Poell, R.F.; Moorsel, M.A.A.H. van
This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of learning groups in organisations. Four theoretical types of learning projects are distinguished. Four different approaches to the learning climate of work groups are compared to the approach offered by t...
Poell, R.F.; Moorsel, M.A.A.H. van
This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of
Sloep, Peter; Berlanga, Adriana
Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05
Spoelstra, Howard; Van Rosmalen, Peter; Van de Vrie, Evert; Obreza, Matija; Sloep, Peter
The Internet affords new approaches to learning. Geographically dispersed self-directed learners can learn in computer-supported communities, forming social learning networks. However, self-directed learners can suffer from a lack of continuous motivation. And surprisingly, social learning networks
Spoelstra, Howard; Van Rosmalen, Peter; Sloep, Peter
Spoelstra, H., Van Rosmalen, P., & Sloep, P. B. (2012). Project team formation support for self-directed learners in social learning networks. In P. Kommers, P. Isaias, & N. Bessis (Eds.), Proceedings of the IADIS International Conference on Web Based Communities and Social Media (ICWBC & SM 2012)
Back, D A; Haberstroh, N; Hoff, E; Plener, J; Haas, N P; Perka, C; Schmidmaier, G
Modern internet-based information technologies offer great possibilities to create and improve teaching methods for students. The eLearning tool NESTOR (Network for Students in Traumatology and Orthopedics) presented here was designed to complement the existing clinical teaching in orthopedics and traumatology at the Charité, University Medicine Berlin. Using a learning management system, videos, podcasts, X-ray diagnosis, virtual patients, tests and further tools for learning and study information were combined. After implementation the eLearning project was evaluated by students. The NESTOR project offers various possibilities for knowledge acquisition. Students using the program voluntarily showed a high acceptance whereby 82.4% were very satisfied with the contents offered and 95.3% supported the idea of a future use of NESTOR in teaching. The blended learning approach was positively evaluated by 93.5% of the students. The project received the eLearning seal of quality of the Charité University Medicine Berlin. Using complex eLearning tools, such as the NESTOR project represents a contemporary teaching approach in the teaching of traumatology and orthopedics and should be offered in a blended learning context as they are well accepted by students.
Full Text Available This paper sets out to explore the paradigm shift in learning culture brought about by the advent of online learning in the mostly print-based ODL system at the Mauritius College of the Air (MCA. It delves into the perceptions of learners and MCA staff involved in a range of undergraduate to Master’s programmes forming part of the Pan African e- Network Project that wires 23 African countries with top-ranking Indian universities through synchronous and interactive state of the art technology. Learners across five of the disciplines offered through tele-learning and a team of MCA staff participating in programme delivery were surveyed through questionnaires and interviews to collect both quantitative and qualitative data. For most of the respondents this new learning ethos has induced an acculturation process requiring radical reconceptualisation of prior notions about teaching/learning. MCA staff, too, have had to learn conducive behavior patterns to consolidate existing support services. Survival in this new learning environment where the tutor is a remote on-screen entity, where e-books replace printed material, where connectivity can be a daily struggle, demands another mindset, another set of values enabling learning and fine-tuned ICT skills. Socialisation with tutors and fellow learners is possible through links in Facebook and Twitter. However, learners still tend to feel somewhat isolated. It is proposed that an e-platform be set up to link up learners as a mutually supportive learning community engaged in the construction of knowledge.
The NSF-funded Navajo Learning Network project, with help from NASA Life Sciences and AFOSR, enabled Dine College to take a giant leap forward technologically - in a way that could never had been possible had these projects been managed separately. The combination of these and other efforts created a network of over 500 computers located at ten sites across the Navajo reservation. Additionally, the college was able to install a modern telephone system which shares network data, and purchase a new higher education management system. The NASA Life Sciences funds further allowed the college library system to go online and become available to the entire campus community. NSF, NASA and AFOSR are committed to improving minority access to higher education opportunities and promoting faculty development and undergraduate research through infrastructure support and development. This project has begun to address critical inequalities in access to science, mathematics, engineering and technology for Navajo students and educators. As a result, Navajo K-12 education has been bolstered and Dine College will therefore better prepare students to transfer successfully to four-year institutions. Due to the integration of the NSF and NASA/AFOSR components of the project, a unified project report is appropriate.
Moeller, Mary R.; Nagy, Dianne
This article details the evolution and results of a service-learning project designed to extend cross-cultural relationships via online social networking between students at a U.S. Bureau of Indian Education boarding school and teacher candidates in a required diversity course. The goals for the partnership included helping Native American…
Andreasen, Lars Birch; Lerche Nielsen, Jørgen
This paper focuses on how learner engagement can be facilitated through use of social media and communication technologies. The discussions are based on the Danish Master’s Programme of ICT and Learning (MIL), where students study in groups within a networked learning structure. The paper reflect...
Presentation in a seminar organized by Christopher Hoadley at Penn State University, October 2004.Contains general introduction into the Learning Network Programme and a demonstration of the Netlogo Simulation of a Learning Network.
Sloep, P. B. (2013). Networked professional learning. In A. Littlejohn, & A. Margaryan (Eds.), Technology-enhanced Professional Learning: Processes, Practices and Tools (pp. 97–108). London: Routledge.
Application data flow .............................................................................2 Fig. 2 Sample JSON data...interface supporting improved network analysis and network communication visualization. 2. Application Design NVP consists of 2 parts: back-end data...notation ( JSON ) format. This JSON is provided as input to the front-end application of the project. This interaction of the user with the back-end
Hoette, Vivian L.; Puckett, Andrew W.; Linder, Tyler R.; Heatherly, Sue Ann; Rector, Travis A.; Haislip, Joshua B.; Meredith, Kate; Caughey, Austin L.; Brown, Johnny E.; McCarty, Cameron B.; Whitmore, Kevin T.
Skynet is a worldwide robotic telescope network operated by the University of North Carolina at Chapel Hill with active observing sites on 3 continents. The queue-based observation request system is simple enough to be used by middle school students, but powerful enough to supply data for research scientists. The Skynet Junior Scholars program, funded by the NSF, has teamed up with professional astronomers to engage students from middle school to undergraduates in authentic research projects, from target selection through image analysis and publication of results. Asteroid research is a particularly fruitful area for youth collaboration that reinforces STEM education standards and can allow students to make real contributions to scientific knowledge, e.g., orbit refinement through astrometric submissions to the Minor Planet Center. We have created a set of projects for youth to: 1. Image an asteroid, make a movie, and post it to a gallery; 2. Measure the asteroid’s apparent motion using the Afterglow online image processor; and 3. Image asteroids from two or more telescopes simultaneously to demonstrate parallax. The apparent motion and parallax projects allow students to estimate the distance to their asteroid, as if they were the discoverer of a brand new object in the solar system. Older students may take on advanced projects, such as analyzing uncertainties in asteroid orbital parameters; studying impact probabilities of known objects; observing time-sensitive targets such as Near Earth Asteroids; and even discovering brand new objects in the solar system.Images are acquired from among seven Skynet telescopes in North Carolina, California, Wisconsin, Canada, Australia, and Chile, as well as collaborating observatories such as WestRock in Columbus, Georgia; Stone Edge in El Verano, California; and Astronomical Research Institute in Westfield, Illinois.
Martens, Harrie; Vogten, Hubert; Koper, Rob; Tattersall, Colin; Van Rosmalen, Peter; Sloep, Peter; Van Bruggen, Jan; Spoelstra, Howard
Learning Networks Distributed Environment is a prototype of an architecture that allows the sharing and modification of learning materials through a number of transport protocols. The prototype implements a p2p protcol using JXTA.
Full Text Available How can other languages be used in conjunction with English to further intercultural and multilingual learning when teachers and students participate in computer-based global learning networks? Two portraits are presented of multilingual activities in the Orillas and I*EARN learning networks, and are discussed as examples of the principal modalities of communication employed in networking projects between distant classes. Next, an important historical precedent --the social controversy which accompanied the introduction of telephone technology at the end of the last century-- is examined in terms of its implications for language choice in contemporary classroom telecomputing projects. Finally, recommendations are offered to guide decision making concerning the role of language choice in promoting collaborative critical inquiry.
Bøttcher, Susanne Gammelgaard
This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....
Hodgson, V.; McConnell, D.
Discusses the theory, nature, and benefits of cooperative learning. Considers the Cooperative Learning and Development Network (CLDN) trial in the JITOL (Just in Time Open Learning) project and examines the relationship between theories about cooperative learning and the reality of a group of professionals participating in a virtual cooperative…
Duong, T. A.; Stubberud, A. R.; Daud, T.; Thakoor, A. P.
A new neural network architecture and a hardware implementable learning algorithm is proposed. The algorithm, called cascade error projection (CEP), handles lack of precision and circuit noise better than existing algorithms.
Spoelstra, Howard; Van Rosmalen, Peter; Sloep, Peter
Open Learning Environments, MOOCs, as well as Social Learning Networks, embody a new approach to learning. Although both emphasise interactive participation, somewhat surprisingly, they do not readily support bond creating and motivating collaborative learning opportunities. Providing project-based
Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan
Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…
This book presents cutting-edge, peer reviewed research on networked learning organized by three themes: policy in networked learning, researching networked learning, and boundaries in networked learning. The "policy in networked learning" section explores networked learning in relation to policy...... networks, spaces of algorithmic governance and more. The "boundaries in networked learning" section investigates frameworks of students' digital literacy practices, among other important frameworks in digital learning. Lastly, the "research in networked learning" section delves into new research methods...
The paper is presenting the overall learning design of MIL (Master in ICT and Learning). The learning design is integrating a number of principles: 1. Principles of problem and project based learning 2. Networked learning / learning in communities of practice. The paper will discuss how these pri......The paper is presenting the overall learning design of MIL (Master in ICT and Learning). The learning design is integrating a number of principles: 1. Principles of problem and project based learning 2. Networked learning / learning in communities of practice. The paper will discuss how...
The original publication is available from www.springerlink.com. Sloep, P. (2009). Social Interaction in Learning Networks. In R. Koper (Ed.), Learning Network Services for Professional Development (pp 13-15). Berlin, Germany: Springer Verlag.
Full Text Available Purpose—the focus of this article is the role of social media in adult education and their impact on adult students in regards to their educational needs and specific personal situations within the frame of the learning partnership project. The Grundtvig learning partnership project “Institutional Strategies Targeting the Uptake of Social Networking in Adult Education (ISTUS is an international partnership that includes partners from 7 EU countries. The aim of the research presented in this paper is to define cases of the uptake of technologies and applications by MRU students; thus, the objectives of the research are 1 to review literature pertaining to the field of social media in adult education context and 2 to analyse the respondents’ insights as regards learning/teaching practices, resources, and facilities that affect their learning in relation to social networking and media use (taking into consideration both personal and educational perspectives. Design/methodology/approach—the research paper adopts qualitative research approach. Findings—students perceive SM mainly as online communication means (usually informal communication is implied. SM is firstly associated by learners with pastime venue, not educational resource. Thus, methods of teaching/learning in SM and with the help of SM have to be developed and improved. They have to be considered in line with the necessity to develop critical and reflexive thinking skills and media and information literacy skills. The respondents have pointed out both positive and negative aspects of social media use for learning/teaching. Creation of an inner institutional SM type involving qualified people with expertise in SM use for education has been suggested. Research limitations/implications—this article is focused only on the attitudes of MRU students though 105 interviews in total have been conducted within the framework of the project and not only students, but also teachers and
Full Text Available Purpose—the focus of this article is the role of social media in adult education and their impact on adult students in regards to their educational needs and specific personal situations within the frame of the learning partnership project. The Grundtvig learning partnership project “Institutional Strategies Targeting the Uptake of Social Networking in Adult Education (ISTUS is an international partnership that includes partners from 7 EU countries. The aim of the research presented in this paper is to define cases of the uptake of technologies and applications by MRU students; thus, the objectives of the research are 1 to review literature pertaining to the field of social media in adult education context and 2 to analyse the respondents’ insights as regards learning/teaching practices, resources, and facilities that affect their learning in relation to social networking and media use (taking into consideration both personal and educational perspectives.Design/methodology/approach—the research paper adopts qualitative research approach.Findings—students perceive SM mainly as online communication means (usually informal communication is implied. SM is firstly associated by learners with pastime venue, not educational resource. Thus, methods of teaching/learning in SM and with the help of SM have to be developed and improved. They have to be considered in line with the necessity to develop critical and reflexive thinking skills and media and information literacy skills. The respondents have pointed out both positive and negative aspects of social media use for learning/teaching. Creation of an inner institutional SM type involving qualified people with expertise in SM use for education has been suggested.Research limitations/implications—this article is focused only on the attitudes of MRU students though 105 interviews in total have been conducted within the framework of the project and not only students, but also teachers and
Brouns, Francis; Sloep, Peter
Brouns, F., & Sloep, P. B. (2009). Learning Networks for Professional Development & Lifelong Learning. Presentation of the Learning Network Programme for a Korean delegation of Chonnam National University and Dankook University (researchers dr. Jeeheon Ryu and dr. Minjeong Kim and a Group of PhD and
Caballero Jambrina, Antonio; Borkowski, Robert; de Miguel, Ignacio
. The incorporation of cognitive techniques can help to optimize a network by employing mechanisms that can observe, act, learn and improve network performance, taking into account end-to-end goals. The EU project CHRON: Cognitive Heterogeneous Reconfigurable Optical Network proposes a strategy to efficiently control...... the network by implementing cognition. In this paper we present a survey of different techniques developed throughout the course of the project to apply cognition in future optical networks....
Ponti, M.; Dirckinck-Holmfeld, Lone; Lindström, B.
are designed without a deep understanding of the pedagogical, communicative and collaborative conditions embedded in networked learning. Despite the existence of good theoretical views pointing to a social understanding of learning, rather than a traditional individualistic and information processing approach......The Kaleidoscope1 Jointly Executed Integrating Research Project (JEIRP) on Conditions for Productive Networked Learning Environments is developing and elaborating conceptual understandings of Computer Supported Collaborative Learning (CSCL) emphasizing the use of cross-cultural comparative......: Pedagogical design and the dialectics of the digital artefacts, the concept of collaboration, ethics/trust, identity and the role of scaffolding of networked learning environments. The JEIRP is motivated by the fact that many networked learning environments in various European educational settings...
Sloep, P. B. (2009). Learning Networks for Professional Development & Lifelong Learning. Presentation at a NeLLL seminar with Etienne Wenger held at the Open Universiteit Nederland. September, 10, 2009, Heerlen, The Netherlands.
Bettencourt, Luis; Kaiser, David
Based on an a historically documented example of scientific discovery - Feynman diagrams as the main calculational tool of theoretical high energy Physics - we map the time evolution of the social network of early adopters through in the US, UK, Japan and the USSR. The spread of the technique for total number of users in each region is then modelled in terms of epidemic models, highlighting parallel and divergent aspects of this analogy. We also show that transient social arrangements develop as the idea is introduced and learned, which later disappear as the technique becomes common knowledge. Such early transient is characterized by abnormally low connectivity distribution powers and by high clustering. This interesting early non-equilibrium stage of network evolution is captured by a new dynamical model for network evolution, which coincides in its long time limit with familiar preferential aggregation dynamics.
Schwalm, Jason; Tylek, Karen Smuck
Citywide implementation of project-based learning highlights the benefits--and the challenges--of promoting exemplary practices across an entire out-of-school time (OST) network. In summer 2009, the City of Philadelphia and its intermediary, the Public Health Management Corporation (PHMC), introduced project-based learning to a network of more…
Klitgaard, Anne; Nissen, Søren Bülow; Beck, Frederikke
This research is a preliminary study performed as part of a primary research into expansive learning in interorganizational network set up to solve a construction project. The construction industry has long had issues about productivity, which can be an indication of lack of learning. A case study...... acquisition and participation but not by expansive learning. The construction industry needs to accept that the learning generated from projects will be limited to learning by acquisition and participation. The interorganizational network cannot facilitate expansive learning while working on object......-fixed projects. Research in construction management fails to generate and document knowledge because of the limitations of case studies....
Bjerland, Øystein Førsund
This thesis explores the model of projective simulation (PS), a novel approach for an artificial intelligence (AI) agent. The model of PS learns by interacting with the environment it is situated in, and allows for simulating actions before real action is taken. The action selection is based on a random walk through the episodic & compositional memory (ECM), which is a network of clips that represent previous experienced percepts. The network takes percepts as inpu...
Duong, T. A.; Stubberud, A. R.; Daud, T.
A detailed mathematical analysis is presented for a new learning algorithm termed cascade error projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters.
Full Text Available Las redes de aprendizaje (Learning Networks son redes sociales en línea mediante las cuales los participantes comparten información y colaboran para crear conocimiento. De esta manera, estas redes enriquecen la experiencia de aprendizaje en cualquier contexto de aprendizaje, ya sea de educación formal (en escuelas o universidades o educación no-formal (formación profesional. Aunque el concepto de aprendizaje en red suscita el interés de diferentes actores del ámbito educativo, aún existen muchos interrogantes sobre cómo debe diseñarse el aprendizaje en red para facilitar adecuadamente la educación y la formación. El artículo toma este interrogante como punto de partida, y posteriormente aborda cuestiones como la dinámica de la evolución de las redes de aprendizaje, la importancia de fomentar la confianza entre los participantes y el papel central que desempeña el perfil de usuario en la construcción de la confianza, así como el apoyo entre compañeros. Además, se elabora el proceso de diseño de una red de aprendizaje, y se describe un ejemplo en el contexto universitario. Basándonos en la investigación que actualmente se lleva a cabo en nuestro propio centro y en otros lugares, el capítulo concluye con una visión del futuro de las redes de aprendizaje.Learning Networks are on-line social networks through which users share knowledge with each other and jointly develop new knowledge. This way, Learning Networks may enrich the experience of formal, school-based learning and form a viable setting for professional development. Although networked learning enjoys an increasing interest, many questions remain on how exactly learning in such networked contexts can contribute to successful education and training. Put differently, how should networked learning be designed best to facilitate education and training? Taking this as its point of departure, the chapter addresses such issues as the dynamic evolution of Learning Networks
Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...
Fiete, Ila Rani
How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and
Full Text Available The article explores the complementary connections between communities of practice and the ways in which individuals orchestrate their engagement with others to further their professional learning. It does so by reporting on part of a research project conducted in New Zealand on teachers’ online professional learning in a university graduate diploma program on ICT education. Evolving from social constructivist pedagogy for online professional development, the research describes how teachers create their own networks of practice as they blend online and offline interactions with fellow learners and workplace colleagues. Teachers’ perspectives of their professional learning activities challenge the way universities design formal online learning communities and highlight the potential for networked learning in the zones and intersections between professional practice and study.The article extends the concepts of Lave and Wenger’s (1991 communities of practice social theory of learning by considering the role participants play in determining their engagement and connections in and across boundaries between online learning communities and professional practice. It provides insights into the applicability of connectivist concepts for developing online pedagogies to promote socially networked learning and for emphasising the role of the learner in defining their learning pathways.
Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa
The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....
Vogten, Hubert; Martens, Harrie; Lemmers, Ruud
The TENCompetence project developed a first release of a Learning Network infrastructure to support individuals, groups and organisations in professional competence development. This infrastructure Learning Network infrastructure was released as open source to the community thereby allowing users and organisations to use and contribute to this development as they see fit. The infrastructure consists of client applications providing the user experience and server components that provide the services to these clients. These services implement the domain model (Koper 2006) by provisioning the entities of the domain model (see also Sect. 18.4) and henceforth will be referenced as domain entity services.
Geok See Ng
Full Text Available In this paper, entropy term is used in the learning phase of a neural network. As learning progresses, more hidden nodes get into saturation. The early creation of such hidden nodes may impair generalisation. Hence entropy approach is proposed to dampen the early creation of such nodes. The entropy learning also helps to increase the importance of relevant nodes while dampening the less important nodes. At the end of learning, the less important nodes can then be eliminated to reduce the memory requirements of the neural network.
Rhodes, Ed; Carter, Ruth
The Knowledge and Learning in Advanced Supply Systems (KLASS) project developed collaborative learning networks of suppliers in the British automotive and aerospace industries. Methods included face-to-face and distance learning, work toward National Vocational Qualifications, and diagnostic workshops for senior managers on improving quality,…
Peters, Linda D.; Pressey, Andrew D.; Johnston, Wesley J.
To increase understanding of the impact of individuals on organizational learning processes, this paper explores the impact of individual cognition and action on the absorptive capacity process of the wider network. In particular this study shows how contingent factors such as social integration mechanisms and power relationships influence how network members engage in, and benefit from, learning. The use of cognitive consistency and sensemaking theory enables examination of how these conting...
in describing the novel pedagogical potentials of these new technologies and practices (e.g. in debates around virtual learning environments versus personal learning environment). Likewise, I shall briefly discuss the notions of ‘digital natives’ or ‘the net generation’ from a critical perspective...... of social technologies. I argue that we are seeing the emergence of new architectures and scales of participation, collaboration and networking e.g. through interesting formations of learning networks at different levels of scale, for different purposes and often bridging boundaries such as formal...
Ewing Marion Kauffman Foundation, Kansas City, MO.
Project Choice began with a simple goal: to increase the number of inner-city students who graduate from high school on time and become productive members of society. To that end, Ewing M. Kauffman, his Foundation, and associates designed and implemented a program that promised postsecondary education or training to some students in the Kansas…
Learning Initiatives for Network Economies in Asia (LIRNEasia) : Building Capacity in ICT Policy ... LIRNEasia seeks to build capacity for evidence-based interventions in the public policy process by persons attuned to the ... Project status.
Fibiger, Bo; Nielsen, Janni; Sorensen, Elsebeth
to the modularity and flexibility that characterize the study and allow admission of part-time students, full-time students and students who only sign up for one accredited module. The methodology will be illustrated through empirical snapshots from selected modules in the start-up phase, and the focus...... will be directed towards problems experienced by the students. From an analytical perspective, the paper will identify and discuss fundamental problems related to the organization, flexibility, and implementation of project pedagogy online. MIL is organized around ICT and Learning and the study theme focuses...... on ICT and Learning. In addition, MIL provides a learning space where practice is under constant negotiation and reconstruction as an inherent, integrated part of the learning process. Consequently, we argue that MIL may be seen as an example of best practice in blended learning....
Hemmecke, R.; Lindner, S.; Studený, Milan
Roč. 53, č. 9 (2012), s. 1336-1349 ISSN 0888-613X R&D Projects: GA MŠk(CZ) 1M0572; GA ČR GA201/08/0539 Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * essential graph * standard imset * characteristic imset * LP relaxation of a polytope Subject RIV: BA - General Mathematics Impact factor: 1.729, year: 2012 http://library.utia.cas.cz/separaty/2012/MTR/studeny-0382596.pdf
Neruda, Roman; Kudová, Petra
Roč. 21, - (2005), s. 1131-1142 ISSN 0167-739X R&D Projects: GA ČR GP201/03/P163; GA ČR GA201/02/0428 Institutional research plan: CEZ:AV0Z10300504 Keywords : radial basis function networks * hybrid supervised learning * genetic algorithms * benchmarking Subject RIV: BA - General Mathematics Impact factor: 0.555, year: 2005
Sarker, M O Faruque
If you're a Python developer or a system administrator with Python experience and you're looking to take your first steps in network programming, then this book is for you. Basic knowledge of Python is assumed.
Tataru, Dragos; Ionescu, Constantin; Zaharia, Bogdan; Grecu, Bogdan; Tibu, Speranta; Popa, Mihaela; Borleanu, Felix; Toma, Dragos; Brisan, Nicoleta; Georgescu, Emil-Sever; Dobre, Daniela; Dragomir, Claudiu-Sorin
Romania is one of the most active seismic countries in Europe, with more than 500 earthquakes occurring every year. The seismic hazard of Romania is relatively high and thus understanding the earthquake phenomena and their effects at the earth surface represents an important step toward the education of population in earthquake affected regions of the country and aims to raise the awareness about the earthquake risk and possible mitigation actions. In this direction, the first national educational project in the field of seismology has recently started in Romania: the ROmanian EDUcational SEISmic NETwork (ROEDUSEIS-NET) project. It involves four partners: the National Institute for Earth Physics as coordinator, the National Institute for Research and Development in Construction, Urban Planning and Sustainable Spatial Development " URBAN - INCERC" Bucharest, the Babeş-Bolyai University (Faculty of Environmental Sciences and Engineering) and the software firm "BETA Software". The project has many educational, scientific and social goals. The main educational objectives are: training students and teachers in the analysis and interpretation of seismological data, preparing of several comprehensive educational materials, designing and testing didactic activities using informatics and web-oriented tools. The scientific objective is to introduce into schools the use of advanced instruments and experimental methods that are usually restricted to research laboratories, with the main product being the creation of an earthquake waveform archive. Thus a large amount of such data will be used by students and teachers for educational purposes. For the social objectives, the project represents an effective instrument for informing and creating an awareness of the seismic risk, for experimentation into the efficacy of scientific communication, and for an increase in the direct involvement of schools and the general public. A network of nine seismic stations with SEP seismometers
Jensen, Lars Peter; Helbo, Jan; Knudsen, Morten
Project organized problem based learning is a successful concept for on-campus engineering education at Aalborg University. Recently this "Aalborg concept" has been used in networked distance education as well. This paper describes the experiences from two years of Internet-mediated project work...... in a new Master of Information Technology education. The main conclusions are, that the project work is a strong learning motivator, enhancing peer collaboration, for off-campus students as well. However, the concept cannot be directly transferred to off-campus learning. In this paper, the main problems...... experienced with group organized project work in distance education are described, and some possible solutions are listed....
Jensen, Lars Peter; Helbo, Jan; Knudsen, Morten
Project organized problem based learning is a successful concept for on-campus engineering education at Aalborg University. Recently this "Aalborg concept" has been used in networked distance education as well. This paper describes the experiences from two years of Internet-mediated project work...... in a new Master of Information Technology education. The main conclusions are, that the project work is a strong learning motivator, enhancing peer collaboration, for off-campus students as well. However, the concept cannot be directly transferred to off-campus learning. In this paper, the main problems...... experienced with group organized project work in distance education are described, and some possible solutions are listed....
Eilks, Ingo; Byers, Bill
This paper summarizes the work and conclusions of a working group established by the European Chemistry Thematic Network (ECTN). The aim of the working group was to identify potential areas for innovative approaches to the teaching and learning of chemistry in Higher Education, and to survey good practice throughout the EU. The paper starts by…
Wilson, Mark; Gochyyev, Perman; Scalise, Kathleen
This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable…
Issa, Ghassan; Hussain, Shakir M.; Al-Bahadili, Hussein
In an effort to enhance the learning process in higher education, a new model for Competition-Based Learning (CBL) is presented. The new model utilizes two well-known learning models, namely, the Project-Based Learning (PBL) and competitions. The new model is also applied in a networked environment with emphasis on collective learning as well as…
Rivkin, Carl H. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Caton, Melanie C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Ainscough, Christopher D. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Marcinkoski, Jason [Dept. of Energy (DOE), Washington DC (United States)
The purpose of this report is to document lessons learned in the installation of the hydrogen fueling station at the National Park Service Brentwood site in Washington, D.C., to help further the deployment of hydrogen infrastructure required to support hydrogen and other fuel cell technologies. Hydrogen fueling is the most difficult infrastructure component to build and permit. Hydrogen fueling can include augmenting hydrogen fueling capability to existing conventional fuel fueling stations as well as building brand new hydrogen fueling stations. This report was produced as part of the Brentwood Lessons Learned project. The project consisted of transplanting an existing modular hydrogen fueling station from Connecticut to the National Park Service Brentwood site. This relocation required design and construction at the Brentwood site to accommodate the existing station design as well as installation and validation of the updated station. One of the most important lessons learned was that simply moving an existing modular station to an operating site was not necessarily straight-forward - performing the relocation required significant effort and cost. The station has to function at the selected operating site and this functionality requires a power supply, building supports connecting to an existing alarm system, electrical grounding and lighting, providing nitrogen for purging, and providing deionized water if an electrolyzer is part of the station package. Most importantly, the station has to fit into the existing site both spatially and operationally and not disrupt existing operations at the site. All of this coordination and integration requires logistical planning and project management. The idea that a hydrogen fueling station can be simply dropped onto a site and made immediately operational is generally not realistic. Other important lessons learned include that delineating the boundaries of the multiple jurisdictions that have authority over a project for
Czerkawski, Betül C.
With the emergence of social software and the advance of web-based technologies, online learning networks provide invaluable opportunities for learning, whether formal or informal. Unlike top-down, instructor-centered, and carefully planned formal learning settings, informal learning networks offer more bottom-up, student-centered participatory…
.... In this research project, we have investigated methods and implemented algorithms for efficiently making certain classes of inference in belief networks, and for automatically learning certain...
Bessant, John; Barnes, Justin; Morris, Mike; Kaplinsky, Raphael
Research suggests that there are a number of potential advantages to learning in some form of network which include being able to benefit from other’s experience, being able to reduce the risks in experimentation, being able to engage in challenging reflection and in making use of peer group support. Examples of such configurations can be found in regional clusters, in sector groupings, in heterogeneous groups sharing a common topic of interest, in user groups concerned with le...
Parraguez, Pedro; Maier, Anja
Complex engineering design projects need to manage simultaneously multiple information flows across design activities associated with different areas of the design process. Previous research on this area has mostly focused on either analysing the “required information flows” through activity...... networks at the project level or in studying the social networks that deliver the “actual information flow”. In this paper we propose and empirically test a model and method that integrates both social and activity networks into one compact representation, allowing to compare actual and required...... information flows between design spaces, and to assess the influence that these misalignments could have on the performance of engineering design projects....
