development of novel solutions in almost any field of application. Making reference to the specific scenario of Technology Enhanced Learning (TEL), we observe significant steps ahead in techniques and methodology and, consequently, technological solutions undergo a continuous upgrade to cope with these, to the aim of improving the quality of services, the usability, the overall performances, the effectiveness of education, and to provide a more pervasive experience for learners. Accordingly, e-learning environments and the related tools have been growing in complexity.

Cognitive Computing in Education

Journal of e-learning and knowledge society, 2016

Cognitive computing is the new wave of Artificial Intelligence (AI), relying on traditional techn... more Cognitive computing is the new wave of Artificial Intelligence (AI), relying on traditional techniques based on expert systems and also exploiting statistics and mathematical model. In particular, cognitive computing systems can be regarded as a "more human" artificial intelligence. In fact, they mimic human reasoning methodologies, showing special capabilities in dealing with uncertainties and in solving problems that typically entail computation consuming processes. Moreover, they can evolve, exploiting the accumulated experience to learn from the past, both from errors and from successful findings. From a theoretical point of view, cognitive computing could replace existing calculators in many fields of application but hardware requirements are still high, even if the cloud infrastructure, which is expected to uphold its rapid growth in the very next future, can support their diffusion and ease the penetration of such a novel variety of systems, fostering new services a...

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