Supporting Collective Inquiry: A Technology Framework for Distributed Learning

NASA Astrophysics Data System (ADS)

Tissenbaum, Michael

This design-based study describes the implementation and evaluation of a technology framework to support smart classrooms and Distributed Technology Enhanced Learning (DTEL) called SAIL Smart Space (S3). S3 is an open-source technology framework designed to support students engaged in inquiry investigations as a knowledge community. To evaluate the effectiveness of S3 as a generalizable technology framework, a curriculum named PLACE (Physics Learning Across Contexts and Environments) was developed to support two grade-11 physics classes (n = 22; n = 23) engaged in a multi-context inquiry curriculum based on the Knowledge Community and Inquiry (KCI) pedagogical model. This dissertation outlines three initial design studies that established a set of design principles for DTEL curricula, and related technology infrastructures. These principles guided the development of PLACE, a twelve-week inquiry curriculum in which students drew upon their community-generated knowledge base as a source of evidence for solving ill-structured physics problems based on the physics of Hollywood movies. During the culminating smart classroom activity, the S3 framework played a central role in orchestrating student activities, including managing the flow of materials and students using real-time data mining and intelligent agents that responded to emergent class patterns. S3 supported students' construction of knowledge through the use individual, collective and collaborative scripts and technologies, including tablets and interactive large-format displays. Aggregate and real-time ambient visualizations helped the teacher act as a wondering facilitator, supporting students in their inquiry where needed. A teacher orchestration tablet gave the teacher some control over the flow of the scripted activities, and alerted him to critical moments for intervention. Analysis focuses on S3's effectiveness in supporting students' inquiry across multiple learning contexts and scales of time, and in making timely and effective use of the community's knowledge base, towards producing solutions to sophisticated, ill defined problems in the domain of physics. Video analysis examined whether S3 supported teacher orchestration, freeing him to focus less on classroom management and more on students' inquiry. Three important outcomes of this research are a set of design principles for DTEL environments, a specific technology infrastructure (S3), and a DTEL research framework.

Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow.

PubMed

Wongsuphasawat, Kanit; Smilkov, Daniel; Wexler, James; Wilson, Jimbo; Mane, Dandelion; Fritz, Doug; Krishnan, Dilip; Viegas, Fernanda B; Wattenberg, Martin

2018-01-01

We present a design study of the TensorFlow Graph Visualizer, part of the TensorFlow machine intelligence platform. This tool helps users understand complex machine learning architectures by visualizing their underlying dataflow graphs. The tool works by applying a series of graph transformations that enable standard layout techniques to produce a legible interactive diagram. To declutter the graph, we decouple non-critical nodes from the layout. To provide an overview, we build a clustered graph using the hierarchical structure annotated in the source code. To support exploration of nested structure on demand, we perform edge bundling to enable stable and responsive cluster expansion. Finally, we detect and highlight repeated structures to emphasize a model's modular composition. To demonstrate the utility of the visualizer, we describe example usage scenarios and report user feedback. Overall, users find the visualizer useful for understanding, debugging, and sharing the structures of their models.

ATM: The Key To Harnessing the Power of Networked Multimedia.

ERIC Educational Resources Information Center

Gross, Rod

1996-01-01

ATM (Asynchronous Transfer Mode) network technology handles the real-time continuous traffic flow necessary to support desktop multimedia applications. Describes network applications already used: desktop video collaboration, distance learning, and broadcasting video delivery. Examines the architecture of ATM technology, video delivery and sound…

Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

NASA Astrophysics Data System (ADS)

Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

2017-12-01

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

"Ready, Set, FLOW!"

ERIC Educational Resources Information Center

Stroud, Wesley

2018-01-01

All educators want their classrooms to be inviting areas that support investigations. However, a common mistake is to fill learning spaces with items or objects that are set up by the teacher or are simply "for show." This type of setting, although it may create a comfortable space for students, fails to stimulate investigations and…

Representing Energy. II. Energy Tracking Representations

ERIC Educational Resources Information Center

Scherr, Rachel E.; Close, Hunter G.; Close, Eleanor W.; Vokos, Stamatis

2012-01-01

The Energy Project at Seattle Pacific University has developed representations that embody the substance metaphor and support learners in conserving and tracking energy as it flows from object to object and changes form. Such representations enable detailed modeling of energy dynamics in complex physical processes. We assess student learning by…

Learning about Governance through Nonprofit Board Service

ERIC Educational Resources Information Center

Purdy, Jill M.; Lawless, Joseph

2012-01-01

Business educators have a responsibility to ensure that future managers, employees, and shareholders are well versed in governance. Governance provides a vital link between organizations and society, allowing people to place their trust in an organization, support its mission, and ensure a continuing flow of resources to accomplish the mission.…

Deriving Process-Driven Collaborative Editing Pattern from Collaborative Learning Flow Patterns

ERIC Educational Resources Information Center

Marjanovic, Olivera; Skaf-Molli, Hala; Molli, Pascal; Godart, Claude

2007-01-01

Collaborative Learning Flow Patterns (CLFPs) have recently emerged as a new method to formulate best practices in structuring the flow of activities within various collaborative learning scenarios. The term "learning flow" is used to describe coordination and sequencing of learning tasks. This paper adopts the existing concept of CLFP and argues…

A Study of Flow Theory in the Foreign Language Classroom.

ERIC Educational Resources Information Center

Egbert, Joy

2003-01-01

Focuses on the relationship between flow experiences and language learning. Flow theory suggests that flow experiences can lead to optimal learning. Findings suggest flow does exist in the foreign language classroom and that flow theory offers an interesting and useful framework for conceptualizing and evaluating language learning activities.…

Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty

DOE PAGES

Ling, Julia; Templeton, Jeremy Alan

2015-08-04

Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests.more » The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. As a result, feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.« less

MotionFlow: Visual Abstraction and Aggregation of Sequential Patterns in Human Motion Tracking Data.

PubMed

Jang, Sujin; Elmqvist, Niklas; Ramani, Karthik

2016-01-01

Pattern analysis of human motions, which is useful in many research areas, requires understanding and comparison of different styles of motion patterns. However, working with human motion tracking data to support such analysis poses great challenges. In this paper, we propose MotionFlow, a visual analytics system that provides an effective overview of various motion patterns based on an interactive flow visualization. This visualization formulates a motion sequence as transitions between static poses, and aggregates these sequences into a tree diagram to construct a set of motion patterns. The system also allows the users to directly reflect the context of data and their perception of pose similarities in generating representative pose states. We provide local and global controls over the partition-based clustering process. To support the users in organizing unstructured motion data into pattern groups, we designed a set of interactions that enables searching for similar motion sequences from the data, detailed exploration of data subsets, and creating and modifying the group of motion patterns. To evaluate the usability of MotionFlow, we conducted a user study with six researchers with expertise in gesture-based interaction design. They used MotionFlow to explore and organize unstructured motion tracking data. Results show that the researchers were able to easily learn how to use MotionFlow, and the system effectively supported their pattern analysis activities, including leveraging their perception and domain knowledge.

Towards DMD-Based Estimation and Control of Flow Separation using an Array of Surface Pressure Sensors

NASA Astrophysics Data System (ADS)

Deem, Eric; Cattafesta, Louis; Zhang, Hao; Rowley, Clancy

2016-11-01

Closed-loop control of flow separation requires the spatio-temporal states of the flow to be fed back through the controller in real time. Previously, static and dynamic estimation methods have been employed that provide reduced-order model estimates of the POD-coefficients of the flow velocity using surface pressure measurements. However, this requires a "learning" dataset a priori. This approach is effective as long as the dynamics during control do not stray from the learning dataset. Since only a few dynamical features are required for feedback control of flow separation, many of the details provided by full-field snapshots are superfluous. This motivates a state-observation technique that extracts key dynamical features directly from surface pressure, without requiring PIV snapshots. The results of identifying DMD modes of separated flow through an array of surface pressure sensors in real-time are presented. This is accomplished by employing streaming DMD "on the fly" to surface pressure snapshots. These modal characteristics exhibit striking similarities to those extracted from PIV data and the pressure field obtained via solving Poisson's equation. Progress towards closed-loop separation control based on the dynamic modes of surface pressure will be discussed. Supported by AFOSR Grant FA9550-14-1-0289.

Overview of Fluid Dynamics Activities at the Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Garcia, Roberto; Griffin, Lisa W.; Wang, Ten-See

1999-01-01

Since its inception 40 years ago, Marshall Space Flight Center (MSFC) has had the need to maintain and advance state-of-the-art flow analysis and cold-flow testing capability to support its roles and missions. This overview discusses the recent organizational changes that have occurred at MSFC with emphasis on the resulting three groups that form the core of fluid dynamics expertise at MSFC: the Fluid Physics and Dynamics Group, the Applied Fluid Dynamics Analysis Group, and the Experimental Fluid Dynamics Group. Recently completed activities discussed include the analysis and flow testing in support of the Fastrac engine design, the X-33 vehicle design, and the X34 propulsion system design. Ongoing activities include support of the RLV vehicle design, Liquid Fly Back Booster aerodynamic configuration definition, and RLV focused technologies development. Other ongoing activities discussed are efforts sponsored by the Center Director's Discretionary Fund (CDDF) to develop an advanced incompressible flow code and to develop optimization techniques. Recently initiated programs and their anticipated required fluid dynamics support are discussed. Based on recent experiences and on the anticipated program needs, required analytical and experimental technique improvements are presented. Due to anticipated budgetary constraints, there is a strong need to leverage activities and to pursue teaming arrangements in order to advance the state-of-the-art and to adequately support concept development. Throughout this overview there is discussion of the lessons learned and of the capabilities demonstrated and established in support of the hardware development programs.

Fluid Mechanics

NASA Astrophysics Data System (ADS)

Pnueli, David; Gutfinger, Chaim

1997-01-01

This text is intended for the study of fluid mechanics at an intermediate level. The presentation starts with basic concepts, in order to form a sound conceptual structure that can support engineering applications and encourage further learning. The presentation is exact, incorporating both the mathematics involved and the physics needed to understand the various phenomena in fluid mechanics. Where a didactical choice must be made between the two, the physics prevails. Throughout the book the authors have tried to reach a balance between exact presentation, intuitive grasp of new ideas, and creative applications of concepts. This approach is reflected in the examples presented in the text and in the exercises given at the end of each chapter. Subjects treated are hydrostatics, viscous flow, similitude and order of magnitude, creeping flow, potential flow, boundary layer flow, turbulent flow, compressible flow, and non-Newtonian flows. This book is ideal for advanced undergraduate students in mechanical, chemical, aerospace, and civil engineering. Solutions manual available.

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors.

PubMed

Cheung, Kit; Schultz, Simon R; Luk, Wayne

2015-01-01

NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation.

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

PubMed Central

Cheung, Kit; Schultz, Simon R.; Luk, Wayne

2016-01-01

NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation. PMID:26834542

Choosing a School Turnaround Provider. Lessons Learned. Volume 1, Issue 3

ERIC Educational Resources Information Center

Lockwood, Anne Turnbaugh; Fleischman, Steve

2010-01-01

Droves of school turnaround providers are chasing the massive federal infusion of funds flowing into failing schools. They arrive armed with glossy materials, impressive sounding claims, and, often, citing their prior relationships or experiences with one's school to support their promises of great service and impressive outcomes. But, are their…

Designing an Electronic Educational Game to Facilitate Immersion and Flow

ERIC Educational Resources Information Center

Ma, Yuxin; Williams, Doug; Prejean, Louise

2014-01-01

Advocates of electronic educational games often cite the work on motivation to support the use of games in education. However, motivation alone is inadequate to facilitate learning. Many of the educational games that focused their game design solely on the motivational effect failed to be either educational or entertaining. Theory and research is…

Designing a Web-Based Science Learning Environment for Model-Based Collaborative Inquiry

NASA Astrophysics Data System (ADS)

Sun, Daner; Looi, Chee-Kit

2013-02-01

The paper traces a research process in the design and development of a science learning environment called WiMVT (web-based inquirer with modeling and visualization technology). The WiMVT system is designed to help secondary school students build a sophisticated understanding of scientific conceptions, and the science inquiry process, as well as develop critical learning skills through model-based collaborative inquiry approach. It is intended to support collaborative inquiry, real-time social interaction, progressive modeling, and to provide multiple sources of scaffolding for students. We first discuss the theoretical underpinnings for synthesizing the WiMVT design framework, introduce the components and features of the system, and describe the proposed work flow of WiMVT instruction. We also elucidate our research approach that supports the development of the system. Finally, the findings of a pilot study are briefly presented to demonstrate of the potential for learning efficacy of the WiMVT implementation in science learning. Implications are drawn on how to improve the existing system, refine teaching strategies and provide feedback to researchers, designers and teachers. This pilot study informs designers like us on how to narrow the gap between the learning environment's intended design and its actual usage in the classroom.

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices

PubMed Central

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B.

2018-01-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support. PMID:29629431

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices.

PubMed

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B

2017-06-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support.

An Examination of the Effects of Flow on Learning in a Graduate-Level Introductory Operations Management Course

ERIC Educational Resources Information Center

Klein, Barbara D.; Rossin, Don; Guo, Yi Maggie; Ro, Young K.

2010-01-01

The authors investigated the effects of flow on learning outcomes in a graduate-level operations management course. Flow was assessed through an overall flow score, four dimensions of flow, and three characteristics of flow activities. Learning outcomes were measured objectively through multiple-choice quiz scores and subjectively using measures…

Statistical analysis on the signals monitoring multiphase flow patterns in pipeline-riser system

NASA Astrophysics Data System (ADS)

Ye, Jing; Guo, Liejin

2013-07-01

The signals monitoring petroleum transmission pipeline in offshore oil industry usually contain abundant information about the multiphase flow on flow assurance which includes the avoidance of most undesirable flow pattern. Therefore, extracting reliable features form these signals to analyze is an alternative way to examine the potential risks to oil platform. This paper is focused on characterizing multiphase flow patterns in pipeline-riser system that is often appeared in offshore oil industry and finding an objective criterion to describe the transition of flow patterns. Statistical analysis on pressure signal at the riser top is proposed, instead of normal prediction method based on inlet and outlet flow conditions which could not be easily determined during most situations. Besides, machine learning method (least square supported vector machine) is also performed to classify automatically the different flow patterns. The experiment results from a small-scale loop show that the proposed method is effective for analyzing the multiphase flow pattern.

Evaluating the use of augmented reality to support undergraduate student learning in geomorphology

NASA Astrophysics Data System (ADS)

Ockelford, A.; Bullard, J. E.; Burton, E.; Hackney, C. R.

2016-12-01

Augmented Reality (AR) supports the understanding of complex phenomena by providing unique visual and interactive experiences that combine real and virtual information and help communicate abstract problems to learners. With AR, designers can superimpose virtual graphics over real objects, allowing users to interact with digital content through physical manipulation. One of the most significant pedagogic features of AR is that it provides an essentially student-centred and flexible space in which students can learn. By actively engaging participants using a design-thinking approach, this technology has the potential to provide a more productive and engaging learning environment than real or virtual learning environments alone. AR is increasingly being used in support of undergraduate learning and public engagement activities across engineering, medical and humanities disciplines but it is not widely used across the geosciences disciplines despite the obvious applicability. This paper presents preliminary results from a multi-institutional project which seeks to evaluate the benefits and challenges of using an augmented reality sand box to support undergraduate learning in geomorphology. The sandbox enables users to create and visualise topography. As the sand is sculpted, contours are projected onto the miniature landscape. By hovering a hand over the box, users can make it `rain' over the landscape and the water `flows' down in to rivers and valleys. At undergraduate level, the sand-box is an ideal focus for problem-solving exercises, for example exploring how geomorphology controls hydrological processes, how such processes can be altered and the subsequent impacts of the changes for environmental risk. It is particularly valuable for students who favour a visual or kinesthetic learning style. Results presented in this paper discuss how the sandbox provides a complex interactive environment that encourages communication, collaboration and co-design.

Drag Reduction of an Airfoil Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, Chiyu; Sun, Anzhu; Marcus, Philip

2017-11-01

We reduced the drag of a 2D airfoil by starting with a NACA-0012 airfoil and used deep learning methods. We created a database which consists of simulations of 2D external flow over randomly generated shapes. We then developed a machine learning framework for external flow field inference given input shapes. Past work which utilized machine learning in Computational Fluid Dynamics focused on estimations of specific flow parameters, but this work is novel in the inference of entire flow fields. We further showed that learned flow patterns are transferable to cases that share certain similarities. This study illustrates the prospects of deeper integration of data-based modeling into current CFD simulation frameworks for faster flow inference and more accurate flow modeling.

A Model for Predicting Learning Flow and Achievement in Corporate e-Learning

ERIC Educational Resources Information Center

Joo, Young Ju; Lim, Kyu Yon; Kim, Su Mi

2012-01-01

The primary objective of this study was to investigate the determinants of learning flow and achievement in corporate online training. Self-efficacy, intrinsic value, and test anxiety were selected as learners' motivational factors, while perceived usefulness and ease of use were also selected as learning environmental factors. Learning flow was…

Prediction of Weather Impacted Airport Capacity using Ensemble Learning

NASA Technical Reports Server (NTRS)

Wang, Yao Xun

2011-01-01

Ensemble learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The ensemble bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the performance of BDT, along with traditional single Support Vector Machines (SVM), for airport runway configuration selection and airport arrival rates (AAR) prediction during weather impacts. Testing of these models was accomplished using observed weather, weather forecast, and airport operation information at the chosen airports. The experimental results show that ensemble methods are more accurate than a single SVM classifier. The airport capacity ensemble method presented here can be used as a decision support model that supports air traffic flow management to meet the weather impacted airport capacity in order to reduce costs and increase safety.

Freedom, Flow and Fairness: Exploring How Children Develop Socially at School through Outdoor Play

ERIC Educational Resources Information Center

Waite, Sue; Rogers, Sue; Evans, Julie

2013-01-01

In this article, we report on a study that sought to discover micro-level social interactions in fluid outdoor learning spaces. Our methodology was centred around the children; our methods moved with them and captured their social interactions through mobile audio-recording. We argue that our methodological approach supported access to…

Detection of Abnormal Events via Optical Flow Feature Analysis

PubMed Central

Wang, Tian; Snoussi, Hichem

2015-01-01

In this paper, a novel algorithm is proposed to detect abnormal events in video streams. The algorithm is based on the histogram of the optical flow orientation descriptor and the classification method. The details of the histogram of the optical flow orientation descriptor are illustrated for describing movement information of the global video frame or foreground frame. By combining one-class support vector machine and kernel principal component analysis methods, the abnormal events in the current frame can be detected after a learning period characterizing normal behaviors. The difference abnormal detection results are analyzed and explained. The proposed detection method is tested on benchmark datasets, then the experimental results show the effectiveness of the algorithm. PMID:25811227

Big Data and machine learning in radiation oncology: State of the art and future prospects.