Nielsen, Jørgen Lerche
Internationally, new pedagogical approaches emphasizing collaboration or learning in networks have been developed following the introduction of new technologies, especially the spread of social media. It is interesting to see such pedagogical developments in relation to similar approaches......, developed from the traditions of organizing university studies through student-driven project work and problem-driven learning approaches, which have been developed at the Danish universities of Roskilde and Aalborg as early as from the beginning of the 1970s. Specific educational designs integrating...... digital media are discussed, especially focusing on student engagement and the implications of organizing the pedagogical practice as networked project work. The discussions are based on the author’s experiences during 16 years of teaching and supervising at the Danish Master’s Program of ICT and Learning...
Ahmed R. Abas
Full Text Available In this paper, the adaptive competitive learning (ACL neural network algorithm is proposed. This neural network not only groups similar input feature vectors together but also determines the appropriate number of groups of these vectors. This algorithm uses a new proposed criterion referred to as the ACL criterion. This criterion evaluates different clustering structures produced by the ACL neural network for an input data set. Then, it selects the best clustering structure and the corresponding network architecture for this data set. The selected structure is composed of the minimum number of clusters that are compact and balanced in their sizes. The selected network architecture is efficient, in terms of its complexity, as it contains the minimum number of neurons. Synaptic weight vectors of these neurons represent well-separated, compact and balanced clusters in the input data set. The performance of the ACL algorithm is evaluated and compared with the performance of a recently proposed algorithm in the literature in clustering an input data set and determining its number of clusters. Results show that the ACL algorithm is more accurate and robust in both determining the number of clusters and allocating input feature vectors into these clusters than the other algorithm especially with data sets that are sparsely distributed.
Neruda, Roman; Vidnerová, Petra
Roč. 1, č. 2 (2009), s. 49-57 ISSN 2005-4262 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : neural network * RBF networks * regularization * learning Subject RIV: IN - Informatics, Computer Science http://www.sersc.org/journals/IJGDC/vol2_no1/5.pdf
Kosterman, S.; Gierasimczuk, N.; Armentano, M.G.; Monteserin, A.; Tang, J.; Yannibelli, V.
This paper argues that combining social networks communication and games can positively influence the learning behavior of players. We propose a computational model that combines features of social network learning (communication) and game-based learning (strategy reinforcement). The focus is on
Tu, Chih-Hsiung; Sujo-Montes, Laura; Yen, Cherng-Jyh; Chan, Junn-Yih; Blocher, Michael
Learning management systems traditionally provide structures to guide online learners to achieve their learning goals. Web 2.0 technology empowers learners to create, share, and organize their personal learning environments in open network environments; and allows learners to engage in social networking and collaborating activities. Advanced…
Larson, Erik; Drexler, John A., Jr.
This article describes a service-learning assignment for a project management course. It is designed to facilitate hands-on student learning of both the technical and the interpersonal aspects of project management, and it involves student engagement with real customers and real stakeholders in the creation of real events with real outcomes. As…
Liang, Faming; Zhang, Jian
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly
Gursakal, Necmi; Bozkurt, Aras
The rise of the networked society has not only changed our perceptions but also the definitions, roles, processes and dynamics of online learning networks. From offline to online worlds, networks are everywhere and gatekeepers are an important entity in these networks. In this context, the purpose of this paper is to explore gatekeeping and…
This work concentrates on two topics, networks and game theory, and learning in games. The first part of this thesis looks at network games and the role of incomplete information in such games. It is assumed that players are located on a network and interact with their neighbors in the network.
Zha, Hong; Zhang, Lianying
We investigate the project scheduling problem with multiskill learning effect. A new model is proposed to deal with the problem, where both autonomous and induced learning are considered. In order to obtain the optimal solution, a genetic algorithm with specific encoding and decoding schemes is introduced. A numerical example is used to illustrate the proposed model. The computational results show that the learning effect cannot be neglected in project scheduling. By means of determining the level of induced learning, the project manager can balance the project makespan with total cost.
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ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.
AFRIKAANSE OPSOMMING: Die navorsing beskryf ’n nuwerwetse metode vir die ontleding en bestuur van die sekwensiële aktiwiteite van projekte. Die voorgestelde metode bepaal kritiese aktiwiteite, die kritieke pad, aanvangstye, speling, verhasing, en ander groothede sonder die gebruik van ’n netwerkmodel. Die metode funksioneer bevredigend in die praktyk, en omseil die administratiewe rompslomp van die tradisionele netwerkmodelle.
Lerche Nielsen, Jørgen; Andreasen, Lars Birch
within a networked learning structure are studying in groups combining on-site seminars with independent and challenging virtually organized project periods, implementing new educational technology, which require teachers who are flexible and aware of the different challenges in the networked environment...... activities that unfold. This interplay is important in order to make a difference, as the experience is that new technologies do not in themselves guarantee increasing learning quality. The chapter will discuss examples of how learners as well as teachers have developed imaginative ways of implementing new...... technological possibilities in educational settings. The examples will include how sometimes seemingly simple technologies can be used in innovative pedagogical ways to increase learners’ involvement. Another example to be discussed in the chapter derives from an online seminar on ICT and Learning...
Bhattacharyya, Dhruba Kumar
With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents mach
Bohemia, Erik; Ghassan, Aysar
This article explores project-based cross-cultural and cross-institutional learning. Using Web 2.0 technologies, this project involved more than 240 students and eighteen academic staff from seven international universities. The focus of this article relates to a project-based learning activity named "The Gift". At each institution the…
We study the effect of learning dynamics on network topology. Firstly, a network of discrete dynamical systems is considered for this purpose and the coupling strengths are made to evolve according to a temporal learning rule that is based on the paradigm of spike-time-dependent plasticity (STDP). This incorporates ...
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned...
Eby, Gulsun; Yuzer, T. Volkan
Developments in online learning and its design are areas that continue to grow in order to enhance students' learning environments and experiences. However, in the implementation of new technologies, the importance of properly and fairly overseeing these courses is often undervalued. "Project Management Approaches for Online Learning Design"…
Heskes, Tom M.; Kappen, Bert
We present a learning-parameter adjustment algorithm, valid for a large class of learning rules in neural-network literature. The algorithm follows directly from a consideration of the statistics of the weights in the network. The characteristic behavior of the algorithm is calculated, both in a fixed and a changing environment. A simple example, Widrow-Hoff learning for statistical classification, serves as an illustration.
Weaver, Sallie J; Lofthus, Jennifer; Sawyer, Melinda; Greer, Lee; Opett, Kristin; Reynolds, Catherine; Wyskiel, Rhonda; Peditto, Stephanie; Pronovost, Peter J
Collaborative improvement networks draw on the science of collaborative organizational learning and communities of practice to facilitate peer-to-peer learning, coaching, and local adaption. Although significant improvements in patient safety and quality have been achieved through collaborative methods, insight regarding how collaborative networks are used by members is needed. Improvement Strategy: The Comprehensive Unit-based Safety Program (CUSP) Learning Network is a multi-institutional collaborative network that is designed to facilitate peer-to-peer learning and coaching specifically related to CUSP. Member organizations implement all or part of the CUSP methodology to improve organizational safety culture, patient safety, and care quality. Qualitative case studies developed by participating members examine the impact of network participation across three levels of analysis (unit, hospital, health system). In addition, results of a satisfaction survey designed to evaluate member experiences were collected to inform network development. Common themes across case studies suggest that members found value in collaborative learning and sharing strategies across organizational boundaries related to a specific improvement strategy. The CUSP Learning Network is an example of network-based collaborative learning in action. Although this learning network focuses on a particular improvement methodology-CUSP-there is clear potential for member-driven learning networks to grow around other methods or topic areas. Such collaborative learning networks may offer a way to develop an infrastructure for longer-term support of improvement efforts and to more quickly diffuse creative sustainment strategies.
Full Text Available New materials, use of sophisticated technologies and increased customer demands, in combination with growing competition among construction companies, have led to a high organizational boundaries. The results indicate that personal networks are the most common source of learning for all professions. While clients, architects, and designers also engage in reading and attending courses, site managers and workers are less engaged in these activities. Experimenting and organizing for learning appear to be underutilized strategies by all professions. This leads to the conclusion that attempts to increase learning have to address the differences in learning behaviours of the various groups. Further, focus on experimenting and organizing for learning is a possibility to change the learning behaviour from learning as a consequence of problems to learning for future improvement.degree of specialization. For successful integration of the different professional specialists, there is a need for shared learning between project co-workers. Based on twenty eight interviews in six different Swedish construction projects, this paper illustrates strategies for individual and shared learning, among different actors and across various
The AVN is one of the most significant vehicles through which capacity development in Africa for SKA participation will be realized. It is a forerunner to the long baseline Phase 2 component of the mid-frequency SKA. Besides the 26m HartRAO telescope in South Africa, Ghana is expected to be the first to establish a VLBI-capable telescope through conversion of a redundant 32m telecommunications system near Accra. The most widely used receivers in the EVN are L-band and C-band (5 GHz). L-band is divided into a low band around the hydrogen (HI) line frequency of 1420 MHz, and a high band covering the hydroxyl line frequencies of 1612-1720 MHz. The high band is much more commonly used for VLBI as it provides more bandwidth. For the AVN, the methanol maser line at 6668 MHz is a key target for the initial receiver and the related 12178MHz methanol maser line also seen in star-forming regions a potential future Ku-band receiver. In the potential future band around 22GHz(K-band), water masers in star-forming regions and meg-maser galaxies at 22.235 GHz are targets, as are other radio continuum sources such as AGNs. The AVN system will include 5GHz and 6.668GHz receiver systems with recommendation to partner countries that the first upgrade should be L-band receivers. The original satellite telecommunications feed horns cover 3.8 - 6.4 GHz and should work at 5 GHz and operation at 6.668 GHz for the methanol maser is yet to be verified. The first light science will be conducted in the 6.7 GHz methanol maser band. Telescopes developed for the AVN will initially join other global networks for VLBI. When at least four VLBI-capable telescopes are operational on the continent, it will be possible to initiate stand-alone AVN VLBI. Each country where an AVN telescope becomes operational will have its own single-dish observing program. Capacity building to run an observatory includes the establishment of competent core essential observatory staff in partner countries who can train
Danilo eJimenez Rezende
Full Text Available The ability to learn and perform statistical inference with biologically plausible recurrent network of spiking neurons is an important step towards understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators conveying information about ``novelty on a statistically rigorous ground.Simulations show that our model is able to learn bothstationary and non-stationary patterns of spike trains.We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.
Jimenez Rezende, Danilo; Gerstner, Wulfram
The ability to learn and perform statistical inference with biologically plausible recurrent networks of spiking neurons is an important step toward understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators) conveying information about "novelty" on a statistically rigorous ground. Simulations show that our model is able to learn both stationary and non-stationary patterns of spike trains. We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.
Arora, Sanjeev; Kalishman, Summers G; Thornton, Karla A; Komaromy, Miriam S; Katzman, Joanna G; Struminger, Bruce B; Rayburn, William F
A major challenge with current systems of CME is the inability to translate the explosive growth in health care knowledge into daily practice. Project ECHO (Extension for Community Healthcare Outcomes) is a telementoring network designed for continuing professional development (CPD) and improving patient outcomes. The purpose of this article was to describe how the model has complied with recommendations from several authoritative reports about redesigning and enhancing CPD. This model links primary care clinicians through a knowledge network with an interprofessional team of specialists from an academic medical center who provide telementoring and ongoing education enabling community clinicians to treat patients with a variety of complex conditions. Knowledge and skills are shared during weekly condition-specific videoconferences. The model exemplifies learning as described in the seven levels of CPD by Moore (participation, satisfaction, learning, competence, performance, patient, and community health). The model is also aligned with recommendations from four national reports intended to redesign knowledge transfer in improving health care. Efforts in learning sessions focus on information that is relevant to practice, focus on evidence, education methodology, tailoring of recommendations to individual needs and community resources, and interprofessionalism. Project ECHO serves as a telementoring network model of CPD that aligns with current best practice recommendations for CME. This transformative initiative has the potential to serve as a leading model for larger scale CPD, nationally and globally, to enhance access to care, improve quality, and reduce cost.
Dixit, Vijaya; Srivastava, Rajiv K; Chaudhuri, Atanu
This work devises a materials management policy integrated with project network characteristics of complex projects. It proposes a relative quantitative measure, overall criticality (OC), for prioritisation of items based on penalty incurred due to their non-availability. In complex projects...... managerial tacit knowledge which provides them enough flexibility to provide information in real form. Computed OC values can be used for items prioritisation and as shortage cost coefficient in inventory models. The revised materials management policy was applied to a shipbuilding project. OC values were......, practicing managers find it difficult to measure OC of items because of the subjective factors and intractable nature of penalties involved. However, using their experience, they can linguistically identify the antecedents and relate them to consequent OC. This work adopts Fuzzy Set Theory to capture...
Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng
Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.
Gilbert, Nigel; Ahrweiler, Petra; Pyka, Andreas
According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning.
Ritchie, Ewen; Leban, Krisztina Monika
This paper presents the didactic problem based learning method in general use at Aalborg University as applied to Electric Mobility. Advantage is taken of this method to link student learning to current research projects. This offers advantages to the students and the researchers. The paper...... introduces the subject, presents the research of the Department of Energy Technology and describes the relevant syllabus. It continues to present a range of titles of previous research linked student project projects, and to fill in some of the detail, an example of such a student project. The paper...
Full Text Available The driver for this paper is the need to better understand the potential for learning and innovation that networks canprovide especially for small and medium sized enterprises (SMEs which comprise by far the majority of enterprises in the food sector. With the challenges the food sector is facing in the near future, learning and innovation or more focused, as it is being discussed in the paper, ‘learning for innovation’ are not just opportunities but pre‐conditions for the sustainability of the sector. Network initiatives that could provide appropriate support involve social interaction and knowledge exchange, learning, competence development, and coordination (organization and management of implementation. The analysis identifies case studies in any of these orientations which serve different stages of the innovation process: invention and implementation. The variety of network case studies cover networks linked to a focus group for training, research, orconsulting, networks dealing with focused market oriented product or process development, promotional networks, and networks for open exchange and social networking.
In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarizes relevant work, much of it from the previous millennium. Shallow and Deep Learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Nielsen, Louise Møller
experiences and expertise to guide the students’ decisions in relation to the design project. This paper focuses on project supervision in the context of design education – and more specifically on how this supervision is unfolded in a Problem Based Learning culture. The paper explores the supervisor......’s balance between the roles: 1) Design Project Supervisor – and 2) Learning Facilitator – with the aim to understand when to apply the different roles, and what to be aware of when doing so. This paper represents the first pilot-study of a larger research effort. It is based on a Lego Serious Play workshop......In design there is a long tradition for apprenticeship, as well as tradition for learning through design projects. Today many design educations are positioned within the University context, and have to be aligned with the learning culture and structure, which they represent. This raises a specific...
Ceri, Stefano; Matera, Maristella; Raffio, Alessandro; Spoelstra, Howard
Ceri, S., Matera, M., Raffio, A. & Spoelstra, H. (2007). Flexible Processes in Project-Centred Learning. In E. Duval, R. Klamma, and M. Wolpers (Eds.), European Conference on Technology Enhanced Learning, Lecture Notes in Computer Science, Vol. 4753, pp. 463-468. Berlin Heidelberg: Springer-Verlag
Ariani, Y.; Helsa, Y.; Ahmad, S.; Prahmana, RCI
A developed instructional media can be as printed media, visual media, audio media, and multimedia. The development of instructional media can also take advantage of technological development by utilizing Edmodo social network. This research aims to develop a digital classroom learning model using Edmodo social learning network for elementary school mathematics learning which is practical, valid and effective in order to improve the quality of learning activities. The result of this research showed that the prototype of mathematics learning device for elementary school students using Edmodo was in good category. There were 72% of students passed the assessment as a result of Edmodo learning. Edmodo has become a promising way to engage students in a collaborative learning process.
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.
The article describes the development of a project-based approach to learning in seven Scottish prisons. It argues that the project-based approach is ideally suited to prison education due to its flexibility and ability to enrich the relatively narrow prison curriculum and create meaningful links with wider society, reducing the isolation of…
This article examines a study of seven learners who logged their experiences on the language leaning social networking site Livemocha over a period of three months. The features of the site are described and the likelihood of their future success is considered. The learners were introduced to the Social Networking Site (SNS) and asked to learn a…
Bayer, Péter; Herings, P. Jean-Jacques; Peeters, Ronald; Thuijsman, Frank
This paper studies adaptive learning in the class of weighted network games. This class of games includes applications like research and development within interlinked firms, crime within social networks, the economics of pollution, and defense expenditures within allied nations. We show that for
Biehl, Michael; Schwarze, Holm
The learning of time-dependent concepts with a neural network is studied analytically and numerically. The linearly separable target rule is represented by an N-vector, whose time dependence is modelled by a random or deterministic drift process. A single-layer network is trained online using
Brett, Valerie; Mullally, Martina; O'Gorman, Bill; Fuller-Love, Nerys
Developing sustainable learning networks for entrepreneurs is the core objective of the Sustainable Learning Networks in Ireland and Wales (SLNIW) project. One research team drawn from the Centre for Enterprise Development and Regional Economy at Waterford Institute of Technology and the School of Management and Business from Aberystwyth…
Icaza, José I.; Heredia, Yolanda; Borch, Ole M.
A pedagogical approach called “project oriented immersion learning” is presented and tested on a graduate online course. The approach combines the Project Oriented Learning method with immersion learning in a virtual enterprise. Students assumed the role of authors hired by a fictitious publishing...... house that develops digital products including e-books, tutorials, web sites and so on. The students defined the problem that their product was to solve; choose the type of product and the content; and built the product following a strict project methodology. A wiki server was used as a platform to hold...
Sathasivam, Saratha; Abdullah, Wan Ahmad Tajuddin Wan
Synaptic weights for neurons in logic programming can be calculated either by using Hebbian learning or by Wan Abdullah's method. In other words, Hebbian learning for governing events corresponding to some respective program clauses is equivalent with learning using Wan Abdullah's method for the same respective program clauses. In this paper we will evaluate experimentally the equivalence between these two types of learning through computer simulations.
Berlanga, Adriana; Sloep, Peter; Brouns, Francis; Van Rosmalen, Peter; Bitter-Rijpkema, Marlies; Koper, Rob
Berlanga, A. J., Sloep, P., Brouns, F., Van Rosmalen, P., Bitter-Rijpkema, M., & Koper, R. (2007). Functionality for learning networks: lessons learned from social web applications. Proceedings of the ePortfolio 2007 Conference. October, 18-19, 2007, Maastricht, The Netherlands. [See also
Docherty, P.; Huzzard, T.; Leede, J. de
This report is a comparative analysis of the various learning networks established within the Innoflex Project. The report recaps on the central argument underpinning Innoflex, namely that traditional ways of organising workplaces and traditional styles of management cannot achieve the commitment,
Baran, Medine; Maskan, Abdulkadir; Yasar, Seyma
The aim of the present study, in which Project and game techniques are used together, is to examine the impact of project-based learning games on students' physics achievement. Participants of the study consist of 34 9th grade students (N = 34). The data were collected using achievement tests and a questionnaire. Throughout the applications, the…
Mørup, Morten; Hansen, Lars Kai
such as the Modularity, it has recently been shown that latent structure in complex networks is learnable by Bayesian generative link distribution models (Airoldi et al., 2008, Hofman and Wiggins, 2008). In this paper we propose a new generative model that allows representation of latent community structure......Latent structure in complex networks, e.g., in the form of community structure, can help understand network dynamics, identify heterogeneities in network properties, and predict ‘missing’ links. While most community detection algorithms are based on optimizing heuristic clustering objectives...... as in the previous Bayesian approaches and in addition allows learning of node specific link properties similar to that in the modularity objective. We employ a new relaxation method for efficient inference in these generative models that allows us to learn the behavior of very large networks. We compare the link...
Zhang, Pengfei; Shen, Huitao; Zhai, Hui
In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.
Love, Bradley C; Medin, Douglas L; Gureckis, Todd M
SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.
Hartmann, Andreas; Dorée, André
Although learning from projects has gained much importance in research and practice, progress in understanding and improving inter-project learning appears to be slight. We argue that the adoption of a sender/receiver approach limits the learning effectiveness in project-based organisations. Drawing upon the notion of learning as a social activity embedded in an organisational context, we develop the argument that learning from projects takes place within projects rooted in the historical, or...
Giani, U; Martone, P
This paper is an attempt to develop a distance learning model grounded upon a strict integration of problem based learning (PBL), dynamic knowledge networks (DKN) and web tools, such as hypermedia documents, synchronous and asynchronous communication facilities, etc. The main objective is to develop a theory of distance learning based upon the idea that learning is a highly dynamic cognitive process aimed at connecting different concepts in a network of mutually supporting concepts. Moreover, this process is supposed to be the result of a social interaction that has to be facilitated by the web. The model was tested by creating a virtual classroom of medical and nursing students and activating a learning session on the concept of knowledge representation in health sciences.
Dolog, Peter; Simon, Bernd; Nejdl, Wolfgang
In this article, we describe a Smart Space for Learning™ (SS4L) framework and infrastructure that enables personalized access to distributed heterogeneous knowledge repositories. Helping a learner to choose an appropriate learning resource or activity is a key problem which we address in this fra......In this article, we describe a Smart Space for Learning™ (SS4L) framework and infrastructure that enables personalized access to distributed heterogeneous knowledge repositories. Helping a learner to choose an appropriate learning resource or activity is a key problem which we address...... in this framework, enabling personalized access to federated learning repositories with a vast number of learning offers. Our infrastructure includes personalization strategies both at the query and the query results level. Query rewriting is based on learning and language preferences; rule-based and ranking...
Abd ELhamid, A.; Ayad, N.M.A.; Fouad, Y.; Abdelkader, T.
Recently, Electronic Learning Technology (ELT) has been widely spread as one of the new technologies in the world through using Information and Communication Technology (ICT). One of the strategies of ELT is Simulation, for instance Military and Medical simulations that are used to avoid risks and reduce Costs. A wireless communication network refers to any network not physically connected by cables, which enables the desired convenience and mobility for the user. Wireless communication networks have been useful in areas such as commerce, education and defense. According to the nature of a particular application, they can be used in home-based and industrial systems or in commercial and military environments. Historically, Mobile Ad-hoc Networks (MANET) have primarily been used for tactical military network related applications to improve battlefield communications/ survivability. MANET is a collection of wireless nodes that can dynamically be set up anywhere and anytime without using any pre-existing network infrastructure. Mobility in wireless networks basically refers to nodes changing its point of attachment to the network. Also, how the end terminals can move, there are many mobility models described the movement of nodes, many researchers use the Random Way point Mobility Model (RWPM). In this paper, a Graphical User Interface (GUI) for RWPM simulation is introduced as a proposal to be used through ELT Project. In the research area of computer and communications networks, simulation is a very useful technique for the behavior of networks
Firdausiah Mansur, Andi Besse; Yusof, Norazah
Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…
Full Text Available The Educational Seismological Project (EduSeis is a scientific and educational project, the main aim of which is the development and implementation of new teaching methodologies in Earth Sciences, using seismology as a vehicle for scientific learning and awareness of earthquake risk. Within this framework, we have recently been experimenting with new learning and information approaches that are mainly aimed at a high school audience. In particular, we have designed, implemented and tested a model of an e-learning environment in a high school located in the surroundings of the Mt. Vesuvius volcano. The proposed e-learning model is built on the EduSeis concepts and educational materials (web-oriented, and is based on computer-supported collaborative learning. Ten teachers from different disciplines and fifty students at the I.T.I.S. Majorana technical high school (Naples have been taking part in a cooperative e-learning experiment in which the students have been working in small groups (communities. The learning process is assisted and supervised by the teachers. The evaluation of the results from this cooperative e-learning experiment has provided useful insights into the content and didactic value of the EduSeis modules and activities. The use of network utilities and the Learning Community approach promoted the exchange of ideas and expertises between students and teachers and allowed a new approach to the seismology teaching through a multidisciplinary study.
This is the Final Report for the Live From Space Station (LFSS) project under the Learning Technologies Project FY 2001 of the MSFC Education Programs Department. AZ Technology, Inc. (AZTek) has developed and implemented science education software tools to support tasks under the LTP program. Initial audience consisted of 26 TreK in the Classroom schools and thousands of museum visitors to the International Space Station: The Earth Tour exhibit sponsored by Discovery Place museum.
Zeng, Yifeng; Cordero Hernandez, Jorge
It is a challenging task of learning a large Bayesian network from a small data set. Most conventional structural learning approaches run into the computational as well as the statistical problems. We propose a decomposition algorithm for the structure construction without having to learn...... the complete network. The new learning algorithm firstly finds local components from the data, and then recover the complete network by joining the learned components. We show the empirical performance of the decomposition algorithm in several benchmark networks....
Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi
Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.
Ryberg, Thomas; Davidsen, Jacob; Hodgson, Vivien
There is a need within networked learning to understand and conceptualise the interplay between digital and physical spaces or what we could term hybrid spaces. Therefore, we discuss a recent study of students from two different programmes who are engaged in long-term, group-based problem...... and project based learning. Based on interviews, workshops and observations of students’ actual group practices in open, shared and flexible spaces in Aalborg University (AAU), we identify and discuss how students incorporate networked and digital technologies into their group work and into the study places...... they create for themselves. We describe how in one of the programmes ‘nomadic’ groups of students used different technologies and spaces for ‘placemaking’. We then show how their experience and approach to collaborative work differs to that of the more static or ‘artisan’ groups of students in the other...
predecessor, Gale and Kariv (2003) who generalize the payoff equalization result of Bala and Goyal (1998) in connected social networks (discussed below...requires more notation. Using Bayes’ Rule and the assumption of equal priors on the state θ, we have that the social belief given by observing... Social Networks: Rational Learning and Information Aggregation by Ilan Lobel B.Sc., Pontif́ıcia Universidade Católica do Rio de Janeiro (2004
Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.
Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...
Tammets, Kairit; Brouns, Francis
The EMMA project provides a MOOC platform to aggregate and delivers massive open online courses (MOOC) in multiple languages from a variety of European universities. Learning analytics play an important role in MOOCs to support the individual needs of the learner.
Cox, Dannon G.; Meaney, Karen S.
A physical education instructor incorporates a teaching method known as project-based learning (PBL) in his physical education curriculum. Utilizing video-production equipment to imitate the production of a televisions show, sixth-grade students attending a charter school invited college students to share their stories about physical activity and…
This article reports on the current status of client projects (CPs) in business communication courses, provides a scaffolded model for implementing CP, and assesses student learning in CPs. Using a longitudinal mixed method research design, survey data and qualitative materials from six semesters are presented. The instructor survey indicated need…
The NASA Lewis Research Center's Learning Technologies Project (LTP) has responded to requests from local school district technology coordinators to provide content for videoconferencing workshops. Over the past year we have offered three teacher professional development workshops that showcase NASA Lewis-developed educational products and NASA educational Internet sites. In order to determine the direction of our involvement with distance learning, the LTP staff conducted a survey of 500 U.S. schools. We received responses from 72 schools that either currently use distance learning or will be using distance learning in 98-99 school year. The results of the survey are summarized in the article. In addition, the article provides information on distance learners, distance learning technologies, and the NASA Lewis LTP videoconferencing workshops. The LTP staff will continue to offer teacher development workshops through videoconferencing during the 98-99 school year. We hope to add workshops on new educational products as they are developed at NASA Lewis.
Ozyildirim, Buse Melis; Avci, Mutlu
Generalized classifier neural network is introduced as an efficient classifier among the others. Unless the initial smoothing parameter value is close to the optimal one, generalized classifier neural network suffers from convergence problem and requires quite a long time to converge. In this work, to overcome this problem, a logarithmic learning approach is proposed. The proposed method uses logarithmic cost function instead of squared error. Minimization of this cost function reduces the number of iterations used for reaching the minima. The proposed method is tested on 15 different data sets and performance of logarithmic learning generalized classifier neural network is compared with that of standard one. Thanks to operation range of radial basis function included by generalized classifier neural network, proposed logarithmic approach and its derivative has continuous values. This makes it possible to adopt the advantage of logarithmic fast convergence by the proposed learning method. Due to fast convergence ability of logarithmic cost function, training time is maximally decreased to 99.2%. In addition to decrease in training time, classification performance may also be improved till 60%. According to the test results, while the proposed method provides a solution for time requirement problem of generalized classifier neural network, it may also improve the classification accuracy. The proposed method can be considered as an efficient way for reducing the time requirement problem of generalized classifier neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.
Full Text Available Distributed data collection and analysis over a network are ubiquitous, especially over a wireless sensor network (WSN. To our knowledge, the data model used in most of the distributed algorithms is linear. However, in real applications, the linearity of systems is not always guaranteed. In nonlinear cases, the single hidden layer feedforward neural network (SLFN with radial basis function (RBF hidden neurons has the ability to approximate any continuous functions and, thus, may be used as the nonlinear learning system. However, confined by the communication cost, using the distributed version of the conventional algorithms to train the neural network directly is usually prohibited. Fortunately, based on the theorems provided in the extreme learning machine (ELM literature, we only need to compute the output weights of the SLFN. Computing the output weights itself is a linear learning problem, although the input-output mapping of the overall SLFN is still nonlinear. Using the distributed algorithmto cooperatively compute the output weights of the SLFN, we obtain a distributed extreme learning machine (dELM for nonlinear learning in this paper. This dELM is applied to the regression problem and classification problem to demonstrate its effectiveness and advantages.
