161,637 research outputs found
Service Learning Models Connecting Computer Science to the Community
Service learning is an educational experience that enables students to apply material learned in the classroom by volunteering in a real-world situation. This paper provides a brief review of service learning and describes two models that the computer science department at Saint Anselm College implemented successfully
Research and Development Workstation Environment: the new class of Current Research Information Systems
Against the backdrop of the development of modern technologies in the field
of scientific research the new class of Current Research Information Systems
(CRIS) and related intelligent information technologies has arisen. It was
called - Research and Development Workstation Environment (RDWE) - the
comprehensive problem-oriented information systems for scientific research and
development lifecycle support. The given paper describes design and development
fundamentals of the RDWE class systems. The RDWE class system's generalized
information model is represented in the article as a three-tuple composite web
service that include: a set of atomic web services, each of them can be
designed and developed as a microservice or a desktop application, that allows
them to be used as an independent software separately; a set of functions, the
functional filling-up of the Research and Development Workstation Environment;
a subset of atomic web services that are required to implement function of
composite web service. In accordance with the fundamental information model of
the RDWE class the system for supporting research in the field of ontology
engineering - the automated building of applied ontology in an arbitrary domain
area, scientific and technical creativity - the automated preparation of
application documents for patenting inventions in Ukraine was developed. It was
called - Personal Research Information System. A distinctive feature of such
systems is the possibility of their problematic orientation to various types of
scientific activities by combining on a variety of functional services and
adding new ones within the cloud integrated environment. The main results of
our work are focused on enhancing the effectiveness of the scientist's research
and development lifecycle in the arbitrary domain area.Comment: In English, 13 pages, 1 figure, 1 table, added references in Russian.
Published. Prepared for special issue (UkrPROG 2018 conference) of the
scientific journal "Problems of programming" (Founder: National Academy of
Sciences of Ukraine, Institute of Software Systems of NAS Ukraine
Connecting Levels of Analysis in Educational Neuroscience: A Review of Multi-level Structure of Educational Neuroscience with Concrete Examples
In its origins educational neuroscience has started as an endeavor to discuss implications of neuroscience studies for education. However, it is now on its way to become a transdisciplinary field, incorporating findings, theoretical frameworks and methodologies from education, and cognitive and brain sciences. Given the differences and diversity in the originating disciplines, it has been a challenge for educational neuroscience to integrate both theoretical and methodological perspective in education and neuroscience in a coherent way. We present a multi-level framework for educational neuroscience, which argues for integration of multiple levels of analysis, some originating in brain and cognitive sciences, others in education, as a roadmap for the future of educational neuroscience with concrete examples in moral education
Link Prediction in Complex Networks: A Survey
Link prediction in complex networks has attracted increasing attention from
both physical and computer science communities. The algorithms can be used to
extract missing information, identify spurious interactions, evaluate network
evolving mechanisms, and so on. This article summaries recent progress about
link prediction algorithms, emphasizing on the contributions from physical
perspectives and approaches, such as the random-walk-based methods and the
maximum likelihood methods. We also introduce three typical applications:
reconstruction of networks, evaluation of network evolving mechanism and
classification of partially labelled networks. Finally, we introduce some
applications and outline future challenges of link prediction algorithms.Comment: 44 pages, 5 figure
Civic Identities, Online Technologies: From Designing Civics Curriculum to Supporting Civic Experiences
Part of the Volume on Civic Life Online: Learning How Digital Media Can Engage Youth.Youth today are often criticized for their lack of civic participation and involvement in political life. Technology has been blamed, amongst many other causes, for fostering social isolation and youth's retreat into a private world disconnected from their communities. However, current research is beginning to indicate that these might be inaccurate perceptions. The Internet has provided new opportunities to create communities that extend beyond geographic boundaries, to engage in civic and volunteering activities across local and national frontiers, to learn about political life, and to experience the challenges of democratic participation. How do we leverage youth's interest in new technologies by developing technology-based educational programs to promote civic engagement? This chapter explores this question by proposing socio-technical design elements to be considered when developing technology-rich experiences. It presents a typology to guide the design of Internet-based interventions, taking into account both the affordances of the technology and the educational approach to the use of the technology. It also presents a pilot experience in a northeastern university that offered a pre-orientation program in which incoming freshman designed a three-dimensional virtual campus of the future and developed new policies and programs to strengthen the relationship between college campus and neighbor communities
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
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