PubMed

Bibault, Jean-Emmanuel; Giraud, Philippe; Burgun, Anita

2016-11-01

Precision medicine relies on an increasing amount of heterogeneous data. Advances in radiation oncology, through the use of CT Scan, dosimetry and imaging performed before each fraction, have generated a considerable flow of data that needs to be integrated. In the same time, Electronic Health Records now provide phenotypic profiles of large cohorts of patients that could be correlated to this information. In this review, we describe methods that could be used to create integrative predictive models in radiation oncology. Potential uses of machine learning methods such as support vector machine, artificial neural networks, and deep learning are also discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Case of Flow and Learning Revisited

ERIC Educational Resources Information Center

Ro, Young K.; Guo, Yi Maggie; Klein, Barbara D.

2018-01-01

Many business schools are criticized for being ineffective in helping students learn proper management skills and knowledge. Flow theory has been cited as being helpful in many learning environments in that flow experience can enhance student learning. The authors conducted a study of 315 students in an undergraduate operations management (OM)…

An Examination of Game-Based Learning from Theories of Flow Experience and Cognitive Load

ERIC Educational Resources Information Center

Lai, Chih-Hung; Chu, Chih-Ming; Liu, Hsiang-Hsuan; Yang, Shun-Bo; Chen, Wei-Hsuan

2013-01-01

This study aims to discuss whether game-based learning with the integration of games and digital learning could enhance not only the flow experience in learning but achieve the same flow experience in pure games. In addition, the authors discovered that whether the game-based learning could make learners to reveal higher cognitive load. The…

Effects of milk flow on the physiological and behavioural responses to feeding in an infant with hypoplastic left heart syndrome.

PubMed

Pados, Britt F; Thoyre, Suzanne M; Estrem, Hayley H; Park, Jinhee; Knafl, George J; Nix, Brant

2017-01-01

Infants with hypoplastic left heart syndrome often experience difficulty with oral feeding, which contributes to growth failure, morbidity, and mortality. In response to feeding difficulty, clinicians often change the bottle nipple, and thus milk flow rate. Slow-flow nipples have been found to reduce the stress of feeding in other fragile infants, but no research has evaluated the responses of infants with hypoplastic left heart syndrome to alterations in milk flow. The purpose of this study was to evaluate the physiological and behavioural responses of an infant with hypoplastic left heart syndrome to bottle feeding with either a slow-flow (Dr. Brown's Preemie) or a standard-flow (Dr. Brown's Level 2) nipple. A single infant was studied for three feedings: two slow-flow and one standard-flow. Oral feeding, whether with a slow-flow or a standard-flow nipple, was distressing for this infant. During slow-flow feeding, she experienced more coughing events, whereas during standard-flow she experienced more gagging. Disengagement and compelling disorganisation were most common during feeding 3, that is slow-flow, which occurred 2 days after surgical placement of a gastrostomy tube. Clinically significant changes in heart rate, oxygen saturation, and respiratory rate were seen during all feedings. Heart rate was higher during standard-flow and respiratory rate was higher during slow-flow. Further research is needed to examine the responses of infants with hypoplastic left heart syndrome to oral feeding and to identify strategies that will support these fragile infants as they learn to feed. Future research should evaluate an even slower-flow nipple along with additional supportive feeding strategies.

Basic life support: evaluation of learning using simulation and immediate feedback devices1.

PubMed

Tobase, Lucia; Peres, Heloisa Helena Ciqueto; Tomazini, Edenir Aparecida Sartorelli; Teodoro, Simone Valentim; Ramos, Meire Bruna; Polastri, Thatiane Facholi

2017-10-30

to evaluate students' learning in an online course on basic life support with immediate feedback devices, during a simulation of care during cardiorespiratory arrest. a quasi-experimental study, using a before-and-after design. An online course on basic life support was developed and administered to participants, as an educational intervention. Theoretical learning was evaluated by means of a pre- and post-test and, to verify the practice, simulation with immediate feedback devices was used. there were 62 participants, 87% female, 90% in the first and second year of college, with a mean age of 21.47 (standard deviation 2.39). With a 95% confidence level, the mean scores in the pre-test were 6.4 (standard deviation 1.61), and 9.3 in the post-test (standard deviation 0.82, p <0.001); in practice, 9.1 (standard deviation 0.95) with performance equivalent to basic cardiopulmonary resuscitation, according to the feedback device; 43.7 (standard deviation 26.86) mean duration of the compression cycle by second of 20.5 (standard deviation 9.47); number of compressions 167.2 (standard deviation 57.06); depth of compressions of 48.1 millimeter (standard deviation 10.49); volume of ventilation 742.7 (standard deviation 301.12); flow fraction percentage of 40.3 (standard deviation 10.03). the online course contributed to learning of basic life support. In view of the need for technological innovations in teaching and systematization of cardiopulmonary resuscitation, simulation and feedback devices are resources that favor learning and performance awareness in performing the maneuvers.

Embedding Hands-On Mini Laboratory Experiences in a Core Undergraduate Fluid Mechanics Course: A Pilot Study

ERIC Educational Resources Information Center

Han, Duanduan; Ugaz, Victor

2017-01-01

Three self-contained mini-labs were integrated into a core undergraduate fluid mechanics course, with the goal of delivering hands-on content in a manner scalable to large class sizes. These mini-labs supported learning objectives involving friction loss in pipes, flow measurement, and centrifugal pump analysis. The hands-on experiments were…

Prioritising Paradigms, Mixing Methods, and Characterising the "Qualitative" in Educational Research

ERIC Educational Resources Information Center

Taber, Keith S.

2012-01-01

There seems to be a continuous flow of new and revised books to support the teaching and learning of research methods in education and related fields. At one level, this is to be welcomed in an area such as research methodology where there is no single, widely accepted and coherent overview of the subject. The availability of diverse voices and…

The Corticohippocampal Circuit, Synaptic Plasticity, and Memory

PubMed Central

Basu, Jayeeta; Siegelbaum, Steven A.

2015-01-01

Synaptic plasticity serves as a cellular substrate for information storage in the central nervous system. The entorhinal cortex (EC) and hippocampus are interconnected brain areas supporting basic cognitive functions important for the formation and retrieval of declarative memories. Here, we discuss how information flow in the EC–hippocampal loop is organized through circuit design. We highlight recently identified corticohippocampal and intrahippocampal connections and how these long-range and local microcircuits contribute to learning. This review also describes various forms of activity-dependent mechanisms that change the strength of corticohippocampal synaptic transmission. A key point to emerge from these studies is that patterned activity and interaction of coincident inputs gives rise to associational plasticity and long-term regulation of information flow. Finally, we offer insights about how learning-related synaptic plasticity within the corticohippocampal circuit during sensory experiences may enable adaptive behaviors for encoding spatial, episodic, social, and contextual memories. PMID:26525152

Organisational learning and self-adaptation in dynamic disaster environments.

PubMed

Corbacioglu, Sitki; Kapucu, Naim

2006-06-01

This paper examines the problems associated with inter-organisational learning and adaptation in the dynamic environments that characterise disasters. The research uses both qualitative and quantitative methods to investigate whether organisational learning took place during and in the time in between five disaster response operations in Turkey. The availability of information and its exchange and distribution within and among organisational actors determine whether self-adaptation happens in the course of a disaster response operation. Organisational flexibility supported by an appropriate information infrastructure creates conditions conducive to essential interaction and permits the flow of information. The study found that no significant organisational learning occurred within Turkish disaster management following the earthquakes in Erzincan (1992), Dinar (1995) and Ceyhan (1998). By contrast, the 'symmetry-breaking' Marmara earthquake of 1999 initiated a 'double loop' learning process that led to change in the organisational, technical and cultural aspects of Turkish disaster management, as revealed by the Duzce earthquake response operations.

Testing and Oxygen Assessment Results for a Next Generation Extravehicular Activity Portable Life Support System Fan

NASA Technical Reports Server (NTRS)

Paul, Heather L.; Jennings, Mallory A.; Rivera, Fatonia L.; Martin, Devin

2011-01-01

NASA is designing a next generation Extravehicular Activity (EVA) Portable Life Support System (PLSS) for use in future surface exploration endeavors. To meet the new requirements for ventilation flow at nominal and buddy modes, a fan has been developed and tested. This paper summarizes the results of the performance and life cycle testing efforts conducted at the NASA Johnson Space Center. Additionally, oxygen compatibility assessment results from an evaluation conducted at White Sands Test Facility (WSTF) are provided, and lessons learned and future recommendations are outlined.

A Proposed Methodology to Classify Frontier Capital Markets

DTIC Science & Technology

2011-07-31

out of charity, but because it is the surest route to our common good.” -Inaugural Speech by President Barack Obama, Jan 2009 This project...identification, and machine learning. The algorithm consists of a unique binary classifier mechanism that combines three methods: k-Nearest Neighbors ( kNN ...Support Through kNN Ensemble Classification Techniques E. Capital Market Classification Based on Capital Flows and Trading Architecture F

A Tale of Two Chambers: Iterative Approaches and Lessons Learned from Life Support Systems Testing in Altitude Chambers

NASA Technical Reports Server (NTRS)

Callini, Gianluca

2016-01-01

With a brand new fire set ablaze by a serendipitous convergence of events ranging from a science fiction novel and movie ("The Martian"), to ground-breaking recent discoveries of flowing water on its surface, the drive for the journey to Mars seems to be in a higher gear than ever before. We are developing new spacecraft and support systems to take humans to the Red Planet, while scientists on Earth continue using the International Space Station as a laboratory to evaluate the effects of long duration space flight on the human body. Written from the perspective of a facility test director rather than a researcher, and using past and current life support systems tests as examples, this paper seeks to provide an overview on how facility teams approach testing, the kind of information they need to ensure efficient collaborations and successful tests, and how, together with researchers and principal investigators, we can collectively apply what we learn to execute future tests.

Space: the final frontier in the learning of science?

NASA Astrophysics Data System (ADS)

Milne, Catherine

2014-03-01

In Space, relations, and the learning of science, Wolff-Michael Roth and Pei-Ling Hsu use ethnomethodology to explore high school interns learning shopwork and shoptalk in a research lab that is located in a world class facility for water quality analysis. Using interaction analysis they identify how spaces, like a research laboratory, can be structured as smart spaces to create a workflow (learning flow) so that shoptalk and shopwork can projectively organize the actions of interns even in new and unfamiliar settings. Using these findings they explore implications for the design of curriculum and learning spaces more broadly. The Forum papers of Erica Blatt and Cassie Quigley complement this analysis. Blatt expands the discussion on space as an active component of learning with an examination of teaching settings, beyond laboratory spaces, as active participants of education. Quigley examines smart spaces as authentic learning spaces while acknowledging how internship experiences all empirical elements of authentic learning including open-ended inquiry and empowerment. In this paper I synthesize these ideas and propose that a narrative structure might better support workflow, student agency and democratic decision making.

Exploring the Role of Flow Experience, Learning Performance and Potential Behavior Clusters in Elementary Students' Game-Based Learning

ERIC Educational Resources Information Center

Hsieh, Ya-Hui; Lin, Yi-Chun; Hou, Huei-Tse

2016-01-01

Well-designed game-based learning can provide students with an innovative environment that may enhance students' motivation and engagement in learning and thus improve their learning performance. The purpose of this study was to examine the relationships among elementary school students' flow experience and learning performances. We also…

Adaptive Neuron Apoptosis for Accelerating Deep Learning on Large Scale Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siegel, Charles M.; Daily, Jeffrey A.; Vishnu, Abhinav

Machine Learning and Data Mining (MLDM) algorithms are becoming ubiquitous in {\\em model learning} from the large volume of data generated using simulations, experiments and handheld devices. Deep Learning algorithms -- a class of MLDM algorithms -- are applied for automatic feature extraction, and learning non-linear models for unsupervised and supervised algorithms. Naturally, several libraries which support large scale Deep Learning -- such as TensorFlow and Caffe -- have become popular. In this paper, we present novel techniques to accelerate the convergence of Deep Learning algorithms by conducting low overhead removal of redundant neurons -- {\\em apoptosis} of neurons --more » which do not contribute to model learning, during the training phase itself. We provide in-depth theoretical underpinnings of our heuristics (bounding accuracy loss and handling apoptosis of several neuron types), and present the methods to conduct adaptive neuron apoptosis. We implement our proposed heuristics with the recently introduced TensorFlow and using its recently proposed extension with MPI. Our performance evaluation on two difference clusters -- one connected with Intel Haswell multi-core systems, and other with nVIDIA GPUs -- using InfiniBand, indicates the efficacy of the proposed heuristics and implementations. Specifically, we are able to improve the training time for several datasets by 2-3x, while reducing the number of parameters by 30x (4-5x on average) on datasets such as ImageNet classification. For the Higgs Boson dataset, our implementation improves the accuracy (measured by Area Under Curve (AUC)) for classification from 0.88/1 to 0.94/1, while reducing the number of parameters by 3x in comparison to existing literature, while achieving a 2.44x speedup in comparison to the default (no apoptosis) algorithm.« less

Mechanical Design of a Performance Test Rig for the Turbine Air-Flow Task (TAFT)

NASA Technical Reports Server (NTRS)

Forbes, John C.; Xenofos, George D.; Farrow, John L.; Tyler, Tom; Williams, Robert; Sargent, Scott; Moharos, Jozsef

2004-01-01

To support development of the Boeing-Rocketdyne RS84 rocket engine, a full-flow, reaction turbine geometry was integrated into the NASA-MSFC turbine air-flow test facility. A mechanical design was generated which minimized the amount of new hardware while incorporating all test and instrumentation requirements. This paper provides details of the mechanical design for this Turbine Air-Flow Task (TAFT) test rig. The mechanical design process utilized for this task included the following basic stages: Conceptual Design. Preliminary Design. Detailed Design. Baseline of Design (including Configuration Control and Drawing Revision). Fabrication. Assembly. During the design process, many lessons were learned that should benefit future test rig design projects. Of primary importance are well-defined requirements early in the design process, a thorough detailed design package, and effective communication with both the customer and the fabrication contractors.

Application of machine learning and expert systems to Statistical Process Control (SPC) chart interpretation

NASA Technical Reports Server (NTRS)

Shewhart, Mark

1991-01-01

Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.

Improving Educator Development by Innovation in Teaching Activity via web 2.0

NASA Astrophysics Data System (ADS)

Saadah Abdullah, Nurhanim; Aziz, Mohd Ismail Abd; Ismail, Affero; Hashim, Suhaizal

2017-05-01

Preparing insightful teaching and learning materials for a lesson does need the effort from the educators. Educators should make some research of suitable ways to improve their teaching and learning sessions. In this 21st century, technologies are widely used as tools for education. Even so, there are educators that willing to support and some who do not agree to change. The aim of this study is to develop an innovation teaching materials by applying web 2.0 tools. The intention is to broaden knowledge and in the same time getting response and feedback from people regarding the teaching and learning session materials produced with proper instruction. Action research was used to give a structured flow of this study. The outcome of this study was encouraging and the reflection of this study can help educators in improvising their teaching and learning sessions and materials using action research.

On the Conditioning of Machine-Learning-Assisted Turbulence Modeling

NASA Astrophysics Data System (ADS)

Wu, Jinlong; Sun, Rui; Wang, Qiqi; Xiao, Heng

2017-11-01

Recently, several researchers have demonstrated that machine learning techniques can be used to improve the RANS modeled Reynolds stress by training on available database of high fidelity simulations. However, obtaining improved mean velocity field remains an unsolved challenge, restricting the predictive capability of current machine-learning-assisted turbulence modeling approaches. In this work we define a condition number to evaluate the model conditioning of data-driven turbulence modeling approaches, and propose a stability-oriented machine learning framework to model Reynolds stress. Two canonical flows, the flow in a square duct and the flow over periodic hills, are investigated to demonstrate the predictive capability of the proposed framework. The satisfactory prediction performance of mean velocity field for both flows demonstrates the predictive capability of the proposed framework for machine-learning-assisted turbulence modeling. With showing the capability of improving the prediction of mean flow field, the proposed stability-oriented machine learning framework bridges the gap between the existing machine-learning-assisted turbulence modeling approaches and the demand of predictive capability of turbulence models in real applications.

Deep Learning for Flow Sculpting: Insights into Efficient Learning using Scientific Simulation Data

NASA Astrophysics Data System (ADS)

Stoecklein, Daniel; Lore, Kin Gwn; Davies, Michael; Sarkar, Soumik; Ganapathysubramanian, Baskar

2017-04-01

A new technique for shaping microfluid flow, known as flow sculpting, offers an unprecedented level of passive fluid flow control, with potential breakthrough applications in advancing manufacturing, biology, and chemistry research at the microscale. However, efficiently solving the inverse problem of designing a flow sculpting device for a desired fluid flow shape remains a challenge. Current approaches struggle with the many-to-one design space, requiring substantial user interaction and the necessity of building intuition, all of which are time and resource intensive. Deep learning has emerged as an efficient function approximation technique for high-dimensional spaces, and presents a fast solution to the inverse problem, yet the science of its implementation in similarly defined problems remains largely unexplored. We propose that deep learning methods can completely outpace current approaches for scientific inverse problems while delivering comparable designs. To this end, we show how intelligent sampling of the design space inputs can make deep learning methods more competitive in accuracy, while illustrating their generalization capability to out-of-sample predictions.

Local Learning Strategies for Wake Identification

NASA Astrophysics Data System (ADS)

Colvert, Brendan; Alsalman, Mohamad; Kanso, Eva

2017-11-01

Swimming agents, biological and engineered alike, must navigate the underwater environment to survive. Tasks such as autonomous navigation, foraging, mating, and predation require the ability to extract critical cues from the hydrodynamic environment. A substantial body of evidence supports the hypothesis that biological systems leverage local sensing modalities, including flow sensing, to gain knowledge of their global surroundings. The nonlinear nature and high degree of complexity of fluid dynamics makes the development of algorithms for implementing localized sensing in bioinspired engineering systems essentially intractable for many systems of practical interest. In this work, we use techniques from machine learning for training a bioinspired swimmer to learn from its environment. We demonstrate the efficacy of this strategy by learning how to sense global characteristics of the wakes of other swimmers measured only from local sensory information. We conclude by commenting on the advantages and limitations of this data-driven, machine learning approach and its potential impact on broader applications in underwater sensing and navigation.

Signal information available for plume source tracking with and without surface waves and learning by undergraduates assisting with the research

NASA Astrophysics Data System (ADS)

Wiley, Megan Beth

Autonomous vehicles have had limited success in locating point sources of pollutants, chemicals, and other passive scalars. However, animals such as stomatopods, a mantis shrimp, track odor plumes easily for food, mates, and habitat. Laboratory experiments using Planar Laser Induced Fluorescence measured odor concentration downstream of a diffusive source with and without live stomatopods to investigate their source-tracking strategies in unidirectional and "wave-affected" (surface waves with a mean current) flows. Despite the dearth of signal, extreme temporal variation, and meandering plume centerline, the stomatopods were able to locate the source, especially in the wave-affected flow. Differences in the two plumes far from the source (>160 cm) appeared to help the animals in the wave-affected flow position themselves closer to the source (<70 cm) at times with relatively large amounts of odor and plume filaments of high concentration. At the height of the animals' antennules, the site of their primary chemosensors, the time-averaged Reynolds stresses in the two flows were approximately the same. The temporal variation in stresses over the wave cycle may be responsible for differences in the two plumes. The antennule height falls between a region of large peaks in Reynolds stress in phase with peaks in streamwise acceleration, and a lower region with a smaller Reynolds stress peak in phase with maximum shear during flow reversal. Six undergraduate students assisted with the research. We documented their daily activities and ideas on plume dispersion using open-ended interviews. Most of their time was spent on tasks that required no understanding of fluid mechanics, and there was little evidence of learning by participation in the RAship. One RA's conceptions of turbulence did change, but a group workshop seemed to support this learning more than the RAship. The documented conceptions could aid in curriculum design, since situating new information within current knowledge seems to deepen learning outcomes. The RAs' conceptions varied widely with some overlap of ideas. The interviews also showed that most RAs did not discuss molecular diffusion as part of the mixing process and some remembered information from course demonstrations, but applied them inappropriately to the interview questions.