Full Text Available The Electronic Learning and Mobility Project (ELAMP was a nationally funded project by the Department for Children, Schools and Families, which ran from 2004 to 2010. The main aim of ELAMP was to improve the education of Traveller children, particularly highly mobile learners. ELAMP focussed upon the use of mobile technology and distance learning to support, enhance and extend young Travellers’ educational and vocational opportunities. This article will reflect upon the learning and technological experiences and opportunities that the ELAMP project provided for Traveller children, young people and their families. In doing so it will critically consider the value of information technology in working with Traveller communities and advancing their educational opportunities. Reviewing ELAMP work will also demonstrate how the use of mobile technology can improve educational outcomes and Traveller families’ digital inclusion. Now that the project has ended, this article will question why we are not using what we learnt from ELAMP to move forward. The author was a tutor on the project who also evaluated the Strand B, Wider Key Skills element of ELAMP for The University of Sheffield between 2008 and 2010, which is the main focus of this particular article.
Ezaki, Takahiro; Masuda, Naoki
Evolutionary game theory predicts that cooperation in social dilemma games is promoted when agents are connected as a network. However, when networks are fixed over time, humans do not necessarily show enhanced mutual cooperation. Here we show that reinforcement learning (specifically, the so-called Bush-Mosteller model) approximately explains the experimentally observed network reciprocity and the lack thereof in a parameter region spanned by the benefit-to-cost ratio and the node's degree. Thus, we significantly extend previously obtained numerical results.
Full Text Available Evolutionary game theory predicts that cooperation in social dilemma games is promoted when agents are connected as a network. However, when networks are fixed over time, humans do not necessarily show enhanced mutual cooperation. Here we show that reinforcement learning (specifically, the so-called Bush-Mosteller model approximately explains the experimentally observed network reciprocity and the lack thereof in a parameter region spanned by the benefit-to-cost ratio and the node's degree. Thus, we significantly extend previously obtained numerical results.
Simard, Patrice Yvon
Fully recurrent (asymmetrical) networks can be used to learn temporal trajectories. The network is unfolded in time, and backpropagation is used to train the weights. The presence of recurrent connections creates internal states in the system which vary as a function of time. The resulting dynamics can provide interesting additional computing power but learning is made more difficult by the existence of internal memories. This study first exhibits the properties of recurrent networks in terms of convergence when the internal states of the system are unknown. A new energy functional is provided to change the weights of the units in order to the control the stability of the fixed points of the network's dynamics. The power of the resultant algorithm is illustrated with the simulation of a content addressable memory. Next, the more general case of time trajectories on a recurrent network is studied. An application is proposed in which trajectories are generated to draw letters as a function of an input. In another application of recurrent systems, a neural network certain temporal properties observed in human callosally sectioned brains. Finally the proposed algorithm for stabilizing dynamics around fixed points is extended to one for stabilizing dynamics around time trajectories. Its effects are illustrated on a network which generates Lisajous curves.
Fine, Marija Futchs
The 7000l Training and Employment Institute offers self-paced instruction through the use of computers and audiovisual materials to young people to improve opportunities for success in the work force. In 1988, four sites were equipped with Apple stand-alone software in an integrated learning system that included courses in reading and math, test…
Sheneman, Leigh; Hintze, Arend
There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. These methods have been previously combined, particularly in artificial neural networks using an external objective feedback mechanism. We adapt this approach to Markov Brains, which are evolvable networks of probabilistic and deterministic logic gates. Prior to this work MB could only adapt from one generation to the other, so we introduce feedback gates which augment their ability to learn during their lifetime. We show that Markov Brains can incorporate these feedback gates in such a way that they do not rely on an external objective feedback signal, but instead can generate internal feedback that is then used to learn. This results in a more biologically accurate model of the evolution of learning, which will enable us to study the interplay between evolution and learning and could be another step towards autonomously learning machines.
Sanchez-Casado, Noelia; Cegarra Navarro, Juan Gabriel; Wensley, Anthony; Tomaseti-Solano, Eva
Purpose: Over the past few years, social networking sites (SNSs) have become very useful for firms, allowing companies to manage the customer-brand relationships. In this context, SNSs can be considered as a learning tool because of the brand knowledge that customers develop from these relationships. Because of the fact that knowledge in…
Weber, Peter; Rothe, Hannes
This paper is a report on the findings of a study conducted on the use of the social networking service NING in a cross-location e-learning setting named "Net Economy." We describe how we implemented NING as a fundamental part of the setting through a special phase concept and team building approach. With the help of user statistics, we…
Barrera, D.; Bunt, G. van de
This article investigates the effects of information originating from social networks on the development of interpersonal trust relations in the context of a dialysis department of a Dutch medium-sized hospital. Hypotheses on learning effects are developed from existing theories and tested using
Barrera, D.; van de Bunt, G
This article investigates the effects of information originating from social networks on the development of interpersonal trust relations in the context of a dialysis department of a Dutch medium-sized hospital. Hypotheses on learning effects are developed from existing theories and tested using
Lansu, Angelique; Boon, Jo; Sloep, Peter; Van Dam-Mieras, Rietje
The didactic model of remote internships described in this study provides the flexibility needed to support networked learners, i.e. to facilitate the development and subsequent assessment of their competences. The heterogeneity of the participants (students, employers, tutors) in the learning
Rusman, Ellen; Prinsen, Fleur; Vermeulen, Marjan
Networked learning happens naturally within the social systems of which we are all part. However, in certain circumstances individuals may want to actively take initiative to initiate interaction with others they are not yet regularly in exchange with. This may be the case when external influences
Loureiro-Koechlin, Cecilia; Allan, Barbara
This study focuses on a project, "EMPATHY Net-Works," which developed a learning community as a means of encouraging women to progress into employment and management positions in the logistics and supply chain industries (LaSCI). Learning activities were organised in the form of a taught module containing face-to-face and online elements and…
María Luz Cacheiro-González
Full Text Available Transnational Networked Curricula (TNC provides many benefits to the institutions that offer them as well as to the different stakeholders involved, not only the students but also the academics, the institutions as a whole, and the wider society. Supporting Higher Education Institutions in enhancing and implementing international networked practices in virtual campus building is the main aim of the NetCU project, which has been developed by the EADTU, in partnership with 14 member organizations, from 2009 to 2012. The project outcomes intend to facilitate the future set-up of networked curricula in Higher Education institutions and potentially lead to more transnational partnerships in Open and Distance Education (ODE and blended learning, showing challenges, obstacles and ways to overcome them. This paper presents the main products developed in the project, assesses its completeness and usage, and discusses on the challenges of curricula networking starting from the ideas and opinions shared in different stakeholders workshops organized under the NetCU project.
Jaime, Arturo; Blanco, José Miguel; Domínguez, César; Sánchez, Ana; Heras, Jónathan; Usandizaga, Imanol
Different learning methods such as project-based learning, spiral learning and peer assessment have been implemented in science disciplines with different outcomes. This paper presents a proposal for a project management course in the context of a computer science degree. Our proposal combines three well-known methods: project-based learning,…
Hodgson, Vivien; de Laat, Maarten; McConnell, David
and final section draws attention to a growing topic of interest within networked learning: that of networked learning in informal practices. In addition, we provide a reflection on the theories, methods and settings featured in the networked learning research of the chapters. We conclude the introduction...
Wagstaff, Kiri L.; Rebbapragada, Umaa; Lane, Terran
Collaboration methods for distributed machine-learning algorithms involve the specification of communication protocols for the learners, which can query other learners and/or broadcast their findings preemptively. Each learner incorporates information from its neighbors into its own training set, and they are thereby able to bootstrap each other to higher performance. Each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. After being seeded with an initial labeled training set, each learner proceeds to learn in an iterative fashion. New data is collected and classified. The learner can then either broadcast its most confident classifications for use by other learners, or can query neighbors for their classifications of its least confident items. As such, collaborative learning combines elements of both passive (broadcast) and active (query) learning. It also uses ideas from ensemble learning to combine the multiple responses to a given query into a single useful label. This approach has been evaluated against current non-collaborative alternatives, including training a single classifier and deploying it at all nodes with no further learning possible, and permitting learners to learn from their own most confident judgments, absent interaction with their neighbors. On several data sets, it has been consistently found that active collaboration is the best strategy for a distributed learner network. The main advantages include the ability for learning to take place autonomously by collaboration rather than by requiring intervention from an oracle (usually human), and also the ability to learn in a distributed environment, permitting decisions to be made in situ and to yield faster response time.
This paper describes a survey of technologies and to what extent they support virtual project based learning. The paper argues that a survey of learning technologies should be related to concrete learning tasks and processes. Problem oriented project pedagogy (POPP) is discussed, and a framework...... for evaluation is proposed where negotiation of meaning, coordination and resource management are identified as the key concepts in virtual project based learning. Three e-learning systems are selected for the survey, Virtual-U, Lotus Learningspace and Lotus Quickplace, as each system offers different strategies...... for e-learning. The paper concludes that virtual project based learning may benefit from facilities of all these systems....
IDRC'S PARTNERSHIP AND BUSINESS DEVELOPMENT DIVISION (PBDD) INITIATES, ... determines broad network strategic orientations and a regional scientific .... dissemination workshop of a transnational project on the integration of.
Sie, Rory; Bitter-Rijpkema, Marlies; Stoyanov, Slavi; Sloep, Peter
Networked cooperation fails if the available partnerships remain opaque. A literature review and Delphi study uncovered the elements of a fruitful partnership. They relate to personality, diversity, cooperation, and management. Innovation networks and learning networks share the same cooperative
Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming
Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.
Murphy, Cornelius M.; Carr, Dennis
For nearly 37 years, the U.S. Department of Energy site at Fernald - near Cincinnati, Ohio - produced 230,000 metric tons (250,000 short tons) of high-purity, low-enriched uranium for the U.S. Defense Program, generating more than 5.4 million metric tons (6 million short tons) of liquid and solid waste as it carried out its Cold War mission. The facility was shut down in 1989 and clean up began in 1992, when Fluor won the contract to clean up the site. Cleaning up Fernald and returning it to the people of Ohio was a $4.4 billion mega environmental-remediation project that was completed in October 2006. Project evolved through four phases: - Conducting remedial-investigation studies to determine the extent of damage to the environment and groundwater at, and adjacent to, the production facilities; - Selecting cleanup criteria - final end states that had to be met that protect human health and the environment; - Selecting and implementing the remedial actions to meet the cleanup goals; - Executing the work in a safe, compliant and cost-effective manner. In the early stages of the project, there were strained relationships - in fact total distrust - between the local community and the DOE as a result of aquifer contamination and potential health effects to the workers and local residents. To engage citizens and interested stakeholders groups in the decision-making process, the DOE and Fluor developed a public-participation strategy to open the channels of communication with the various parties: site leadership, technical staff and regulators. This approach proved invaluable to the success of the project, which has become a model for future environmental remediation projects. This paper will summarize the history and shares lessons learned: the completion of the uranium-production mission to the implementation of the Records of Decision defining the cleanup standards and the remedies achieved. Lessons learned fall into ten categories: - Regulatory approach with end
Hartmann, Andreas; Dorée, André
Although learning from projects has gained much importance in research and practice, progress in understanding and improving inter-project learning appears to be slight. We argue that the adoption of a sender/receiver approach limits the learning effectiveness in project-based organisations. Drawing
Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.
Full Text Available The network «Partners in Learning Network» is presented in the article – the Ukrainian segment of global educational community. PILN is created with support of the Microsoft company for teachers who use information communication technology in their professional work. The PILN's purpose and value for Ukrainian teachers, for their professional dialogue and collaboration are described in the article. Functions of PILN's communities for teacher’s cooperation, the joint decision of questions and an exchange of ideas and of technique, teaching tools for increase of level of ICT introduction in educational process are described.
Pea, Roy D.; Gomez, Louis M.
Project-enhanced science learning (PESL) provides students with opportunities for `cognitive apprenticeships' in authentic scientific inquiry using computers for data-collection and analysis. Student teams work on projects with teacher guidance to develop and apply their understanding of science concepts and skills. We are applying advanced computing and communications technologies to augment and transform PESL at-a-distance (beyond the boundaries of the individual school), which is limited today to asynchronous, text-only networking and unsuitable for collaborative science learning involving shared access to multimedia resources such as data, graphs, tables, pictures, and audio-video communication. Our work creates user technology (a Collaborative Science Workbench providing PESL design support and shared synchronous document views, program, and data access; a Science Learning Resource Directory for easy access to resources including two-way video links to collaborators, mentors, museum exhibits, media-rich resources such as scientific visualization graphics), and refine enabling technologies (audiovisual and shared-data telephony, networking) for this PESL niche. We characterize participation scenarios for using these resources and we discuss national networked access to science education expertise.
Tsui, Eric; Sabetzadeh, Farzad
This paper describes the feedback from the configuration and deployment of a Personal Learning Environment & Network (PLE&N) tool to support peer-based social learning for university students and graduates. An extension of an earlier project in which a generic and PLE&N was deployed for all learners, the current PLE&N is a…
Sung, Ko-Yin; Poole, Frederick
This study explored college students' use of a popular smartphone social networking application, WeChat, in a tandem language learning project. The research questions included (1) How do Chinese-English dyads utilize the WeChat app for weekly language learning?, and (2) What are the perceptions of the Chinese-English dyads on the use of the WeChat…
Full Text Available In the last decade we can observe increasing number of applications based on the Artificial Intelligence that are designed to solve problems from different areas of human activity. The reason why there is so much interest in these technologies is that the classical way of solutions does not exist or these technologies are not suitable because of their robustness. They are often used in applications like Business Intelligence that enable to obtain useful information for high-quality decision-making and to increase competitive advantage.One of the most widespread tools for the Artificial Intelligence are the artificial neural networks. Their high advantage is relative simplicity and the possibility of self-learning based on set of pattern situations.For the learning phase is the most commonly used algorithm back-propagation error (BPE. The base of BPE is the method minima of error function representing the sum of squared errors on outputs of neural net, for all patterns of the learning set. However, while performing BPE and in the first usage, we can find out that it is necessary to complete the handling of the learning factor by suitable method. The stability of the learning process and the rate of convergence depend on the selected method. In the article there are derived two functions: one function for the learning process management by the relative great error function value and the second function when the value of error function approximates to global minimum.The aim of the article is to introduce the BPE algorithm in compact matrix form for multilayer neural networks, the derivation of the learning factor handling method and the presentation of the results.
Lassnig, Mario; The ATLAS collaboration; Vamosi, Ralf
The increasing volume of physics data is posing a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from our ongoing automation efforts. First, we describe our framework for distributed data management and network metrics, automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for network-aware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.
Project-based organizations collect lessons learned in order to improve the performance of projects. They aim to repeat successes by using positive lessons learned, and to avoid repeating negative experiences by using negative lessons learned. Cooke-Davies (2002) claimed that the ability to learn
Duong, Tuan Anh
Fully-parallel hardware neural network implementations may be applied to high-speed recognition, classification, and mapping tasks in areas such as vision, or can be used as low-cost self-contained units for tasks such as error detection in mechanical systems (e.g. autos). Learning is required not only to satisfy application requirements, but also to overcome hardware-imposed limitations such as reduced dynamic range of connections.
Fernandes, Sara; Cerone, Antonio; Barbosa, L. S.
This poster presents a pilot project on non-conventional learning strategies based on students’ active participation in real-life FLOSS projects. The aim of the project is to validate the hypothesis that the peer-production model, which underlies most FLOSS projects, can enhance the learning-teaching process based on extensive and systematic collaborative practices.
Simard, D.; Nadeau, L.; Kroeger, H.
We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, and pattern recognition
Mohd Ishak Bin Ismail; Ruzaini Bin Abdullah Arshah
Social networking sites, a web-based application have permeated the boundary between personal lives and student lives. Nowadays, students in higher learning used social networking site such as Facebook to facilitate their learning through the academic collaboration which it further enhances students’ social capital. Social networking site has many advantages to improve students’ learning. To date, Facebook is the leading social networking sites at this time which it being widely used by stude...
Norris, Jeff; Goza, Sharon; Shores, David
Project KEWL is a joint project between NASA/JPL and NASA/JSC to stimulate interest of children in Science, Technology, Engineering and Math (STEM) and bring the NASA space exploration experience to the classroom, museum and ultimately the living room. Using the Kinect game controller KEWL allows children to engage in NASA s missions in a fundamentally new way. KEWL allows children to experiment with gravity on Mars and the Moon; navigate through the International Space Station; fix a torn solar array on the ISS; drive a robot on Mars; visit an Asteroid; learn about the differences in gravity on different planets and control Robonaut 2 using their body as the input device. Project KEWL complements NASA s outreach investments in television, mobile platforms and the web by engaging the public through the rapidly expanding medium of console gaming. In 2008, 97% of teenagers played video games and 86% played on a home gaming console. (source: http://pewresearch.org/pubs/953/) As of March 2011, there have been more than 10 million Kinects sold. (source: http://www.itproportal.com/2011/03/10/kinect-record-breaking-sales-figures-top-10-million/) Project KEWL interacts with children on a platform on which they spend much of their time and teaches them information about NASA while they are having fun. Project KEWL progressed from completely custom C++ code written in house to using a commercial game engine. The art work and 3D geometry models come from existing engineering work or are created by the KEWL development team. Six different KEWL applications have been demonstrated at nine different venues including schools, museums, conferences, and NASA outreach events. These demonstrations have allowed the developers the chance to interact with players and observe the gameplay mechanics in action. The lessons learned were then incorporated into the subsequent versions of the applications.
Full Text Available he concept of project management expresses an indispensable approach to investment projects. Time is often the most important factor in these projects. The artificial neural network is the paradigm of data processing, which is inspired by the one used by the biological brain, and it is used in numerous, different fields, among which is the project management. This research is oriented to application of artificial neural networks in managing time of investment project. The artificial neural networks are used to define the optimistic, the most probable and the pessimistic time in PERT method. The program package Matlab: Neural Network Toolbox is used in data simulation. The feed-forward back propagation network is chosen.
Stevanovic, Matija; Pedersen, Jens Myrup
. Due to promise of non-invasive and resilient detection, botnet detection based on network traffic analysis has drawn a special attention of the research community. Furthermore, many authors have turned their attention to the use of machine learning algorithms as the mean of inferring botnet......-related knowledge from the monitored traffic. This paper presents a review of contemporary botnet detection methods that use machine learning as a tool of identifying botnet-related traffic. The main goal of the paper is to provide a comprehensive overview on the field by summarizing current scientific efforts....... The contribution of the paper is three-fold. First, the paper provides a detailed insight on the existing detection methods by investigating which bot-related heuristic were assumed by the detection systems and how different machine learning techniques were adapted in order to capture botnet-related knowledge...
Liles, Charles A.
Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.
Arantes do Amaral, Joao Alberto; Gonçalves, Paulo; Hess, Aurélio
This article describes the project-based learning environment created to support project management graduate courses. The paper will focus on the learning context and procedures followed for 13 years, in 47 project-based learning MBA courses, involving approximately 1,400 students and 34 community partners.
Borkowski, Robert; Duran, Ramon J.; Kachris, Christoforos
The aim of cognition in optical networks is to introduce intelligence into the control plane that allows for autonomous end-to-end performance optimization and minimization of required human intervention, particularly targeted at heterogeneous network scenarios. A cognitive network observes, lear...
multimedia, and Continuum of eLearning | Purpose and Vision 19 << UNCLASSIFIED>> (limited) situated learning. Future versions of the CoL self-paced...Continuum of eLearning : 2012 Project Summary Report Continuum of eLearning The Next Evolution of Joint Training on JKO October 2012 Joint...Technical Report November 2011 – August 2012 Continuum of eLearning : 2012 Project Summary Report N00140-06-D-0060 David T. Fautua, Sae Schatz, Andrea
Virtual Campus for a Sustainable Europe (VCSE) network has been selected to be part of the EC DG EAC Inventory of innovative good practice on education for sustainable development. The main purpose of the Inventory is to show concrete examples which have been implemented in the Member States under the concept of ESD in formal and non-formal learning contexts and which are at the forefront as regards innovative approaches. Projects/programmes selected as innovative good practice will be use...
Studený, Milan; Vomlel, Jiří; Hemmecke, R.
Roč. 51, č. 5 (2010), s. 578-586 ISSN 0888-613X. [PGM 2008] R&D Projects: GA AV ČR(CZ) IAA100750603; GA MŠk(CZ) 1M0572; GA ČR GA201/08/0539 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : learning Bayesian networks * standard imset * inclusion neighborhood * geometric neighborhood * GES algorithm Subject RIV: BA - General Mathematics Impact factor: 1.679, year: 2010 http://library.utia.cas.cz/separaty/2010/MTR/studeny-0342804. pdf
Cooper, Lynne P.; Majchrzak, Ann; Faraj, Samer
As project teams become used more widely, the question of how to capitalize on the knowledge learned in project teams remains an open issue. Using previous research on shared cognition in groups, an approach to promoting post-project learning was developed. This Legacy Review concept was tested on four in tact project teams. The results from those test sessions were used to develop a model of team learning via group cognitive processes. The model and supporting propositions are presented.
Gilra, Aditya; Gerstner, Wulfram
The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.
Dart, Richard A; Egan, Brent M
Community-based practice networks for research and improving the quality of care are growing in size and number but have variable success rates. In this paper, the authors review recent efforts to initiate a community-based hypertension network modeled after the successful Outpatient Quality Improvement Network (O'QUIN) project, located at the Medical University of South Carolina. Key lessons learned and new directions to be explored are highlighted. ©2014 Wiley Periodicals, Inc.
González-Avella, Juan Carlos; Eguíluz, Victor M.; Marsili, Matteo; Vega-Redondo, Fernado; San Miguel, Maxi
Social learning is defined as the ability of a population to aggregate information, a process which must crucially depend on the mechanisms of social interaction. Consumers choosing which product to buy, or voters deciding which option to take with respect to an important issue, typically confront external signals to the information gathered from their contacts. Economic models typically predict that correct social learning occurs in large populations unless some individuals display unbounded influence. We challenge this conclusion by showing that an intuitive threshold process of individual adjustment does not always lead to such social learning. We find, specifically, that three generic regimes exist separated by sharp discontinuous transitions. And only in one of them, where the threshold is within a suitable intermediate range, the population learns the correct information. In the other two, where the threshold is either too high or too low, the system either freezes or enters into persistent flux, respectively. These regimes are generally observed in different social networks (both complex or regular), but limited interaction is found to promote correct learning by enlarging the parameter region where it occurs. PMID:21637714
Tisenkopfs, Talis; Kunda, Ilona; Šumane, Sandra
Purpose: Networks are increasingly viewed as entities of learning and innovation in agriculture. In this article we explore learning as issue framing in two agricultural innovation networks. Design/methodology/approach: We combine frame analysis and social learning theories to analyse the processes and factors contributing to frame convergence and…
Maria Angeles Antequera
Full Text Available Florida is a higher education centre specialising in technical and business training. Postgraduate programs, university qualifications, vocational training, secondary education, further education, occupational training and languages are taught at Florida. An educational model in accordance with the demands of the European Higher Education Area has been designed, focussing on teaching for professional competencies. We have chosen to use a methodology which promotes the development of skills and abilities, it promotes participation and it is student-centric as s/he must look for knowledge him/herself thus connecting the educational and the real world. In the different university degrees taught in our centre, each year the student carries out a project set in a real context which integrates specific competencies from the course subject and develops transversal competencies associated with the project which are the purpose of planning and progressive learning: team work, effective communication, conflict resolution, leadership skills, innovation and creativity. The IP counts for 25% of each course in terms of objectives, scheduling and final evaluation. The project grade is an individual grade for each student and is the same for all subjects which form part of the project.
This paper describes lessons learned over the last 20 years from 12 decommissioning projects at Los Alamos National Laboratory. These lessons relate both to overall program management and to management of specific projects during the planning and operations phases. The issues include waste management; the National Environmental Policy Act (NEPA); the Resource Conservation and Recovery Act (RCRA); the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA); contracting; public involvement; client/customer interface; and funding. Key elements of our approach are to be proactive; follow the observation method; perform field activities concurrently; develop strategies to keep reportable incidents from delaying work; seek and use programs, methods, etc., in existence to shorten learning curves; network to help develop solutions; and avoid overstudying and overcharacterizing. This approach results in preliminary plans that require very little revision before implementation, reasonable costs and schedules, early acquisition of permits and NEPA documents, preliminary characterization reports, and contracting documents. Our track record is good -- the last four projects (uranium and plutonium-processing facility and three research reactors) have been on budget and on schedule
Duke, Nell K.; Halvorsen, Anne-Lise; Strachan, Stephanie L.
The popularity of project-based learning has been driven in part by a growing number of STEM schools and programs. But STEM subjects are not the only fertile ground for project-based learning (PBL). Social studies and literacy content, too, can be adapted into PBL units to benefit teaching and learning, the authors argue. They review key studies…
Even though quite different in occurrence and consequences, from a modelling perspective many natural hazards share similar properties and challenges. Their complex nature as well as lacking knowledge about their driving forces and potential effects make their analysis demanding. On top of the uncertainty about the modelling framework, inaccurate or incomplete event observations and the intrinsic randomness of the natural phenomenon add up to different interacting layers of uncertainty, which require a careful handling. Thus, for reliable natural hazard assessments it is crucial not only to capture and quantify involved uncertainties, but also to express and communicate uncertainties in an intuitive way. Decision-makers, who often find it difficult to deal with uncertainties, might otherwise return to familiar (mostly deterministic) proceedings. In the scope of the DFG research training group „NatRiskChange" we apply the probabilistic framework of Bayesian networks for diverse natural hazard and vulnerability studies. The great potential of Bayesian networks was already shown in previous natural hazard assessments. Treating each model component as random variable, Bayesian networks aim at capturing the joint distribution of all considered variables. Hence, each conditional distribution of interest (e.g. the effect of precautionary measures on damage reduction) can be inferred. The (in-)dependencies between the considered variables can be learned purely data driven or be given by experts. Even a combination of both is possible. By translating the (in-)dependences into a graph structure, Bayesian networks provide direct insights into the workings of the system and allow to learn about the underlying processes. Besides numerous studies on the topic, learning Bayesian networks from real-world data remains challenging. In previous studies, e.g. on earthquake induced ground motion and flood damage assessments, we tackled the problems arising with continuous variables
Narabayashi, Tadashi; Tsuji, Masashi; Shimazu, Yoichiro
Trial in education of nuclear engineering in Hokkaido University has proved to be quite attractive for students. It is an education system called Project Based Learning (PBL), which is not based on education by lecture only but based mostly on practice of students in the classroom. The system was adopted four years ago. In the actual class, we separated the student into several groups of the size about 6 students. In the beginning of each class room time, a brief explanations of the related theory or technical bases. Then the students discuss in their own group how to precede their design calculations and do the required calculation and evaluation. The target reactor type of each group was selected by the group members for themselves at the beginning of the semester as the first step of the project. The reactor types range from a small in house type to that for a nuclear ship. At the end of the semester, each group presents the final design. The presentation experience gives students a kind of fresh sensation. Nowadays the evaluation results of the subject by the students rank in the highest in the faculty of engineering. Based on the considerations above, we designed the framework of our PBL for reactor engineering. In this paper, we will present some lessons learned in this PBL education system from the educational points of view. The PBL education program is supported by IAE/METI in Japan for Nuclear Engineering Education. (author)
Knudsen, Morten; Helbo, Jan; Jensen, Lars Peter
-study, whereas the project study form is based on collaboration and dialogue. Consequently, successful implementation of project work in distance education requires extensive utilisation of new information and communication technology. In this paper the experiences of project work in a new Master of Industrial...... devoted to courses and the other half to project work. A computer conference system, LuvitÒ provides facilities for the courses, as well as structured synchronous and asynchronous communication. Eight times per year two-day seminars are held at the university for intensive lectures, project work......Problem oriented project work has been the foundation for the educational system at Aalborg University since its start 25 years ago. The duration of each student project is one semester, and the students spend half of their time working on the project in groups of typically 5-6 persons...
Stereochemistry, conforma- tional analysis, hands-on learn- ing, Fischer projections, zig-zag projection, C–C bond rotations. Interconversion of Fischer and Zig-Zag Projections. Learning Stereochemistry with the Help of Hands. Visualization of molecules in three dimensions is an important aspect of organic chemistry.
Deka, Deepjyoti [Univ. of Texas, Austin, TX (United States); Chertkov, Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Backhaus, Scott N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Traditionally power distribution networks are either not observable or only partially observable. This complicates development and implementation of new smart grid technologies, such as these related to demand response, outage detection and management, and improved load-monitoring. Here, inspired by proliferation of the metering technology, we discuss statistical estimation problems in structurally loopy but operationally radial distribution grids consisting in learning operational layout of the network from measurements, e.g. voltage data, which are either already available or can be made available with a relatively minor investment. Our newly suggested algorithms apply to a wide range of realistic scenarios. The algorithms are also computationally efficient – polynomial in time – which is proven theoretically and illustrated computationally on a number of test cases. The technique developed can be applied to detect line failures in real time as well as to understand the scope of possible adversarial attacks on the grid.
Full Text Available The popular deep Q learning algorithm is known to be instability because of the Q-value’s shake and overestimation action values under certain conditions. These issues tend to adversely affect their performance. In this paper, we develop the ensemble network architecture for deep reinforcement learning which is based on value function approximation. The temporal ensemble stabilizes the training process by reducing the variance of target approximation error and the ensemble of target values reduces the overestimate and makes better performance by estimating more accurate Q-value. Our results show that this architecture leads to statistically significant better value evaluation and more stable and better performance on several classical control tasks at OpenAI Gym environment.