Effects of Presence, Copresence, and Flow on Learning Outcomes in 3D Learning Spaces

ERIC Educational Resources Information Center

Hassell, Martin D.; Goyal, Sandeep; Limayem, Moez; Boughzala, Imed

2012-01-01

The level of satisfaction and effectiveness of 3D virtual learning environments were examined. Additionally, 3D virtual learning environments were compared with face-to-face learning environments. Students that experienced higher levels of flow and presence also experienced more satisfaction but not necessarily more effectiveness with 3D virtual…

An Exploratory Study Comparing the Effectiveness of Lecturing versus Team-Based Learning

ERIC Educational Resources Information Center

Huggins, Christopher M.; Stamatel, Janet P.

2015-01-01

Lecturing has been criticized for fostering a passive learning environment, emphasizing a one-way flow of information, and not adequately engaging students. In contrast, active-learning approaches, such as team-based learning (TBL), prioritize student interaction and engagement and create multidirectional flows of information. This paper presents…

Accurate Descriptions of Hot Flow Behaviors Across β Transus of Ti-6Al-4V Alloy by Intelligence Algorithm GA-SVR

NASA Astrophysics Data System (ADS)

Wang, Li-yong; Li, Le; Zhang, Zhi-hua

2016-09-01

Hot compression tests of Ti-6Al-4V alloy in a wide temperature range of 1023-1323 K and strain rate range of 0.01-10 s-1 were conducted by a servo-hydraulic and computer-controlled Gleeble-3500 machine. In order to accurately and effectively characterize the highly nonlinear flow behaviors, support vector regression (SVR) which is a machine learning method was combined with genetic algorithm (GA) for characterizing the flow behaviors, namely, the GA-SVR. The prominent character of GA-SVR is that it with identical training parameters will keep training accuracy and prediction accuracy at a stable level in different attempts for a certain dataset. The learning abilities, generalization abilities, and modeling efficiencies of the mathematical regression model, ANN, and GA-SVR for Ti-6Al-4V alloy were detailedly compared. Comparison results show that the learning ability of the GA-SVR is stronger than the mathematical regression model. The generalization abilities and modeling efficiencies of these models were shown as follows in ascending order: the mathematical regression model < ANN < GA-SVR. The stress-strain data outside experimental conditions were predicted by the well-trained GA-SVR, which improved simulation accuracy of the load-stroke curve and can further improve the related research fields where stress-strain data play important roles, such as speculating work hardening and dynamic recovery, characterizing dynamic recrystallization evolution, and improving processing maps.

Implementation of a Learning Design Run-Time Environment for the .LRN Learning Management System

ERIC Educational Resources Information Center

del Cid, Jose Pablo Escobedo; de la Fuente Valentin, Luis; Gutierrez, Sergio; Pardo, Abelardo; Kloos, Carlos Delgado

2007-01-01

The IMS Learning Design specification aims at capturing the complete learning flow of courses, without being restricted to a particular pedagogical model. Such flow description for a course, called a Unit of Learning, must be able to be reproduced in different systems using a so called run-time environment. In the last few years there has been…

Deep Learning for Flow Sculpting: Insights into Efficient Learning using Scientific Simulation Data

PubMed Central

Stoecklein, Daniel; Lore, Kin Gwn; Davies, Michael; Sarkar, Soumik; Ganapathysubramanian, Baskar

2017-01-01

A new technique for shaping microfluid flow, known as flow sculpting, offers an unprecedented level of passive fluid flow control, with potential breakthrough applications in advancing manufacturing, biology, and chemistry research at the microscale. However, efficiently solving the inverse problem of designing a flow sculpting device for a desired fluid flow shape remains a challenge. Current approaches struggle with the many-to-one design space, requiring substantial user interaction and the necessity of building intuition, all of which are time and resource intensive. Deep learning has emerged as an efficient function approximation technique for high-dimensional spaces, and presents a fast solution to the inverse problem, yet the science of its implementation in similarly defined problems remains largely unexplored. We propose that deep learning methods can completely outpace current approaches for scientific inverse problems while delivering comparable designs. To this end, we show how intelligent sampling of the design space inputs can make deep learning methods more competitive in accuracy, while illustrating their generalization capability to out-of-sample predictions. PMID:28402332

Exploring the roles of interaction and flow in explaining nurses' e-learning acceptance.

PubMed

Cheng, Yung-Ming

2013-01-01

To provide safe and competent patient care, it is very important that medical institutions should provide nurses with continuing education by using appropriate learning methods. As compared to traditional learning, electronic learning (e-learning) is a more flexible method for nurses' in-service learning. Hence, e-learning is expected to play a pivotal role in providing continuing education for nurses. This study's purpose was to explore the role and relevance of interaction factors, intrinsic motivator (i.e., flow), and extrinsic motivators (i.e., perceived usefulness (PU) and perceived ease of use (PEOU)) in explaining nurses' intention to use the e-learning system. Based on the technology acceptance model (TAM) with the flow theory, this study's research model presents three types of interaction factors, learner-system interaction, instructor-learner interaction, and learner-learner interaction to construct an extended TAM to explore nurses' intention to use the e-learning system. Sample data were gathered from nurses at two regional hospitals in Taiwan. A total of 320 questionnaires were distributed, 254 (79.375%) questionnaires were returned. Consequently, 218 usable questionnaires were analyzed in this study, with a usable response rate of 68.125%. First, confirmatory factor analysis was used to develop the measurement model. Second, to explore the causal relationships among all constructs, the structural model for the research model was tested by using structural equation modeling. First, learner-system interaction, instructor-learner interaction, and learner-learner interaction respectively had significant effects on PU, PEOU, and flow. Next, flow had significant effects on PU and PEOU, and PEOU had a significant effect on PU. Finally, the effects of flow, PU, and PEOU on intention to use were significant. Synthetically speaking, learner-system interaction, instructor-learner interaction, and learner-learner interaction can indirectly make significant impacts on nurses' usage intention of the e-learning system via their extrinsic motivators (i.e., PU and PEOU) and intrinsic motivator (i.e., flow). Copyright © 2012 Elsevier Ltd. All rights reserved.

Measuring Flow Experience in an Immersive Virtual Environment for Collaborative Learning

ERIC Educational Resources Information Center

van Schaik, P.; Martin, S.; Vallance, M.

2012-01-01

In contexts other than immersive virtual environments, theoretical and empirical work has identified flow experience as a major factor in learning and human-computer interaction. Flow is defined as a "holistic sensation that people feel when they act with total involvement". We applied the concept of flow to modeling the experience of…

Factors Impacting Corporate E-Learners' Learning Flow, Satisfaction, and Learning Persistence

ERIC Educational Resources Information Center

Joo, Young Ju; Joung, Sunyong; Kim, Nam Hee; Chung, Hyun Min

2012-01-01

This study aimed to investigate the structural relationships among teaching presence, cognitive presence, usage, learning flow, satisfaction, and learning persistence in corporate e-learners. The research participants were 462 e-learners registered for e-lectures through an electronics company in South Korea. First, the sense of teaching presence,…

Negotiating Energy Dynamics through Embodied Action in a Materially Structured Environment

ERIC Educational Resources Information Center

Scherr, Rachel E.; Close, Hunter G.; Close, Eleanor W.; Flood, Virginia J.; McKagan, Sarah B.; Robertson, Amy D.; Seeley, Lane; Wittmann, Michael C.; Vokos, Stamatis

2013-01-01

We provide evidence that a learning activity called Energy Theater engages learners with key conceptual issues in the learning of energy, including disambiguating matter flow and energy flow and theorizing mechanisms for energy transformation. A participationist theory of learning, in which learning is indicated by changes in speech and behavior,…

Fifth Graders' Flow Experience in a Digital Game-Based Science Learning Environment

ERIC Educational Resources Information Center

Zheng, Meixun; Spires, Hiller A.

2014-01-01

This mixed methods study examined 73 5th graders' flow experience in a game-based science learning environment using two gameplay approaches (solo and collaborative gameplay). Both survey and focus group interview findings revealed that students had high flow experience; however, there were no flow experience differences that were contingent upon…

A Study of Flow Theory in the Foreign Language Classroom

ERIC Educational Resources Information Center

Egbert, Joy

2004-01-01

This article focuses on the relationship between flow experiences and language learning. Flow Theory suggests that flow experiences (characterized by a balance between challenge and skills and by a person's interest, control, and focused attention during a task) can lead to optimal learning. This theory has not yet been tested in the area of…

A Preliminary Analysis of the Theoretical Parameters of Organizaational Learning.

DTIC Science & Technology

1995-09-01

PARAMETERS OF ORGANIZATIONAL LEARNING THESIS Presented to the Faculty of the Graduate School of Logistics and Acquisition Management of the Air...Organizational Learning Parameters in the Knowledge Acquisition Category 2~™ 2-3. Organizational Learning Parameters in the Information Distribution Category...Learning Refined Scale 4-94 4-145. Composition of Refined Scale 4 Knowledge Flow 4-95 4-146. Cronbach’s Alpha Statistics for the Complete Knowledge Flow

Optimally managing water resources in large river basins for an uncertain future

USGS Publications Warehouse

Roehl, Edwin A.; Conrads, Paul

2014-01-01

One of the challenges of basin management is the optimization of water use through ongoing regional economic development, droughts, and climate change. This paper describes a model of the Savannah River Basin designed to continuously optimize regulated flow to meet prioritized objectives set by resource managers and stakeholders. The model was developed from historical data by using machine learning, making it more accurate and adaptable to changing conditions than traditional models. The model is coupled to an optimization routine that computes the daily flow needed to most efficiently meet the water-resource management objectives. The model and optimization routine are packaged in a decision support system that makes it easy for managers and stakeholders to use. Simulation results show that flow can be regulated to substantially reduce salinity intrusions in the Savannah National Wildlife Refuge while conserving more water in the reservoirs. A method for using the model to assess the effectiveness of the flow-alteration features after the deepening also is demonstrated.

Flow Navigation by Smart Microswimmers via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Colabrese, Simona; Gustavsson, Kristian; Celani, Antonio; Biferale, Luca

2017-04-01

Smart active particles can acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. Their goal is to learn the best way to navigate by exploiting the underlying flow whenever possible. As an example, we focus our attention on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, given the constraints enforced by fluid mechanics. By means of numerical experiments, we show that swimmers indeed learn nearly optimal strategies just by experience. A reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This Letter illustrates the potential of reinforcement learning algorithms to model adaptive behavior in complex flows and paves the way towards the engineering of smart microswimmers that solve difficult navigation problems.

Exploring Learners' Sequential Behavioral Patterns, Flow Experience, and Learning Performance in an Anti-Phishing Educational Game

ERIC Educational Resources Information Center

Sun, Jerry Chih-Yuan; Kuo, Cian-Yu; Hou, Huei-Tse; Lin, Yu-Yan

2017-01-01

The purposes of this study were to provide a game-based anti-phishing lesson to 110 elementary school students in Taiwan, explore their learning behavioral patterns, and investigate the effects of the flow states on their learning behavioral patterns and learning achievement. The study recorded behaviour logs, and applied a pre- and post-test on…

Rayleigh- and Prandtl-number dependence of the large-scale flow-structure in weakly-rotating turbulent thermal convection

NASA Astrophysics Data System (ADS)

Weiss, Stephan; Wei, Ping; Ahlers, Guenter

2015-11-01

Turbulent thermal convection under rotation shows a remarkable variety of different flow states. The Nusselt number (Nu) at slow rotation rates (expressed as the dimensionless inverse Rossby number 1/Ro), for example, is not a monotonic function of 1/Ro. Different 1/Ro-ranges can be observed with different slopes ∂Nu / ∂ (1 / Ro) . Some of these ranges are connected by sharp transitions where ∂Nu / ∂ (1 / Ro) changes discontinuously. We investigate different regimes in cylindrical samples of aspect ratio Γ = 1 by measuring temperatures at the sidewall of the sample for various Prandtl numbers in the range 3 < Pr < 35 and Rayleigh numbers in the range of 108 < Ra < 4 ×1011 . From these measurements we deduce changes of the flow structure. We learn about the stability and dynamics of the large-scale circulation (LSC), as well as about its breakdown and the onset of vortex formation close to the top and bottom plate. We shall examine correlations between these measurements and changes in the heat transport. This work was supported by NSF grant DRM11-58514. SW acknowledges support by the Deutsche Forschungsgemeinschaft.

Machine Learning Algorithms for prediction of regions of high Reynolds Averaged Navier Stokes Uncertainty

NASA Astrophysics Data System (ADS)

Mishra, Aashwin; Iaccarino, Gianluca

2017-11-01

In spite of their deficiencies, RANS models represent the workhorse for industrial investigations into turbulent flows. In this context, it is essential to provide diagnostic measures to assess the quality of RANS predictions. To this end, the primary step is to identify feature importances amongst massive sets of potentially descriptive and discriminative flow features. This aids the physical interpretability of the resultant discrepancy model and its extensibility to similar problems. Recent investigations have utilized approaches such as Random Forests, Support Vector Machines and the Least Absolute Shrinkage and Selection Operator for feature selection. With examples, we exhibit how such methods may not be suitable for turbulent flow datasets. The underlying rationale, such as the correlation bias and the required conditions for the success of penalized algorithms, are discussed with illustrative examples. Finally, we provide alternate approaches using convex combinations of regularized regression approaches and randomized sub-sampling in combination with feature selection algorithms, to infer model structure from data. This research was supported by the Defense Advanced Research Projects Agency under the Enabling Quantification of Uncertainty in Physical Systems (EQUiPS) project (technical monitor: Dr Fariba Fahroo).

Learning to classify wakes from local sensory information

NASA Astrophysics Data System (ADS)

Alsalman, Mohamad; Colvert, Brendan; Kanso, Eva; Kanso Team

2017-11-01

Aquatic organisms exhibit remarkable abilities to sense local flow signals contained in their fluid environment and to surmise the origins of these flows. For example, fish can discern the information contained in various flow structures and utilize this information for obstacle avoidance and prey tracking. Flow structures created by flapping and swimming bodies are well characterized in the fluid dynamics literature; however, such characterization relies on classical methods that use an external observer to reconstruct global flow fields. The reconstructed flows, or wakes, are then classified according to the unsteady vortex patterns. Here, we propose a new approach for wake identification: we classify the wakes resulting from a flapping airfoil by applying machine learning algorithms to local flow information. In particular, we simulate the wakes of an oscillating airfoil in an incoming flow, extract the downstream vorticity information, and train a classifier to learn the different flow structures and classify new ones. This data-driven approach provides a promising framework for underwater navigation and detection in application to autonomous bio-inspired vehicles.

Teaching communication and supporting autonomy with a team-based operative simulator.

PubMed

Cook, Mackenzie R; Deal, Shanley B; Scott, Jessica M; Moren, Alexis M; Kiraly, Laszlo N

2016-09-01

Changing residency structure emphasizes the need for formal instruction on team leadership and intraoperative teaching skills. A high fidelity, multi-learner surgical simulation may offer opportunities for senior learners (SLs) to learn these skills while teaching technical skills to junior learners (JLs). We designed and optimized a low-cost inguinal hernia model that paired JLs and SLs as an operative team. This was tested in 3 pilot simulations. Participants' feedback was analyzed using qualitative methods. JL feedback to SLs included the themes "guiding and instructing" and "allowing autonomy." Senior Learner feedback to JLs focused on "mechanics," "knowledge," and "perspective/flow." Both groups focused on "communication" and "professionalism." A multi-learner simulation can successfully meet the technical learning needs of JLs and the teaching and communication learning needs of SLs. This model of resident-driven simulation may illustrate future opportunities for operative simulation. Copyright © 2016 Elsevier Inc. All rights reserved.

An Active, Collaborative Approach to Learning Skills in Flow Cytometry

ERIC Educational Resources Information Center

Fuller, Kathryn; Linden, Matthew D.; Lee-Pullen, Tracey; Fragall, Clayton; Erber, Wendy N.; Röhrig, Kimberley J.

2016-01-01

Advances in science education research have the potential to improve the way students learn to perform scientific interpretations and understand science concepts. We developed active, collaborative activities to teach skills in manipulating flow cytometry data using FlowJo software. Undergraduate students were given compensated clinical flow…

Observing Flow in Young Children's Music Learning.

ERIC Educational Resources Information Center

Custodero, Lori A.

1998-01-01

Explores a study that quantifies preschool children's music learning preferences in teacher-intitiated environments by observing the children on video to determine their flow experiences where the challenge level and skill level are both high. Stresses that using flow to measure music experiences provides a means for teachers to evaluate student…

Thalamocortical and corticothalamic pathways differentially contribute to goal-directed behaviors in the rat

PubMed Central

Alcaraz, Fabien; Fresno, Virginie; Marchand, Alain R; Kremer, Eric J; Coutureau, Etienne

2018-01-01

Highly distributed neural circuits are thought to support adaptive decision-making in volatile and complex environments. Notably, the functional interactions between prefrontal and reciprocally connected thalamic nuclei areas may be important when choices are guided by current goal value or action-outcome contingency. We examined the functional involvement of selected thalamocortical and corticothalamic pathways connecting the dorsomedial prefrontal cortex (dmPFC) and the mediodorsal thalamus (MD) in the behaving rat. Using a chemogenetic approach to inhibit projection-defined dmPFC and MD neurons during an instrumental learning task, we show that thalamocortical and corticothalamic pathways differentially support goal attributes. Both pathways participate in adaptation to the current goal value, but only thalamocortical neurons are required to integrate current causal relationships. These data indicate that antiparallel flow of information within thalamocortical circuits may convey qualitatively distinct aspects of adaptive decision-making and highlight the importance of the direction of information flow within neural circuits. PMID:29405119

Current challenges in quantifying preferential flow through the vadose zone

NASA Astrophysics Data System (ADS)

Koestel, John; Larsbo, Mats; Jarvis, Nick

2017-04-01

In this presentation, we give an overview of current challenges in quantifying preferential flow through the vadose zone. A review of the literature suggests that current generation models do not fully reflect the present state of process understanding and empirical knowledge of preferential flow. We believe that the development of improved models will be stimulated by the increasingly widespread application of novel imaging technologies as well as future advances in computational power and numerical techniques. One of the main challenges in this respect is to bridge the large gap between the scales at which preferential flow occurs (pore to Darcy scales) and the scale of interest for management (fields, catchments, regions). Studies at the pore scale are being supported by the development of 3-D non-invasive imaging and numerical simulation techniques. These studies are leading to a better understanding of how macropore network topology and initial/boundary conditions control key state variables like matric potential and thus the strength of preferential flow. Extrapolation of this knowledge to larger scales would require support from theoretical frameworks such as key concepts from percolation and network theory, since we lack measurement technologies to quantify macropore networks at these large scales. Linked hydro-geophysical measurement techniques that produce highly spatially and temporally resolved data enable investigation of the larger-scale heterogeneities that can generate preferential flow patterns at pedon, hillslope and field scales. At larger regional and global scales, improved methods of data-mining and analyses of large datasets (machine learning) may help in parameterizing models as well as lead to new insights into the relationships between soil susceptibility to preferential flow and site attributes (climate, land uses, soil types).

Efficient collective swimming by harnessing vortices through deep reinforcement learning.

PubMed

Verma, Siddhartha; Novati, Guido; Koumoutsakos, Petros

2018-06-05

Fish in schooling formations navigate complex flow fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behavior has been associated with evolutionary advantages including energy savings, yet the underlying physical mechanisms remain unknown. We show that fish can improve their sustained propulsive efficiency by placing themselves in appropriate locations in the wake of other swimmers and intercepting judiciously their shed vortices. This swimming strategy leads to collective energy savings and is revealed through a combination of high-fidelity flow simulations with a deep reinforcement learning (RL) algorithm. The RL algorithm relies on a policy defined by deep, recurrent neural nets, with long-short-term memory cells, that are essential for capturing the unsteadiness of the two-way interactions between the fish and the vortical flow field. Surprisingly, we find that swimming in-line with a leader is not associated with energetic benefits for the follower. Instead, "smart swimmer(s)" place themselves at off-center positions, with respect to the axis of the leader(s) and deform their body to synchronize with the momentum of the oncoming vortices, thus enhancing their swimming efficiency at no cost to the leader(s). The results confirm that fish may harvest energy deposited in vortices and support the conjecture that swimming in formation is energetically advantageous. Moreover, this study demonstrates that deep RL can produce navigation algorithms for complex unsteady and vortical flow fields, with promising implications for energy savings in autonomous robotic swarms.

Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers

NASA Astrophysics Data System (ADS)

Garimella, Sarvesh; Rothenberg, Daniel A.; Wolf, Martin J.; David, Robert O.; Kanji, Zamin A.; Wang, Chien; Rösch, Michael; Cziczo, Daniel J.

2017-09-01

This study investigates the measurement of ice nucleating particle (INP) concentrations and sizing of crystals using continuous flow diffusion chambers (CFDCs). CFDCs have been deployed for decades to measure the formation of INPs under controlled humidity and temperature conditions in laboratory studies and by ambient aerosol populations. These measurements have, in turn, been used to construct parameterizations for use in models by relating the formation of ice crystals to state variables such as temperature and humidity as well as aerosol particle properties such as composition and number. We show here that assumptions of ideal instrument behavior are not supported by measurements made with a commercially available CFDC, the SPectrometer for Ice Nucleation (SPIN), and the instrument on which it is based, the Zurich Ice Nucleation Chamber (ZINC). Non-ideal instrument behavior, which is likely inherent to varying degrees in all CFDCs, is caused by exposure of particles to different humidities and/or temperatures than predicated from instrument theory of operation. This can result in a systematic, and variable, underestimation of reported INP concentrations. We find here variable correction factors from 1.5 to 9.5, consistent with previous literature values. We use a machine learning approach to show that non-ideality is most likely due to small-scale flow features where the aerosols are combined with sheath flows. Machine learning is also used to minimize the uncertainty in measured INP concentrations. We suggest that detailed measurement, on an instrument-by-instrument basis, be performed to characterize this uncertainty.

Reciprocal learning with task cards for teaching Basic Life Support (BLS): investigating effectiveness and the effect of instructor expertise on learning outcomes. A randomized controlled trial.

PubMed

Iserbyt, Peter; Mols, Liesbet; Charlier, Nathalie; De Meester, Sophie

2014-01-01

Basic Life Support (BLS) education in secondary schools and universities is often neglected or outsourced because teachers indicate not feeling competent to teach this content. Investigate reciprocal learning with task cards as instructional model for teaching BLS and the effect of instructor expertise in BLS on learning outcomes. There were 175 students (mean age = 18.9 years) randomized across a reciprocal/BLS instructor (RBI) group, a reciprocal/non-BLS instructor (RNI) group, and a traditional/BLS instructor group (TBI). In the RBI and RNI group, students were taught BLS through reciprocal learning with task cards. The instructor in the RBI group was certified in BLS by the European Resuscitation Council. In the TBI, students were taught BLS by a certified instructor according to the Belgian Red Cross instructional model. Student performance was assessed 1 day (intervention) and 3 weeks after intervention (retention). At retention, significantly higher BLS performances were found in the RBI group (M = 78%), p = 0.007, ES = 0.25, and the RNI group (M = 80%), p < 0.001, Effect Size (ES) = .36, compared to the TBI (M = 73%). Significantly more students remembered and performed all BLS skills in the experimental groups at intervention and retention. No differences in BLS performance were found between the reciprocal groups. Ventilation volumes and flow rates were significantly better in the TBI at intervention and retention. Reciprocal learning with task cards is a valuable model for teaching BLS when instructors are not experienced or skilled in BLS. Copyright © 2014 Elsevier Inc. All rights reserved.

Application of graph-based semi-supervised learning for development of cyber COP and network intrusion detection

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Colonna-Romano, John; Eslami, Mohammed

2017-05-01

The United States increasingly relies on cyber-physical systems to conduct military and commercial operations. Attacks on these systems have increased dramatically around the globe. The attackers constantly change their methods, making state-of-the-art commercial and military intrusion detection systems ineffective. In this paper, we present a model to identify functional behavior of network devices from netflow traces. Our model includes two innovations. First, we define novel features for a host IP using detection of application graph patterns in IP's host graph constructed from 5-min aggregated packet flows. Second, we present the first application, to the best of our knowledge, of Graph Semi-Supervised Learning (GSSL) to the space of IP behavior classification. Using a cyber-attack dataset collected from NetFlow packet traces, we show that GSSL trained with only 20% of the data achieves higher attack detection rates than Support Vector Machines (SVM) and Naïve Bayes (NB) classifiers trained with 80% of data points. We also show how to improve detection quality by filtering out web browsing data, and conclude with discussion of future research directions.

Do International Health Partnerships contribute to reverse innovation? a mixed methods study of THET-supported partnerships in the UK.

PubMed

Kulasabanathan, Kavian; Issa, Hamdi; Bhatti, Yasser; Prime, Matthew; Del Castillo, Jacqueline; Darzi, Ara; Harris, Matthew

2017-04-18

International health partnerships (IHPs) are changing, with an increased emphasis on mutual accountability and joint agenda setting for both the high- and the low- or middle-income country (LMIC) partners. There is now an important focus on the bi-directionality of learning however for the UK partners, this typically focuses on learning at the individual level, through personal and professional development. We sought to evaluate whether this learning also takes the shape of 'Reverse Innovation' -when an idea conceived in a low-income country is subsequently adopted in a higher-income country. This mixed methods study used an initial scoping survey of all the UK-leads of the Tropical Health Education Trust (THET)-supported International Health Partnerships (n = 114) to ascertain the extent to which the IHPs are or have been vehicles for Reverse Innovation. The survey formed the sampling frame for further deep-dive interviews to focus on volunteers' experiences and attitudes to learning from LMICs. Interviews of IHP leads (n = 12) were audio-recorded and transcribed verbatim. Survey data was analysed descriptively. Interview transcripts were coded thematically, using an inductive approach. Survey response rate was 27% (n = 34). The majority (70%) strongly agreed that supporting LMIC partners best described the mission of the partnership but only 13% of respondents strongly agreed that learning about new innovations and models was a primary mission of their partnership. Although more than half of respondents reported having observed innovative practice in the LMIC, only one IHP respondent indicated that this has led to Reverse Innovation. Interviews with a sample of survey respondents revealed themes primarily around how learning is conceptualised, but also a central power imbalance between the UK and LMIC partners. Paternalistic notions of knowledge could be traced to partnership power dynamics and latent attitudes to LMICs. Given the global flow of innovation, if High-income countries (HICs) are to benefit from LMIC practices, it is paramount to keep an open mind about where such learning can come from. Making the potential for learning more explicit and facilitating innovation dissemination upon return will ultimately underpin the success of adoption.

KSC ISS Logistics Support

NASA Technical Reports Server (NTRS)

Tellado, Joseph

2014-01-01

The presentation contains a status of KSC ISS Logistics Operations. It basically presents current top level ISS Logistics tasks being conducted at KSC, current International Partner activities, hardware processing flow focussing on late Stow operations, list of KSC Logistics POC's, and a backup list of Logistics launch site services. This presentation is being given at the annual International Space Station (ISS) Multi-lateral Logistics Maintenance Control Panel meeting to be held in Turin, Italy during the week of May 13-16. The presentatiuon content doesn't contain any potential lessons learned.

CSWP Networking Reception

NASA Astrophysics Data System (ADS)

Unwind after a long day of sessions by networking with women physicists from the APS Committee on the Status of Women in Physics and members of the APS Panel on Public Affairs (POPA). Cocktails and conversation will flow as we learn about the recently approved APS Statement on the Status of Women in Physics; a POPA study underway, designed to evaluate what top universities are doing to address gender disparity in undergraduate physics programs; and initiatives & programs designed to attract, retain, develop, and support the female physicists in our community.

Exploring New Command and Control Concepts and Capabilities (Exploration de Nouveaux Concepts de Commandement et Controle et de Leurs Capacites)

DTIC Science & Technology

2007-04-01

Anthropology Genetics, Physiology Cognition Knowledge Skills IndividualI i i l Team Personality & Values Dynamic Factors & Behaviors Organizational...better support that group, one should therefore have an eye upon the flow of benefits to the right. The four uses relating to learning more about C2 are...from the scenario evolution discussion outlines above and coloured blue in the figure) with the Reference Model equivalent variables and linkages

A Web-Based Learning Support System for Inquiry-Based Learning

NASA Astrophysics Data System (ADS)

Kim, Dong Won; Yao, Jingtao

The emergence of the Internet and Web technology makes it possible to implement the ideals of inquiry-based learning, in which students seek truth, information, or knowledge by questioning. Web-based learning support systems can provide a good framework for inquiry-based learning. This article presents a study on a Web-based learning support system called Online Treasure Hunt. The Web-based learning support system mainly consists of a teaching support subsystem, a learning support subsystem, and a treasure hunt game. The teaching support subsystem allows instructors to design their own inquiry-based learning environments. The learning support subsystem supports students' inquiry activities. The treasure hunt game enables students to investigate new knowledge, develop ideas, and review their findings. Online Treasure Hunt complies with a treasure hunt model. The treasure hunt model formalizes a general treasure hunt game to contain the learning strategies of inquiry-based learning. This Web-based learning support system empowered with the online-learning game and founded on the sound learning strategies furnishes students with the interactive and collaborative student-centered learning environment.

Flow Theory and GIS: Is There a Connection for Learning?

ERIC Educational Resources Information Center

Smith, Janet S.

2005-01-01

This paper examines how Geographic Information Systems (GIS) can potentially capture a student's imagination, facilitate active learning, and create a state of "flow" in geography classrooms. The paper is organised in four sections. First, the author provides a condensed overview to the major tenets of "FlowTheory." Second, a short discussion…

Abrupt contraction flow of magnetorheological fluids

NASA Astrophysics Data System (ADS)

Kuzhir, P.; López-López, M. T.; Bossis, G.

2009-05-01

Contraction and expansion flows of magnetorheological fluids occur in a variety of smart devices. It is important therefore to learn how these flows can be controlled by means of applied magnetic fields. This paper presents a first investigation into the axisymmetric flow of a magnetorheological fluid through an orifice (so-called abrupt contraction flow). The effect of an external magnetic field, longitudinal or transverse to the flow, is examined. In experiments, the pressure-flow rate curves were measured, and the excess pressure drop (associated with entrance and exit losses) was derived from experimental data through the Bagley correction procedure. The effect of the longitudinal magnetic field is manifested through a significant increase in the slope of the pressure-flow rate curves, while no discernible yield stress occurs. This behavior, observed at shear Mason numbers 10

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nalu is a Sierra ToolKit (STK) based application module, and it has provided a set of "lessons learned" for the STK transition effort through its early adoption of STK. It makes use of the open-sourced Trilinos/ Tpetra library. Through the investment of LORD and ASCR projects, the Nalu code module has been extended beyond prototype status. Physics capability includes low Mach, variable density turbulent flow. The ongoing objective for Nalu is to facilitate partnerships with external organizations in order to extend code capability and knowledge; however, it is not intended to support routine CFD analysis. The targeted usage of thismore » module is for non-NW applications that support work-for-others in the multiphysics energy sector.« less

Prefrontal hemodynamic responses and the degree of flow experience among occupational therapy students during their performance of a cognitive task.

PubMed

Hirao, Kazuki

2014-01-01

Although flow experience is positively associated with motivation to learn, the biological basis of flow experience is poorly understood. Accumulation of evidence on the underlying brain mechanisms related to flow is necessary for a deeper understanding of the motivation to learn. The purpose of this study is to investigate the relationship between flow experience and brain function using near-infrared spectroscopy (NIRS) during the performance of a cognitive task. Sixty right-handed occupational therapy (OT) students participated in this study. These students performed a verbal fluency test (VFT) while 2-channel NIRS was used to assess changes in oxygenated hemoglobin concentration (oxygenated hemoglobin [oxy-Hb]) in the prefrontal cortex. Soon after that, the OT students answered the flow questionnaire (FQ) to assess the degree of flow experience during the VFT. Average oxy-Hb in the prefrontal cortex had a significant negative correlation with the satisfaction scores on the FQ. Satisfaction during the flow experience correlated with prefrontal hemodynamic suppression. This finding may assist in understanding motivation to learn and related flow experience.

A New Framework for Adaptive Sampling and Analysis During Long-Term Monitoring and Remedial Action Management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minsker, Barbara

2004-12-01

The Argonne team has gathered available data on monitoring wells and measured hydraulic heads from the Argonne 317/319 site and sent it to UIUC. Xiaodong Li, a research assistant supported by the project, has reviewed the data and has fit initial spatiotemporal statistical models to it. Another research assistant, Yonas Demissie, has completed generation of the artificial data that will be used for model development and testing. In order to generate the artificial data a detailed groundwater flow and contaminant transport model was developed based upon characteristics of the 317/319 site. The model covers a multi-year time horizon that includesmore » both before and after planting of the trees. As described in the proposal, the artificial data is created by adding ''measurement'' error to the ''true'' value from the numerical model. To date, only simple white noise error models have been considered. He is now reviewing the literature and beginning to develop a hierarchical modeling approach for the artificial data. Abhishek Singh, a third research assistant supported by the project, is implementing learning models for learning users preferences in an interactive genetic algorithm for solving the inverse problem. Meghna Babbar, the fourth research assistant supported by the project, has been improving the user interface for the interactive genetic algorithm and preparing a long-term monitoring design problem for testing the approach. Gayathri Gopalakrishnan, the last research assistant who is partially supported by the project, has collected substantial data from the 317/319 phytoremediation site at Argonne and has begun learning approaches for modeling these data.« less

A Deep Learning based Approach to Reduced Order Modeling of Fluids using LSTM Neural Networks

NASA Astrophysics Data System (ADS)

Mohan, Arvind; Gaitonde, Datta

2017-11-01

Reduced Order Modeling (ROM) can be used as surrogates to prohibitively expensive simulations to model flow behavior for long time periods. ROM is predicated on extracting dominant spatio-temporal features of the flow from CFD or experimental datasets. We explore ROM development with a deep learning approach, which comprises of learning functional relationships between different variables in large datasets for predictive modeling. Although deep learning and related artificial intelligence based predictive modeling techniques have shown varied success in other fields, such approaches are in their initial stages of application to fluid dynamics. Here, we explore the application of the Long Short Term Memory (LSTM) neural network to sequential data, specifically to predict the time coefficients of Proper Orthogonal Decomposition (POD) modes of the flow for future timesteps, by training it on data at previous timesteps. The approach is demonstrated by constructing ROMs of several canonical flows. Additionally, we show that statistical estimates of stationarity in the training data can indicate a priori how amenable a given flow-field is to this approach. Finally, the potential and limitations of deep learning based ROM approaches will be elucidated and further developments discussed.

Integral Mindflow: A Process of Mindfulness-in-Flow to Enhance Individual and Organization Learning

ERIC Educational Resources Information Center

Cacioppe, Ron Lewis

2017-01-01

Purpose: This paper aims to examine the differences in mindfulness, meditation and flow and the conditions in which each occurs. It summarizes research that demonstrates positive benefits of these three for employee and organizational learning. While mindfulness focuses awareness on what is occurring in the moment, flow involves total immersion in…

Active Learning in Fluid Mechanics: Youtube Tube Flow and Puzzling Fluids Questions

ERIC Educational Resources Information Center

Hrenya, Christine M.

2011-01-01

Active-learning exercises appropriate for a course in undergraduate fluid mechanics are presented. The first exercise involves an experiment in gravity-driven tube flow, with small groups of students partaking in a contest to predict the experimental flow rates using the mechanical energy balance. The second exercise takes the form of an…

Fifth Graders' Flow Experience in a Digital Game-Based Science Learning Environment

ERIC Educational Resources Information Center

Zheng, Meixun

2012-01-01

This mixed methods study examined the flow experience of 5th graders in the CRYSTAL ISLAND game-based science learning environment. Participants were 73 5th graders from a suburban public school in the southeastern US. Quantitative data about students' science content learning and attitudes towards science was collected via pre-and post surveys.…

A Flow Theory Perspective on Learner Motivation and Behavior in Distance Education

ERIC Educational Resources Information Center

Liao, Li-Fen

2006-01-01

Motivating learners to continue to study and enjoy learning is one of the critical factors in distance education. Flow theory is a useful framework for studying the individual experience of learning through using computers. In this study, I examine students' emotional and cognitive responses to distance learning systems by constructing two models…

Climate Literacy in the Classroom: Supporting Teachers in the Transition to NGSS

NASA Astrophysics Data System (ADS)

Rogers, M. J. B.; Merrill, J.; Harcourt, P.; Petrone, C.; Shea, N.; Mead, H.

2014-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

Clinical learning environments: place, artefacts and rhythm.