Dalgaard, Jens; Kocka, Tomas; Pena, Jose
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that it allows a trade-off between greediness and randomness, thus exploring different good local optima. When greediness...... is set at maximum, KES corresponds to the greedy equivalence search algorithm (GES). When greediness is kept at minimum, we prove that under mild assumptions KES asymptotically returns any inclusion optimal BN with nonzero probability. Experimental results for both synthetic and real data are reported...
Better reproducibility of networking research results is currently a major goal that the academic community is striving towards. This position paper makes the case that improving the extent and pervasiveness of reproducible research can be greatly fostered by organizing a yearly international contest. We argue that holding a contest undertaken by a plurality of students will have benefits that are two-fold. First, it will promote hands-on learning of skills that are helpful in producing artifacts at the replicable-research level. Second, it will advance the best practices regarding environments, testbeds, and tools that will aid the tasks of reproducibility evaluation committees by and large.
Constanta Nicoleta BODEA
Full Text Available The paper presents the testing and evaluation facilities of the SinPers system. The SinPers is a web based learning environment in project management, capable of building and conducting a complete and personalized training cycle, from the definition of the learning objectives to the assessment of the learning results for each learner. The testing and evaluation facilities of SinPers system are based on the ontological approach. The educational ontology is mapped on a semantic network. Further, the semantic network is projected into a concept space graph. The semantic computability of the concept space graph is used to design the tests. The paper focuses on the applicability of the system in the certification, for the knowledge assessment, related to each element of competence. The semantic computability is used for differentiating between different certification levels.
Wegner, Claas; Homann, Wiebke; Strehlke, Friederike
The German science project "NAWI-Interaktiv" is an example of innovative use of E-Learning and new media education. Since 2009, the learning platform provides learners and teachers with high-quality learning tools, teaching material, useful information and E-learning programs for free. This is to raise the pupils' motivation to learn…
Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation
Adel, Tameem; de Campos, Cassio P.
We present new algorithms for learning Bayesian networks from data with missing values using a data augmentation approach. An exact Bayesian network learning algorithm is obtained by recasting the problem into a standard Bayesian network learning problem without missing data. To the best of our knowledge, this is the first exact algorithm for this problem. As expected, the exact algorithm does not scale to large domains. We build on the exact method to create an approximate algorithm using a ...
Appleby, Yvon; Hillier, Yvonne
This paper discusses the contribution that practice-research networks can make to support critical professional development in the Learning and Skills sector in England. By practice-research networks we mean groups or networks which maintain a connection between research and professional practice. These networks stem from the philosophy of…
Nägele, Andreas; Dejori, Mathäus; Stetter, Martin
Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.
Knudsen, Morten; Helbo, Jan; Jensen, Lars Peter
devoted to courses and the other half to project work. A computer conference system, LuvitÒ provides facilities for the courses, as well as structured synchronous and asynchronous communication. Eight times per year two-day seminars are held at the university for intensive lectures, project work......Problem oriented project work has been the foundation for the educational system at Aalborg University since its start 25 years ago. The duration of each student project is one semester, and the students spend half of their time working on the project in groups of typically 5-6 persons....... As the experience since then has proven this to be a very successful innovation in higher education , it seems to be an obvious idea also to base our new distance educations on the project study form. Traditionally, however, distance education has been characterized by one-way communication and self...
Sri Lanka Telecentre Family Network Project ... will require telecentre manager training, technical and business support, and knowledge-sharing across programs. ... IWRA/IDRC webinar on climate change and adaptive water management.
Malayeri, Amin Daneshmand; Abdollahi, Jalal
One of the most applied learning in virtual spaces is using E-Learning systems. Some E-Learning methodologies has been introduced, but the main subject is the most positive feedback from E-Learning systems. In this paper, we introduce a new methodology of E-Learning systems entitle "Network Learning" with review of another aspects of E-Learning systems. Also, we present benefits and advantages of using these systems in educating and fast learning programs. Network Learning can be programmable...
Full Text Available In the 2010/11 academic year the Institute of Informatics at Wroclaw University of Technology issued ’Software Engineering Team Project’ as a course being a part of the final exam to earn bachelor’s degree. The main assumption about the course was that it should simulate the real environment (a virtual IT company for its participants. The course was aimed to introduce issues regarding programming in the medium scale, project planning and management. It was a real challenge as the course was offered for more than 140 students. The number of staff members involved in its preparation and performance was more than 15. The paper presents the lessons learned from the first course edition as well as more detailed qualitative and quantitative course assessment.
Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl
Leendertse, W.; Arts, J.; De Ridder, H.
The core business of governmental organizations like Rijkswaterstaat in the Netherlands is the optimal management of road-end waterway networks. The coming years many maintenance, renewal and extension projects will be executed in these networks. Projects give a disturbance in functionality of the
...). This NSRP report is funded as an addendum to the Air Quality Best Management Practices (AQBMP) project (N1 -944). The AQBMP project was completed using an intensive project planning process using a variety of quality management tools...
Warin, Bruno; Talbi, Omar; Kolski, Christophe; Hoogstoel, Frédéric
This paper presents the "Multi-Role Project" method (MRP), a broadly applicable project-based learning method, and describes its implementation and evaluation in the context of a Science, Technology, Engineering, and Mathematics (STEM) course. The MRP method is designed around a meta-principle that considers the project learning activity…
Arantes do Amaral, Joao Alberto
In this case study we discuss the dynamics that drive a free-of-charge project-based learning extension course. We discuss the lessons learned in the course, "Laboratory of Social Projects." The course aimed to teach project management skills to the participants. It was conducted from August to November of 2015, at Federal University of…
Ryberg, Thomas; Davidsen, Jacob; Hodgson, Vivien
There is a need within networked learning to understand and conceptualise the interplay between digital and physical spaces or what we could term hybrid spaces. Therefore, we discuss a recent study of students from two different programmes who are engaged in long-term, group-based problem and project based learning. Based on interviews, workshops and observations of students’ actual group practices in open, shared and flexible spaces in Aalborg University (AAU), we identify and discuss how st...
Halyna V. Lutsenko
Full Text Available The peculiarities of modern world experience of implementation of project-based learning in engineering education have been considered. The potential role and place of projects in learning activity have been analyzed. The methodology of organization of project-based activity of engineering students when studying the project management methodology and computer systems of project management has been proposed. The requirements to documentation and actual results of students' projects have been described in detail. The requirements to computer-aided systems of project management developed by using Microsoft Project in the scope of diary scheduling and resources planning have been formulated.
Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.
Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.
Sri Lanka Telecentre Family Network Project. There has been dramatic growth in telecentres and other local information and communication technology (ICT) projects in Sri Lanka. The largest of these, the Nanasala (rural knowledge centres) program, aims to reach 1 000 villages across the nation. Sarvodaya, an early ...
This paper presents recent and current projects at the Idaho National Engineering Laboratory (INEL) that research and apply neural network technology. The projects are summarized in the paper and their direct application to space reactor power and propulsion systems activities is discussed. 9 refs., 10 figs., 3 tabs
Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.
Ryberg, Thomas; Sinclair, Christine
the books that include a selection of reworked and peer-reviewed papers from the conference. The 2014 Networked Learning Conference which was held in Edinburgh was characterised by animated dialogue on emergent influences affecting networked teaching and learning building on work established in earlier...
... ICT collaborative and supportive learning media utilisation within the Nigerian educational system. The concept of ICT was concisely explained vis-à-vis the social network concept, theory and collaborative and supportive learning media utilisation. Different types of social network are highlighted among which Facebook, ...
Reda, Weldemariam Nigusse; Hagos, Girmay Tsegay
Student network is a teaching strategy introduced as cooperative learning to all educational levels above the upper primary schools (grade 5 and above) in Ethiopia. The study was, therefore, aimed at investigating to what extent the student network in Ethiopia is actually practiced in line with the principles of cooperative learning. Consequently,…
Chung, Kon Shing Kenneth; Paredes, Walter Christian
In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…
Ferreday, Debra; Hodgson, Vivien; Jones, Chris
This paper draws on the work of Mikhail Bakhtin and Norman Fairclough to show how dialogue is central to the construction of identity in networked management learning. The paper is based on a case study of a networked management learning course in higher education and attempts to illustrate how participants negotiate issues of difference,…
Chapman, Georgina; Langley, Mark; Skilling, Gus; Walker, John
The national network of Science Learning Centres is a co-ordinating partner in the Getting Practical--Improving Practical Work in Science programme. The principle of training provision for the "Getting Practical" programme is a cascade model. Regional trainers employed by the national network of Science Learning Centres trained the cohort of local…
Shankle, Dean E.; Shankle, Jeremy P.
Please, cite this publication as: Shankle, D.E., & Shankle, J.P. (2006). Problems in the Deployment of Learning Networks In Small Organizations. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence Conference. March 30th-31st, Sofia, Bulgaria:
Rossi, R.; Elliott, E. M.; Bain, D.; Crowley, K. J.; Steiner, M. A.; Divers, M. T.; Hopkins, K. G.; Giarratani, L.; Gilmore, M. E.
While energy links all living and non-living systems, the integration of energy, the environment, and society is often not clearly represented in 9 - 12 classrooms and informal learning venues. However, objective public learning that integrates these components is essential for improving public environmental literacy. ENERGY-NET (Energy, Environment and Society Learning Network) is a National Science Foundation funded initiative that uses an Earth Systems Science framework to guide experimental learning for high school students and to improve public learning opportunities regarding the energy-environment-society nexus in a Museum setting. One of the primary objectives of the ENERGY-NET project is to develop a rich set of experimental learning activities that are presented as exhibits at the Carnegie Museum of Natural History in Pittsburgh, Pennsylvania (USA). Here we detail the evolution of the ENERGY-NET exhibit building process and the subsequent evolution of exhibit content over the past three years. While preliminary plans included the development of five "exploration stations" (i.e., traveling activity carts) per calendar year, the opportunity arose to create a single, larger topical exhibit per semester, which was assumed to have a greater impact on museum visitors. Evaluative assessments conducted to date reveal important practices to be incorporated into ongoing exhibit development: 1) Undergraduate mentors and teen exhibit developers should receive additional content training to allow richer exhibit materials. 2) The development process should be distributed over as long a time period as possible and emphasize iteration. This project can serve as a model for other collaborations between geoscience departments and museums. In particular, these practices may streamline development of public presentations and increase the effectiveness of experimental learning activities.
This article discusses USAID's lessons learned about integrating gender into natural resource management (NRM) projects in Peru, the Philippines, and Kenya. In Peru, USAID integrated women into a solid waste management project by lending money to invest in trash collection supplies. The loans allowed women to collect household waste, transfer it to a landfill, and provide additional sanitary disposal. The women were paid through direct fees from households and through service contracts with municipalities. In Mindanao, the Philippines, women were taught about the health impact of clean water and how to monitor water quality, including the monitoring of E. coli bacteria. Both men and women were taught soil conservation techniques for reducing the amount of silt running into the lake, which interferes with the generation of electricity and affects the health of everyone. The education helped women realize the importance of reducing silt and capitalized on their interest in protecting the health of their families. The women were thus willing to monitor the lake's water quality to determine if the conservation efforts were effective. In Kenya, USAID evaluated its Ecology, Community Organization, and Gender project in the Rift Valley, which helped resettle a landless community and helped with sustainable NRM. The evaluation revealed that women's relative bargaining power was less than men's. Organized capacity building that strengthened women's networks and improved their capacity to push issues onto the community agenda assured women a voice in setting the local NRM agenda.
Seke, F. R.; Sumilat, J. M.; Kembuan, D. R. E.; Kewas, J. C.; Muchtar, H.; Ibrahim, N.
Project-based learning is a learning method that uses project activities as the core of learning and requires student creativity in completing the project. The aims of this study is to investigate the influence of project-based learning methods on students with a high level of creativity in learning the Programmable Logic Controller (PLC). This study used experimental methods with experimental class and control class consisting of 24 students, with 12 students of high creativity and 12 students of low creativity. The application of project-based learning methods into the PLC courses combined with the level of student creativity enables the students to be directly involved in the work of the PLC project which gives them experience in utilizing PLCs for the benefit of the industry. Therefore, it’s concluded that project-based learning method is one of the superior learning methods to apply on highly creative students to PLC courses. This method can be used as an effort to improve student learning outcomes and student creativity as well as to educate prospective teachers to become reliable educators in theory and practice which will be tasked to create qualified human resources candidates in order to meet future industry needs.
Lam, Shui-fong; Cheng, Rebecca Wing-yi; Ma, William Y. K.
In this study we examined the relationship between teacher and student intrinsic motivation in project-based learning. The participants were 126 Hong Kong secondary school teachers and their 631 students who completed evaluation questionnaires after a semester-long project-based learning program. Both teachers and students were asked to indicate…
Environmental education (EE) and education for sustainable development (ESD) pedagogies are intricate, and to enhance learning, teacher education has to be innovative in teaching approach. This article investigates how the change project approach enhances project-based learning in practice. The investigation is ...
The Collaborative Learning Project is a language exchange program in which American and Japanese university students have the opportunity to interact with native speakers over the course of a three-week period. This paper reports the outcomes of the Collaborative Learning Project in terms of its effectiveness in fulfilling student expectations and…
A. Keegan (Anne); J.R. Turner (Rodney)
textabstractIn the midst of the turbulence wrought by the global economy, it has become common to see projects as an essential medium for achieving change. However, project based learning practices - as a subset of organizational learning practices- have not kept pace with this development. To
Full Text Available The UNESCO office in Venice (the Regional Bureau for Science and Culture in Europe has promoted, in collaboration with the Italian Agency for New Technologies, Energy, and the Environment (ENEA, an e-learning project on renewable energy: the DESIRE-net project (Development and Sustainability with International Renewable Energies network. The project's aim is to share the best available knowledge on renewable energies among all the countries that have joined the project and exploit this knowledge at every level. Currently the project involves 30 Eastern European and Southern Mediterranean countries as well as Australia, Indonesia, and China.
Baillie, Sarah; Kinnison, Tierney; Forrest, Neil; Dale, Vicki H M; Ehlers, Jan P; Koch, Michael; Mándoki, Mira; Ciobotaru, Emilia; de Groot, Esther; Boerboom, Tobias B B; van Beukelen, Peter
An online professional network for veterinarians, veterinary students, veterinary educationalists, and ICT (Information and Communication Technology) educationalists is being developed under the EU (European Union) Lifelong Learning Programme. The network uses Web 2.0, a term used to describe the new, more interactive version of the Internet, and includes tools such as wikis, blogs, and discussion boards. Focus groups conducted with qualified and student veterinarians within the project's five founding countries (The Netherlands, Germany, United Kingdom, Hungary, Romania) demonstrated that online professional communities can be valuable for accessing information and establishing contacts. Online networks have the potential to overcome common challenges to face-to-face communities-such as distance, cost, and timing-but they have their own drawbacks, such as security and professionalism issues. The Network Of Veterinary ICt in Education (NOVICE) was developed using Elgg, an open-source, free social networking platform, after several software options had been considered. NOVICE aims to promote the understanding of Web 2.0, confidence to use social software tools, and participation in an online community. Therefore, the Web site contains help sections, Frequently Asked Questions, and access to support from ICT experts. Five months after the network's launch (and just over one year into the project) 515 members from 28 countries had registered. Further research will include analysis of a core group's activities, which will inform ongoing support for and development of informal, lifelong learning in a veterinary context.
Tollestrup, Christian H. T.
In the Problem Based, Project Oriented Learning Program of Industrial Design Engineering at AAU students work and are examined/evaluated in groups. Following a period of a 6 years of ban on group-based exams by the government, the return of the group-based exam at Universities in 2014 has...... and the supervisor. Having the group based exam re-introduced sparked the interest for even further utilizing the exam situation for enhancing the learning outcome for each project and at the same time promote a more open atmosphere. Can the students learn even more and/or put their own project learning...... into perspective by seeing other project exams? So in order to investigate whether there was a possibility to further enhance the learning potential and understanding of the learning outcome the study board for the Architecture & Design program opened for a trial period for 2 semesters for voluntarily organizing...
Suresh, Sundaram; Savitha, Ramasamy
Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks. Furthermore, to efficiently preserve the physical characteristics of these complex-valued signals, it is important to develop complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The concepts of meta-cognition equipped with a self-regulated learning have been known to be the best human learning strategy. In this monograph, the principles of meta-cognition have been introduced for complex-valued neural networks in both the batch and sequential learning modes. For applications where the computati...
Full Text Available This article aims to show how the Nuclear disaster in Fukushima (3 March 2011 affected Japanese Language teaching and learning in Italy, focusing on the ITADICT Project (Marcella Mariotti, project leader, Clemente Beghi, research fellow and Alessandro Mantelli, programmer. The project intends to develop the first Japanese-Italian online database, involving more than 60 students of Japanese language interested in lexicographic research and online learning strategies and tools. A secondary undertaking of ITADICT is its Latin alphabet transliteration of Japanese words into Hepburn style. ITADICT is inspired by EDICT Japanese-English database developed by the Electronic Dictionary Research and Development Group established in 2000 within the Faculty of Information Technology at Monash University. The Japanese-Italian database is evolving within the Department of Asian and North African Studies at Ca’ Foscari University of Venice, the largest in the country and one of the main teaching centres of Japanese in Europe in terms of the number of students dedicated to it (1800 and number of Japanese language teaching hours (1002h at B.A. level, and 387h at M.A. level. In this paper we will describe how and why the project has been carried out and what the expectations are for its future development.-----Pričujoči članek predstavlja projekt ITADICT (vodja projekta Marcella Mariotti, sodelujoči raziskovalec Clemente Beghi, programer Alessandro Mantelli in vpliv nuklearne katastrofe v Fukushimi 3. marca 2011 na učenje japonščine v Italiji. Cilj projekta je razvoj prve spletne japonsko-italijanske baze podatkov, pri njem pa sodeluje več kot 60 študentov japonščine, ki jih zanima slovaropisje in učne strategije ter orodja na spletu. Drugi cilj projekta ITADICT je prečrkovanje japonskih besed v latinico, po sistemu Hepburn. Projekt je zastavljen po vzoru japonsko-angleške podatkovne baze EDICT, ki jo je razvila skupina Electronic Dictionary
Falcao, Rita; Fernandes, Luis
Creating a course for teaching project management online in a full online distance-learning environment was a challenge. Working with adult learners from different continents that want to complete a Master degree was an additional challenge. This paper describes how different MOOCs were used to learn about teaching -(meta) e-learning. MOOCs…
Ogata, Hiroaki; Hou, Bin; Li, Mengmeng; Uosaki, Noriko; Mouri, Kosuke; Liu, Songran
A Ubiquitous Learning Log (ULL) is defined as a digital record of what a learner has learned in daily life using ubiquitous computing technologies. In this paper, a project which developed a system called SCROLL (System for Capturing and Reusing Of Learning Log) is presented. The aim of developing SCROLL is to help learners record, organize,…
Felzien, Lisa; Salem, Laura
Service learning involves providing service to the community while requiring students to meet learning goals in a specific course. A service learning project was implemented in a general biology course at Rockhurst University to involve students in promoting scientific education in conjunction with community partner educators. Students were…
Riyanti, Menul Teguh; Erwin, Tuti Nuriah; Suriani, S. H.
The purpose of this study was to develop a learning model based Commercial Graphic Design Drafting project-based learning approach, was chosen as a strategy in the learning product development research. University students as the target audience of this model are the students of the fifth semester Visual Communications Design Studies Program…
Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT
Ana Ana; Lutfhiyah Nurlaela
The study aims to find a model of patisserie project-based learning with production approach that can improve effectiveness of patisserie learning. Delphi Technique, Cohen's Kappa and percentages of agreements were used to assess model of patisserie project based learning. Data collection techniques employed in the study were questionnaire, check list worksheet, observation, and interview sheets. Subjects were 13 lectures of expertise food and nutrition and 91 students of Food and Nutrition ...
Koch, Christian; Larsen, Casper Schultz
The paper argues that in the AEC-industry the material and knowledge supply chains are increasingly intertwined and moreover characterised by configuration by project. In such a setting creating value for the customers and the enterprises becomes dependent of the ability to organise and coordinate...
Chen, Barry Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
The proliferation of inexpensive sensor technologies like the ubiquitous digital image sensors has resulted in the collection and sharing of vast amounts of unsorted and unexploited raw data. Companies and governments who are able to collect and make sense of large datasets to help them make better decisions more rapidly will have a competitive advantage in the information era. Machine Learning technologies play a critical role for automating the data understanding process; however, to be maximally effective, useful intermediate representations of the data are required. These representations or “features” are transformations of the raw data into a form where patterns are more easily recognized. Recent breakthroughs in Deep Learning have made it possible to learn these features from large amounts of labeled data. The focus of this project is to develop and extend Deep Learning algorithms for learning features from vast amounts of unlabeled data and to develop the HPC neural network training platform to support the training of massive network models. This LDRD project succeeded in developing new unsupervised feature learning algorithms for images and video and created a scalable neural network training toolkit for HPC. Additionally, this LDRD helped create the world’s largest freely-available image and video dataset supporting open multimedia research and used this dataset for training our deep neural networks. This research helped LLNL capture several work-for-others (WFO) projects, attract new talent, and establish collaborations with leading academic and commercial partners. Finally, this project demonstrated the successful training of the largest unsupervised image neural network using HPC resources and helped establish LLNL leadership at the intersection of Machine Learning and HPC research.
Cadima, Rita; Ojeda Rodríguez, Jordi; Monguet Fierro, José María
Social networks play an essential role in learning environments as a key channel for knowledge sharing and students' support. In distributed learning communities, knowledge sharing does not occur as spontaneously as when a working group shares the same physical space; knowledge sharing depends even more on student informal connections. In this study we analyse two distributed learning communities' social networks in order to understand how characteristics of the social structure can enhance s...
Freeman, Jason; Saad, David
An analytic investigation of the average case learning and generalization properties of Radial Basis Function Networks (RBFs) is presented, utilising on-line gradient descent as the learning rule. The analytic method employed allows both the calculation of generalization error and the examination of the internal dynamics of the network. The generalization error and internal dynamics are then used to examine the role of the learning rate and the specialization of the hidden units, which gives ...
Diakonikolas, Ilias; Kane, Daniel; Stewart, Alistair
We investigate the problem of learning Bayesian networks in an agnostic model where an $\\epsilon$-fraction of the samples are adversarially corrupted. Our agnostic learning model is similar to -- in fact, stronger than -- Huber's contamination model in robust statistics. In this work, we study the fully observable Bernoulli case where the structure of the network is given. Even in this basic setting, previous learning algorithms either run in exponential time or lose dimension-dependent facto...
Bilal, Alsallakh; Jourabloo, Amin; Ye, Mao; Liu, Xiaoming; Ren, Liu
Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.
Full Text Available We consider a distributed constrained optimization problem over a time-varying network, where each agent only knows its own cost functions and its constraint set. However, the local constraint set may not be known in advance or consists of huge number of components in some applications. To deal with such cases, we propose a distributed stochastic subgradient algorithm over time-varying networks, where the estimate of each agent projects onto its constraint set by using random projection technique and the implement of information exchange between agents by employing asynchronous broadcast communication protocol. We show that our proposed algorithm is convergent with probability 1 by choosing suitable learning rate. For constant learning rate, we obtain an error bound, which is defined as the expected distance between the estimates of agent and the optimal solution. We also establish an asymptotic upper bound between the global objective function value at the average of the estimates and the optimal value.
Full Text Available This paper examines the differences of learning performance of 5 MNCs (multinational corporations that filed the largest number of patents in China. We establish the innovation network with the patent coauthorship data by these 5 MNCs and classify the networks by the tail of distribution curve of connections. To make a comparison of the learning performance of these 5 MNCs with differing network structures, we develop an organization learning model by regarding the reality as having m dimensions, which denotes the heterogeneous knowledge about the reality. We further set n innovative individuals that are mutually interactive and own unique knowledge about the reality. A longer (shorter distance between the knowledge of the individual and the reality denotes a lower (higher knowledge level of that individual. Individuals interact with and learn from each other within the small-world network. By making 1,000 numerical simulations and averaging the simulated results, we find that the differing structure of the small-world network leads to the differences of learning performance between these 5 MNCs. The network monopolization negatively impacts and network connectivity positively impacts learning performance. Policy implications in the conclusion section suggest that to improve firm learning performance, it is necessary to establish a flat and connective network.
Poell, R.F.; Krogt, F.J. van der
This article introduces a methodology for employees in organizations to set up and carry out their own group learning projects. It is argued that employees can use project-based learning to make their everyday learning more systematic at times, without necessarily formalizing it. The article
This study involved 458 ninth-grade students from two different Arab middle schools in Israel. Half of the students learned science using project-based learning strategies and the other half learned using traditional methods (non-project-based). The classes were heterogeneous regarding their achievements in the sciences. The adapted questionnaire…
Poell, R.F.; van der Krogt, F.J.
This article introduces a methodology for employees in organizations to set up and carry out their own group learning projects. It is argued that employees can use project-based learning to make their everyday learning more systematic at times, without necessarily formalizing it. The article
Hill, P.; Hille, R.
This report presents results and lessons learned by one of the so far largest assessments of a post-accidental situation. Funded by the Federal Republic of Germany the German Chernobyl Project investigated in the years 1991-1993 the radiological situation in contaminated regions of the Russian Federation, Belarus and Ukraine. Measurements included a mass screening of the population in order to determine the Cesium body burdens of 250,000+ individuals in more than 240 settlements as well as the evaluation of external doses in selected settlements with soil contaminations varying from less than 74 kBq/m 2 to about 3700 kBq/m 2 including some, where decontamination measures had previously been taken. Also in many settlements environmental monitoring was undertaken. For most individuals doses did not exceed the international annual limits set for the general population. Open and comprehensive communication of results was favourably accepted by the public. In a few settlements the radiological situation has been followed up till to date. (author)
Hansen, Lars Kai
The use of Bayesian methods to design cellular neural networks for signal processing tasks and the Boltzmann machine learning rule for parameter estimation is discussed. The learning rule can be used for models with hidden units, or for completely unsupervised learning. The latter is exemplified...
The key is to develop online learning strategies at each individual node. Specifically, through local information exchange with its neighbors, each...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning...Stochastic Online Learning in Dynamic Networks under Unknown Models This research aims to develop fundamental theories and practical algorithms for
Labus, A.; Despotovic-Zrakic, M.; Radenkovic, B.; Bogdanovic, Z.; Radenkovic, M.
This paper reports on the investigation of the possibilities of enhancing the formal e-learning process by harnessing the potential of informal game-based learning on social networks. The goal of the research is to improve the outcomes of the formal learning process through the design and implementation of an educational game on a social network…
Pollard, Carol E.
This work proposes that a subtle combination of three learning methods offering "just in time" project management knowledge, coupled with hands-on project management experience can be particularly effective in producing project management students with employable skills. Students were required to apply formal project management knowledge to gain…
van Rooij, Shahron Williams
This paper reports the results of a study of the extent to which processes and procedures from the discipline of project management can scaffold online project-based learning in a graduate-level instructional technology course, by facilitating intra-team interaction, enhancing project outcomes and promoting a positive project team experience. With…
Galas, Aleksander; Pilat, Aleksandra; Leonardi, Matilde; Tobiasz-Adamczyk, Beata
Every research project faces challenges regarding how to achieve its goals in a timely and effective manner. The purpose of this paper is to present a project evaluation methodology gathered during the implementation of the Participation to Healthy Workplaces and Inclusive Strategies in the Work Sector (the EU PATHWAYS Project). The PATHWAYS project involved multiple countries and multi-cultural aspects of re/integrating chronically ill patients into labor markets in different countries. This paper describes key project's evaluation issues including: (1) purposes, (2) advisability, (3) tools, (4) implementation, and (5) possible benefits and presents the advantages of a continuous monitoring. Project evaluation tool to assess structure and resources, process, management and communication, achievements, and outcomes. The project used a mixed evaluation approach and included Strengths (S), Weaknesses (W), Opportunities (O), and Threats (SWOT) analysis. A methodology for longitudinal EU projects' evaluation is described. The evaluation process allowed to highlight strengths and weaknesses and highlighted good coordination and communication between project partners as well as some key issues such as: the need for a shared glossary covering areas investigated by the project, problematic issues related to the involvement of stakeholders from outside the project, and issues with timing. Numerical SWOT analysis showed improvement in project performance over time. The proportion of participating project partners in the evaluation varied from 100% to 83.3%. There is a need for the implementation of a structured evaluation process in multidisciplinary projects involving different stakeholders in diverse socio-environmental and political conditions. Based on the PATHWAYS experience, a clear monitoring methodology is suggested as essential in every multidisciplinary research projects.
Kelling, Steve; Gerbracht, Jeff; Fink, Daniel; Lagoze, Carl; Wong, Weng-Keen; Yu, Jun; Damoulas, Theodoros; Gomes, Carla
In this paper we describe eBird, a citizen-science project that takes advantage of the human observational capacity to identify birds to species, which is then used to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human computation and mechanical computation. We call this a Human-Computer Learning Network,...
I Wayan Eka Mahendra
Full Text Available This study aims to determine differences simultaneously in motivation and mathematics learning outcomes between students taking project based learningmodel charged ethnomathematics and students who followed the conventional learning modelon the class VIII SMP Negeri 3 Abiansemalyear 2016/2017. It was a quasi experiment with a sample of 71 student obtain by using simple random sampling. The data were analyzed by one-way multivariate analysis (Manova.The results of this study indicate that there are differences in simultaneously in learning motivation and learning outcomes between students taking mathematics model project based learning charged ethnomathematics and students who followed the conventional learning model on the class VIII SMP Negeri 3 Abiansemal year 2016/2017. Besed on the research findings, junior high school teachers are suggested to improve their student learning outcome for mathematics. Teachers also need to use a learning models accurately and correctly.