PubMed

Sheehan, Dale; Jowsey, Tanisha; Parwaiz, Mariam; Birch, Mark; Seaton, Philippa; Shaw, Susan; Duggan, Alison; Wilkinson, Tim

2017-10-01

Health care practitioners learn through experience in clinical environments in which supervision is a key component, but how that learning occurs outside the supervision relationship remains largely unknown. This study explores the environmental factors that inform and support workplace learning within a clinical environment. An observational study drawing on ethnographic methods was undertaken in a general medicine ward. Observers paid attention to interactions among staff members that involved potential teaching and learning moments that occurred and were visible in the course of routine work. General purpose thematic analysis of field notes was undertaken. A total of 376 observations were undertaken and documented. The findings suggest that place (location of interaction), rhythm (regularity of activities occurring in the ward) and artefacts (objects and equipment) were strong influences on the interactions and exchanges that occurred. Each of these themes had inherent tensions that could promote or inhibit engagement and therefore learning opportunities. Although many learning opportunities were available, not all were taken up or recognised by the participants. We describe and make explicit how the natural environment of a medical ward and flow of work through patient care contribute to the learning architecture, and how this creates or inhibits opportunities for learning. Awareness of learning opportunities was often tacit and not explicit for either supervisor or learner. We identify strategies through which tensions inherent within space, artefacts and the rhythms of work can be resolved and learning opportunities maximised. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Flowing with the changing needs of hydrogeology instruction

NASA Astrophysics Data System (ADS)

Gleeson, T.; Allen, D. M.; Ferguson, G.

2012-01-01

Hydrogeology is now taught in a broad spectrum of departments and institutions to students with diverse backgrounds. Successful instruction in hydrogeology thus requires a variety of pedagogical approaches depending on desired learning outcomes and the diverse background of students. We review the pedagogical literature in hydrogeology to highlight recent advances and analyze a 2005 survey of 68 hydrogeology instructors. The literature and survey results suggest there are ~15 topics that are considered crucial by most hydrogeologists and >100 other topics that are considered crucial by some hydrogeologists. The crucial topics focus on properties of aquifers and fundamentals of groundwater flow, and should likely be part of all undergraduate hydrogeology courses. Other topics can supplement and support these crucial topics, depending on desired learning outcomes. Classroom settings continue to provide a venue for emphasizing fundamental knowledge. However, recent pedagogical advances are biased towards field and laboratory instruction with a goal of bolstering experiential learning. Field methods build on the fundamentals taught in the classroom and emphasize the collection of data, data uncertainty, and the development of vocational skills. Laboratory and computer-based exercises similarly build on theory, and offer an opportunity for data analysis and integration. The literature suggests curricula at all levels should ideally balance field, laboratory, and classroom pedagogy into an iterative and integrative whole. An integrated approach leads to greater student motivation and advancement of theoretical and vocational knowledge.

The Effects of Game Strategy and Preference-Matching on Flow Experience and Programming Performance in Game-Based Learning

ERIC Educational Resources Information Center

Wang, Li-Chun; Chen, Ming-Puu

2010-01-01

Learning to program is difficult for novices, even for those undergraduates who have majored in computer science. The study described in this paper has investigated the effects of game strategy and preference-matching on novice learners' flow experience and performance in learning to program using an experiential gaming activity. One hundred and…

Mechanical Design of a Performance Test Rig for the Turbine Air-Flow Task (TAFT)

NASA Technical Reports Server (NTRS)

Xenofos, George; Forbes, John; Farrow, John; Williams, Robert; Tyler, Tom; Sargent, Scott; Moharos, Jozsef

2003-01-01

To support development of the Boeing-Rocketdyne RS84 rocket engine, a fill-flow, reaction turbine geometry was integrated into the NASA-MSFC turbine air-flow test facility. A mechanical design was generated which minimized the amount of new hardware while incorporating all test and instrUmentation requirements. This paper provides details of the mechanical design for this Turbine Air-Flow Task (TAFT) test rig. The mechanical design process utilized for this task included the following basic stages: Conceptual Design. Preliminary Design. Detailed Design. Baseline of Design (including Configuration Control and Drawing Revision). Fabrication. Assembly. During the design process, many lessons were learned that should benefit future test rig design projects. Of primary importance are well-defined requirements early in the design process, a thorough detailed design package, and effective communication with both the customer and the fabrication contractors. The test rig provided steady and unsteady pressure data necessary to validate the computational fluid dynamics (CFD) code. The rig also helped characterize the turbine blade loading conditions. Test and CFD analysis results are to be presented in another JANNAF paper.

Partial liquid-penetration inside a deep trench by film flowing over it

NASA Astrophysics Data System (ADS)

Nguyen, Phuc-Khanh; Dimakopoulos, Yiannis; Tsamopoulos, John

2014-11-01

Liquid film flow along substrates featuring a deep trench may not wet the trench floor, but create a second gas-liquid interface inside the trench. The liquid penetration inside the trench depends on the location and shape of this inner interface. The penetration increases by decreasing the two three-phase contact lines between the inner interface and the two side-walls or the flow rate and depends on the liquid properties. This partial-penetration is studied by employing the Galerkin / finite element method to solve the two-dimensional steady-state Navier-Stokes equations in a physical domain that is adaptively remeshed. Multiple branches of steady solutions connected via turning points are revealed by pseudo arc-length continuation. Flow hysteresis may occur in a certain range of liquid penetration depth, when the interaction of the two interfaces changes qualitatively. This induces an abrupt jump of penetration distance and deformation amplitude of the outer interface. Work supported by the General Secretariat of Research & Technology of Greece through the program ``Excellence'' (Grant No. 1918) in the framework ``Education and Lifelong Learning'' co-funded by the ESF.

The Virtual Learning Commons: An Emerging Technology for Learning About Emerging Technologies

NASA Astrophysics Data System (ADS)

Pennington, D. D.; Del Rio, N.; Fierro, C.; Gandara, A.; Garcia, A.; Garza, J.; Giandoni, M.; Ochoa, O.; Padilla, E.; Salamah, S.

2013-12-01

The Virtual Learning Commons (VLC), funded by the National Science Foundation Office of Cyberinfrastructure CI-Team Program, is a combination of semantic, visualization, and social media tools that support knowledge sharing and innovation across research disciplines. The explosion of new scientific tools and techniques challenges the ability of researchers to be aware of emerging technologies that might benefit them. Even when aware, it can be difficult to understand enough about emerging technologies to become potential adopters or re-users. Often, emerging technologies have little documentation, especially about the context of their use. The VLC tackles this challenge by providing mechanisms for individuals and groups of researchers to collectively organize Web resources through social bookmarking, and engage each other around those collections in order to a) learn about potentially relevant technologies that are emerging; and b) get feedback from other researchers on innovative ideas and designs. Concurrently, developers of emerging technologies can learn about potential users and the issues they encounter, and they can analyze the impact of their tools on other projects. The VLC aims to support the 'fuzzy front end' of innovation, where novel ideas emerge and there is the greatest potential for impact on research design. It is during the fuzzy front end that conceptual collisions across disciplines and exposure to diverse perspectives provide opportunity for creative thinking that can lead to inventive outcomes. This presentation will discuss the innovation theories that have informed design of the VLC, and hypotheses about the flow of information in virtual settings that can enable the process of innovation. The presentation will include a brief demonstration of key capabilities within the VLC that enable learning about emerging technologies, including the technologies that are presented in this session.

A New Void Fraction Measurement Method for Gas-Liquid Two-Phase Flow in Small Channels

PubMed Central

Li, Huajun; Ji, Haifeng; Huang, Zhiyao; Wang, Baoliang; Li, Haiqing; Wu, Guohua

2016-01-01

Based on a laser diode, a 12 × 6 photodiode array sensor, and machine learning techniques, a new void fraction measurement method for gas-liquid two-phase flow in small channels is proposed. To overcome the influence of flow pattern on the void fraction measurement, the flow pattern of the two-phase flow is firstly identified by Fisher Discriminant Analysis (FDA). Then, according to the identification result, a relevant void fraction measurement model which is developed by Support Vector Machine (SVM) is selected to implement the void fraction measurement. A void fraction measurement system for the two-phase flow is developed and experiments are carried out in four different small channels. Four typical flow patterns (including bubble flow, slug flow, stratified flow and annular flow) are investigated. The experimental results show that the development of the measurement system is successful. The proposed void fraction measurement method is effective and the void fraction measurement accuracy is satisfactory. Compared with the conventional laser measurement systems using standard laser sources, the developed measurement system has the advantages of low cost and simple structure. Compared with the conventional void fraction measurement methods, the proposed method overcomes the influence of flow pattern on the void fraction measurement. This work also provides a good example of using low-cost laser diode as a competent replacement of the expensive standard laser source and hence implementing the parameter measurement of gas-liquid two-phase flow. The research results can be a useful reference for other researchers’ works. PMID:26828488

A New Void Fraction Measurement Method for Gas-Liquid Two-Phase Flow in Small Channels.

PubMed

Li, Huajun; Ji, Haifeng; Huang, Zhiyao; Wang, Baoliang; Li, Haiqing; Wu, Guohua

2016-01-27

Based on a laser diode, a 12 × 6 photodiode array sensor, and machine learning techniques, a new void fraction measurement method for gas-liquid two-phase flow in small channels is proposed. To overcome the influence of flow pattern on the void fraction measurement, the flow pattern of the two-phase flow is firstly identified by Fisher Discriminant Analysis (FDA). Then, according to the identification result, a relevant void fraction measurement model which is developed by Support Vector Machine (SVM) is selected to implement the void fraction measurement. A void fraction measurement system for the two-phase flow is developed and experiments are carried out in four different small channels. Four typical flow patterns (including bubble flow, slug flow, stratified flow and annular flow) are investigated. The experimental results show that the development of the measurement system is successful. The proposed void fraction measurement method is effective and the void fraction measurement accuracy is satisfactory. Compared with the conventional laser measurement systems using standard laser sources, the developed measurement system has the advantages of low cost and simple structure. Compared with the conventional void fraction measurement methods, the proposed method overcomes the influence of flow pattern on the void fraction measurement. This work also provides a good example of using low-cost laser diode as a competent replacement of the expensive standard laser source and hence implementing the parameter measurement of gas-liquid two-phase flow. The research results can be a useful reference for other researchers' works.

Flow Navigation by Smart Microswimmers via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Colabrese, Simona; Biferale, Luca; Celani, Antonio; Gustavsson, Kristian

2017-11-01

We have numerically modeled active particles which are able to acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. We show that those swimmers can learn effective strategies just by experience, using a reinforcement learning algorithm. As an example, we focus on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, exploiting the underlying flow whenever possible. The reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This work paves the way towards the engineering of smart microswimmers that solve difficult navigation problems. ERC AdG NewTURB 339032.

Research on geological hazard identification based on deep learning

NASA Astrophysics Data System (ADS)

Zhu, Cheng; Cheng, Tao

2018-05-01

Geological hazards such as landslides, debris flows and collapses are potential hazards affecting the safety of nearby roads and people. Land and Resources Bureau and other relevant departments to undertake the responsibility of prevention and control of geological disasters, an important body, how to deal with the characteristics of sudden geological disasters in the region, according to pre-established emergency measures quickly and accurately survey, is an important issue to be solved. Based on the analysis of the types and effects of typical geological disasters, this paper studies the relevant methods of identifying typical geological disasters through artificial neural networks, and proposes and designs intelligent geological survey methods and systems based on deep learning to provide relevant departments such as Land and Resources Bureau Related Mountain Geological Survey and Information Support.

An active, collaborative approach to learning skills in flow cytometry.

PubMed

Fuller, Kathryn; Linden, Matthew D; Lee-Pullen, Tracey; Fragall, Clayton; Erber, Wendy N; Röhrig, Kimberley J

2016-06-01

Advances in science education research have the potential to improve the way students learn to perform scientific interpretations and understand science concepts. We developed active, collaborative activities to teach skills in manipulating flow cytometry data using FlowJo software. Undergraduate students were given compensated clinical flow cytometry listmode output (FCS) files and asked to design a gating strategy to diagnose patients with different hematological malignancies on the basis of their immunophenotype. A separate cohort of research trainees was given uncompensated data files on which they performed their own compensation, calculated the antibody staining index, designed a sequential gating strategy, and quantified rare immune cell subsets. Student engagement, confidence, and perceptions of flow cytometry were assessed using a survey. Competency against the learning outcomes was assessed by asking students to undertake tasks that required understanding of flow cytometry dot plot data and gating sequences. The active, collaborative approach allowed students to achieve learning outcomes not previously possible with traditional teaching formats, for example, having students design their own gating strategy, without forgoing essential outcomes such as the interpretation of dot plots. In undergraduate students, favorable perceptions of flow cytometry as a field and as a potential career choice were correlated with student confidence but not the ability to perform flow cytometry data analysis. We demonstrate that this new pedagogical approach to teaching flow cytometry is beneficial for student understanding and interpretation of complex concepts. It should be considered as a useful new method for incorporating complex data analysis tasks such as flow cytometry into curricula. Copyright © 2016 The American Physiological Society.

Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers

DOE PAGES

Garimella, Sarvesh; Rothenberg, Daniel A.; Wolf, Martin J.; ...

2017-09-14

This study investigates the measurement of ice nucleating particle (INP) concentrations and sizing of crystals using continuous flow diffusion chambers (CFDCs). CFDCs have been deployed for decades to measure the formation of INPs under controlled humidity and temperature conditions in laboratory studies and by ambient aerosol populations. These measurements have, in turn, been used to construct parameterizations for use in models by relating the formation of ice crystals to state variables such as temperature and humidity as well as aerosol particle properties such as composition and number. We show here that assumptions of ideal instrument behavior are not supported by measurements mademore » with a commercially available CFDC, the SPectrometer for Ice Nucleation (SPIN), and the instrument on which it is based, the Zurich Ice Nucleation Chamber (ZINC). Non-ideal instrument behavior, which is likely inherent to varying degrees in all CFDCs, is caused by exposure of particles to different humidities and/or temperatures than predicated from instrument theory of operation. This can result in a systematic, and variable, underestimation of reported INP concentrations. Here we find here variable correction factors from 1.5 to 9.5, consistent with previous literature values. We use a machine learning approach to show that non-ideality is most likely due to small-scale flow features where the aerosols are combined with sheath flows. Machine learning is also used to minimize the uncertainty in measured INP concentrations. Finally, we suggest that detailed measurement, on an instrument-by-instrument basis, be performed to characterize this uncertainty.« less

Mutual learning and reverse innovation--where next?

PubMed

Crisp, Nigel

2014-03-28

There is a clear and evident need for mutual learning in global health systems. It is increasingly recognized that innovation needs to be sourced globally and that we need to think in terms of co-development as ideas are developed and spread from richer to poorer countries and vice versa. The Globalization and Health journal's ongoing thematic series, "Reverse innovation in global health systems: learning from low-income countries" illustrates how mutual learning and ideas about so-called "reverse innovation" or "frugal innovation" are being developed and utilized by researchers and practitioners around the world. The knowledge emerging from the series is already catalyzing change and challenging the status quo in global health. The path to truly "global innovation flow", although not fully established, is now well under way. Mobilization of knowledge and resources through continuous communication and awareness raising can help sustain this movement. Global health learning laboratories, where partners can support each other in generating and sharing lessons, have the potential to construct solutions for the world. At the heart of this dialogue is a focus on creating practical local solutions and, simultaneously, drawing out the lessons for the whole world.

Social networks and expertise development for Australian breast radiologists.

PubMed

Taba, Seyedamir Tavakoli; Hossain, Liaquat; Willis, Karen; Lewis, Sarah

2017-02-11

In this study, we explore the nexus between social networks and expertise development of Australian breast radiologists. Background literature has shown that a lack of appropriate social networks and interaction among certain professional group(s) may be an obstacle for knowledge acquisition, information flow and expertise sharing. To date there have not been any systematic studies investigating how social networks and expertise development are interconnected and whether this leads to improved performance for breast radiologists. This study explores the value of social networks in building expertise alongside with other constructs of performance for the Australian radiology workforce using semi-structured in-depth interviews with 17 breast radiologists. The findings from this study emphasise the influences of knowledge transfer and learning through social networks and interactions as well as knowledge acquisition and development through experience and feedback. The results also show that accessibility to learning resources and a variety of timely feedback on performance through the information and communication technologies (ICT) is likely to facilitate improved performance and build social support. We argue that radiologists' and, in particular, breast radiologists' work performance, needs to be explored not only through individual numerical characteristics but also by analysing the social context and peer support networks in which they operate and we identify multidisciplinary care as a core entity of social learning.

Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; Jaafar, Othman; Deo, Ravinesh C.; Kisi, Ozgur; Adamowski, Jan; Quilty, John; El-Shafie, Ahmed

2016-11-01

Monthly stream-flow forecasting can yield important information for hydrological applications including sustainable design of rural and urban water management systems, optimization of water resource allocations, water use, pricing and water quality assessment, and agriculture and irrigation operations. The motivation for exploring and developing expert predictive models is an ongoing endeavor for hydrological applications. In this study, the potential of a relatively new data-driven method, namely the extreme learning machine (ELM) method, was explored for forecasting monthly stream-flow discharge rates in the Tigris River, Iraq. The ELM algorithm is a single-layer feedforward neural network (SLFNs) which randomly selects the input weights, hidden layer biases and analytically determines the output weights of the SLFNs. Based on the partial autocorrelation functions of historical stream-flow data, a set of five input combinations with lagged stream-flow values are employed to establish the best forecasting model. A comparative investigation is conducted to evaluate the performance of the ELM compared to other data-driven models: support vector regression (SVR) and generalized regression neural network (GRNN). The forecasting metrics defined as the correlation coefficient (r), Nash-Sutcliffe efficiency (ENS), Willmott's Index (WI), root-mean-square error (RMSE) and mean absolute error (MAE) computed between the observed and forecasted stream-flow data are employed to assess the ELM model's effectiveness. The results revealed that the ELM model outperformed the SVR and the GRNN models across a number of statistical measures. In quantitative terms, superiority of ELM over SVR and GRNN models was exhibited by ENS = 0.578, 0.378 and 0.144, r = 0.799, 0.761 and 0.468 and WI = 0.853, 0.802 and 0.689, respectively and the ELM model attained lower RMSE value by approximately 21.3% (relative to SVR) and by approximately 44.7% (relative to GRNN). Based on the findings of this study, several recommendations were suggested for further exploration of the ELM model in hydrological forecasting problems.

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

2016-01-01

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Evidence for Vocal Learning and Limited Dispersal as Dual Mechanisms for Dialect Maintenance in a Parrot

PubMed Central

Salinas-Melgoza, Alejandro; Wright, Timothy F.