Full Text Available This article is a reflection on the problems, challenges and strengths of network-based distance learning in archaeology. Based on the experience of one project - the PATOIS (Publications and Archives Teaching with Online Information Systems Project - it looks at how archaeologists might best respond (and by implication how they ought not to respond to the use of information technology in teaching. The PATOIS project is an attempt on behalf of a consortium of UK higher education institutions and allied research bodies to tell students about the information tools that are emerging in archaeology, and which are changing the culture of scholarship. Funded by the Joint Information Systems Committee (JISC and led by the Archaeology Data Service (ADS, PATOIS presents students with these new research tools and novel forms of academic literacy by direct exposure to 'primary' datasets. The PATOIS project is producing a set of Internet-based tutorials that lead students through different datasets and show how they may be deployed in research. This article describes the institutional and intellectual background to the project, and reports on the content of the tutorials themselves. Perhaps more importantly, it looks at the process through which PATOIS was developed, reviewing the challenges and constraints that the development team faced. Thereafter, we turn to the implementation of PATOIS in real teaching scenarios and look at how and when these have been successful as well as the challenges that remain unanswered. The project is not yet complete, so at this stage we can come to no firm conclusions about the long-term impact of PATOIS in facilitating change in undergraduate research training. Nonetheless, from the perspective of development work, the project has largely been completed, so those conclusions that may be drawn are most appropriately addressed to developers hoping or planning to undertake similar work in the future, or academics looking to
Wangel, Arne; Stærdahl, Jens; Bransholm Pedersen, Kirsten
Engineers and planners working in trans-national production and aid project interventions in Third World countries must be able to 're-invent' technological systems across cultures and plan and build the capacities of their counterparts. A series of joint courses on cleaner production (CP......) and environmental impact assessment (EIA) in Malaysia 1998-2003 has sought to address these needs for new competences. Differences in educational background and the work culture of the participants have presented difficulties during these courses, in particular in terms of achieving a mixed team building to turn...... some of the obstacles into resources for knowledge sharing. However, students have stressed their positive experience of cross-cultural communication. While a joint course of three week duration by itself may involve only limited cross-cultural learning, serving primarily as an introduction to a long...
If you are an OpenStack-based cloud operator with experience in OpenStack Compute and nova-network but are new to Neutron networking, then this book is for you. Some networking experience is recommended, and a physical network infrastructure is required to provide connectivity to instances and other network resources configured in the book.
Full Text Available Background: Every research project faces challenges regarding how to achieve its goals in a timely and effective manner. The purpose of this paper is to present a project evaluation methodology gathered during the implementation of the Participation to Healthy Workplaces and Inclusive Strategies in the Work Sector (the EU PATHWAYS Project. The PATHWAYS project involved multiple countries and multi-cultural aspects of re/integrating chronically ill patients into labor markets in different countries. This paper describes key project’s evaluation issues including: (1 purposes, (2 advisability, (3 tools, (4 implementation, and (5 possible benefits and presents the advantages of a continuous monitoring. Methods: Project evaluation tool to assess structure and resources, process, management and communication, achievements, and outcomes. The project used a mixed evaluation approach and included Strengths (S, Weaknesses (W, Opportunities (O, and Threats (SWOT analysis. Results: A methodology for longitudinal EU projects’ evaluation is described. The evaluation process allowed to highlight strengths and weaknesses and highlighted good coordination and communication between project partners as well as some key issues such as: the need for a shared glossary covering areas investigated by the project, problematic issues related to the involvement of stakeholders from outside the project, and issues with timing. Numerical SWOT analysis showed improvement in project performance over time. The proportion of participating project partners in the evaluation varied from 100% to 83.3%. Conclusions: There is a need for the implementation of a structured evaluation process in multidisciplinary projects involving different stakeholders in diverse socio-environmental and political conditions. Based on the PATHWAYS experience, a clear monitoring methodology is suggested as essential in every multidisciplinary research projects.
TD2005 build project network includes three layers. the first layer is backbone network. The second layer has m level and each level has horizontal subnetwork composed of n cluster bin ND2002-n. The third layer is equipment. When the second layer has only 1 level, the number of the equipment entered is 28 x n (n =3D 1,2,3,......63), which are allowed linking to horizontal subnetwork of TD2005 network. The number of the equipment of per cluster bin ND2002-n is 28. TD2005 network is used for P300 project. It has highest running reliability and long-term stability as well as powerful suitability and flexibility. It has many tie points, strong real-time ability and excellent interference suppression. Through testing, all kinds of characteristics are satisfactory. It is an ideal selection for industrial use
Liao, Hao; Zeng, An; Zhou, Mingyang; Mao, Rui; Wang, Bing-Hong
Weighted rating networks are commonly used by e-commerce providers nowadays. In order to generate an objective ranking of online items' quality according to users' ratings, many sophisticated algorithms have been proposed in the complex networks domain. In this paper, instead of proposing new algorithms we focus on a more fundamental problem: the nonlinear rating projection. The basic idea is that even though the rating values given by users are linearly separated, the real preference of users to items between the different given values is nonlinear. We thus design an approach to project the original ratings of users to more representative values. This approach can be regarded as a data pretreatment method. Simulation in both artificial and real networks shows that the performance of the ranking algorithms can be improved when the projected ratings are used.
Davidovitch, Nitza; Belichenko, Margarita; Kravchenko, Yurii
The article combines a theoretical approach to structuring knowledge that is based on the integrated use of fuzzy semantic network theory predicates, Boolean functions, theory of complexity of network structures and some practical aspects to be considered in the distance learning at the university. The paper proposes a methodological approach that…
Mohd Ishak Bin Ismail
Full Text Available Social networking sites, a web-based application have permeated the boundary between personal lives and student lives. Nowadays, students in higher learning used social networking site such as Facebook to facilitate their learning through the academic collaboration which it further enhances students’ social capital. Social networking site has many advantages to improve students’ learning. To date, Facebook is the leading social networking sites at this time which it being widely used by students in higher learning to communicate to each other, to carry out academic collaboration and sharing resources. Learning through social networking sites is based on the social interaction which learning are emphasizing on students, real world resources, active students` participation, diversity of learning resources and the use of digital tools to deliver meaningful learning. Many studies found the positive, neutral and negative impact of social networking sites on academic performance. Thus, this study will determine the relationship between Facebook usage and academic achievement. Also, it will investigate the association of social capital and academic collaboration to Facebook usage.
Oedewald, Pia; Gotcheva, Nadezhda
In safety critical industries many activities are currently carried out by subcontractor networks. Nevertheless, there are few studies where the core dimensions of resilience would have been studied in safety critical network activities. This paper claims that engineering resilience into a system is largely about steering the development of culture of the system towards better ability to anticipate, monitor, respond and learn. Thus, safety culture literature has relevance in resilience engineering field. This paper analyzes practical and theoretical challenges in applying the concept of safety culture in a complex, dynamic network of subcontractors involved in the construction of a new nuclear power plant in Finland, Olkiluoto 3. The concept of safety culture is in focus since it is widely used in nuclear industry and bridges the scientific and practical interests. This paper approaches subcontractor networks as complex systems. However, the management model of the Olkiluoto 3 project is to a large degree a traditional top-down hierarchy, which creates a mismatch between the management approach and the characteristics of the system to be managed. New insights were drawn from network governance studies. - Highlights: • We studied a relevant topical subject safety culture in nuclear new build project. • We integrated safety science challenges and network governance studies. • We produced practicable insights in managing safety of subcontractor networks
Baser, Derya; Ozden, M. Yasar; Karaarslan, Hasan
Background: Blending collaborative learning and project-based learning (PBL) based on Wolff (2003) design categories, students interacted in a learning environment where they developed their technology integration practices as well as their technological and collaborative skills. Purpose: The study aims to understand how seventh grade students…
This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Western Solar Utilization Network Region. (WHK)
Anazifa, R. D; Djukri, D
The study aims at finding (1) the effect of project-based learning and problem-based learning on student's creativity and critical thinking and (2) the difference effect of project-based learning and problem-based learning on student's creativity and critical thinking. This study is quasi experiment using non-equivalent control-group design. Research population of this study was all classes in eleventh grade of mathematics and natural science program of SMA N 1 Temanggung. The participants we...
Litt, Mark D.; Kadden, Ronald M.; Kabela-Cormier, Elise; Petry, Nancy M.
The Network Support Project was designed to determine whether a treatment could lead patients to change their social network from one that supports drinking to one that supports sobriety. This study reports 2-year posttreatment outcomes. Alcohol-dependent men and women (N = 210) were randomly assigned to 1 of 3 outpatient treatment conditions:…
Full Text Available The project-based learning is an active learning strategy that helps break the paradigm of traditional teaching methods. The student is involved in the learning proposal that includes the PiBL, on which one is not passive and becomes the main actor in one's own teaching learning process. Within this learning strategy, the teacher becomes a mediator between theory and practice thus each different subject interact with one another in order to develop a topic that is mutual to all areas because the learning environment is naturally interdisciplinary. The idea of this kind of learning strategy was applied during a workshop that took place with primary and secondary schoolteachers in order to help them approach the strategy in the classroom, contributing with experiences and ideas towards the interdisciplinary based project.
Khisamova, E. D.
Economical production implies primarily new approaches to culture of management and organization of production and offers a set of tools and techniques that allows reducing losses significantly and making the process cheaper and faster. Economical production tools are simple solutions that allow one to see opportunities for improvement of all aspects of the business, to reduce losses significantly, to constantly improve the whole spectrum of business processes, to increase significantly the transparency and manageability of the organization, to take advantage of the potential of each employee of the company, to increase competitiveness, and to obtain significant economic benefits without making large financial expenditures. Each of economical production tools solves a specific part of the problems, and only application of their combination will allow one to solve the problem or minimize it to acceptable values. The research of the governance process project "Lean Production" permitted studying the methods and tools of lean production and developing measures for their improvement.
Deng, Licai; Xin, Yu; Zhang, Xiaobin; Li, Yan; Jiang, Xiaojun; Wang, Guomin; Wang, Kun; Zhou, Jilin; Yan, Zhengzhou; Luo, Zhiquan
SONG (Stellar Observations Network Goup) is a low-cost ground based international collaboration aimed at two cutting edge problems in contemporary astrophysics in the time-domain: 1) Direct diagnostics of the internal structure of stars and 2) looking for and studying extra solar planets, possibly in the habitable zone. The general plan is to set up a network of 1m telescopes uniformly distributed in geographic latitude (in both hemispheres). China jointed the collaboration (initiated by Danish astronomers) at the very beginning. In addition to SONG's original plan (http://song.phys.au.dk), the Chinese team proposed a parallel photometry subnet work in the northern hemisphere, namely 50BiN (50cm Binocular Network, previously known as mini-SONG), to enable a large field photometric capability for the network, therefore maximising the potential of the network platform. The network will be able to produce nearly continuous time series observations of a number of selected objects with high resolution spectroscopy (SONG) and accurate photometry (50BiN), and to produce ultra-high accuracy photometry in dense field to look for micro-lensing events caused by planetary systems. This project has great synergy with Chinese Astronomical activities in Antarctica (Dome A), and other similar networks (e.g. LCOGT). The plan and current status of the project are overviewed in this poster.
Shahrabi Farahani, Hossein; Lagergren, Jens
Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) ,a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does no...
Koper, Rob; Sloep, Peter
Koper, E.J.R., Sloep, P.B. (2002) Learning Networks connecting people, organizations, autonomous agents and learning resources to establish the emergence of effective lifelong learning. RTD Programma into Learning Technologies 2003-2008. More is different… Heerlen, Nederland: Open Universiteit
van der Meij, Marjoleine G.; Kupper, Frank; Beers, Pieter J.; Broerse, Jacqueline E. W.
E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach "TransLearning" by investigation into how its storytelling e-tool supported informal vicarious…
Full Text Available We develop an efficient learning strategy of Chinese characters based on the network of the hierarchical structural relations between Chinese characters. A more efficient strategy is that of learning the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW strategy, which is based on a new measure of nodes' importance that considers both the weight of the nodes and its location in the network hierarchical structure. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as a second language. We find that the DNW method significantly outperforms the others, implying that the efficiency of current learning methods of major textbooks can be greatly improved.
Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi
Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.
Laing, Gregory Kenneth
There is a growing demand in higher education for universities to introduce teaching methods that achieve the learning outcomes of vocational education. The need for vocational educational outcomes was met in this study involving a service learning activity designed to provide basic professional auditing competencies. The details of the design and…
Gerhana, M. T. C.; Mardiyana, M.; Pramudya, I.
This research aimed to explore the effectiveness of Project-Based Learning (PjBL) with scientific approach viewed from interpersonal intelligence toward students’ achievement learning in mathematics. This research employed quasi experimental research. The subjects of this research were grade X MIPA students in Sleman Yogyakarta. The result of the research showed that project-based learning model is more effective to generate students’ mathematics learning achievement that classical model with scientific approach. This is because in PjBL model students are more able to think actively and creatively. Students are faced with a pleasant atmosphere to solve a problem in everyday life. The use of project-based learning model is expected to be the choice of teachers to improve mathematics education.
Veeraraghavan, Malathi [Univ. of Virginia, Charlottesville, VA (United States)
This report describes our accomplishments and activities for the project titled Terabit-Scale Hybrid Networking. The key accomplishment is that we developed, tested and deployed an Alpha Flow Characterization System (AFCS) in ESnet. It is being run in production mode since Sept. 2015. Also, a new QoS class was added to ESnet5 to support alpha flows.
Duong, T. A.
A new learning algorithm termed cascade error projection (CEP) is presented. CEP is an adaption of a constructive architecture from cascade correlation and the dynamical stepsize of A/D conversion from the cascade back propagation algorithm.
Pompe, P.P.M.; Feelders, A.J.; Feelders, A.J.
Recent literature strongly suggests that machine learning approaches to classification outperform "classical" statistical methods. We make a comparison between the performance of linear discriminant analysis, classification trees, and neural networks in predicting corporate bankruptcy. Linear
. The Design, Experience and Practice of Networked Learning will prove indispensable reading for researchers, teachers, consultants, and instructional designers in higher and continuing education; for those involved in staff and educational development, and for those studying post graduate qualifications...
A comprehensive theoretical framework is proposed for the learning of a class of gradient-type neural networks with an additive Gaussian white noise process. The study is based on stochastic sensitivity analysis techniques, and formal expressions are obtained for stochastic learning laws in terms of functional derivative sensitivity coefficients. The present method, based on Langevin simulation techniques, uses only the internal states of the network and ubiquitous noise to compute the learning information inherent in the stochastic correlation between noise signals and the performance functional. In particular, the method does not require the solution of adjoint equations of the back-propagation type. Thus, the present algorithm has the potential for efficiently learning network weights with significantly fewer computations. Application to an unfolded multi-layered network is described, and the results are compared with those obtained by using a back-propagation method
Berlanga, Adriana; Bitter-Rijpkema, Marlies; Brouns, Francis; Sloep, Peter; Fetter, Sibren
Berlanga, A. J., Bitter-Rijpkema, M., Brouns, F., Sloep, P. B., & Fetter, S. (2011). Personal Profiles: Enhancing Social Interaction in Learning Networks. International Journal of Web Based Communities, 7(1), 66-82.
Goldt, Sebastian; Seifert, Udo
Biological systems have to build models from their sensory input data that allow them to efficiently process previously unseen inputs. Here, we study a neural network learning a binary classification rule for these inputs from examples provided by a teacher. We analyse the ability of the network to apply the rule to new inputs, that is to generalise from past experience. Using stochastic thermodynamics, we show that the thermodynamic costs of the learning process provide an upper bound on the amount of information that the network is able to learn from its teacher for both batch and online learning. This allows us to introduce a thermodynamic efficiency of learning. We analytically compute the dynamics and the efficiency of a noisy neural network performing online learning in the thermodynamic limit. In particular, we analyse three popular learning algorithms, namely Hebbian, Perceptron and AdaTron learning. Our work extends the methods of stochastic thermodynamics to a new type of learning problem and might form a suitable basis for investigating the thermodynamics of decision-making.
Vyas, Rashmi; Faith, Minnie; Selvakumar, Dhayakani; Pulimood, Anna; Lee, Mary
The Christian Medical College, Vellore, in collaboration with Tufts University, Boston, conducted an advanced workshop in e-learning for medical faculty members in India. E-learning can enhance educational reforms for today's computer-literate generation, and keep faculty members up to speed in a rapidly changing world. The purpose of this paper is to report on the design and evaluation of a project-based faculty member development programme focused on developing faculty members as educators and as peer trainers who can use e-learning for educational reforms. During a 2-day workshop, 29 participants in groups of two or three developed 13 e-learning projects for implementation in their institutions. Evaluation of the workshop was through written feedback from the participants at the end of the workshop and by telephone interview with one participant from each project group at the end of one year. Content analysis of qualitative data was perfomed. The participants reported that they were motivated to implement e-learning projects and recognised the need for and usefulness of e-learning. The majority of projects (10 out of 13) that were implemented 'to some extent' or 'to a great extent' faced challenges with a lack of resources and administrative support, but faculty members were able to overcome them. E-learning can enhance educational reforms for today's computer-literate generation IMPLICATIONS: Designing feasible e-learning projects in small groups and obtaining hands-on experience with e-learning tools enhance the effectiveness of subsequent implementation. To successfully incorporate e-learning when designing educational reforms, faculty member training, continuing support and infrastructure facilities are essential. © 2016 John Wiley & Sons Ltd.
Zeng, Yifeng; Xiang, Yanping; Cordero, Jorge
(domain experts) to extract accurate information from a large Bayesian network due to dimensional difficulty. We define a formulation of local components and propose a clustering algorithm to learn such local components given complete data. The algorithm groups together most inter-relevant attributes......Bayesian networks are known for providing an intuitive and compact representation of probabilistic information and allowing the creation of models over a large and complex domain. Bayesian learning and reasoning are nontrivial for a large Bayesian network. In parallel, it is a tough job for users...... in a domain. We evaluate its performance on three benchmark Bayesian networks and provide results in support. We further show that the learned components may represent local knowledge more precisely in comparison to the full Bayesian networks when working with a small amount of data....
Natalia Stozhko; Boris Bortnik; Ludmila Mironova; Albina Tchernysheva; Ekaterina Podshivalova
The article studies a way of enhancing student cognition by using interdisciplinary project-based learning (IPBL) in a higher education institution. IPBL is a creative pedagogic approach allowing students of one area of specialisation to develop projects for students with different academic profiles. The application of this approach in the Ural State University of Economics resulted in a computer-assisted learning system (CALS) designed by IT students. The CALS was used in an analytical chemi...
Derrida, B.; Nadal, J.P.
It is possible to construct diluted asymmetric models of neural networks for which the dynamics can be calculated exactly. The authors test several learning schemes, in particular, models for which the values of the synapses remain bounded and depend on the history. Our analytical results on the relative efficiencies of the various learning schemes are qualitatively similar to the corresponding ones obtained numerically on fully connected symmetric networks
Nita, Andreea; Rozylowicz, Laurentiu; Manolache, Steluta; Ciocănea, Cristiana Maria; Miu, Iulia Viorica; Popescu, Viorel Dan
The main funding instrument for implementing EU policies on nature conservation and supporting environmental and climate action is the LIFE Nature programme, established by the European Commission in 1992. LIFE Nature projects (>1400 awarded) are applied conservation projects in which partnerships between institutions are critical for successful conservation outcomes, yet little is known about the structure of collaborative networks within and between EU countries. The aim of our study is to understand the nature of collaboration in LIFE Nature projects using a novel application of social network theory at two levels: (1) collaboration between countries, and (2) collaboration within countries using six case studies: Western Europe (United Kingdom and Netherlands), Eastern Europe (Romania and Latvia) and Southern Europe (Greece and Portugal). Using data on 1261 projects financed between 1996 and 2013, we found that Italy was the most successful country not only in terms of awarded number of projects, but also in terms of overall influence being by far the most influent country in the European LIFE Nature network, having the highest eigenvector (0.989) and degree centrality (0.177). Another key player in the network is Netherlands, which ensures a fast communication flow with other network members (closeness-0.318) by staying connected with the most active countries. Although Western European countries have higher centrality scores than most of the Eastern European countries, our results showed that overall there is a lower tendency to create partnerships between different organization categories. Also, the comparisons of the six case studies indicates significant differences in regards to the pattern of creating partnerships, providing valuable information on collaboration on EU nature conservation. This study represents a starting point in predicting the formation of future partnerships within LIFE Nature programme, suggesting ways to improve transnational
Borges, Nicole J.; Hartung, Paul J.
Although medical education has long recognized the importance of community service, most medical schools have not formally nor fully incorporated service learning into their curricula. To address this problem, we describe the initial design, development, implementation, and evaluation of a service-learning project within a first-year medical…
Andreasen, Lars Birch; Lerche Nielsen, Jørgen
The paper discusses how teaching and learning practices at universities can implement new information technologies, inspired by the traditions of problem- and project-based learning. The changing roles in the teacher-student relationship, and students’ development of information literacy are disc...
Baysura, Ozge Deniz; Altun, Sertel; Yucel-Toy, Banu
Problem Statement: Project-based learning (PBL) is a learning and teaching approach that makes students search for new knowledge and skills, helps them overcome real-life questions, and makes them design their own studies and performances. Research in Turkey reveals that teachers are not well-informed about PBL, can not guide students in this…
This report describes the Learning Disabled College Writer's Project, implemented at the University of Minnesota during the 1985-86 school year and designed to aid learning disabled college students master composition skills through training in the use of microcomputer word processors. Following an executive summary, an introduction states the…
Ciftci, Sabahattin; Baykan, Ayse Aysun
The purpose of this study is to evaluate project based learning in multi-grade classes. This study, based on a student-centered learning approach, aims to analyze students' and parents' interpretations. The study was done in a primary village school belonging to the Centre of Batman, already adapting multi-grade classes in their education system,…
Annetta, Leonard; Vallett, David; Fusarelli, Bonnie; Lamb, Richard; Cheng, Meng-Tzu; Holmes, Shawn; Folta, Elizabeth; Thurmond, Brandi
The purpose of this study was to examine the effect Serious Educational Games (SEGs) had on student interest in science in a federally funded game-based learning project. It can be argued that today's students are more likely to engage in video games than they are to interact in live, face-to-face learning environments. With a keen eye on…
Svihla, Vanessa; Reeve, Richard
While problem solving is a relatively well understood process, problem framing is less well understood, particularly with regard to supporting students to learn as they frame problems. Project-based learning classrooms are an ideal setting to investigate how teachers facilitate this process. Using participant observation, this study investigated…
This study describes an attempt of using an educational social networking platform, which is called Edmodo, for English language learning outside classrooms at tertiary level. Considering the notion of communicative competence, the instructor incorporated Edmodo into his English classes as a project which is a formal assignment. In the project,…
Helen B. Boholano
Full Text Available Education in the 21st century highlights globalization and internationalization. Preservice teachers in the 21st century are technology savvy. To effectively engage and teach generation Z students, preservice teachers will help the educational system meet this requirement. The educational systems must be outfitted with a prerequisite of ICT resources both hardware and software, and curricula must be designed to promote a collaborative learner-centered environment to which students will relate and respond. This study determines the 21st century skills possessed by the pre-service teachers in terms of social networking. Pre-service teachers use computers in very advanced ways, but educators must remember that they still need guidance to use technology safely and effectively. Through social media the pre-service teachers can use a multitude of applications, including Web 2.0, for their projects. Smart social networking requires critical-thinking skills and the ability to integrate and evaluate real-world scenarios and authentic learning skills for validation.
One of the teaching-learning strategies that may .... together in small groups, while sharing ideas ... lecturer and learner when scaffolding pedagogy, .... their roles, interaction and access to resources. ... When using the measure of practical.
Rongbutsri, Nikorn; Ryberg, Thomas; Zander, Pär-Ola
is in contrast to an artificial learning setting often found in traditional education. As many other higher education institutions, Aalborg University aims at providing learning environments that support the underlying pedagogical approach employed, and which can lead to different online and offline learning.......g. coordination, communication, negotiation, document sharing, calendars, meetings and version control. Furthermore, the pedagogical fabric of LMSs/VLEs have recently been called into question and critiqued by proponents of Personal Learning Environments (PLEs)(Ryberg, Buus, & Georgsen, 2011) . In sum....... making it important to understand and conceptualise students’ use of technology. Ecology is the study of relationship between organisms in an environment which is the set of circumstances surrounding that organism. Learning ecologies are the study of the relationship of a learner or a group of learners...
Batchelder, Cecil W.
Social networking tools used in learning provides instructional design with tools for transformative change in education. This study focused on defining the meanings and essences of social networking through the lived common experiences of 7 college students. The problem of the study was a lack of learner voice in understanding the value of social…
Yeo, Michelle Mei Ling
This paper aims to better understand the experiences of the youth and the educators with the tapping of social media like YouTube videos and the social networking application of Facebook for teaching and learning. This paper is interested in appropriating the benefits of leveraging of social media and networking applications like YouTube and…
structures, protein–protein interaction networks, social interactions, the Internet, and so on can be described by complex networks [1–5]. Recent developments in the understanding of complex networks has led to deeper insights about their origin and other properties [1–5]. One common realization that emerges from these ...
Full Text Available An organization’s strategic objectives are accomplished through portfolios. However, the materialization of portfolio risks may affect a portfolio’s sustainable success and the achievement of those objectives. Moreover, project interdependencies and cause–effect relationships between risks create complexity for portfolio risk analysis. This paper presents a model using Bayesian network (BN methodology for modeling and analyzing portfolio risks. To develop this model, first, portfolio-level risks and risks caused by project interdependencies are identified. Then, based on their cause–effect relationships all portfolio risks are organized in a BN. Conditional probability distributions for this network are specified and the Bayesian networks method is used to estimate the probability of portfolio risk. This model was applied to a portfolio of a construction company located in Iran and proved effective in analyzing portfolio risk probability. Furthermore, the model provided valuable information for selecting a portfolio’s projects and making strategic decisions.
Cohen, M.X.; Wilmes, K.A.; van de Vijver, I.
Understanding the neurophysiological mechanisms of learning is important for both fundamental and clinical neuroscience. We present a neurophysiologically inspired framework for understanding cortical mechanisms of feedback-guided learning. This framework is based on dynamic changes in systems-level
This action research was conducted to investigate the efficacy of networking, an adjusted cooperative learning method employed in an English literature class for non-English majors in China. Questionnaire was administered online anonymously to college students after a 14-week cooperative learning in literature class in a Chinese university, aiming…
Greenhow, Christine; Robelia, Beth
All students today are increasingly expected to develop technological fluency, digital citizenship, and other twenty-first century competencies despite wide variability in the quality of learning opportunities schools provide. Social network sites (SNSs) available via the internet may provide promising contexts for learning to supplement…
Cadima, Rita; Ojeda, Jordi; Monguet, Josep M.
Social networks play an essential role in learning environments as a key channel for knowledge sharing and students' support. In distributed learning communities, knowledge sharing does not occur as spontaneously as when a working group shares the same physical space; knowledge sharing depends even more on student informal connections. In this…
Hsiao, Amy; Brouns, Francis; Kester, Liesbeth; Sloep, Peter
Hsiao, Y. P., Brouns, F., Kester, L., & Sloep, P. B. (2009). Optimizing Knowledge Sharing In Learning Networks Through Peer Tutoring. In D. Kinshuk, J. Sampson, J. Spector, P. Isaías, P. Barbosa & D. Ifenthaler (Eds.). Proceedings of IADIS International Conference Cognition and Exploratory Learning
Lin, Chin-Hsi; Warschauer, Mark; Blake, Robert
Language Learning Social Network Sites (LLSNSs) have attracted millions of users around the world. However, little is known about how people participate in these sites and what they learn from them. This study investigated learners' attitudes, usage, and progress in a major LLSNS through a survey of 4,174 as well as 20 individual case studies. The…
Ivanov, V.V.; Puzynin, I.V.; Purehvdorzh, B.
First- and second-order learning methods for feed-forward multilayer networks are considered. A Newton-type algorithm is proposed and compared with the common back-propagation algorithm. It is shown that the proposed algorithm provides better learning quality. Some recommendations for their usage are given. 11 refs.; 1 fig.; 1 tab
Conroy, Michael G.
States that the Progressive Novella Project for high school students involves the collaborative writing of a 35-50 page novella. Explains that prior to the actual writing process, students are educated in the basic elements of fiction writing. Describes the division of labor into groups. Comments that the results of the project are invariably…
A self-teaching neural network used as an adaptive controller quickly learns to control an unstable reactor configuration. The network models the behavior of a human operator. It is trained by allowing it to operate the reactivity control impulsively. It is punished whenever either the power or fuel temperature stray outside technical limits. Using a simple paradigm, the network constructs an internal representation of the punishment and of the reactor system. The reactor is constrained to small power orbits
Full Text Available The semantic relations of hypernymy and hyponymy are widely used in various natural language processing tasks for modelling the subsumptions in common sense reasoning. Since the popularisation of the distributional semantics, a significant attention is paid to applying word embeddings for inducing the relations between words. In this paper, we show our preliminary results on adopting the projection learning technique for computing hypernyms from hyponyms using word embeddings. We also conduct a series of experiments on the Russian language and release the open source software for learning hyponym-hypernym projections using both CPUs and GPUs, implemented with the TensorFlow machine learning framework.
Yun-Ping, Sun; Jun-Min, Li; Hui-Lin, Wang; Jiang-An, Wang
In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)
Leeds Univ. (England). Centre for Studies in Science and Mathematics Education.
During the period 1984-1986, over 30 teachers from the Yorkshire (England) region have worked in collaboration with the Children's Learning in Science Project (CLIS) developing and testing teaching schemes in the areas of energy, particle theory, and plant nutrition. The project is based upon the constructivist approach to teaching. This document…
Harrison, Melinda A.; Dunbar, David; Lopatto, David
A service-learning project appropriate for a biochemistry or advanced biochemistry course was designed and implemented. The project involved students partnering with a homeless shelter to design informational pamphlets to be displayed at the shelter for the clients' use. The pamphlet topics were based on diseases studied within the course.…
Reijenga, J.C.; Siepe, A.H.M.; Yu, L.E.; Wang, C.H.
In order to stimulate international cooperation in collaborative learning, a pilot project was initiated in which students from different disciplines (3 TU/e departments), at different Universities (TU/e and the National University of Singapore) worked together on a project, using information
In this research we used a project-based learning approach to teach robotics basics to undergraduate business computing students. The course coverage includes basic electronics, robot construction and programming using arduino. Students developed and tested a robot prototype. The project was evaluated using a ...
Huang, Hsin-Hsiung; Su, Juing-Huei; Lee, Chyi-Shyong
A contest-oriented project for undergraduate students to learn implementation skills and theories related to intelligent mobile robots is presented in this paper. The project, related to Micromouse, Robotrace (Robotrace is the title of Taiwanese and Japanese robot races), and line-maze contests was developed by the embedded control system research…
Individuals and project-based organisations in the construction industry can learn in a (more) systematic way from case studies and the monitoring of underground construction works. Underground construction projects such as tunnels and excavations suffer as much or more from failure costs
The purpose of this study is to investigate the effect of project-based learning on students' attitudes toward the environment. In the study that was performed with 39 students who take the "Environmental Education" course, attitude changes toward the environment were investigated in students who developed projects on environmental…
Иван Николаевич Куринин
Full Text Available The article describes a method of interactive learning based on educational integrating projects. Some examples of content of such projects for the disciplines related to the study of information and Internet technologies and their application in management are presented.
Knight, Kevin; Murphey, Tim
In this article, we initially focus on how the conceptualization of leadership by Knight (2013a) in his leadership seminars became the basis for choosing a project-based learning (PBL) approach. We then consider how soft assembling can enhance the leadership project activities of student teams and group-work in general classes. Soft assembling…
A case study of project-based learning (PBL) implemented in Tianjin University of Technology and Education is presented. This multidiscipline project is innovated to meet the novel requirements of industry while keeping its traditional effectiveness in driving students to apply knowledge to practice and problem-solving. The implementation of PBL…
Project-based learning (PBL) that has authenticity in the pupils' world enables the teaching of science and technology to pupils from a variety of backgrounds. PBL has the potential to enable pupils to research, plan, design, and reflect on the creation of technological projects (Doppelt, 2000). Engineering education, which is common in Israel,…
Students can become disengaged from marketing material if they cannot see the direct application. Marketing material needs to be applied to a meaningful business task to engage and motivate students. This article introduces the Kickstarter Active Learning Project--an innovative semester-long project in which students create a Kickstarter…
De Jong, Tim; Fuertes, Alba; Schmeits, Tally; Specht, Marcus; Koper, Rob
De Jong, T., Fuertes, A., Schmeits, T., Specht, M., & Koper, R. (2009). A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks. In D. Goh (Ed.), Multiplatform E-Learning Systems and Technologies: Mobile Devices for Ubiquitous ICT-Based Education (pp.
Petley, Rebecca; Parker, Guy; Attewell, Jill
The Mobile Learning Network currently in its third year, is a unique collaborative initiative encouraging and enabling the introduction of mobile learning in English post-14 education. The programme, funded jointly by the Learning and Skills Council and participating colleges and schools and supported by LSN has involved nearly 40,000 learners and…
Yang, Z. Z.; Lu, X. M.; Tian, J. F.; Zhuang, C. G.; Wang, K.; Deng, L. C.
Driven by advancements in technology and scientific objectives, data acquisition in observational astronomy has been changed greatly in recent years. Fully automated or even autonomous ground-based network of telescopes has now become a tendency for time-domain observational projects. The Stellar Observations Network Group (SONG) is an international collaboration with the participation and contribution of the Chinese astronomy community. The scientific goal of SONG is time-domain astrophysics such as asteroseismology and open cluster research. The SONG project aims to build a global network of 1 m telescopes equipped with high-precision and high-resolution spectrographs, and two-channel lucky-imaging cameras. It is the Chinese initiative to install a 50 cm binocular photometry telescope at each SONG node sharing the network platform and infrastructure. This work is focused on design and implementation in technology and methodology of SONG/50BiN, a typical ground-based network composed of multiple sites and a variety of instruments.
Li, Xin; Gray, Kathleen; Verspoor, Karin; Barnett, Stephen
Online social networks (OSN) enable health professionals to learn informally, for example by sharing medical knowledge, or discussing practice management challenges and clinical issues. Understanding the learning context in OSN is necessary to get a complete picture of the learning process, in order to better support this type of learning. This study proposes critical contextual factors for understanding the learning context in OSN for health professionals, and demonstrates how these contextual factors can be used to analyse the learning context in a designated online learning environment for health professionals.
Yuk Chan, Cecilia Ka
Experiential learning pedagogy is taking a lead in the development of graduate attributes and educational aims as these are of prime importance for society. This paper shows a community service experiential project conducted in China. The project enabled students to serve the affected community in a post-earthquake area by applying their knowledge and skills. This paper documented the students' learning process from their project goals, pre-trip preparations, work progress, obstacles encountered to the final results and reflections. Using the data gathered from a focus group interview approach, the four components of Kolb's learning cycle, the concrete experience, reflection observation, abstract conceptualisation and active experimentation, have been shown to transform and internalise student's learning experience, achieving a variety of learning outcomes. The author will also explore how this community service type of experiential learning in the engineering discipline allowed students to experience deep learning and develop their graduate attributes.
Yasaka, Koichiro; Akai, Hiroyuki; Kunimatsu, Akira; Kiryu, Shigeru; Abe, Osamu
Deep learning with a convolutional neural network (CNN) is gaining attention recently for its high performance in image recognition. Images themselves can be utilized in a learning process with this technique, and feature extraction in advance of the learning process is not required. Important features can be automatically learned. Thanks to the development of hardware and software in addition to techniques regarding deep learning, application of this technique to radiological images for predicting clinically useful information, such as the detection and the evaluation of lesions, etc., are beginning to be investigated. This article illustrates basic technical knowledge regarding deep learning with CNNs along the actual course (collecting data, implementing CNNs, and training and testing phases). Pitfalls regarding this technique and how to manage them are also illustrated. We also described some advanced topics of deep learning, results of recent clinical studies, and the future directions of clinical application of deep learning techniques.
Ann M Hermundstad
Full Text Available The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.
Hansen, Daniel Sollie; Storjord, David
The goal of this thesis is to explore the teaching capabilities of games by motivating players through fun. We do this by first exploring perspectives of fun and learning in games; project management concepts and previous games. From these findings we implement our own game prototype where the player learns project management concepts simultaneously as they learn the game. This prototype is then evaluated through a number of experiments. Finally we discuss the results of the experiments and c...
Pérez Calle, Elio
The Department of Modern Physics of the University of Science and Technology of China is hosting a Tier-3 centre for the ATLAS experiment. A interdisciplinary team of researchers, engineers and students are devoted to the task of receiving, storing and analysing the scientific data produced by the LHC. In order to achieve the highest performance and to develop a knowledge base shared by all members of the team, the research activities and their coordination are being supported by an array of computing systems. These systems have been designed to foster communication, collaboration and coordination among the members of the team, both face-to-face and remotely, and both in synchronous and asynchronous ways. The result is a collaborative learning-research network whose main objectives are awareness (to get shared knowledge about other's activities and therefore obtain synergies), articulation (to allow a project to be divided, work units to be assigned and then reintegrated) and adaptation (to adapt information technologies to the needs of the group). The main technologies involved are Communication Tools such as web publishing, revision control and wikis, Conferencing Tools such as forums, instant messaging and video conferencing and Coordination Tools, such as time management, project management and social networks. The software toolkit has been deployed by the members of the team and it has been based on free and open source software.
Calle, Elio Pérez
The Department of Modern Physics of the University of Science and Technology of China is hosting a Tier-3 centre for the ATLAS experiment. A interdisciplinary team of researchers, engineers and students are devoted to the task of receiving, storing and analysing the scientific data produced by the LHC. In order to achieve the highest performance and to develop a knowledge base shared by all members of the team, the research activities and their coordination are being supported by an array of computing systems. These systems have been designed to foster communication, collaboration and coordination among the members of the team, both face-to-face and remotely, and both in synchronous and asynchronous ways. The result is a collaborative learning-research network whose main objectives are awareness (to get shared knowledge about other's activities and therefore obtain synergies), articulation (to allow a project to be divided, work units to be assigned and then reintegrated) and adaptation (to adapt information technologies to the needs of the group). The main technologies involved are Communication Tools such as web publishing, revision control and wikis, Conferencing Tools such as forums, instant messaging and video conferencing and Coordination Tools, such as time management, project management and social networks. The software toolkit has been deployed by the members of the team and it has been based on free and open source software.
It is widely acknowledged that to be able to teach language and literacy with digital technologies, teachers need to engage in relevant professional learning. Existing formal models of professional learning are often criticised for being ineffective. In contrast, informal and self-initiated forms of learning have been recently recognised as…
Blaabjerg, Frede; Teodorescu, Remus; Chen, Zhe
. Generally, the content of the curriculum should be more expanded without extra study time. This paper presents a teaching approach, which makes it possible very fast for the students to obtain in-depth skills into new research areas, and this method is the problem-oriented and project-based learning....... In this paper the necessary skills for power electronic engineers are outlined that is followed up by a description on how the problem-oriented and project-based learning are implemented. A complete curriculum in power electronics and drives at Aalborg University is presented where different power electronics...... related projects at different study levels also are presented....
Lehmann, Torsten; Woodburn, Robin
Self-learning chips to implement many popular ANN (artificial neural network) algorithms are very difficult to design. We explain why this is so and say what lessons previous work teaches us in the design of self-learning systems. We offer a contribution to the `biologically-inspired' approach......, explaining what we mean by this term and providing an example of a robust, self-learning design that can solve simple classical-conditioning tasks. We give details of the design of individual circuits to perform component functions, which can then be combined into a network to solve the task. We argue...
Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo
A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E
The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.
Wang, Ye; Dragoi, Valentin
Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.
Full Text Available This paper offers a critical examination of an e-learning project in the context of a Distance Education training program delivered to teacher trainers by an external university in Rwanda. In examining the successes and failures of the project, it uses a framework based on ideas promulgated by Moore (1995 and strives to provide guidance and reference for future projects in this field.
This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains feasible, albeit non-Bayesian. The topics discussed are: basic concepts about probabilities, graph theory and conditional independence; Bayesian network learning from data; Monte Carlo simulation techniques; and, the concept of incomplete data. In order to provide a coherent treatment of matters, thereby helping the reader to gain a thorough understanding of the whole concept of learning Bayesian networks from (in)complete data, this publication combines in a clarifying way all the issues presented in the papers with previously unpublished work.
Wessel, C; Spreckelsen, C
Problem- and project-based learning are approved methods to train students, graduates and post-graduates in scientific and other professional skills. The students are trained on realistic scenarios in a broader context. For students specializing in health informatics we introduced continued multidisciplinary project-based learning (CM-PBL) at a department of medical informatics. The training approach addresses both students of medicine and students of computer science. The students are full members of an ongoing research project and develop a project-related application or module, or explore or evaluate a sub-project. Two teachers guide and review the students' work. The training on scientific work follows a workflow with defined milestones. The team acts as peer group. By participating in the research team's work the students are trained on professional skills. A research project on a web-based information system on hospitals built the scenario for the realistic context. The research team consisted of up to 14 active members at a time, who were scientists and students of computer science and medicine. The well communicated educational approach and team policy fostered the participation of the students. Formative assessment and evaluation showed a considerable improvement of the students' skills and a high participant satisfaction. Alternative education approaches such as project-based learning empower students to acquire scientific knowledge and professional skills, especially the ability of life-long learning, multidisciplinary team work and social responsibility.
The IT PPM improvement process is not well understood, and our knowledge about what makes IT PPM improvement succeed or fail is not well developed. This article presents lessons learned from organizations trying to improve their IT PPM practice. Based on this research IT PPM practitioners are adv...
García Martín, Javier; Pérez Martínez, Jorge Enrique
The aim of this study is to evaluate the effects obtained after applying two active learning methodologies (cooperative learning and project based learning) to the achievement of the competence problem solving. This study was carried out at the Technical University of Madrid, where these methodologies were applied to two Operating Systems courses. The first hypothesis tested was whether the implementation of active learning methodologies favours the achievement of ?problem solving?. The secon...
Schreiber, Trine Louise
Introduction. With actor-network theory (ANT) as the theoretical lens the aim of the paper is to examine attempts to build network for shaping information literacy teaching. Method. The paper is based on a study of a project in 2014-2016 where information professionals representing ten educational...... libraries produced and implemented e-learning objects in information literacy teaching. The material was collected through interviews, observations, documents and feedback sessions. Analysis. Latour´s concept of translation and Callon´s four translation moments are used to analyze the network building...... that a network configuring information literacy teaching based on new interactive roles has not been stabilized. Conclusion. The paper concludes that the strength of ANT is first of all the mediation of an overview of different kinds of actors involved in network building. Further, the paper proposes to combine...
When the HIFAR research reactor was commissioned in 1958 it was both constructed and regulated by the then Australian Atomic Energy Commission. The situation now is much more complicated, with an independent regulator, The Australian Radiation Protection and Nuclear Safety Agency (ARPANSA) and oversight by national security agencies and the Australian Safeguards and Non proliferation Organisation (ASNO). In July 2000 ANSTO contracted INVAP SE a suitably qualified and experienced nuclear organisation based in Argentina to provide the Replacement Research Reactor (RRR). INVAP subcontracted an Australian entity, a joint venture between John Holland and Evans Deakin Industries (JHEDI) to provide resources in Australia. There is an international network of over 100 subcontractors providing services, products and materials to INVAP and JHEDI and a significant number of contractors providing project support services to ANSTO. The interaction of all these entities to provide the RRR is a significant networking challenge, involving a complex network of legal, contractual and functional relationships and communication processes
Broberg, Ole; Souza da Conceição, Carolina
Summative Statement: A preliminary framework for participatory design projects (PDP) was developed based on a retrospective analysis of five PDPs across different industries. The framework may serve as a guidance for planning and conducting PDPs. Problem statement: A growing number of experiences...... with participatory design or participatory ergonomics projects have been gained within the field of macro-ergonomics. It is suggested that the Participatory Ergonomics Framework (PEF) validated by Haines et al. (2002) needs to be updated based on these experiences and hence more focussed on design activities....... Research Objective / Question: The objective of this study was to update and design-orient the PEF based on experiences with PDPs within the last ten years. Methodology: Five participatory design projects across different industries were systematically analyzed and compared in order to develop a framework...
There’s a lot of talk about the benefits of deep learning (neural networks) and how it’s the new electricity that will power us into the future. Medical diagnosis, computer vision and speech recognition are all examples of use-cases where neural networks are being applied in our everyday business environment. This begs the question…what are the uses of neural-network applications for cyber security? How does the AI process work when applying neural networks to detect malicious software bombar...
Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff
The ability to recognize and predict temporal sequences of sensory inputs is vital for survival in natural environments. Based on many known properties of cortical neurons, hierarchical temporal memory (HTM) sequence memory recently has been proposed as a theoretical framework for sequence learning in the cortex. In this letter, we analyze properties of HTM sequence memory and apply it to sequence learning and prediction problems with streaming data. We show the model is able to continuously learn a large number of variableorder temporal sequences using an unsupervised Hebbian-like learning rule. The sparse temporal codes formed by the model can robustly handle branching temporal sequences by maintaining multiple predictions until there is sufficient disambiguating evidence. We compare the HTM sequence memory with other sequence learning algorithms, including statistical methods: autoregressive integrated moving average; feedforward neural networks-time delay neural network and online sequential extreme learning machine; and recurrent neural networks-long short-term memory and echo-state networks on sequence prediction problems with both artificial and real-world data. The HTM model achieves comparable accuracy to other state-of-the-art algorithms. The model also exhibits properties that are critical for sequence learning, including continuous online learning, the ability to handle multiple predictions and branching sequences with high-order statistics, robustness to sensor noise and fault tolerance, and good performance without task-specific hyperparameter tuning. Therefore, the HTM sequence memory not only advances our understanding of how the brain may solve the sequence learning problem but is also applicable to real-world sequence learning problems from continuous data streams.
Gisiger-Camata, Silvia; Nolan, Timiya S; Vo, Jacqueline B; Bail, Jennifer R; Lewis, Kayla A; Meneses, Karen
The Young Breast Cancer Survivors Network (Network) is an academic and community-based partnership dedicated to education, support, and networking. The Network used a multi-pronged approach via monthly support and networking, annual education seminars, website networking, and individual survivor consultation. Formative and summative evaluations were conducted using group survey and individual survivor interviews for monthly gatherings, annual education meetings, and individual consultation. Google Analytics was applied to evaluate website use. The Network began with 4 initial partnerships and grew to 38 in the period from 2011 to 2017. During this 5-year period, 5 annual meetings (598 attendees), 23 support and networking meetings (373), and 115 individual survivor consultations were conducted. The Network website had nearly 12,000 individual users and more than 25,000 page views. Lessons learned include active community engagement, survivor empowerment, capacity building, social media outreach, and network sustainability. The 5-year experiences with the Network demonstrated that a regional program dedicated to the education, support, networking, and needs of young breast cancer survivors and their families can become a vital part of cancer survivorship services in a community. Strong community support, engagement, and encouragement were vital components to sustain the program.
The first report of a connection between vocabulary learning and phonological short-term memory was published in 1988 (Baddeley, Papagno, & Vallar, 1988). At that time, both Susan Gathercole and I were involved in longitudinal studies, investigating the relation between nonword repetition and language learning. We both found a connection. Now,…
Holmes, Kathryn; Preston, Greg; Shaw, Kylie; Buchanan, Rachel
Effective professional learning for teachers is fundamental for any school system aiming to make transformative and sustainable change to teacher practice. This paper investigates the efficacy of Twitter as a medium for teachers to participate in professional learning by analysing the tweets of 30 influential users of the popular medium. We find…
Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco
Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.
Kampf, Constance Elizabeth
This is a series of online videos designed for the Project management course, in my YouTube channel. The video links are currently private for my university course. Please email me at firstname.lastname@example.org if you are interested in viewing them. The videos total about 12 hours of lectures, and are adapted...
Schanzenbach, Diane Whitmore
Project STAR (Student/Teacher Achievement Ratio) was a large-scale randomized trial of reduced class sizes in kindergarten through the third grade. Because of the scope of the experiment, it has been used in many policy discussions. For example, the California statewide class-size-reduction policy was justified, in part, by the successes of…
To lead a project effectively, one has to establish and maintain the flexibility to take appropriate actions when needed. Overconstrained situations should be avoided. To get on top of matters and stay there, a manager needs to anticipate what it will take to successfully complete the job. Physical and financial resources, personnel, and management structure are all important considerations. Carving out the necessary turf up front can make a world of difference to the project's outcome. After the "what," "where," and "when" of a project are nailed down, the next question is "how" to do the job. When I first interviewed for the job of Science Payload Manager on the Advanced Composition (ACE) Explorer mission, Dr. Edward Stone (ACE Principal Investigator) asked, "Al, give me an idea of your management style." It was a question I had not considered before. I thought about it for a few seconds and then answered, "Well, the first descriptive term that comes to mind is the word "tranquility". That seemed to startle him. So I added, "I guess what I mean is, that if the situation is tranquil and the project is running smoothly, then I've anticipated all the problems and taken necessary actions to head them off." He then asked: "Have you ever reached this state?" "No," I admitted, "but I strive for it." That seemed to satisfy him because I got the job.
Schwieger, Dana; Surendran, Ken
The value of experiential learning projects (which are usually major assessments in courses) in education has been touted since the early 1900s (Dewey, 1938). These projects have the potential to deepen students' understanding of course topics by allowing them to put concepts into practice and watch the results develop. However, experiential…
Remijan, Kelly W.
This article illustrates how mathematics teachers can develop design-focused projects, related to project-based learning, to motivate secondary mathematics students. With first-hand experience as a secondary mathematics teacher, I provide a series of steps related to the engineering design process, which are helpful to teachers in developing…
Luo, Airong; Omollo, Kathleen Ludewig
There is a growing trend of academic partnerships between U.S., Canadian, and European health science institutions and academic health centers in low- and middle-income countries. These partnerships often encounter challenges such as resource disparities and power differentials, which affect the motivations, expectations, balance of benefits, and results of the joint projects. Little has been discussed in previous literature regarding the communication and project management processes that affect the success of such partnerships. To fill the gap in the literature, the authors present lessons learned from the African Health Open Educational Resources Network, a multicountry, multiorganizational partnership established in May 2008. The authors introduce the history of the network, then discuss actively engaging stakeholders throughout the project's life cycle (design, planning, execution, and closure) through professional development, relationship building, and assessment activities. They focus on communication and management practices used to identify mutually beneficial project goals, ensure timely completion of deliverables, and develop sustainable sociotechnical infrastructure for future collaborative projects. These activities yielded an interactive process of action, assessment, and reflection to ensure that project goals and values were aligned with implementation. The authors conclude with a discussion of lessons learned and how the partnership project may serve as a model for other universities and academic health centers in high-income countries and low- and middle-income countries that are interested in or currently pursuing international academic partnerships.
Hasan A. A. Al-Rawi
Full Text Available Cognitive radio (CR enables unlicensed users (or secondary users, SUs to sense for and exploit underutilized licensed spectrum owned by the licensed users (or primary users, PUs. Reinforcement learning (RL is an artificial intelligence approach that enables a node to observe, learn, and make appropriate decisions on action selection in order to maximize network performance. Routing enables a source node to search for a least-cost route to its destination node. While there have been increasing efforts to enhance the traditional RL approach for routing in wireless networks, this research area remains largely unexplored in the domain of routing in CR networks. This paper applies RL in routing and investigates the effects of various features of RL (i.e., reward function, exploitation, and exploration, as well as learning rate through simulation. New approaches and recommendations are proposed to enhance the features in order to improve the network performance brought about by RL to routing. Simulation results show that the RL parameters of the reward function, exploitation, and exploration, as well as learning rate, must be well regulated, and the new approaches proposed in this paper improves SUs’ network performance without significantly jeopardizing PUs’ network performance, specifically SUs’ interference to PUs.
Lecluijze, Suzanne Elisabeth; de Haan, Mariëtte; Ünlüsoy, Asli
This exploratory study examines ethno-cultural diversity in youth's narratives regarding their "online" learning experiences while also investigating how these narratives can be understood from the analysis of their online network structure and composition. Based on ego-network data of 79 respondents this study compared the…
This dissertation discusses the role the social activity of networking plays in lifelong learners’ professional and personal continuous development. The main hypothesis of this thesis is that networking is a learning strategy for lifelong learners, in which conversations are key activities through which they reassess their held thoughts and make sense of their experiences together with others.
This dissertation discusses the role the social activity of networking plays in lifelong learners’ professional and personal continuous development. The main hypothesis of this thesis is that networking is a learning strategy for lifelong learners, in which conversations are key activities through
Full Text Available This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the action research methodology. It then identifies key dimensions of four interconnected developmental processes–orientation, communication, socialisation and organisation–that were associated with ‘learning to learn' in the course's networked environment, and offers a flavour of participants' experiences in relation to these processes. A number of key evaluation issues that arose are highlighted. Finally, the paper presents the broad conceptual framework for the design and facilitation of process support in networked learning that was derived from this research. The framework proposes a strong, explicit focus on support for process as well as domain learning, and progression from tighter to looser design and facilitation structures for process-focused (as well as domain-focused learning tasks.
During the last ten years, Engineering Education has undergone tremendous changes. A lot of these changes were caused by external and internal factors. The external factors such as government policy concerning resources, and educational and quality assurance policies are rather simple to describe......). Particularly five Engineering University Colleges have undergone changes towards PBL. The Pedagogical Network for Danish Engineering Education (IPN) has been one of the central agents in the change processes for engineering education in Denmark. IPN has been responsible for staff and faculty development...
van den Beemt, Antoine; Ketelaar, Evelien; Diepstraten, Isabelle; de Laat, Maarten
Background: This paper discusses teachers' perspectives on learning networks and their motives for participating in these networks. Although it is widely held that teachers' learning may be developed through learning networks, not all teachers participate in such networks. Purpose: The theme of reciprocity, central to studies in the area of…
van den Beemt, A.A.J.; Ketelaar, E.; Diepstraten, I.; de Laat, M.
Background: This paper discusses teachers’ perspectives on learning networks and their motives for participating in these networks. Although it is widely held that teachers’ learning may be developed through learning networks, not all teachers participate in such networks. Purpose: The theme of
One of the key fundaments of building a society is common interest or shared aims of the group members. This research work is a try to analyze web-based services oriented towards money collection for various social and charity projects. The phenomenon of social founding is worth a closer look at because its success strongly depends on the ability to build an ad-hoc or persistent groups of people sharing their believes and willing to support external institutions or individuals. The paper presents a review of money collection sites, various models of donation and money collection process as well as ways how the projects' results are reported to their founders. There is also a proposal of money collection service, where donators are not charged until total declared help overheads required resources to complete the project. The risk of missing real donations for declared payments, after the collection is closed, can be assessed and minimized by building a social network.
Ghassan F. Issa
Full Text Available This paper presents a comprehensive framework for building collaborative learning networks within higher educational institutions. This framework focuses on systems design and implementation issues in addition to a complete set of evaluation, and analysis tools. The objective of this project is to improve the standards of higher education in Jordan through the implementation of transparent, collaborative, innovative, and modern quality educational programs. The framework highlights the major steps required to plan, design, and implement collaborative learning systems. Several issues are discussed such as unification of courses and program of studies, using appropriate learning management system, software design development using Agile methodology, infrastructure design, access issues, proprietary data storage, and social network analysis (SNA techniques.
Levinsen, Karin; Nielsen, Janni; Sørensen, Birgitte Holm
The transition from the industrial to the networked society produces contradictions that challenges the educational system and force it to adapt to new conditions. In a Danish virtual Master in Information and Communication Technologies and Learning (MIL) these contradictions appear as a field of...... which enables students to develop Networked Society competencies and maintain progression in the learning process also during the online periods. Additionally we suggest that our model contributes to the innovation of a networked society's design for learning....... is continuously decreasing. We teach for deep learning but are confronted by students' cost-benefit strategies when they navigate through the study programme under time pressure. To meet these challenges a Design for Learning Model has been developed. The aim is to provide a scaffold that ensures students......' acquisition of the subject matter within a time limit and at a learning quality that support their deep learning process during a subsequent period of on-line study work. In the process of moving from theory to application the model passes through three stages: 1) Conceptual modelling; 2) Orchestration, and 3...
Studený, Milan; Haws, D.
Roč. 55, č. 4 (2014), s. 1043-1071 ISSN 0888-613X R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * integer linear programming * characteristic imset * essential graph Subject RIV: BA - General Mathematics Impact factor: 2.451, year: 2014 http://library.utia.cas.cz/separaty/2014/MTR/studeny-0427002.pdf
Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki
In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.
De Kraker, Joop; Cörvers, Ron; Ruelle, Christine; Valkering, Pieter
Sustainable regional development is a participatory, multi-actor process, involving a diversity of societal stakeholders, administrators, policy makers, practitioners and scientific experts. In this process, mutual and collective learning plays a major role as participants have to exchange and
Full Text Available Present technology and the accessibility of internet have made distance learning easier, more efficient, and more convenient for students. This technology allows instructors and students to communicate asynchronously, at times and locations of their own choosing, by exchanging printed or electronic information. The use of project-based approach is being recognized in the literature as a potential component of courses in the faculties of engineering, science, and technology. Instructors may have to restructure their course differently to accommodate and facilitate the effectiveness of distance learning. A project-based engineering course, traditionally taught in a classroom settings using live mode at the College of Engineering and Computer Sciences at the University of Central Florida (UCF has been transformed to a distance course taught using distance modes. In this case, pedagogical transitions and adjustments are required, in particular for obtaining an optimal balance between the course material and the project work. Project collaboration in groups requires communication, which is possible with extensive utilization of new information and communication technology, such as virtual meetings. This paper discusses the course transition from live to distance modes and touches on some issues as they relate to the effectiveness of this methodology and the lessons learned from its application within different context. More specifically, this discussion includes the benefit of implementing project-based work in the domain of the distance learning courses.
Ryberg, Thomas; Christiansen, Ellen
This paper examines the affordance of the Danish social networking site Mingler.dk for peer-to-peer learning and development. With inspiration from different theoretical frameworks, the authors argue how learning and development in such social online systems can be conceptualised and analysed....... Theoretically the paper defines development in accordance with Vygotsky's concept of the zone of proximal development, and learning in accordance with Wenger's concept of communities of practice. The authors suggest analysing the learning and development taking place on Mingler.dk by using these concepts...... supplemented by the notion of horizontal learning adopted from Engestrm and Wenger. Their analysis shows how horizontal learning happens by crossing boundaries between several sites of engagement, and how the actors' multiple membership enables the community members to draw on a vast amount of resources from...