2012-01-01

Studies of avian vocal dialects commonly find evidence of geographic and acoustic stability in the face of substantial gene flow between dialects. The vocal imitation and reduced dispersal hypotheses are alternatives to explain this mismatch between vocal and genetic variation. We experimentally simulated dispersal in the yellow-naped amazon (Amazona auropalliata) by moving individuals within and across dialect boundaries in Costa Rica. One juvenile translocated across dialect boundaries altered its contact call to imitate the acoustic form of the local call six weeks post-release. In contrast, four adults translocated across dialect boundaries returned to their original capture site within 120 days, while five cross-dialect translocated adults who remained at the release site did not alter their contact calls. Translocated individuals were observed to show some segregation from resident flocks. The observation of vocal imitation by the juvenile bird supports the vocal imitation, whereas the behavior of adults is more consistent with the reduced dispersal hypotheses. Taken together, our results suggest that both post-dispersal learning by juveniles and high philopatry in adults could explain the stability of vocal dialects in the face of immigration and gene flow. PMID:23139809

Factors Influencing Learning Environments in an Integrated Experiential Program

NASA Astrophysics Data System (ADS)

Koci, Peter

The research conducted for this dissertation examined the learning environment of a specific high school program that delivered the explicit curriculum through an integrated experiential manner, which utilized field and outdoor experiences. The program ran over one semester (five months) and it integrated the grade 10 British Columbian curriculum in five subjects. A mixed methods approach was employed to identify the students' perceptions and provide richer descriptions of their experiences related to their unique learning environment. Quantitative instruments were used to assess changes in students' perspectives of their learning environment, as well as other supporting factors including students' mindfulness, and behaviours towards the environment. Qualitative data collection included observations, open-ended questions, and impromptu interviews with the teacher. The qualitative data describe the factors and processes that influenced the learning environment and give a richer, deeper interpretation which complements the quantitative findings. The research results showed positive scores on all the quantitative measures conducted, and the qualitative data provided further insight into descriptions of learning environment constructs that the students perceived as most important. A major finding was that the group cohesion measure was perceived by students as the most important attribute of their preferred learning environment. A flow chart was developed to help the researcher conceptualize how the learning environment, learning process, and outcomes relate to one another in the studied program. This research attempts to explain through the consideration of this case study: how learning environments can influence behavioural change and how an interconnectedness among several factors in the learning process is influenced by the type of learning environment facilitated. Considerably more research is needed in this area to understand fully the complexity learning environments and how they influence learning and behaviour. Keywords: learning environments; integrated experiential programs; environmental education.

Murals as Models: Supporting NGSS three-dimensional teaching in climate change educator professional learning

NASA Astrophysics Data System (ADS)

Rogers, M. J. B.; Petrone, C.; Merrick, B. A.; Drewes, A.

2017-12-01

The current shift in K-12 science education is towards a teaching and learning approach in which students actively do and experience science in a deep, meaningful way while being fully active in their learning. For students and teachers who have not experienced this approach, this shift is difficult without scaffolding. Professional learning for educators must allow teachers to experience this approach and reflect on their experience. We share an example from our 2017 K-12 Climate Change Academy in which educators created and modified murals of Earth's climate system while investigating ecosystem interactions, the carbon cycle, energy flow, and human impacts. The Academy constituted an online component followed by three consecutive in person days. The mural activity served as a framework. The first mural modeling occurred online. A1: Take a photo of an outdoor landscape. Annotate it with elements of Earth's atmosphere, biosphere, geosphere, hydrosphere and indicate energy flow, carbon cycling, and the processes driving these. Activities 2-6 were employed throughout the in person days. A2: Small groups create 2D, mural sized models of Earth's climate system. A3: Groups use carbon themed cards to document naturally occurring and human-influenced aspects of the carbon cycle on their models. A4-5: Teams add climate change impacts and possible mitigation/adaptation responses to murals. A6: Ongoing throughout, team members modify models as needed based on learning. Throughout the Academy, participants were able to experience the activities as students. As Academy facilitators, we modeled how educators could use these models in their classrooms. We used A1 submissions as a formative assessment tool and also as a guide for forming groups for the first in person mural. A2 was used as a small group icebreaker, serving as a bridge between the online and in person sessions both for community building and for providing peer support in knowledge building. A3-A5 allowed for reflection upon and meaning making from other activities. At set stopping points, participants changed roles to discuss the 3D NGSS elements they experienced and think about how each activity could be used in their classroom. We will share best practices from these activities, how they can be adapted for other uses, and Academy participants' reflections.

Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.

PubMed

Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe

2017-10-01

Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.

Self-Contained Compressed-Flow Generation Device for Use in Making Differential Measurements

NASA Technical Reports Server (NTRS)

England, John Dwight (Inventor); Kelley, Anthony R. (Inventor); Cronise, Raymond J. (Inventor)

2014-01-01

A device used in making differential measurements of a flow includes a flow obstruction and a support arm. The flow obstruction's forward portion is a nose cone. The flow obstruction's aft portion is coupled to the nose cone. The support arm's first end is coupled to an exterior wall of a conduit, and its second end is coupled to the forward portion of the flow obstruction. The support arm positions the flow obstruction in the conduit such that a flow region is defined around its nose cone, and such that the support arm's first and second end are separated from one another with respect to a length dimension of the conduit. Measurement ports are provided in the support arm and flow obstruction. Manifolds extending through the flow obstruction and support arm couple the ports to points at the exterior wall of the conduit.

Fooling Around with Water

ERIC Educational Resources Information Center

Rice, Michael

1969-01-01

Describes four different styles of working exhibited by four different children as they worked with water flow. Each of the four children's approaches varied substantially, but each learned in his own way about water flow. The author believes that each child should be encouraged to follow his own style of learning. (BR)

The Effects of Flow on Learning Outcomes in an Online Information Management Course

ERIC Educational Resources Information Center

Rossin, Don; Ro, Young K.; Klein, Barbara D.; Guo, Yi Maggie

2009-01-01

As online courses and programs expand in business schools, it becomes increasingly important to understand the link between students' experiences in these courses and learning outcomes. The study reported here investigates the relationship between students' experiences of flow, a psychological state generally associated with improved task…

Making Games Not Work: Paradoxes Embedded in Game-Based Training and Concepts for Overcoming Them

NASA Technical Reports Server (NTRS)

Jones, Phillip N.; Cuper, Taryn

2010-01-01

An interest in game-based training solutions is natural. All one has to do is watch someone fully engaged in a modern game to see the potential of harnessing that attention for training. However, the reality of game-based training has not fully satisfied these expectations. This paper explains two paradoxes that must be overcome for games to support training. These paradoxes are a result of the realities of the basic human condition clashing with the requirements of learning theory. 80th paradoxes arise from the concept of "engagement" that is central to games. The first comes from a more robust definition of engagement, which is the condition of Flow or Optimal Experience. Flow is the state game developers want to see in users. One aspect of Flow is loss of sense of self as the individual becomes immersed in the experience. The paradox arises because this loss of self directly contradicts the learning requirement of self-reflection. The second paradox comes from theories of play, which state in part that play requires a level of individual freedom. The contradiction arises when game-based play must be harnessed to an organizational training program or regimen. The paper will discuss these paradoxes in the context of an effort to design a game-based training modality to train combat medics and will close with a review of compensating strategies identified by the designers. The paper will provide information important to anyone interested in conceptualizing and designing game-based training.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garimella, Sarvesh; Rothenberg, Daniel A.; Wolf, Martin J.

This study investigates the measurement of ice nucleating particle (INP) concentrations and sizing of crystals using continuous flow diffusion chambers (CFDCs). CFDCs have been deployed for decades to measure the formation of INPs under controlled humidity and temperature conditions in laboratory studies and by ambient aerosol populations. These measurements have, in turn, been used to construct parameterizations for use in models by relating the formation of ice crystals to state variables such as temperature and humidity as well as aerosol particle properties such as composition and number. We show here that assumptions of ideal instrument behavior are not supported by measurements mademore » with a commercially available CFDC, the SPectrometer for Ice Nucleation (SPIN), and the instrument on which it is based, the Zurich Ice Nucleation Chamber (ZINC). Non-ideal instrument behavior, which is likely inherent to varying degrees in all CFDCs, is caused by exposure of particles to different humidities and/or temperatures than predicated from instrument theory of operation. This can result in a systematic, and variable, underestimation of reported INP concentrations. Here we find here variable correction factors from 1.5 to 9.5, consistent with previous literature values. We use a machine learning approach to show that non-ideality is most likely due to small-scale flow features where the aerosols are combined with sheath flows. Machine learning is also used to minimize the uncertainty in measured INP concentrations. Finally, we suggest that detailed measurement, on an instrument-by-instrument basis, be performed to characterize this uncertainty.« less

New Techniques for Deep Learning with Geospatial Data using TensorFlow, Earth Engine, and Google Cloud Platform

NASA Astrophysics Data System (ADS)

Hancher, M.

2017-12-01

Recent years have seen promising results from many research teams applying deep learning techniques to geospatial data processing. In that same timeframe, TensorFlow has emerged as the most popular framework for deep learning in general, and Google has assembled petabytes of Earth observation data from a wide variety of sources and made them available in analysis-ready form in the cloud through Google Earth Engine. Nevertheless, developing and applying deep learning to geospatial data at scale has been somewhat cumbersome to date. We present a new set of tools and techniques that simplify this process. Our approach combines the strengths of several underlying tools: TensorFlow for its expressive deep learning framework; Earth Engine for data management, preprocessing, postprocessing, and visualization; and other tools in Google Cloud Platform to train TensorFlow models at scale, perform additional custom parallel data processing, and drive the entire process from a single familiar Python development environment. These tools can be used to easily apply standard deep neural networks, convolutional neural networks, and other custom model architectures to a variety of geospatial data structures. We discuss our experiences applying these and related tools to a range of machine learning problems, including classic problems like cloud detection, building detection, land cover classification, as well as more novel problems like illegal fishing detection. Our improved tools will make it easier for geospatial data scientists to apply modern deep learning techniques to their own problems, and will also make it easier for machine learning researchers to advance the state of the art of those techniques.

GP Supervisors' Experience in Supporting Self-Regulated Learning: A Balancing Act

ERIC Educational Resources Information Center

Sagasser, Margaretha H.; Kramer, Anneke W. M.; van Weel, Chris; van der Vleuten, Cees P. M.

2015-01-01

Self-regulated learning is essential for professional development and lifelong learning. As self-regulated learning has many inaccuracies, the need to support self-regulated learning has been recommended. Supervisors can provide such support. In a prior study trainees reported on the variation in received supervisor support. This study aims at…

Effects of Mobile Phone-Based App Learning Compared to Computer-Based Web Learning on Nursing Students: Pilot Randomized Controlled Trial

PubMed Central

2015-01-01

Objectives This study aimed to determine the effect of mobile-based discussion versus computer-based discussion on self-directed learning readiness, academic motivation, learner-interface interaction, and flow state. Methods This randomized controlled trial was conducted at one university. Eighty-six nursing students who were able to use a computer, had home Internet access, and used a mobile phone were recruited. Participants were randomly assigned to either the mobile phone app-based discussion group (n = 45) or a computer web-based discussion group (n = 41). The effect was measured at before and after an online discussion via self-reported surveys that addressed academic motivation, self-directed learning readiness, time distortion, learner-learner interaction, learner-interface interaction, and flow state. Results The change in extrinsic motivation on identified regulation in the academic motivation (p = 0.011) as well as independence and ability to use basic study (p = 0.047) and positive orientation to the future in self-directed learning readiness (p = 0.021) from pre-intervention to post-intervention was significantly more positive in the mobile phone app-based group compared to the computer web-based discussion group. Interaction between learner and interface (p = 0.002), having clear goals (p = 0.012), and giving and receiving unambiguous feedback (p = 0.049) in flow state was significantly higher in the mobile phone app-based discussion group than it was in the computer web-based discussion group at post-test. Conclusions The mobile phone might offer more valuable learning opportunities for discussion teaching and learning methods in terms of self-directed learning readiness, academic motivation, learner-interface interaction, and the flow state of the learning process compared to the computer. PMID:25995965

The design of instructional tools affects secondary school students' learning of cardiopulmonary resuscitation (CPR) in reciprocal peer learning: a randomized controlled trial.

PubMed

Iserbyt, Peter; Byra, Mark

2013-11-01

Research investigating design effects of instructional tools for learning Basic Life Support (BLS) is almost non-existent. To demonstrate the design of instructional tools matter. The effect of spatial contiguity, a design principle stating that people learn more deeply when words and corresponding pictures are placed close (i.e., integrated) rather than far from each other on a page was investigated on task cards for learning Cardiopulmonary Resuscitation (CPR) during reciprocal peer learning. A randomized controlled trial. A total of 111 students (mean age: 13 years) constituting six intact classes learned BLS through reciprocal learning with task cards. Task cards combine a picture of the skill with written instructions about how to perform it. In each class, students were randomly assigned to the experimental group or the control. In the control, written instructions were placed under the picture on the task cards. In the experimental group, written instructions were placed close to the corresponding part of the picture on the task cards reflecting application of the spatial contiguity principle. One-way analysis of variance found significantly better performances in the experimental group for ventilation volumes (P=.03, ηp2=.10) and flow rates (P=.02, ηp2=.10). For chest compression depth, compression frequency, compressions with correct hand placement, and duty cycles no significant differences were found. This study shows that the design of instructional tools (i.e., task cards) affects student learning. Research-based design of learning tools can enhance BLS and CPR education. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Revealing Adaptive Management of Environmental Flows

NASA Astrophysics Data System (ADS)

Allan, Catherine; Watts, Robyn J.

2018-03-01

Managers of land, water, and biodiversity are working with increasingly complex social ecological systems with high uncertainty. Adaptive management (learning from doing) is an ideal approach for working with this complexity. The competing social and environmental demands for water have prompted interest in freshwater adaptive management, but its success and uptake appear to be slow. Some of the perceived "failure" of adaptive management may reflect the way success is conceived and measured; learning, rarely used as an indicator of success, is narrowly defined when it is. In this paper, we document the process of adaptive flow management in the Edward-Wakool system in the southern Murray-Darling Basin, Australia. Data are from interviews with environmental water managers, document review, and the authors' structured reflection on their experiences of adaptive management and environmental flows. Substantial learning occurred in relation to the management of environmental flows in the Edward-Wakool system, with evidence found in planning documents, water-use reports, technical reports, stakeholder committee minutes, and refereed papers, while other evidence was anecdotal. Based on this case, we suggest it may be difficult for external observers to perceive the success of large adaptive management projects because evidence of learning is dispersed across multiple documents, and learning is not necessarily considered a measure of success. We suggest that documentation and sharing of new insights, and of the processes of learning, should be resourced to facilitate social learning within the water management sector, and to help demonstrate the successes of adaptive management.

Revealing Adaptive Management of Environmental Flows.

PubMed

Allan, Catherine; Watts, Robyn J

2018-03-01

Managers of land, water, and biodiversity are working with increasingly complex social ecological systems with high uncertainty. Adaptive management (learning from doing) is an ideal approach for working with this complexity. The competing social and environmental demands for water have prompted interest in freshwater adaptive management, but its success and uptake appear to be slow. Some of the perceived "failure" of adaptive management may reflect the way success is conceived and measured; learning, rarely used as an indicator of success, is narrowly defined when it is. In this paper, we document the process of adaptive flow management in the Edward-Wakool system in the southern Murray-Darling Basin, Australia. Data are from interviews with environmental water managers, document review, and the authors' structured reflection on their experiences of adaptive management and environmental flows. Substantial learning occurred in relation to the management of environmental flows in the Edward-Wakool system, with evidence found in planning documents, water-use reports, technical reports, stakeholder committee minutes, and refereed papers, while other evidence was anecdotal. Based on this case, we suggest it may be difficult for external observers to perceive the success of large adaptive management projects because evidence of learning is dispersed across multiple documents, and learning is not necessarily considered a measure of success. We suggest that documentation and sharing of new insights, and of the processes of learning, should be resourced to facilitate social learning within the water management sector, and to help demonstrate the successes of adaptive management.

Machine Learning and Inverse Problem in Geodynamics

NASA Astrophysics Data System (ADS)

Shahnas, M. H.; Yuen, D. A.; Pysklywec, R.

2017-12-01

During the past few decades numerical modeling and traditional HPC have been widely deployed in many diverse fields for problem solutions. However, in recent years the rapid emergence of machine learning (ML), a subfield of the artificial intelligence (AI), in many fields of sciences, engineering, and finance seems to mark a turning point in the replacement of traditional modeling procedures with artificial intelligence-based techniques. The study of the circulation in the interior of Earth relies on the study of high pressure mineral physics, geochemistry, and petrology where the number of the mantle parameters is large and the thermoelastic parameters are highly pressure- and temperature-dependent. More complexity arises from the fact that many of these parameters that are incorporated in the numerical models as input parameters are not yet well established. In such complex systems the application of machine learning algorithms can play a valuable role. Our focus in this study is the application of supervised machine learning (SML) algorithms in predicting mantle properties with the emphasis on SML techniques in solving the inverse problem. As a sample problem we focus on the spin transition in ferropericlase and perovskite that may cause slab and plume stagnation at mid-mantle depths. The degree of the stagnation depends on the degree of negative density anomaly at the spin transition zone. The training and testing samples for the machine learning models are produced by the numerical convection models with known magnitudes of density anomaly (as the class labels of the samples). The volume fractions of the stagnated slabs and plumes which can be considered as measures for the degree of stagnation are assigned as sample features. The machine learning models can determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at mid-mantle depths. Employing support vector machine (SVM) algorithms we show that SML techniques can successfully predict the magnitude of the mantle density anomalies and can also be used in characterizing mantle flow patterns. The technique can be extended to more complex problems in mantle dynamics by employing deep learning algorithms for estimation of mantle properties such as viscosity, elastic parameters, and thermal and chemical anomalies.

Educating the Educators: Developing Those Who Support Learning for Students with Additional Learning Needs

ERIC Educational Resources Information Center

McLachlan, Benita; Davis, Geraldine

2013-01-01

This article reports findings from a research project which developed and introduced the Enhanced Learning Support Assistant Programme (ELSAP) as a source of professional development for learning support assistants who were supporting students with additional learning needs in a college of further education in England. The purpose of this article…

Improving Clinical Workflow in Ambulatory Care: Implemented Recommendations in an Innovation Prototype for the Veteran’s Health Administration

PubMed Central

Patterson, Emily S.; Lowry, Svetlana Z.; Ramaiah, Mala; Gibbons, Michael C.; Brick, David; Calco, Robert; Matton, Greg; Miller, Anne; Makar, Ellen; Ferrer, Jorge A.

2015-01-01

Introduction: Human factors workflow analyses in healthcare settings prior to technology implemented are recommended to improve workflow in ambulatory care settings. In this paper we describe how insights from a workflow analysis conducted by NIST were implemented in a software prototype developed for a Veteran’s Health Administration (VHA) VAi2 innovation project and associated lessons learned. Methods: We organize the original recommendations and associated stages and steps visualized in process maps from NIST and the VA’s lessons learned from implementing the recommendations in the VAi2 prototype according to four stages: 1) before the patient visit, 2) during the visit, 3) discharge, and 4) visit documentation. NIST recommendations to improve workflow in ambulatory care (outpatient) settings and process map representations were based on reflective statements collected during one-hour discussions with three physicians. The development of the VAi2 prototype was conducted initially independently from the NIST recommendations, but at a midpoint in the process development, all of the implementation elements were compared with the NIST recommendations and lessons learned were documented. Findings: Story-based displays and templates with default preliminary order sets were used to support scheduling, time-critical notifications, drafting medication orders, and supporting a diagnosis-based workflow. These templates enabled customization to the level of diagnostic uncertainty. Functionality was designed to support cooperative work across interdisciplinary team members, including shared documentation sessions with tracking of text modifications, medication lists, and patient education features. Displays were customized to the role and included access for consultants and site-defined educator teams. Discussion: Workflow, usability, and patient safety can be enhanced through clinician-centered design of electronic health records. The lessons learned from implementing NIST recommendations to improve workflow in ambulatory care using an EHR provide a first step in moving from a billing-centered perspective on how to maintain accurate, comprehensive, and up-to-date information about a group of patients to a clinician-centered perspective. These recommendations point the way towards a “patient visit management system,” which incorporates broader notions of supporting workload management, supporting flexible flow of patients and tasks, enabling accountable distributed work across members of the clinical team, and supporting dynamic tracking of steps in tasks that have longer time distributions. PMID:26290887

The effects of academic literacy instruction on engagement and conceptual understanding of biology of ninth-grade students

NASA Astrophysics Data System (ADS)

Larson, Susan C.

Academic language, discourse, vocabulary, motivation, and comprehension of complex texts and concepts are keys to learning subject-area content. The need for a disciplinary literacy approach in high school classrooms accelerates as students become increasing disengaged in school and as content complexity increases. In the present quasi-experimental mixed-method study, a ninth-grade biology unit was designed with an emphasis on promoting academic literacy skills, discourse, meaningful constructivist learning, interest development, and positive learning experiences in order to learn science content. Quantitative and qualitative analyses on a variety of measures completed by 222 students in two high schools revealed that those who received academic literacy instruction in science class performed at significantly higher levels of conceptual understanding of biology content, academic language and vocabulary use, reasoned thought, engagement, and quality of learning experience than control-group students receiving traditionally-organized instruction. Academic literacy was embedded into biology instruction to engage students in meaning-making discourses of science to promote learning. Academic literacy activities were organized according the phases of interest development to trigger and sustain interest and goal-oriented engagement throughout the unit. Specific methods included the Generative Vocabulary Matrix (GVM), scenario-based writing, and involvement in a variety of strategically-placed discourse activities to sustain or "boost" engagement for learning. Traditional instruction for the control group included teacher lecture, whole-group discussion, a conceptual organizer, and textbook reading. Theoretical foundations include flow theory, sociocultural learning theory, and interest theory. Qualitative data were obtained from field notes and participants' journals. Quantitative survey data were collected and analyzed using the Experience Sampling Method (ESM) to measure cognitive and emotional states, revealing patterns of engagement, quality of experience, and flow over the course of the instructional unit. Conceptual understanding was measured using the state persuasive writing rubric to analyze science essays in which students supported a claim with scientific evidence. The study contributes an Engagement Model of Academic Literacy for Learning (EngageALL), a Rubric for Academic Persuasive Writing (RAPW), a unique classification system for analyzing academic vocabulary, and suggestions for situated professional development around a research-based planning framework. A discussion addresses a new direction for future research that explores academic identity development.

Preliminary Assessment of the Flow of Used Electronics, In ...

EPA Pesticide Factsheets

Electronic waste (e-waste) is the largest growing municipal waste stream in the United States. The improper disposal of e-waste has environmental, economic, and social impacts, thus there is a need for sustainable stewardship of electronics. EPA/ORD has been working to improve our understanding of the quantity and flow of electronic devices from initial purchase to final disposition. Understanding the pathways of used electronics from the consumer to their final disposition would provide insight to decision makers about their impacts and support efforts to encourage improvements in policy, technology, and beneficial use. This report is the first stage of study of EPA/ORD's efforts to understand the flows of used electronics and e-waste by reviewing the regulatory programs for the selected states and identifying the key lessons learned and best practices that have emerged since their inception. Additionally, a proof-of-concept e-waste flow model has been developed to provide estimates of the quantity of e-waste generated annually at the national level, as well as for selected states. This report documents a preliminary assessment of available data and development of the model that can be used as a starting point to estimate domestic flows of used electronics from generation, to collection and reuse, to final disposition. The electronics waste flow model can estimate the amount of electronic products entering the EOL management phase based on unit sales dat

Soft Sensing of Non-Newtonian Fluid Flow in Open Venturi Channel Using an Array of Ultrasonic Level Sensors—AI Models and Their Validations

PubMed Central

Viumdal, Håkon; Mylvaganam, Saba

2017-01-01

In oil and gas and geothermal installations, open channels followed by sieves for removal of drill cuttings, are used to monitor the quality and quantity of the drilling fluids. Drilling fluid flow rate is difficult to measure due to the varying flow conditions (e.g., wavy, turbulent and irregular) and the presence of drilling cuttings and gas bubbles. Inclusion of a Venturi section in the open channel and an array of ultrasonic level sensors above it at locations in the vicinity of and above the Venturi constriction gives the varying levels of the drilling fluid in the channel. The time series of the levels from this array of ultrasonic level sensors are used to estimate the drilling fluid flow rate, which is compared with Coriolis meter measurements. Fuzzy logic, neural networks and support vector regression algorithms applied to the data from temporal and spatial ultrasonic level measurements of the drilling fluid in the open channel give estimates of its flow rate with sufficient reliability, repeatability and uncertainty, providing a novel soft sensing of an important process variable. Simulations, cross-validations and experimental results show that feedforward neural networks with the Bayesian regularization learning algorithm provide the best flow rate estimates. Finally, the benefits of using this soft sensing technique combined with Venturi constriction in open channels are discussed. PMID:29072595

Landslides and Mudslides

MedlinePlus

... from landslides and debris flows In the United States, landslides and debris flows result in 25 to 50 deaths each year. ... and debris flows. Learn whether landslides or debris flows have ... department, state geological surveys or departments of natural resources, or ...

Fast interactive exploration of 4D MRI flow data

NASA Astrophysics Data System (ADS)

Hennemuth, A.; Friman, O.; Schumann, C.; Bock, J.; Drexl, J.; Huellebrand, M.; Markl, M.; Peitgen, H.-O.

2011-03-01

1- or 2-directional MRI blood flow mapping sequences are an integral part of standard MR protocols for diagnosis and therapy control in heart diseases. Recent progress in rapid MRI has made it possible to acquire volumetric, 3-directional cine images in reasonable scan time. In addition to flow and velocity measurements relative to arbitrarily oriented image planes, the analysis of 3-dimensional trajectories enables the visualization of flow patterns, local features of flow trajectories or possible paths into specific regions. The anatomical and functional information allows for advanced hemodynamic analysis in different application areas like stroke risk assessment, congenital and acquired heart disease, aneurysms or abdominal collaterals and cranial blood flow. The complexity of the 4D MRI flow datasets and the flow related image analysis tasks makes the development of fast comprehensive data exploration software for advanced flow analysis a challenging task. Most existing tools address only individual aspects of the analysis pipeline such as pre-processing, quantification or visualization, or are difficult to use for clinicians. The goal of the presented work is to provide a software solution that supports the whole image analysis pipeline and enables data exploration with fast intuitive interaction and visualization methods. The implemented methods facilitate the segmentation and inspection of different vascular systems. Arbitrary 2- or 3-dimensional regions for quantitative analysis and particle tracing can be defined interactively. Synchronized views of animated 3D path lines, 2D velocity or flow overlays and flow curves offer a detailed insight into local hemodynamics. The application of the analysis pipeline is shown for 6 cases from clinical practice, illustrating the usefulness for different clinical questions. Initial user tests show that the software is intuitive to learn and even inexperienced users achieve good results within reasonable processing times.

2010 Presidential Address: Learning Religion and Religiously Learning amid Global Cultural Flows

ERIC Educational Resources Information Center

Hess, Mary E.

2011-01-01

Emerging social media that build on digital technologies are reshaping how we interact with each other. Religious education and identity formation within these new cultural flows demands recognition of the shifts in authority, authenticity, and agency that are taking place, as well as the challenges posed by "context collapse." Digital…

Structural Relationships among E-Learners' Sense of Presence, Usage, Flow, Satisfaction, and Persistence

ERIC Educational Resources Information Center

Joo, Young Ju; Joung, Sunyoung; Kim, Eun Kyung

2013-01-01

This study aimed to investigate the structural relationships among teaching presence, cognitive presence, usage, learning flow, satisfaction, and learning persistence in corporate e-learners. The research participants were 462 e-learners registered for cyber-lectures through an electronics company in South Korea. The extrinsic variables were sense…

Individual differences in spatial configuration learning predict the occurrence of intrusive memories.

PubMed

Meyer, Thomas; Smeets, Tom; Giesbrecht, Timo; Quaedflieg, Conny W E M; Girardelli, Marta M; Mackay, Georgina R N; Merckelbach, Harald

2013-03-01

The dual-representation model of posttraumatic stress disorder (PTSD; Brewin, Gregory, Lipton, & Burgess, Psychological Review, 117, 210-232 2010) argues that intrusions occur when people fail to construct context-based representations during adverse experiences. The present study tested a specific prediction flowing from this model. In particular, we investigated whether the efficiency of temporal-lobe-based spatial configuration learning would account for individual differences in intrusive experiences and physiological reactivity in the laboratory. Participants (N = 82) completed the contextual cuing paradigm, which assesses spatial configuration learning that is believed to depend on associative encoding in the parahippocampus. They were then shown a trauma film. Afterward, startle responses were quantified during presentation of trauma reminder pictures versus unrelated neutral and emotional pictures. PTSD symptoms were recorded in the week following participation. Better configuration learning performance was associated with fewer perceptual intrusions, r = -.33, p < .01, but was unrelated to physiological responses to trauma reminder images (ps > .46) and had no direct effect on intrusion-related distress and overall PTSD symptoms, rs > -.12, ps > .29. However, configuration learning performance tended to be associated with reduced physiological responses to unrelated negative images, r = -.20, p = .07. Thus, while spatial configuration learning appears to be unrelated to affective responding to trauma reminders, our overall findings support the idea that the context-based memory system helps to reduce intrusions.

Learning in Educational Computer Games for Novices: The Impact of Support Provision Types on Virtual Presence, Cognitive Load, and Learning Outcomes

ERIC Educational Resources Information Center

Schrader, Claudia; Bastiaens, Theo

2012-01-01

Embedding support devices in educational computer games has been asserted to positively affect learning outcomes. However, there is only limited direct empirical evidence on which design variations of support provision influence learning. In order to better understand the impact of support design on novices' learning, the current study…

Geoscience Training for NASA Astronaut Candidates

NASA Technical Reports Server (NTRS)

Young, K. E.; Evans, C. A.; Bleacher, J. E.; Graff, T. G.; Zeigler, R.

2017-01-01

After being selected to the astronaut office, crewmembers go through an initial two year training flow, astronaut candidacy, where they learn the basic skills necessary for spaceflight. While the bulk of astronaut candidate training currently centers on the multiple subjects required for ISS operations (EVA skills, Russian language, ISS systems, etc.), training also includes geoscience training designed to train crewmembers in Earth observations, teach astronauts about other planetary systems, and provide field training designed to investigate field operations and boost team skills. This training goes back to Apollo training and has evolved to support ISS operations and future exploration missions.

Recurrent Neural Networks With Auxiliary Memory Units.

PubMed

Wang, Jianyong; Zhang, Lei; Guo, Quan; Yi, Zhang

2018-05-01

Memory is one of the most important mechanisms in recurrent neural networks (RNNs) learning. It plays a crucial role in practical applications, such as sequence learning. With a good memory mechanism, long term history can be fused with current information, and can thus improve RNNs learning. Developing a suitable memory mechanism is always desirable in the field of RNNs. This paper proposes a novel memory mechanism for RNNs. The main contributions of this paper are: 1) an auxiliary memory unit (AMU) is proposed, which results in a new special RNN model (AMU-RNN), separating the memory and output explicitly and 2) an efficient learning algorithm is developed by employing the technique of error flow truncation. The proposed AMU-RNN model, together with the developed learning algorithm, can learn and maintain stable memory over a long time range. This method overcomes both the learning conflict problem and gradient vanishing problem. Unlike the traditional method, which mixes the memory and output with a single neuron in a recurrent unit, the AMU provides an auxiliary memory neuron to maintain memory in particular. By separating the memory and output in a recurrent unit, the problem of learning conflicts can be eliminated easily. Moreover, by using the technique of error flow truncation, each auxiliary memory neuron ensures constant error flow during the learning process. The experiments demonstrate good performance of the proposed AMU-RNNs and the developed learning algorithm. The method exhibits quite efficient learning performance with stable convergence in the AMU-RNN learning and outperforms the state-of-the-art RNN models in sequence generation and sequence classification tasks.

Capturing Flow in the Business Classroom

ERIC Educational Resources Information Center

Guo, Yi Maggie; Ro, Young K.

2008-01-01

This study focuses on the flow experience in business education. Flow experience, characterized by concentration, control, and enjoyment, can lead to better learning outcomes. Leading preconditions of flow include the balance of challenge and skill, feedback, and goal clarity. Other situational factors affect the flow experience through the…

Monitoring Collaborative Activities in Computer Supported Collaborative Learning

ERIC Educational Resources Information Center

Persico, Donatella; Pozzi, Francesca; Sarti, Luigi

2010-01-01

Monitoring the learning process in computer supported collaborative learning (CSCL) environments is a key element for supporting the efficacy of tutor actions. This article proposes an approach for analysing learning processes in a CSCL environment to support tutors in their monitoring tasks. The approach entails tracking the interactions within…

Implementation of Multiple Intelligences Supported Project-Based Learning in EFL/ESL Classrooms

ERIC Educational Resources Information Center

Bas, Gokhan

2008-01-01

This article deals with the implementation of Multiple Intelligences supported Project-Based learning in EFL/ESL Classrooms. In this study, after Multiple Intelligences supported Project-based learning was presented shortly, the implementation of this learning method into English classrooms. Implementation process of MI supported Project-based…

Navigation Assistance: A Trade-Off between Wayfinding Support and Configural Learning Support

ERIC Educational Resources Information Center

Munzer, Stefan; Zimmer, Hubert D.; Baus, Jorg

2012-01-01

Current GPS-based mobile navigation assistance systems support wayfinding, but they do not support learning about the spatial configuration of an environment. The present study examined effects of visual presentation modes for navigation assistance on wayfinding accuracy, route learning, and configural learning. Participants (high-school students)…

Data Flow System operations: from the NTT to the VLT

NASA Astrophysics Data System (ADS)

Silva, David R.; Leibundgut, Bruno; Quinn, Peter J.; Spyromilio, Jason; Tarenghi, Massimo

1998-07-01

Science operations at the ESO very large telescope is scheduled to begin in April 1999. ESO is currently finalizing the VLT science operations plan. This plan describes the operations tasks and staffing needed to support both visitor and service mode operations. The Data Flow Systems (DFS) currently being developed by ESO will provide the infrastructure necessary for VLT science operations. This paper describes the current VLT science operations plan, first by discussing the tasks involved and then by describing the operations teams that have responsibility for those tasks. Prototypes of many of these operational concepts and tools have been in use at the ESO New Technology Telescope (NTT) since February 1997. This paper briefly summarizes the status of these prototypes and then discusses what operation lessons have been learned from the NTT experience and how they can be applied to the VLT.

A predictive universal fractional-order differential model of wall-turbulence

NASA Astrophysics Data System (ADS)

Song, Fangying; Karniadakis, George

2017-11-01

Fractional calculus has been around for centuries but its use in computational since and engineering has emerged only recently. Here we develop a relatively simple one-dimensional model for fully-developed wall-turbulence that involves a fractional operator with variable fractional order. We use available DNS data bases to ``learn'' the function that describes the fractional order, which has a high value at the wall and decays monotonically to an asymptotic value at the centerline. We show that this function is universal upon re-scaling and hence it can be used to predict the mean velocity profile at all Reynolds numbers. We demonstrate the accuracy of our universal fractional model for channel flow at high Reynolds number as well as for pipe flow and we obtain good agreement with the Princeton super-pipe data up to Reynolds numbers 35,000,000. This work was supported by an ARO MURI Number: W911NF-15-1-0562.

Compatibility of information and mode of control: The case for natural control systems

NASA Technical Reports Server (NTRS)

Owen, Dean H.

1993-01-01

The operation of control systems has been determined largely by mechanical constraints. Compatibility with the characteristics of the operator is a secondary consideration, with the result that control may never be optimal, control workload may interfere with performance of secondary tasks, and learning may be more difficult and protracted than necessary. With the introduction of a computer in the control loop, the mode of operation can be adapted to the operator, rather than vice versa. The concept of natural control is introduced to describe a system that supports control of the information used by the operator in achieving an intended goal. As an example, control of speed during simulated approach to a pad by helicopter pilots is used to contrast path-speed control with direct control of global optical flow-pattern information. Differences are evidenced in the performance domains of control activity, speed, and global optical flow velocity.

A Framework to Support Mobile Learning in Multilingual Environments

ERIC Educational Resources Information Center

Jantjies, Mmaki E.; Joy, Mike

2014-01-01

This paper presents a multilingual mobile learning framework that can be used to support the pedagogical development of mobile learning systems which can support learning in under-resourced multilingual schools. The framework has been developed following two empirical mobile learning studies. Both studies were conducted in multilingual South…

Simulating Serious Games: A Discrete-Time Computational Model Based on Cognitive Flow Theory

ERIC Educational Resources Information Center

Westera, Wim

2018-01-01

This paper presents a computational model for simulating how people learn from serious games. While avoiding the combinatorial explosion of a games micro-states, the model offers a meso-level pathfinding approach, which is guided by cognitive flow theory and various concepts from learning sciences. It extends a basic, existing model by exposing…

A Mixed Methods Assessment of Students' Flow Experiences during a Mobile Augmented Reality Science Game

ERIC Educational Resources Information Center

Bressler, D. M.; Bodzin, A. M.

2013-01-01

Current studies have reported that secondary students are highly engaged while playing mobile augmented reality (AR) learning games. Some researchers have posited that players' engagement may indicate a flow experience, but no research results have confirmed this hypothesis with vision-based AR learning games. This study investigated factors…

Path Analysis on the Factors Influencing Learning Outcome for Hospitality Interns--From the Flow Theory Perspective

ERIC Educational Resources Information Center

Wang, Shu-Tai; Chen, Cheng-Chung

2015-01-01

Learning outcome is an important indicator for educators in evaluating curriculum design. The focus of this study has been to examine the factors within internship programs, recognizing the complex nature of knowledge application in a practical industry environment. Flow theory was adopted to explain the psychological state of hospitality students…

Exploring Factors of Media Characteristic Influencing Flow in Learning through Virtual Worlds

ERIC Educational Resources Information Center

Choi, Beomkyu; Baek, Youngkyun

2011-01-01

This study aims to find out factors of media characteristic which are considered to influence flow in learning through virtual worlds. One hundred ninety eight elementary students who are eleven to twelve years old participated in this study. After the exploratory factor analysis, to extract media characteristics of virtual worlds, seventy-eight…

Computational Fluid Dynamics (CFD) Analysis Of Optical Payload For Lasercomm Science (OPALS) sealed enclosure module

NASA Technical Reports Server (NTRS)

Anderson, Kevin R.; Zayas, Daniel; Turner, Daniel

2012-01-01

Computational Fluid Dynamics (CFD) using the commercial CFD package CFDesign has been performed at NASA Jet Propulsion Laboratory (JPL) California Institute of Technology (Caltech) in support of the Phaeton Early Career Hire Program's Optical Payload for Lasercomm Science (OPALS) mission. The OPALS project is one which involves an International Space Station payload that will be using forced convection cooling in a hermetically sealed enclosure at 1 atm of air to cool "off-the-shelf" vendor electronics. The CFD analysis was used to characterize the thermal and fluid flow environment within a complicated labyrinth of electronics boards, fans, instrumentation, harnessing, ductwork and heat exchanger fins. The paradigm of iteratively using CAD/CAE tools and CFD was followed in order to determine the optimum flow geometry and heat sink configuration to yield operational convective film coefficients and temperature survivability limits for the electronics payload. Results from this current CFD analysis and correlation of the CFD model against thermal test data will be presented. Lessons learned and coupled thermal / flow modeling strategies will be shared in this paper.