Margolis, Alvaro; Parboosingh, John
Prior interpersonal relationships and interactivity among members of professional associations may impact the learning process in continuing medical education (CME). On the other hand, CME programs that encourage interactivity between participants may impact structures and behaviors in these professional associations. With the advent of information and communication technologies, new communication spaces have emerged that have the potential to enhance networked learning in national and international professional associations and increase the effectiveness of CME for health professionals. In this article, network science, based on the application of network theory and other theories, is proposed as an approach to better understand the contribution networking and interactivity between health professionals in professional communities make to their learning and adoption of new practices over time. © 2015 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on Continuing Medical Education, Association for Hospital Medical Education.
Temple, D.; Poole, M.; Camp, M.
Since the advent of modern computational capacity, machine learning algorithms and techniques have served as a method through which to solve numerous challenging problems. However, for machine learning methods to be effective and robust, sufficient data sets must be available; specifically, in the space domain, these are generally difficult to acquire. Rapidly evolving commercial space-situational awareness companies boast the capability to collect hundreds of thousands nightly observations of resident space objects (RSOs) using a ground-based optical sensor network. This provides the ability to maintain custody of and characterize thousands of objects persistently. With this information available, novel deep learning techniques can be implemented. The technique discussed in this paper utilizes deep learning to make distinctions between nightly data collects with and without maneuvers. Implementation of these techniques will allow the data collected from optical ground-based networks to enable well informed and timely the space domain decision making.
Full Text Available This study aims to improve the physics Science Process Skills Students on cognitive and psychomotor aspects by using model based Project Based Learning training.The object of this study is the Project Based Learning model used in the learning process of Computationa Physics.The method used is classroom action research through two learning cycles, each cycle consisting of the stages of planning, implementation, observation and reflection. In the first cycle of treatment with their emphasis given training in the first phase up to third in the model Project Based Learning, while the second cycle is given additional treatment with emphasis discussion is collaboration in achieving the best results for each group of products. The results of data analysis showed increased ability to think Students on cognitive and Science Process Skills in the psychomotor.
Hon, Marc; Stello, Dennis; Yu, Jie
Deep learning in the form of 1D convolutional neural networks have previously been shown to be capable of efficiently classifying the evolutionary state of oscillating red giants into red giant branch stars and helium-core burning stars by recognizing visual features in their asteroseismic...... frequency spectra. We elaborate further on the deep learning method by developing an improved convolutional neural network classifier. To make our method useful for current and future space missions such as K2, TESS, and PLATO, we train classifiers that are able to classify the evolutionary states of lower...
Lee, Y.C.; Doolen, G.; Chen, H.H.; Sun, G.Z.; Maxwell, T.; Lee, H.Y.
A high-order correlation tensor formalism for neural networks is described. The model can simulate auto associative, heteroassociative, as well as multiassociative memory. For the autoassociative model, simulation results show a drastic increase in the memory capacity and speed over that of the standard Hopfield-like correlation matrix methods. The possibility of using multiassociative memory for a learning universal inference network is also discussed. 9 refs., 5 figs.
Kuss, Daria J.; Griffiths, Mark D.
Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning onl...
Shen, Li; Lin, Zhouchen; Huang, Qingming
Learning deeper convolutional neural networks becomes a tendency in recent years. However, many empirical evidences suggest that performance improvement cannot be gained by simply stacking more layers. In this paper, we consider the issue from an information theoretical perspective, and propose a novel method Relay Backpropagation, that encourages the propagation of effective information through the network in training stage. By virtue of the method, we achieved the first place in ILSVRC 2015...
Pfeiffer, Joseph J.
People increasingly communicate through email and social networks to maintain friendships and conduct business, as well as share online content such as pictures, videos and products. Relational machine learning (RML) utilizes a set of observed attributes and network structure to predict corresponding labels for items; for example, to predict individuals engaged in securities fraud, we can utilize phone calls and workplace information to make joint predictions over the individuals. However, in...
Djordjilović, V.; Chiogna, M.; Vomlel, Jiří
Roč. 88, č. 1 (2017), s. 602-613 ISSN 0888-613X R&D Projects: GA ČR(CZ) GA16-12010S Institutional support: RVO:67985556 Keywords : Bayesian networks * Structure learning * Reverse engineering * Gene networks Subject RIV: JD - Computer Applications, Robotics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.845, year: 2016 http://library.utia.cas.cz/separaty/2017/MTR/vomlel-0477168.pdf
Zenke, Friedemann; Ganguli, Surya
A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.
Bridges, S; Chang, J W W; Chu, C H; Gardner, K
Situated and sociocultural perspectives on learning indicate that the design of complex tasks supported by educational technologies holds potential for dental education in moving novices towards closer approximation of the clinical outcomes of their expert mentors. A cross-faculty-, student-centred, web-based project in operative dentistry was established within the Universitas 21 (U21) network of higher education institutions to support university goals for internationalisation in clinical learning by enabling distributed interactions across sites and institutions. This paper aims to present evaluation of one dental faculty's project experience of curriculum redesign for deeper student learning. A mixed-method case study approach was utilised. Three cohorts of second-year students from a 5-year bachelor of dental surgery (BDS) programme were invited to participate in annual surveys and focus group interviews on project completion. Survey data were analysed for differences between years using multivariate logistical regression analysis. Thematic analysis of questionnaire open responses and interview transcripts was conducted. Multivariate logistic regression analysis noted significant differences across items over time indicating learning improvements, attainment of university aims and the positive influence of redesign. Students perceived the enquiry-based project as stimulating and motivating, and building confidence in operative techniques. Institutional goals for greater understanding of others and lifelong learning showed improvement over time. Despite positive scores, students indicated global citizenship and intercultural understanding were conceptually challenging. Establishment of online student learning communities through a blended approach to learning stimulated motivation and intellectual engagement, thereby supporting a situated approach to cognition. Sociocultural perspectives indicate that novice-expert interactions supported student development of
Mange Gladys Nkatha
Full Text Available Abstract Institutions of higher learning are facing greater challenges to change and subjected to various transformations in the surrounding environment including technology. These challenge and motivate them to explore new ways to improve their teaching approaches. This study sought to investigate the use of social networking site in institutions of higher learning. To this end two objectives were formulated 1 to investigate the current state of the use of social networking sites by the students 2 investigate how social networking sites can be used to promote authentic learning in institutions of higher learning. The study adopted exploratory approach using descriptive survey design where a sample of 10 67 students were picked from Jomo Kenyatta University of Agriculture and Technology JKUAT main campus. The findings indicate the use of social networking sites is a viable option as the students are not only members of social networking sites but also that majority have access to the requisite technological devices. Additionally recommendations for ensuring authentic learning were presented. The researcher recommends the exploration of the leveraging of the existing social networking sites for learning in conjunction with key stakeholders.
Full Text Available This article explores academics’ writing practices, focusing on the ways in which they use digital platforms in their processes of collaborative learning. It draws on interview data from a research project that has involved working closely with academics across different disciplines and institutions to explore their writing practices, understanding academic literacies as situated social practices. The article outlines the characteristics of academics’ ongoing professional learning, demonstrating the importance of collaborations on specific projects in generating learning in relation to using digital platforms and for sharing and collaborating on scholarly writing. A very wide range of digital platforms have been identified by these academics, enabling new kinds of collaboration across time and space on writing and research; but challenges around online learning are also identified, particularly the dangers of engaging in learning in public, the pressures of ‘always-on’-ness and the different values systems around publishing in different forums.
Paul Alexander Howard-Jones
Full Text Available We hypothesised that embedding educational learning in a game would improve learning outcomes, with increased engagement and recruitment of cognitive resources evidenced by increased activation of working memory network (WMN and deactivation of Default Mode Network (DMN regions. In an fMRI study, we compared activity during periods of learning in three conditions that were increasingly game-like: Study-only (when periods of learning were followed by an exemplar question together with its correct answer, Self-quizzing (when periods of learning were followed by a multiple choice question in return for a fixed number of points and Game-based (when, following each period of learning, participants competed with a peer to answer the question for escalating, uncertain rewards. DMN hubs deactivated as conditions became more game-like, alongside greater self-reported engagement and, in the Game-based condition, higher learning scores. These changes did not occur with any detectable increase in WMN activity. Additionally, ventral striatal activation was associated with responding to questions and receiving positive question feedback. Results support the significance of DMN deactivation for educational learning, and are aligned with recent evidence suggesting DMN and WMN activity may not always be anti-correlated.
Howard-Jones, Paul A; Jay, Tim; Mason, Alice; Jones, Harvey
We hypothesized that embedding educational learning in a game would improve learning outcomes, with increased engagement and recruitment of cognitive resources evidenced by increased activation of working memory network (WMN) and deactivation of default mode network (DMN) regions. In an fMRI study, we compared activity during periods of learning in three conditions that were increasingly game-like: Study-only (when periods of learning were followed by an exemplar question together with its correct answer), Self-quizzing (when periods of learning were followed by a multiple choice question in return for a fixed number of points) and Game-based (when, following each period of learning, participants competed with a peer to answer the question for escalating, uncertain rewards). DMN hubs deactivated as conditions became more game-like, alongside greater self-reported engagement and, in the Game-based condition, higher learning scores. These changes did not occur with any detectable increase in WMN activity. Additionally, ventral striatal activation was associated with responding to questions and receiving positive question feedback. Results support the significance of DMN deactivation for educational learning, and are aligned with recent evidence suggesting DMN and WMN activity may not always be anti-correlated.
Duane, Gregory S.
It is shown that the "FORCE" algorithm for learning in arbitrarily connected networks of simple neuronal units can be cast as a Kalman Filter, with a particular state-dependent form for the background error covariances. The resulting interpretation has implications for initialization of the learning algorithm, leads to an extension to include interactions between the weight updates for different neurons, and can represent relationships within groups of multiple target output signals.
We study learning and generalisation ability of a specific two-layer feed-forward neural network and compare its properties to that of a simple perceptron. The input patterns are mapped nonlinearly onto a hidden layer, much larger than the input layer, and this mapping is either fixed or may result from an unsupervised learning process. Such preprocessing of initially uncorrelated random patterns results in the correlated patterns in the hidden layer. The hidden-to-output mapping of the net...
We propose that a general learning system should have three kinds of agents corresponding to sensory, short-term, and long-term memory that implicitly will facilitate context-free and context-sensitive aspects of learning. These three agents perform mututally complementary functions that capture aspects of the human cognition system. We investigate the use of CC1 and CC4 networks for use as models of short-term and sensory memory.
Training biomedical engineers while effectively keeping up with the fast paced scientific breakthroughs and the growth in technical innovations poses arduous challenges for educators. Traditional pedagogical methods are employed for coping with the increasing demands in biomedical engineering (BME) training and continuous improvements have been attempted with some success. Project-based learning (PBL) is an academic effort that challenges students by making them carry out interdisciplinary projects aimed at accomplishing a wide range of student learning outcomes. PBL has been shown to be effective in the medical field and has been adopted by other fields including engineering. The impact of globalization in healthcare appears to be steadily increasing which necessitates the inclusion of awareness of relevant international activities in the curriculum. Numerous difficulties are encountered when the formation of a collaborative team is tried, and additional difficulties occur as the collaboration team is extended to international partners. Understanding and agreement of responsibilities becomes somewhat complex and hence the collaborative project has to be planned and executed with clear understanding by all partners and participants. A model for training BME students by adopting PBL with international collaboration is proposed. The results of previous BME project work with international collaboration fit partially into the model. There were many logistic issues and constraints; however, the collaborative projects themselves greatly enhanced the student learning outcomes. This PBL type of learning experience tends to promote long term retention of multidisciplinary material and foster high-order cognitive activities such as analysis, synthesis and evaluation. In addition to introducing the students to experiences encountered in the real-life workforce, the proposed approach enhances developing professional contracts and global networking. In conclusion, despite
Gardner, Brian; Sporea, Ioana; Grüning, André
Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we examine how multilayered networks of spiking neurons can learn to encode for input patterns using a fully temporal coding scheme. To this end, we introduce a new supervised learning rule, MultilayerSpiker, that can train spiking networks containing hidden layer neurons to perform transformations between spatiotemporal input and output spike patterns. The performance of the proposed learning rule is demonstrated in terms of the number of pattern mappings it can learn, the complexity of network structures it can be used on, and its classification accuracy when using multispike-based encodings. In particular, the learning rule displays robustness against input noise and can generalize well on an example data set. Our approach contributes to both a systematic understanding of how computations might take place in the nervous system and a learning rule that displays strong technical capability.
Alvarez Valencia, Jose Aldemar
Recent progress in the discipline of computer applications such as the advent of web-based communication, afforded by the Web 2.0, has paved the way for novel applications in language learning, namely, social networking. Social networking has challenged the area of Computer Mediated Communication (CMC) to expand its research palette in order to…
Jong, Amos A. de; Runhaar, Hens A.C.; Runhaar, Piety R.; Kolhoff, Arend J.; Driessen, Peter P.J.
A growing number of low and middle income nations (LMCs) have adopted some sort of system for environmental impact assessment (EIA). However, generally many of these EIA systems are characterised by a low performance in terms of timely information dissemination, monitoring and enforcement after licencing. Donor actors (such as the World Bank) have attempted to contribute to a higher performance of EIA systems in LMCs by intervening at two levels: the project level (e.g. by providing scoping advice or EIS quality review) and the system level (e.g. by advising on EIA legislation or by capacity building). The aims of these interventions are environmental protection in concrete cases and enforcing the institutionalisation of environmental protection, respectively. Learning by actors involved is an important condition for realising these aims. A relatively underexplored form of learning concerns learning at EIA system-level via project level donor interventions. This ‘indirect’ learning potentially results in system changes that better fit the specific context(s) and hence contribute to higher performances. Our exploratory research in Ghana and the Maldives shows that thus far, ‘indirect’ learning only occurs incidentally and that donors play a modest role in promoting it. Barriers to indirect learning are related to the institutional context rather than to individual characteristics. Moreover, ‘indirect’ learning seems to flourish best in large projects where donors achieved a position of influence that they can use to evoke reflection upon system malfunctions. In order to enhance learning at all levels donors should thereby present the outcomes of the intervention elaborately (i.e. discuss the outcomes with a large audience), include practical suggestions about post-EIS activities such as monitoring procedures and enforcement options and stimulate the use of their advisory reports to generate organisational memory and ensure a better information
Jong, Amos A. de, E-mail: email@example.com [Innovation Management, Utrecht (Netherlands); Runhaar, Hens A.C., E-mail: firstname.lastname@example.org [Section of Environmental Governance, Utrecht University, Utrecht (Netherlands); Runhaar, Piety R., E-mail: email@example.com [Organisational Psychology and Human Resource Development, University of Twente, Enschede (Netherlands); Kolhoff, Arend J., E-mail: Akolhoff@eia.nl [The Netherlands Commission for Environmental Assessment, Utrecht (Netherlands); Driessen, Peter P.J., E-mail: firstname.lastname@example.org [Department of Innovation and Environment Sciences, Utrecht University, Utrecht (Netherlands)
A growing number of low and middle income nations (LMCs) have adopted some sort of system for environmental impact assessment (EIA). However, generally many of these EIA systems are characterised by a low performance in terms of timely information dissemination, monitoring and enforcement after licencing. Donor actors (such as the World Bank) have attempted to contribute to a higher performance of EIA systems in LMCs by intervening at two levels: the project level (e.g. by providing scoping advice or EIS quality review) and the system level (e.g. by advising on EIA legislation or by capacity building). The aims of these interventions are environmental protection in concrete cases and enforcing the institutionalisation of environmental protection, respectively. Learning by actors involved is an important condition for realising these aims. A relatively underexplored form of learning concerns learning at EIA system-level via project level donor interventions. This 'indirect' learning potentially results in system changes that better fit the specific context(s) and hence contribute to higher performances. Our exploratory research in Ghana and the Maldives shows that thus far, 'indirect' learning only occurs incidentally and that donors play a modest role in promoting it. Barriers to indirect learning are related to the institutional context rather than to individual characteristics. Moreover, 'indirect' learning seems to flourish best in large projects where donors achieved a position of influence that they can use to evoke reflection upon system malfunctions. In order to enhance learning at all levels donors should thereby present the outcomes of the intervention elaborately (i.e. discuss the outcomes with a large audience), include practical suggestions about post-EIS activities such as monitoring procedures and enforcement options and stimulate the use of their advisory reports to generate organisational memory and ensure a better
Fontoura Costa, Luciano da
An approach to modeling knowledge acquisition in terms of walks along complex networks is described. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchical networks--i.e., networks composed of successive interconnected layers--are related to compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks--i.e., unreachable nodes--the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barabasi-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaus of knowledge stagnation in the case of the preferential movement strategy in the presence of conditional edges
Kean, Ang Chooi; Kwe, Ngu Moi
This paper reports on a collaborative effort taken by a team of three teacher educators in using the Project Based Learning (PBL) approach in the teaching of Japanese culture with the aim to investigate the presence of actual "meaningful learning" among 15 students of a 12-Week Preparatory Japanese Language course under a teacher…
The paper first explores the factors that affect the use of social networks to enhance teaching and learning experiences among students and lecturers, using structured questionnaires prepared based on the Push-Pull-Mooring framework. A total of 455 students and lecturers from higher learning institutions in Malaysia participated in this study.…
Foshee Reed, Lynn
The Joint Science Education Project (JSEP) is a successful summer science and culture opportunity in which students and teachers from the United States, Denmark, and Greenland come together to learn about the research conducted in Greenland and the logistics involved in supporting the research. They conduct experiments first-hand and participate in inquiry-based educational activities alongside scientists and graduate students at a variety of locations in and around Kangerlussuaq, Greenland, and on the top of the ice sheet at Summit Station. The Joint Committee, a high-level forum involving the Greenlandic, Danish and U.S. governments, established the Joint Science Education Project in 2007, as a collaborative diplomatic effort during the International Polar Year to: • Educate and inspire the next generation of polar scientists; • Build strong networks of students and teachers among the three countries; and • Provide an opportunity to practice language and communication skills Since its inception, JSEP has had 82 student and 22 teacher participants and has involved numerous scientists and field researchers. The JSEP format has evolved over the years into its current state, which consists of two field-based subprograms on site in Greenland: the Greenland-led Kangerlussuaq Science Field School and the U.S.-led Arctic Science Education Week. All travel, transportation, accommodations, and meals are provided to the participants at no cost. During the 2013 Kangerlussuaq Science Field School, students and teachers gathered data in a biodiversity study, created and set geo- and EarthCaches, calculated glacial discharge at a melt-water stream and river, examined microbes and tested for chemical differences in a variety of lakes, measured ablation at the edge of the Greenland Ice Sheet, and learned about fossils, plants, animals, minerals and rocks of Greenland. In addition, the students planned and led cultural nights, sharing food, games, stories, and traditions of
University Coll. Worcester (England). Centre for Research in Early Childhood Education.
Building upon the work of the Effective Early Learning (EEL) Project in raising the quality of early learning for young children in the United Kingdom, the 3-year Accounting Early for Life Long Learning Project (AcE Project) focuses on enhancing in 3- to 6-year-olds those attitudes and dispositions that are important to life-long learning. This…
Monterola, Christopher; Saloma, Caesar
We show that the generalization capability of a mature thresholding neural network to process above-threshold disturbances in a noise-free environment is extended to subthreshold disturbances by ambient noise without retraining. The ability to benefit from noise is intrinsic and does not have to be learned separately. Nonlinear dependence of sensitivity with noise strength is significantly narrower than in individual threshold systems. Noise has a minimal effect on network performance for above-threshold signals. We resolve two seemingly contradictory responses of trained networks to noise--their ability to benefit from its presence and their robustness against noisy strong disturbances
Kraft, Toni; Herrmann, Marcus; Bethmann, Falko; Stefan, Wiemer
In the past several years, geological energy technologies receive growing attention and have been initiated in or close to urban areas. Some of these technologies involve injecting fluids into the subsurface (e.g., oil and gas development, waste disposal, and geothermal energy development) and have been found or suspected to cause small to moderate sized earthquakes. These earthquakes, which may have gone unnoticed in the past when they occurred in remote sparsely populated areas, are now posing a considerable risk for the public acceptance of these technologies in urban areas. The permanent termination of the EGS project in Basel, Switzerland after a number of induced ML~3 (minor) earthquakes in 2006 is one prominent example. It is therefore essential for the future development and success of these geological energy technologies to develop strategies for managing induced seismicity and keeping the size of induced earthquakes at a level that is acceptable to all stakeholders. Most guidelines and recommendations on induced seismicity published since the 1970ies conclude that an indispensable component of such a strategy is the establishment of seismic monitoring in an early stage of a project. This is because an appropriate seismic monitoring is the only way to detect and locate induced microearthquakes with sufficient certainty to develop an understanding of the seismic and geomechanical response of the reservoir to the geotechnical operation. In addition, seismic monitoring lays the foundation for the establishment of advanced traffic light systems and is therefore an important confidence building measure towards the local population and authorities. We have developed an optimization algorithm for seismic monitoring networks in urban areas that allows to design and evaluate seismic network geometries for arbitrary geotechnical operation layouts. The algorithm is based on the D-optimal experimental design that aims to minimize the error ellipsoid of the linearized
Stajduhar, Ivan; Dalbelo-Basić, Bojana; Bogunović, Nikola
Bayesian networks are commonly used for presenting uncertainty and covariate interactions in an easily interpretable way. Because of their efficient inference and ability to represent causal relationships, they are an excellent choice for medical decision support systems in diagnosis, treatment, and prognosis. Although good procedures for learning Bayesian networks from data have been defined, their performance in learning from censored survival data has not been widely studied. In this paper, we explore how to use these procedures to learn about possible interactions between prognostic factors and their influence on the variate of interest. We study how censoring affects the probability of learning correct Bayesian network structures. Additionally, we analyse the potential usefulness of the learnt models for predicting the time-independent probability of an event of interest. We analysed the influence of censoring with a simulation on synthetic data sampled from randomly generated Bayesian networks. We used two well-known methods for learning Bayesian networks from data: a constraint-based method and a score-based method. We compared the performance of each method under different levels of censoring to those of the naive Bayes classifier and the proportional hazards model. We did additional experiments on several datasets from real-world medical domains. The machine-learning methods treated censored cases in the data as event-free. We report and compare results for several commonly used model evaluation metrics. On average, the proportional hazards method outperformed other methods in most censoring setups. As part of the simulation study, we also analysed structural similarities of the learnt networks. Heavy censoring, as opposed to no censoring, produces up to a 5% surplus and up to 10% missing total arcs. It also produces up to 50% missing arcs that should originally be connected to the variate of interest. Presented methods for learning Bayesian networks from
Project selection is an essential matter of design teaching. Based on observations of a specific curriculum, the author claims that a wide repertoire of subjects including offices, restaurants, hotels, and other public places are used to prepare design students, but that schools and other "learning environments/ schools" are similarly…
Chan, Lim Ha; Chen, Ching-Huei
This study investigated the conflict occurring during teamwork among college seniors in project-based collaborative learning in a capstone course. It found that conflict emerged with poor communication, task management, and work allocation; unequal treatments among classmates; egocentricity; a clash of values; and lack of responsibility and…
Tilchin, Oleg; Kittany, Mohamed
The goal of an approach to Adaptive Knowledge Management (AKM) of project-based learning (PBL) is to intensify subject study through guiding, inducing, and facilitating development knowledge, accountability skills, and collaborative skills of students. Knowledge development is attained by knowledge acquisition, knowledge sharing, and knowledge…
Sibona, Christopher; Pourreza, Saba; Hill, Stephen
Scrum is a popular project management model for iterative delivery of software that subscribes to Agile principles. This paper describes an origami active learning exercise to teach the principles of Scrum in management information systems courses. The exercise shows students how Agile methods respond to changes in requirements during project…
Hite, Linda M.
In a college course on diversity in the workplace, students' experiences with conducting a cultural audit of the university as a workplace illustrate the dilemmas that can arise when students conduct action research in a real client system. Despite the inherent problems, the project resulted in significant student learning about the subject and…
This paper seeks to explore some persistent issues which impact on externally funded teaching and learning projects. The discussion considers these issues using the lens of „heterotopias‟, a concept introduced by Michel Foucault. Utilising insights from Foucault's suggestive comments about „heterotopias‟, the paper ...
In recent years, professional practice has been an issue of concern in higher education. The purpose of this study is to design students' projects to facilitate collaborative learning in authentic contexts. Ten students majoring in Management Information Systems conducted fieldwork with spatial technologies to collect data and provided information…
Rutti, Raina M.; LaBonte, Joanne; Helms, Marilyn Michelle; Hervani, Aref Agahei; Sarkarat, Sy
Purpose: The purpose of this paper is to summarize the benefits of including a service learning project in college classes and focusses on benefits to all stakeholders, including students, community, and faculty. Design/methodology/approach: Using a snowball approach in academic databases as well as a nominal group technique to poll faculty, key…
Lumsdaine, A.A.; And Others
The work of a three-year series of experimental studies of human cognition is summarized in this report. Proglem solving and learning in man-machine interaction was investigated, as well as relevant variables and processes. The work included four separate projects: (1) computer-aided problem solving, (2) computer-aided instruction techniques, (3)…
Gieskes, J.F.B.; ten Broeke, André M.
Continuous improvement and learning are popular concepts in management literature and practice. Often they are situated in an environment where the work is of a repetitive nature. However, there are a lot of organisations where (part of) the primary processes are carried out by means of projects. An
Wang, Feng; Zhou, Chunfang; Chen, Hongbing
This paper aims to emphasize the necessity of introducing Project-Based Learning (PBL) to design enterprises in order to foster designers creativity and facilitate innovation of design enterprises. According to the literature review, creativity can be viewed as the first stage of innovation; PBL...
Teodorescu, Remus; Bech, Michael Møller; Holm, Allan J.
A new approach in prototyping for project- and problem-based learning is achieved by using the new Total Development Environment concept introduced by dSPACE that allows a full visual block-oriented programming of dynamic real-time systems to be achieved using the Matlab/Simulink environment...
Wurdinger, Scott; Qureshi, Mariam
This study examined whether life skills could be developed in a Project Based Learning (PBL) course. The participants were students enrolled in a graduate level PBL course. The same 35-question survey was given to students at the beginning and end of the course, and students were asked to rank their life skills using a Likert scale. Additionally,…
Kokotsaki, Dimitra; Menzies, Victoria; Wiggins, Andy
Project-based learning (PBL) is an active student-centred form of instruction which is characterised by students' autonomy, constructive investigations, goal-setting, collaboration, communication and reflection within real-world practices. It has been explored in various contexts and in different phases of schooling, from primary to higher…
Pinho-Lopes, Margarida; Macedo, Joaquim
Since 2007/2008 project-based learning models have been used to deliver two fundamental courses on Geotechnics in University of Aveiro, Portugal. These models have evolved and have encompassed either cooperative or collaborative teamwork. Using data collected in five editions of each course (Soil Mechanics I and Soil Mechanics II), the different…
MacMath, Sheryl; Sivia, Awneet; Britton, Vandy
This study examines teacher perceptions of their experiences with Project Based Learning (PBL) at a secondary school in Western Canada. This PBL initiative included English language arts, mathematics, science, and digital literacy courses and all the grade nines at this large secondary school. This article reports on two teacher focus group…
Heilig, Morton L.
The learning wall system, which consists primarily of a special wall used instead of a screen for a variety of projection purposes, is described, shown diagrammatically, and pictured. Designed to provide visual perceptual motor training on a level that would fall between gross and fine motor performance for perceptually handicapped children, the…
Abel, Marie-Helene; Lenne, Dominique; Cisse, Omar
E-learning leads to changes in the way courses are conceived. Diffused through the Web, course content cannot be the pure transcription of a "classical" course. The students need to personalize it and to access it when they need it (just-in-time). The MEMORAe project aims at applying knowledge management techniques to improve the…
Airola, Rasmus; Hager, Kristoffer
The use of machine learning and specifically neural networks is a growing trend in software development, and has grown immensely in the last couple of years in the light of an increasing need to handle big data and large information flows. Machine learning has a broad area of application, such as human-computer interaction, predicting stock prices, real-time translation, and self driving vehicles. Large companies such as Microsoft and Google have already implemented machine learning in some o...
... process and results of collaborative networking in a particular region and on a specific theme. They will share knowledge in the form of thematic information, best practices, policy analysis, practical methodologies and tools, online courses and seminars, coaching and mentoring, face-to-face exchanges, and workshops.
AlDahdouh, Alaa A.; Osório, António J.; Caires, Susana
Behaviorism, Cognitivism, Constructivism and other growing theories such as Actor-Network and Connectivism are circulating in the educational field. For each, there are allies who stand behind research evidence and consistency of observation. Meantime, those existing theories dominate the field until the background is changed or new concrete…
Current research on social networks in some rural communities reports continuing demise despite efforts to build resilient communities. Several factors are identified as contributing to social decline including globalisation and rural social characteristics. Particular rural social characteristics, such as strong social bonds among members of…
Bauch, Garland T.
Most failures occur at interfaces between organizations and hardware. Processing interface requirements at the start of a project life cycle will reduce the likelihood of costly interface changes/failures later. This can be done by adding Interface Control Documents (ICDs) to the Project top level drawing tree, providing technical direction to the Projects for interface requirements, and by funding the interface requirements function directly from the Project Manager's office. The interface requirements function within the Project Systems Engineering and Integration (SE&I) Office would work in-line with the project element design engineers early in the life cycle to enhance communications and negotiate technical issues between the elements. This function would work as the technical arm of the Project Manager to help ensure that the Project cost, schedule, and risk objectives can be met during the Life Cycle. Some ICD Lessons Learned during the Space Shuttle Program (SSP) Life Cycle will include the use of hardware interface photos in the ICD, progressive life cycle design certification by analysis, test, & operations experience, assigning interface design engineers to Element Interface (EI) and Project technical panels, and linking interface design drawings with project build drawings
Sangrà Morer, Albert
Aquest projecte es basa en la hipòtesi que en l'actualitat no existeix un concepte únic d'e-learning -acceptat per la majoria de la comunitat científica o, és més, pels professionals. Per tant, l'objectiu és contribuir a la consolidació i l'especificació del concepte d'e-learning tant des del punt de vista científic com des del punt de vista del camp de l'activitat educativa. This project is based on the hypothesis that currently there is no single concept of e-learning -accepted by the ma...
Nicola, Wilten; Clopath, Claudia
Populations of neurons display an extraordinary diversity in the behaviors they affect and display. Machine learning techniques have recently emerged that allow us to create networks of model neurons that display behaviors of similar complexity. Here we demonstrate the direct applicability of one such technique, the FORCE method, to spiking neural networks. We train these networks to mimic dynamical systems, classify inputs, and store discrete sequences that correspond to the notes of a song. Finally, we use FORCE training to create two biologically motivated model circuits. One is inspired by the zebra finch and successfully reproduces songbird singing. The second network is motivated by the hippocampus and is trained to store and replay a movie scene. FORCE trained networks reproduce behaviors comparable in complexity to their inspired circuits and yield information not easily obtainable with other techniques, such as behavioral responses to pharmacological manipulations and spike timing statistics.
Goodrich, Michael S.
Conventional training methods for neural networks involve starting al a random location in the solution space of the network weights, navigating an error hyper surface to reach a minimum, and sometime stochastic based techniques (e.g., genetic algorithms) to avoid entrapment in a local minimum. It is further typically necessary to preprocess the data (e.g., normalization) to keep the training algorithm on course. Conversely, Bayesian based learning is an epistemological approach concerned with formally updating the plausibility of competing candidate hypotheses thereby obtaining a posterior distribution for the network weights conditioned on the available data and a prior distribution. In this paper, we developed a powerful methodology for estimating the full residual uncertainty in network weights and therefore network predictions by using a modified Jeffery's prior combined with a Metropolis Markov Chain Monte Carlo method.
Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C
Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.
Canini, Marco; Crowcroft, Jon
fostered by organizing a yearly international contest. We argue that holding a contest undertaken by a plurality of students will have benefits that are two-fold. First, it will promote hands-on learning of skills that are helpful in producing artifacts
De Kraker, Joop; Cörvers, Ron
Sustainable development is a participatory, multi-actor process. In this process, learning plays a major role as participants have to exchange and integrate a diversity of perspectives and types of knowledge and expertise in order to arrive at innovative, jointly supported solutions. Virtual
Contribution to Prolearn Summerschool, 7-6-2006; Bled; Slovenia. Slides of the lecture and the 'user questions' we produced in the workshop. The task in the workshop was to identify learning questions that a user could have for the TENCompetence system. These questions should be a) hard to answer
Bonderup Dohn, Nina; Sime, Julie-Ann; Cranmer, Susan
with a short presentation of each of the chapters. This leads us to identify broader themes which point out significant perspectives and challenges for future research and practice. Among these are social justice, criticality, mobility, new forms of openness and learning in the public arena (all leading themes...
Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui
Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli , and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.
Taifi, Nouha; Passiante, Giuseppina
The firms in the business environment have to choose adequate partners in order to sustain their competitive advantage and their economic performance. Plus, the creation of special communities consisting of these partners is essential for the life-long development of these latter and the firms creating them. The research project XStrat.Net aims at the identification of factors and indicators about the organizations for the modelling of intelligent agents -XStrat intelligent agents- and the engineering of a software -XStrat- to process these backbones intelligent agents. Through the use of the software, the firms will be able to select the needed partners for the creation of special communities for the purpose of learning, interest or innovation. The XStrat.Net project also intends to provide guidelines for the creation of the special communities.
Hampshire, John B., II; Vijaya Kumar, Bhagavatula
We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.
Chan, Cecilia Ka Yuk
Experiential learning pedagogy is taking a lead in the development of graduate attributes and educational aims as these are of prime importance for society. This paper shows a community service experiential project conducted in China. The project enabled students to serve the affected community in a post-earthquake area by applying their knowledge…
Beaumont, Chris; Savin-Baden, Maggi; Conradi, Emily; Poulton, Terry
This article reports the findings of a demonstrator project to evaluate how effectively Immersive Virtual Worlds (IVWs) could support problem-based learning. The project designed, created and evaluated eight scenarios within "Second Life" (SL) for undergraduate courses in health care management and paramedic training. Evaluation was…
Bers, Marina U.
This paper presents Project InterActions, a series of 5-week workshops in which very young learners (4- to 7-year-old children) and their parents come together to build and program a personally meaningful robotic project in the context of a multigenerational robotics-based community of practice. The goal of these family workshops is to teach both parents and children about the mechanical and programming aspects involved in robotics, as well as to initiate them in a learning trajectory with and about technology. Results from this project address different ways in which parents and children learn together and provide insights into how to develop educational interventions that would educate parents, as well as children, in new domains of knowledge and skills such as robotics and new technologies.
Lidia SÁNCHEZ GONZÁLEZ
Full Text Available A key issue for any educational institution is to train individuals in such a way that they participate efficiently in their context. The current context where learning is carried out is digital era. With this landscape, and taking into account the current socioeconomic situation, it is necessary to increase students’ employability. This requires that what is taught in educational institutions fits with companies’ requirements. In this sense one of most common companies’ requirement is that students have knowledge about how to develop a project from scratch. In order to address this issue, the present paper poses the application of a project based learning methodology. This methodology is applied in an experiment that comprises two academic years. During each year, the students should develop complete projects working as teams and obtain final products. In this way, it was possible to develop competences that can be interesting for companies and also to increment students’ motivation.
Knudsen, Morten; Bajard, Christine; Helbo, Jan
) programme indicates, however, that adjustments are required in transforming the on-campus model to distance education. The main problem is that while project work is an excellent regulator of the learning process for on-campus students, this does not seem to be the case for off-campus students. Consequently......This article describes the experiences drawn from an experiment in transferring positive experience with a project-organised on-campus engineering programme to a technology supported distance education programme. Three years of experience with the Master of Industrial Information Technology (MII......, didactic adjustments have been made based on feedback, in particular from evaluation questionnaires. This process has been very constructive in approaching the goal: a successful model for project organized learning in distance education....
This paper provides a summary of lessons learned from experiences on the Waste Isolation Pilot Plant (WJPP) Project in implementation of quality assurance controls surrounding inputs for performance assessment analysis. Since the performance assessment (PA) process is inherent in compliance determination for any waste repository, these lessons-learned are intended to be useful to investigators, analysts, and Quality Assurance (QA) practitioners working on high level waste disposal projects. On the WIPP Project, PA analyses for regulatory-compliance determination utilized several inter-related computer programs (codes) that mathematically modeled phenomena such as radionuclide release, retardation, and transport. The input information for those codes are the parameters that are the subject of this paper. Parameters were maintained in a computer database, which was then queried electronically by the PA codes whenever input was needed as the analyses were run
The paper deals with the education in Geomatics at Aalborg University (AAU), Denmark. Since its foundation in 1974 AAU has used Project-Based Learning (PBL) as its educational model. In each of the 10 semesters a project has to be carried out by a group of students. The paper presents the ideas...... behind PBL and the use of this approach in Geomatics. Some examples of project work in the field of photogrammetry and remote sensing are given. Teachers and researchers at AAU recently published a book on the Aalborg PBL model, in which progress, diversity and challenges of the approach are documented....... Some of the findings in this investigation are presented. The on-campus education in Geomatics uses the Internet, and the paper informs about its application on campus. PBL is also practised at AAU's distance education programmes, which combine e-learning and weekend seminars on the campus. Experiences...
Full Text Available Project-based learning facilitates hands-on learning in student-driven investigations, resulting in high-quality, challenging activities. Students participate actively in projects that revolve around their interests, questions or needs. PBL also develops the 21st century skills including critical thinking, collaboration and communication. The essence of PBL is problem-solving, a key critical thinking skill. Since problem-solving is an integral part of medicine, projects represent a significant method of instruction in English for Medical Purposes. Depending on their individual interests and abilities, each student contributes to the whole group work and the final outcome. The approach also requires students to work in teams and to communicate their findings. Using real-life problems to motivate students, challenging them to think deeply about meaningful content, and enabling them to work collaboratively are practices that yield benefits for all students and their future careers.
Fetter, Sibren; Rajagopal, Kamakshi; Berlanga, Adriana; Sloep, Peter
Fetter, S., Rajagopal, K., Berlanga, A. J., & Sloep, P. B. (2011). Ad Hoc Transient Groups: Instruments for Awareness in Learning Networks. In W. Reinhardt, T. D. Ullmann, P. Scott, V. Pammer, O. Conlan, & A. J. Berlanga (Eds.), Proceedings of the 1st European Workshop on Awareness and Reflection in
and based on different, mutually complementary, principles of traffic analysis. The proposed approaches rely on machine learning algorithms (MLAs) for automated and resource-efficient identification of the patterns of malicious network traffic. We evaluated the proposed methods through extensive evaluations...
Huang, Yanping; Rao, Rajesh P N
Motivated by the growing evidence for Bayesian computation in the brain, we show how a two-layer recurrent network of Poisson neurons can perform both approximate Bayesian inference and learning for any hidden Markov model. The lower-layer sensory neurons receive noisy measurements of hidden world states. The higher-layer neurons infer a posterior distribution over world states via Bayesian inference from inputs generated by sensory neurons. We demonstrate how such a neuronal network with synaptic plasticity can implement a form of Bayesian inference similar to Monte Carlo methods such as particle filtering. Each spike in a higher-layer neuron represents a sample of a particular hidden world state. The spiking activity across the neural population approximates the posterior distribution over hidden states. In this model, variability in spiking is regarded not as a nuisance but as an integral feature that provides the variability necessary for sampling during inference. We demonstrate how the network can learn the likelihood model, as well as the transition probabilities underlying the dynamics, using a Hebbian learning rule. We present results illustrating the ability of the network to perform inference and learning for arbitrary hidden Markov models.
Alfred, Mary V.
This chapter describes social capital theory as a framework for exploring women's networking and social capital resources. It presents the foundational assumptions of the theory, the benefits and risks of social capital engagement, a feminist critique of social capital, and the role of social capital in adult learning.
D. Deichmann (Dirk)
textabstractIn this dissertation, we focus on how leadership styles, individual learning behaviors, and social network structures drive or inhibit organizational members to repeatedly generate and develop innovative ideas. Taking the idea management programs of three multinational companies as the
Barnacle, Robyn; Mewburn, Inger
Scholars such as Kamler and Thompson argue that identity formation has a key role to play in doctoral learning, particularly the process of thesis writing. This article builds on these insights to address other sites in which scholarly identity is performed within doctoral candidature. Drawing on actor-network theory, the authors examine the role…
Computer based communication technologies, or what could be more conveniently called networking, are bringing new possibilities into teacher education in many different ways. As with distance education more generally they can facilitate flexibility in time and place of learning, but the range of
Hsiao, Amy; Brouns, Francis; Kester, Liesbeth; Sloep, Peter
Hsiao, Y. P., Brouns, F., Kester, L., & Sloep, P. (2009). Optimizing Knowledge Sharing in Learning Networks through Peer Tutoring. Presentation at the IADIS international conference on Cognition and Exploratory in Digital Age (CELDA 2009). November, 20-22, 2009, Rome, Italy.
The topic of networking the learning community with home-school links is addressed in four papers: "Internet Access via School: Expectations of Students and Parents" (Roy Crotty); "The School Library as Community Information Gateway" (Megan Perry); "Rural Access to the Internet" (Ken Eustace); and "NetDay '96:…
Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…
In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…
Cankaya, Serkan; Yunkul, Eyup
The purpose of this study was to reveal the attitudes and views of university students about the use of Edmodo as a cooperative learning environment. In the research process, the students were divided into groups of 4 or 5 within the scope of a course given in the department of Computer Education and Instructional Technology. For each group,…
Bornholdt, S. [Heidelberg Univ., (Germany). Inst., fuer Theoretische Physik; Graudenz, D. [Lawrence Berkeley Lab., CA (United States)
A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.
A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback
Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.
Bredeweg, B.; Liem, J.
Different project management tools have been evaluated. We have chosen several well-known, flexible and mature tools to support management activities and communication between the DynaLearn project participants. We have created a DynaLearn website for stakeholders outside the DynaLearn website. An
This paper addresses the design of a discontinuous finite time convergent learning law for neural networks with continuous dynamics. The neural network was used here to obtain a non-parametric model for uncertain systems described by a set of ordinary differential equations. The source of uncertainties was the presence of some external perturbations and poor knowledge of the nonlinear function describing the system dynamics. A new adaptive algorithm based on discontinuous algorithms was used to adjust the weights of the neural network. The adaptive algorithm was derived by means of a non-standard Lyapunov function that is lower semi-continuous and differentiable in almost the whole space. A compensator term was included in the identifier to reject some specific perturbations using a nonlinear robust algorithm. Two numerical examples demonstrated the improvements achieved by the learning algorithm introduced in this paper compared to classical schemes with continuous learning methods. The first one dealt with a benchmark problem used in the paper to explain how the discontinuous learning law works. The second one used the methane production model to show the benefits in engineering applications of the learning law proposed in this paper. Copyright © 2013 Elsevier Ltd. All rights reserved.
Research suggests that students benefit from peer interaction and active engagement in the classroom. The quality, nature, effect of these interactions is currently being explored by Physics Education Researchers. Spelman College offers an introductory physics sequence that addresses content and research skills by engaging students in open-ended research projects, a form of Project-Based Learning. Students have been surveyed at regular intervals during the second semester of trigonometry-based course to determine the frequency of interactions in and out of class. These interactions can be with current or past students, tutors, and instructors. This line of inquiry focuses on metrics of Social Network analysis, such as centrality of participants as well as segmentation of groups. Further research will refine and highlight deeper questions regarding student performance in this pedagogy and course sequence.
Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook
This study presents students' feedback and learning impact on design and development of a multimedia learning in Direct Problem-Based Learning approach (mDPBL) for Computer Networks in Dian Nuswantoro University, Indonesia. This study examined the usefulness, contents and navigation of the multimedia learning as well as learning impacts towards…
AUTHOR|(INSPIRE)INSPIRE-00218873; The ATLAS collaboration; Toler, Wesley; Vamosi, Ralf; Bogado Garcia, Joaquin Ignacio
The increasing volume of physics data poses a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from one of our ongoing automation efforts that focuses on network metrics. First, we describe our machine learning framework built atop the ATLAS Analytics Platform. This framework can automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for network-aware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our m...
Hayakawa, Takashi; Aoyagi, Toshio
Information maximization has been investigated as a possible mechanism of learning governing the self-organization that occurs within the neural systems of animals. Within the general context of models of neural systems bidirectionally interacting with environments, however, the role of information maximization remains to be elucidated. For bidirectionally interacting physical systems, universal laws describing the fluctuation they exhibit and the information they possess have recently been discovered. These laws are termed fluctuation theorems. In the present study, we formulate a theory of learning in neural networks bidirectionally interacting with environments based on the principle of information maximization. Our formulation begins with the introduction of a generalized fluctuation theorem, employing an interpretation appropriate for the present application, which differs from the original thermodynamic interpretation. We analytically and numerically demonstrate that the learning mechanism presented in our theory allows neural networks to efficiently explore their environments and optimally encode information about them.
Full Text Available Digital games are receiving increasing attention by researchers and practitioners in education; however, most of the theory and pedagogy focus on general education or language and literacy development of native speakers. There are very few investigations of game play or game culture and second language development. Language teachers and institutions must know more about games to use the media effectively. Two completed extracurricular projects, based on constructionist learning and media literacy theories and practices, are described in this paper: game design and game magazine creation. The action research projects aimed to guide students towards a better understanding of games’ formal features and technologies through their active creation of games and game-related media, and to improve their spoken and written English language skills. In general, students learned and practised a variety of language and technology skills with the design projects. The projects motivated the students, challenged the students, and provided many opportunities for authentic discussions in the foreign language. Various suggestions, based on the teacher and student experiences of these projects, are made for other language teachers interested in conducting creative game-based projects with their students.
Full Text Available The aim of that research, it is the project based learning process suffuciency of teacher candidates who developedmultimedia by working in online and blended groups. Importance of research Being able to guide to studies that is going tobe done about assessment of multimedia projection for project based educational application to teachers and teachercandidates and It has been thought as an advisor source about being arranged new educational environment for the futureto teacher and teacher candidates for project based educational application and multimedia projection. Research is anexperimental study and has been shaped according to pre-test and last-test research model with the two groups. This groupsare online group and blended group. Discussion of research In the result of the study, in the process of project basedlearning, it is determined that the success level in multimedia development of teacher candidates who work in blendedlearning model is higher than the success level of teacher candidates who work in online learning model.
Zhang, Limao; Wu, Xianguo; Skibniewski, Miroslaw J.; Zhong, Jingbing; Lu, Yujie
This paper presents a systemic decision support approach for safety risk analysis under uncertainty in tunnel construction. Fuzzy Bayesian Networks (FBN) is used to investigate causal relationships between tunnel-induced damage and its influential variables based upon the risk/hazard mechanism analysis. Aiming to overcome limitations on the current probability estimation, an expert confidence indicator is proposed to ensure the reliability of the surveyed data for fuzzy probability assessment of basic risk factors. A detailed fuzzy-based inference procedure is developed, which has a capacity of implementing deductive reasoning, sensitivity analysis and abductive reasoning. The “3σ criterion” is adopted to calculate the characteristic values of a triangular fuzzy number in the probability fuzzification process, and the α-weighted valuation method is adopted for defuzzification. The construction safety analysis progress is extended to the entire life cycle of risk-prone events, including the pre-accident, during-construction continuous and post-accident control. A typical hazard concerning the tunnel leakage in the construction of Wuhan Yangtze Metro Tunnel in China is presented as a case study, in order to verify the applicability of the proposed approach. The results demonstrate the feasibility of the proposed approach and its application potential. A comparison of advantages and disadvantages between FBN and fuzzy fault tree analysis (FFTA) as risk analysis tools is also conducted. The proposed approach can be used to provide guidelines for safety analysis and management in construction projects, and thus increase the likelihood of a successful project in a complex environment. - Highlights: • A systemic Bayesian network based approach for safety risk analysis is developed. • An expert confidence indicator for probability fuzzification is proposed. • Safety risk analysis progress is extended to entire life cycle of risk-prone events. • A typical
Koush, Yury; Meskaldji, Djalel-E; Pichon, Swann; Rey, Gwladys; Rieger, Sebastian W; Linden, David E J; Van De Ville, Dimitri; Vuilleumier, Patrik; Scharnowski, Frank
Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically, we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivity-based neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com.
Full Text Available Exploring topics that are personally relevant and interesting to young adult English as a foreign language (EFL learners remains a core challenge in language teaching. At the same time, the advent of Web 2.0 applications has many repercussions for authentic language learning. The “U.S. Embassy School Election Project 2012” has addressed these questions by combining a close focus on the U.S. Presidential Election with an interactive project scenario. Over 1,400 students across Germany participated in this project and produced an election forecast for an assigned U.S. state based on a survey of regional news media and social network data. Their predictions were in many cases more accurate than those of major U.S. broadcasting networks. This paper discusses the general educational potential of such projects in the contexts of computer-assisted language learning (CALL, intercultural learning, and learning in a task-based project environment. The authors have applied a multimodal qualitative approach to analyze tasks and learner perceptions of tasks in the context of the election project. In a first step, the micro-perspective of the perception of web-based tasks is investigated by example of one selected task cycle and a focus group of three learners. The second part of the analysis represents a bird’s-eye view on the learner products arising out of such tasks.
Takeda, Manabu; Ikeda, Kazushi; Furukawa, Tetsuo
The Modular Network Self-Organizing Map (mnSOM) is a generalization of the SOM, where each node represents a parametric function such as a multi-layer perceptron or another SOM. Since given datasets are, in general, fewer than nodes, some nodes never win in competition and have to update their parameters from the winners in the neighborhood. This is a process that can be regarded as interpolation. This study derives the interpolation curve between winners in simple cases and discusses the distribution of winners based on the neighborhood function.
Ignacio TRAVERSO RIBÓN
Full Text Available In a project-based learning experience, the detailed monitoring of the activities in which team members participate can be useful to evaluate their work. Using learning-oriented assessment procedures, supervisors can assess the teamwork abilities with a formative purpose. Evaluation strategies such as self-assessment, peer assessment and co-assessment are often used to make evaluation formative and sustainable. Conducting an assessment strategy is not easy for team members, since they need before to have a reasonable understanding of the evaluation process and criteria. This paper describes a learning-oriented evaluation methodology and an open data framework that can be applied to collaborative project settings. An evaluation rubric and a series of indicators that provide evidences about the developed skills have been elaborated and applied in a small-scale project-based course. Projects were managed and developed with the help of an open source software forge that contains a ticketing tool for planning and tracking of tasks, a version control repository to save the software outcomes, and using a wiki to host text deliverables. The experience provides evidences in favor of using the assessment method and open data framework to make teamwork evaluation more sustainable.
Noor, Ahmed K. (Compiler)
This document contains the proceedings of the training workshop on Advanced Learning Technologies and Learning Networks and their impact on Future Aerospace Workforce. The workshop was held at the Peninsula Workforce Development Center, Hampton, Virginia, April 2 3, 2003. The workshop was jointly sponsored by Old Dominion University and NASA. Workshop attendees came from NASA, other government agencies, industry, and universities. The objectives of the workshop were to: 1) provide broad overviews of the diverse activities related to advanced learning technologies and learning environments, and 2) identify future directions for research that have high potential for aerospace workforce development. Eighteen half-hour overviewtype presentations were made at the workshop.
Full Text Available The project’s primary target groups are the European secondary schools. More specifically: secondary school and university teachers, students and managers of schools, museum employees and their visitors, and other STEM education providers. The main goal of the OLAREX project is to offer the providers of formal and non-formal education an efficient way to improve their e-didactic and digital competences. For this purpose a training program is created with using ICT-based learning materials, remote laboratories, and e-learning methodologies
Knudsen, Morten; Bajard, C.; Helbo, Jan
Transferring a successful on-campus project-organized learning method to distance continued education is complicated by the fact, that the target group as well as the learning environment and forms of communication are fundamentally different. The Master of Industrial Information Technology...... distance education has been selected for experiments with utilization of new information and commu-nication technology and didactic adjustments to make this transfer from on-campus to off-campus a successful endeavor. The adjustments, as well as the assessment of their effect, are based on a system......-atic monitoring and evaluation of the first year, and subsequent reflections by students and teachers....
Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko
Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden
Rojas de la Escalera, D
Medical imaging is one of the most important diagnostic instruments in clinical practice. The technological development of digital medical imaging has enabled healthcare services to undertake large scale projects that require the participation and collaboration of many professionals of varied backgrounds and interests as well as substantial investments in infrastructures. Rather than focusing on systems for dealing with digital medical images, this article deals with the management of projects for implementing these systems, reviewing various organizational, technological, and human factors that are critical to ensure the success of these projects and to guarantee the compatibility and integration of digital medical imaging systems with other health information systems. To this end, the author relates several lessons learned from a review of the literature and the author's own experience in the technical coordination of digital medical imaging projects. Copyright © 2012 SERAM. Published by Elsevier Espana. All rights reserved.
Casquero, Oskar; Ovelar, Ramón; Romo, Jesús; Benito, Manuel; Alberdi, Mikel
The main objective of this paper is to analyse the effect of the affordances of a virtual learning environment and a personal learning environment (PLE) in the configuration of the students' personal networks in a higher education context. The results are discussed in light of the adaptation of the students to the learning network made up by two…
The Data Refuge project began as concerns were raised about the vulnerability of federal climate and environmental data. The concern stemmed from the idea that if the federal agency that curates the data lost funding, and with it staff and infrastructure, that the data could be lost. The team worked to determine what factors contributed to the vulnerability of these data and how we might mitigate their risks. After speaking with many partners and collaborators around the country who all had different roles and perspectives working with these data, we saw the landscape of government data in new ways. We began seeing potential in various initiatives to ensure continued access to these data regardless of political, technological, or other risks. One recurring theme in our assessment was that libraries would be natural backup stewards for federal data.From and with our partners, we learned just how complicated the problem of creating networks of backup stewards for government data would be, but also how important it is to make the effort. As Data Refuge moves into its next stages into the Libraries+ Network, we're making plans to work with our partners on federal, state, and local projects that address different aspects of the problem space. These projects are examples of ways to approach this problem in concert with a variety of stakeholders.
Ponulak, Filip; Kasinski, Andrzej
The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.
Carmen ÁLVAREZ ÁLVAREZ
Full Text Available This article reflects on the interrelationships that exist between two educational projects of today: service-learning (ApS and learning communities (CdA. The ApS is an educational methodology applied worldwide where a single project combines a learning based on experience with the implementation of a service to the community. CdA is a school transformation project to achieve that the information society does not exclude any person, constituting a reality in more than one hundred and ninety schools in Spain and Latin America. Between the two, it is possible to show differences, especially in what refers to its theoretical substrates, but in actual teaching practice in schools there is some harmony, particularly in the so closely that they cultivate both projects with the school community. Therefore, we conclude that service-learning and learning communities can occur as two innovative and relevant today projects which can be mutually enriching: because for both the approach school-community-environment and volunteering is essential.
Ulhøi, John Parm; Madsen, Henning
to reconsider organisational learning as being both an internal as well as an external phenomenon. By bringing network learning into an existing interorganisational setting (such as industrial ecology) new potentials for increased learning emerge for the participating companies. The concept of network learning...
Nalepa, Gislaine M.; Ávila, Bráulio C.; Enembreck, Fabrício; Scalabrin, Edson E.
This paper presents an intelligent offer policy in a negotiation environment, in which each agent involved learns the preferences of its opponent in order to improve its own performance. Each agent must also be able to detect drifts in the opponent's preferences so as to quickly adjust itself to their new offer policy. For this purpose, two simple learning techniques were first evaluated: (i) based on instances (IB3) and (ii) based on Bayesian Networks. Additionally, as its known that in theory group learning produces better results than individual/single learning, the efficiency of IB3 and Bayesian classifier groups were also analyzed. Finally, each decision model was evaluated in moments of concept drift, being the drift gradual, moderate or abrupt. Results showed that both groups of classifiers were able to effectively detect drifts in the opponent's preferences.
Protopopescu, V.; Rao, N.S.V.
We address three problems in machine learning, namely: (i) function learning, (ii) regression estimation, and (iii) sensor fusion, in the Probably and Approximately Correct (PAC) framework. We show that, under certain conditions, one can reduce the three problems above to the regression estimation. The latter is usually tackled with artificial neural networks (ANNs) that satisfy the PAC criteria, but have high computational complexity. We propose several computationally efficient PAC alternatives to ANNs to solve the regression estimation. Thereby we also provide efficient PAC solutions to the function learning and sensor fusion problems. The approach is based on cross-fertilizing concepts and methods from statistical estimation, nonlinear algorithms, and the theory of computational complexity, and is designed as part of a new, coherent paradigm for machine learning.
Hommes, F.; Pless, E.
The report describes experiences from networking support for two three years virtual reality projects. Networking requirements depending on the virtual reality environment and the planned distributed scenarios are specified and verified in the real network. Networking problems especially due to the collaborative, distributed character of interaction via the Internet are presented.
text production, but discusses an individual dictionary for a particular function. It is shown that in a general context of learning accounting and its relevant LSP with a view to writing or translating financial reporting texts, the modern theory of dictionary functions provides a good theoretical...... and usage of a subject-field, particularly when they have to read, write or translate domain-specific texts. The modern theory of dictionary functions presented in Bergenholtz and Tarp (2002) opens up exciting new possibilities for theoretical and practical lexicography and encourages lexicographers......-lexicographic environment, i.e. what happens outside the dictionary when users write or translate texts, and relate these findings to the lexicographic environment represented by the theoretical basis and the dictionary itself. Nielsen (2006) gives a preliminary discussion of monolingual accounting dictionaries for EFL...
Roč. 4, č. 12 (2005), s. 1867-1872 ISSN 1109-2750 R&D Projects: GA ČR GA201/05/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : search space * feed-forward networks * genetic algorithm s Subject RIV: BA - General Mathematics
Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume
Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The
Kuss, Daria J.; Griffiths, Mark D.
Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided. PMID:28304359
Daria J. Kuss
Full Text Available Online social networking sites (SNSs have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i social networking and social media use are not the same; (ii social networking is eclectic; (iii social networking is a way of being; (iv individuals can become addicted to using social networking sites; (v Facebook addiction is only one example of SNS addiction; (vi fear of missing out (FOMO may be part of SNS addiction; (vii smartphone addiction may be part of SNS addiction; (viii nomophobia may be part of SNS addiction; (ix there are sociodemographic differences in SNS addiction; and (x there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided.
Kuss, Daria J; Griffiths, Mark D
Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided.
Williams-Hayes, Peggy S.
The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.