Teaching Economics: A Cooperative Learning Model.

ERIC Educational Resources Information Center

Caropreso, Edward J.; Haggerty, Mark

2000-01-01

Describes an alternative approach to introductory economics based on a cooperative learning model, "Learning Together." Discussion of issues in economics education and cooperative learning in higher education leads to explanation of how to adapt the Learning Together Model to lesson planning in economics. A flow chart illustrates the process for a…

Kīlauea June 27th Lava Flow Hazard Mapping and Disaster Response with UAS

NASA Astrophysics Data System (ADS)

Turner, N.; Perroy, R. L.; Hon, K. A.; Rasgado, V.

2015-12-01

In June of 2014, pāhoehoe lava flows from the Púu ´Ō´ō eruption began threatening communities and infrastructure on eastern Hawaii Island. During the subsequent declared state of emergency by Hawaii Civil Defense and temporary flight restriction by the Federal Aviation Administration (FAA), we used a small fixed-wing Unmanned Aircraft System (UAS) to collect high spatial and temporal resolution imagery over the active flow in support of natural hazard assessment by emergency managers. Integration of our UAS into busy airspace, populated by emergency aircraft and tour helicopters, required close operational coordination with the FAA and local operators. We logged >80 hours of UAS flight operations between October 2014 and March 2015, generating a dense time-series of 4-5 cm resolution imagery and derived topographic datasets using structure from motion. These data were used to monitor flow activity, document pre- and post- lava flow damage, identify hazardous areas for first responders, and model lava flow paths in complex topography ahead of the active flow front. Turnaround times for delivered spatial data products improved from 24-48 hours at the beginning of the study to ~2-4 hours by the end. Data from this project are being incorporated into cloud computing applications to shorten delivery time and extract useful analytics regarding lava flow hazards in near real-time. The lessons learned from this event have advanced UAS integration in disaster operations in U.S. airspace and show the high potential UAS hold for natural hazards assessment and real-time emergency management.

Emotional engagement with participatory simulations as a tool for learning and decision-support for coupled human-natural systems: Flood hazards and urban development

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; Corey, B.; Camp, J. V.; John, N. J.; Sengupta, P.

2015-12-01

The complex interactions between land use and natural hazards pose serious challenges in education, research, and public policy. Where complex nonlinear interactions produce unintuitive results, interactive computer simulations can be useful tools for education and decision support. Emotions play important roles in cognition and learning, especially where risks are concerned. Interactive simulations have the potential to harness emotional engagement to enhance learning and understanding of risks in coupled human-natural systems. We developed a participatory agent-based simulation of cities at risk of river flooding. Participants play the role of managers of neighboring cities along a flood-prone river and make choices about building flood walls to protect their inhabitants. Simulated agents participate in dynamic real estate markets in which demand for property, and thus values and decisions to build, respond to experience with flooding over time. By reducing high-frequency low-magnitude flooding, flood walls may stimulate development, thus increasing tax revenues but also increasing vulnerability to uncommon floods that overtop the walls. Flood waves are launched stochastically and propagate downstream. Flood walls that restrict overbank flow at one city can increase the amplitude of a flood wave at neighboring cities, both up and downstream. We conducted a pilot experiment with a group of three pre-service teachers. The subjects successfully learned key concepts of risk tradeoffs and unintended consequences that can accompany flood-control measures. We also observed strong emotional responses, including hope, fear, and sense of loss. This emotional engagement with a model of coupled human-natural systems was very different from previous experiments on participatory simulations of purely natural systems for physics pedagogy. We conducted a second session in which the participants were expert engineers. We will present the results of these experiments and the prospects for using such models for middle-school, high-school, and post-secondary environmental science pedagogy, for improving public understanding of flood risks, and as decision support tools for planners.

The Mediating Effect of Intrinsic Motivation to Learn on the Relationship between Student´s Autonomy Support and Vitality and Deep Learning.

PubMed

Núñez, Juan L; León, Jaime

2016-07-18

Self-determination theory has shown that autonomy support in the classroom is associated with an increase of students' intrinsic motivation. Moreover, intrinsic motivation is related with positive outcomes. This study examines the relationships between autonomy support, intrinsic motivation to learn and two motivational consequences, deep learning and vitality. Specifically, the hypotheses were that autonomy support predicts the two types of consequences, and that autonomy support directly and indirectly predicts the vitality and the deep learning through intrinsic motivation to learn. Participants were 276 undergraduate students. The mean age was 21.80 years (SD = 2.94). Structural equation modeling was used to test the relationships between variables and delta method was used to analyze the mediating effect of intrinsic motivation to learn. Results indicated that student perception of autonomy support had a positive effect on deep learning and vitality (p < .001). In addition, these associations were mediated by intrinsic motivation to learn. These findings suggest that teachers are key elements in generating of autonomy support environment to promote intrinsic motivation, deep learning, and vitality in classroom. Educational implications are discussed.

Facilitation of learning: part 2.

PubMed

Warburton, Tyler; Houghton, Trish; Barry, Debbie

2016-04-27

The previous article in this series of 11, Facilitation of learning: part 1, reviewed learning theories and how they relate to clinical practice. Developing an understanding of these theories is essential for mentors and practice teachers to enable them to deliver evidence-based learning support. This is important given that effective learning support is dependent on an educator who possesses knowledge of their specialist area as well as the relevent tools and methods to support learning. The second domain of the Nursing and Midwifery Council's Standards to Support Learning and Assessment in Practice relates to the facilitation of learning. To fulfil this domain, mentors and practice teachers are required to demonstrate their ability to recognise the needs of learners and provide appropriate support to meet those needs. This article expands on some of the discussions from part 1 of this article and considers these from a practical perspective, in addition to introducing some of the tools that can be used to support learning.

Student Engagement as a General Factor of Classroom Experience: Associations with Student Practices and Educational Outcomes in a University Gateway Course

PubMed Central

Shernof, David J.; Ruzek, Erik A.; Sannella, Alexander J.; Schorr, Roberta Y.; Sanchez-Wall, Lina; Bressler, Denise M.

2017-01-01

The purpose of this study was to evaluate a model for considering general and specific elements of student experience in a gateway course in undergraduate Financial Accounting in a large university on the East Coast, USA. Specifically, the study evaluated a bifactor analytic strategy including a general factor of student classroom experience, conceptualized as student engagement as rooted in flow theory, as well as factors representing specific dimensions of experience. The study further evaluated the association between these general and specific factors and both student classroom practices and educational outcomes. The sample of students (N = 407) in two cohorts of the undergraduate financial accounting course participated in the Experience Sampling Method (ESM) measuring students' classroom practices, perceptions, engagement, and perceived learning throughout the one-semester course. Course grade information was also collected. Results showed that a two-level bifactor model fit the data better than two traditional (i.e., non-bifactor) models and also avoided significant multicollinearity of the traditional models. In addition to student engagement (general factor), specific dimensions of classroom experience in the bifactor model at the within-student level included intrinsic motivation, academic intensity, salience, and classroom self-esteem. At the between-student level, specific aspects included work orientation, learning orientation, classroom self-esteem, and disengagement. Multilevel Structural Equation Modeling (MSEM) demonstrated that sitting in the front of the classroom (compared to the sitting in the back), taking notes, active listening, and working on problems during class had a positive effect on within-student variation in student engagement and attention. Engagement, in turn, predicted perceived learning. With respect to between-student effects, the tendency to sit in front seats had a significant effect on student engagement, which in turn had a significant effect on perceived learning and course grades. A significant indirect relationship of seating and active learning strategies on learning and course grade as mediated by student engagement was found. Support for the general aspect of student classroom experience was interpreted with flow theory and suggested the need for additional research. Findings also suggested that active learning strategies are associated with positive learning outcomes even in educational environments where possibilities for action are relatively constrained. PMID:28663733

Student Engagement as a General Factor of Classroom Experience: Associations with Student Practices and Educational Outcomes in a University Gateway Course.

PubMed

Shernof, David J; Ruzek, Erik A; Sannella, Alexander J; Schorr, Roberta Y; Sanchez-Wall, Lina; Bressler, Denise M

2017-01-01

The purpose of this study was to evaluate a model for considering general and specific elements of student experience in a gateway course in undergraduate Financial Accounting in a large university on the East Coast, USA. Specifically, the study evaluated a bifactor analytic strategy including a general factor of student classroom experience, conceptualized as student engagement as rooted in flow theory, as well as factors representing specific dimensions of experience. The study further evaluated the association between these general and specific factors and both student classroom practices and educational outcomes. The sample of students ( N = 407) in two cohorts of the undergraduate financial accounting course participated in the Experience Sampling Method (ESM) measuring students' classroom practices, perceptions, engagement, and perceived learning throughout the one-semester course. Course grade information was also collected. Results showed that a two-level bifactor model fit the data better than two traditional (i.e., non-bifactor) models and also avoided significant multicollinearity of the traditional models. In addition to student engagement (general factor), specific dimensions of classroom experience in the bifactor model at the within-student level included intrinsic motivation, academic intensity, salience, and classroom self-esteem. At the between-student level, specific aspects included work orientation, learning orientation, classroom self-esteem, and disengagement. Multilevel Structural Equation Modeling (MSEM) demonstrated that sitting in the front of the classroom (compared to the sitting in the back), taking notes, active listening, and working on problems during class had a positive effect on within-student variation in student engagement and attention. Engagement, in turn, predicted perceived learning. With respect to between-student effects, the tendency to sit in front seats had a significant effect on student engagement, which in turn had a significant effect on perceived learning and course grades. A significant indirect relationship of seating and active learning strategies on learning and course grade as mediated by student engagement was found. Support for the general aspect of student classroom experience was interpreted with flow theory and suggested the need for additional research. Findings also suggested that active learning strategies are associated with positive learning outcomes even in educational environments where possibilities for action are relatively constrained.

Theories of Learning for the Workplace: Building Blocks for Training and Professional Development Programs. Routledge Psychology in Education

ERIC Educational Resources Information Center

Dochy, Filip; Gijbels, David; Segers, Mien; Van den Bossche, Piet

2011-01-01

Workplace and professional learning, lifelong learning, adult learning, learning in different contexts have become of more and more interest and now dominate all aspects of 21st century life. Learning is no longer about "storing and recall" but "development and flow". "Theories of Learning in the Workplace" offers fascinating overviews into some…

A work-based learning approach for clinical support workers on mental health inpatient wards.

PubMed

Kemp, Philip; Gilding, Moorene; Seewooruttun, Khooseal; Walsh, Hannah

2016-09-14

Background With a rise in the number of unqualified staff providing health and social care, and reports raising concerns about the quality of care provided, there is a need to address the learning needs of clinical support workers. This article describes a qualitative evaluation of a service improvement project that involved a work-based learning approach for clinical support workers on mental health inpatient wards. Aim To investigate and identify insights in relation to the content and process of learning using a work-based learning approach for clinical support workers. Method This was a qualitative evaluation of a service improvement project involving 25 clinical support workers at the seven mental health inpatient units in South London and Maudsley NHS Foundation Trust. Three clinical skills tutors were appointed to develop, implement and evaluate the work-based learning approach. Four sources of data were used to evaluate this approach, including reflective journals, qualitative responses to questionnaires, three focus groups involving the clinical support workers and a group interview involving the clinical skills tutors. Data were analysed using thematic analysis. Findings The work-based learning approach was highly valued by the clinical support workers and enhanced learning in practice. Face-to-face learning in practice helped the clinical support workers to develop practice skills and reflective learning skills. Insights relating to the role of clinical support workers were also identified, including the benefits of face-to-face supervision in practice, particularly in relation to the interpersonal aspects of care. Conclusion A work-based learning approach has the potential to enhance care delivery by meeting the learning needs of clinical support workers and enabling them to apply learning to practice. Care providers should consider how the work-based learning approach can be used on a systematic, organisation-wide basis in the context of budgetary restrictions.

Sustained Professional Development on Cooperative Learning: Impact on Six Teachers' Practices and Students' Learning.

PubMed

Goodyear, Victoria A

2017-03-01

It has been argued, extensively and internationally, that sustained school-based continuous professional development (CPD) has the potential to overcome some of the shortcomings of traditional one-off CPD programs. Yet, the evidence base on more effective or less effective forms of CPD is contradictory. The mechanisms by which sustained support should be offered are unclear, and the impacts on teachers' and students' learning are complex and difficult to track. The purpose of this study was to examine the impact of a sustained school-based, tailored, and supported CPD program on teachers' practices and students' learning. Data are reported from 6 case studies of individual teachers engaged in a yearlong CPD program focused on cooperative learning. The CPD program involved participatory action research and frequent interaction/support from a boundary spanner (researcher/facilitator). Data were gathered from 29 video-recorded lessons, 108 interviews, and 35 field journal entries. (a) Individualized (external) support, (b) departmental (internal) support, and (c) sustained support impacted teachers' practices of cooperative learning. The teachers adapted their practices of cooperative learning in response to their students' learning needs. Teachers began to develop a level of pedagogical fluency, and in doing so, teachers advanced students' learning. Because this study demonstrates impact, it contributes to international literature on effective CPD. The key contribution is the detailed evidence about how and why CPD supported 6 individual teachers to learn-differently-and the complexity of the learning support required to engage in ongoing curriculum development to positively impact student learning.

Influences of Formal Learning, Personal Learning Orientation, and Supportive Learning Environment on Informal Learning

ERIC Educational Resources Information Center

Choi, Woojae; Jacobs, Ronald L.

2011-01-01

While workplace learning includes formal and informal learning, the relationship between the two has been overlooked, because they have been viewed as separate entities. This study investigated the effects of formal learning, personal learning orientation, and supportive learning environment on informal learning among 203 middle managers in Korean…

Seven Affordances of Computer-Supported Collaborative Learning: How to Support Collaborative Learning? How Can Technologies Help?

ERIC Educational Resources Information Center

Jeong, Heisawn; Hmelo-Silver, Cindy E.

2016-01-01

This article proposes 7 core affordances of technology for collaborative learning based on theories of collaborative learning and CSCL (Computer-Supported Collaborative Learning) practices. Technology affords learner opportunities to (1) engage in a joint task, (2) communicate, (3) share resources, (4) engage in productive collaborative learning…

A Digital Coach That Provides Affective and Social Learning Support to Low-Literate Learners

ERIC Educational Resources Information Center

Schouten, Dylan G. M.; Venneker, Fleur; Bosse, Tibor; Neerincx, Mark A.; Cremers, Anita H. M.

2018-01-01

In this study, we investigate if a digital coach for low-literate learners that provides cognitive learning support based on scaffolding can be improved by adding affective learning support based on motivational interviewing, and social learning support based on small talk. Several knowledge gaps are identified: motivational interviewing and small…

Semi-supervised Machine Learning for Analysis of Hydrogeochemical Data and Models

NASA Astrophysics Data System (ADS)

Vesselinov, Velimir; O'Malley, Daniel; Alexandrov, Boian; Moore, Bryan

2017-04-01

Data- and model-based analyses such as uncertainty quantification, sensitivity analysis, and decision support using complex physics models with numerous model parameters and typically require a huge number of model evaluations (on order of 10^6). Furthermore, model simulations of complex physics may require substantial computational time. For example, accounting for simultaneously occurring physical processes such as fluid flow and biogeochemical reactions in heterogeneous porous medium may require several hours of wall-clock computational time. To address these issues, we have developed a novel methodology for semi-supervised machine learning based on Non-negative Matrix Factorization (NMF) coupled with customized k-means clustering. The algorithm allows for automated, robust Blind Source Separation (BSS) of groundwater types (contamination sources) based on model-free analyses of observed hydrogeochemical data. We have also developed reduced order modeling tools, which coupling support vector regression (SVR), genetic algorithms (GA) and artificial and convolutional neural network (ANN/CNN). SVR is applied to predict the model behavior within prior uncertainty ranges associated with the model parameters. ANN and CNN procedures are applied to upscale heterogeneity of the porous medium. In the upscaling process, fine-scale high-resolution models of heterogeneity are applied to inform coarse-resolution models which have improved computational efficiency while capturing the impact of fine-scale effects at the course scale of interest. These techniques are tested independently on a series of synthetic problems. We also present a decision analysis related to contaminant remediation where the developed reduced order models are applied to reproduce groundwater flow and contaminant transport in a synthetic heterogeneous aquifer. The tools are coded in Julia and are a part of the MADS high-performance computational framework (https://github.com/madsjulia/Mads.jl).

Three Philosophical Pillars That Support Collaborative Learning.

ERIC Educational Resources Information Center

Maltese, Ralph

1991-01-01

Discusses three philosophical pillars that support collaborative learning: "spaces of appearance," active engagement, and ownership. Describes classroom experiences with collaborative learning supported by these pillars. (PRA)

Learning an Eddy Viscosity Model Using Shrinkage and Bayesian Calibration: A Jet-in-Crossflow Case Study

DOE PAGES

Ray, Jaideep; Lefantzi, Sophia; Arunajatesan, Srinivasan; ...

2017-09-07

In this paper, we demonstrate a statistical procedure for learning a high-order eddy viscosity model (EVM) from experimental data and using it to improve the predictive skill of a Reynolds-averaged Navier–Stokes (RANS) simulator. The method is tested in a three-dimensional (3D), transonic jet-in-crossflow (JIC) configuration. The process starts with a cubic eddy viscosity model (CEVM) developed for incompressible flows. It is fitted to limited experimental JIC data using shrinkage regression. The shrinkage process removes all the terms from the model, except an intercept, a linear term, and a quadratic one involving the square of the vorticity. The shrunk eddy viscositymore » model is implemented in an RANS simulator and calibrated, using vorticity measurements, to infer three parameters. The calibration is Bayesian and is solved using a Markov chain Monte Carlo (MCMC) method. A 3D probability density distribution for the inferred parameters is constructed, thus quantifying the uncertainty in the estimate. The phenomenal cost of using a 3D flow simulator inside an MCMC loop is mitigated by using surrogate models (“curve-fits”). A support vector machine classifier (SVMC) is used to impose our prior belief regarding parameter values, specifically to exclude nonphysical parameter combinations. The calibrated model is compared, in terms of its predictive skill, to simulations using uncalibrated linear and CEVMs. Finally, we find that the calibrated model, with one quadratic term, is more accurate than the uncalibrated simulator. The model is also checked at a flow condition at which the model was not calibrated.« less

Learning an Eddy Viscosity Model Using Shrinkage and Bayesian Calibration: A Jet-in-Crossflow Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ray, Jaideep; Lefantzi, Sophia; Arunajatesan, Srinivasan

In this paper, we demonstrate a statistical procedure for learning a high-order eddy viscosity model (EVM) from experimental data and using it to improve the predictive skill of a Reynolds-averaged Navier–Stokes (RANS) simulator. The method is tested in a three-dimensional (3D), transonic jet-in-crossflow (JIC) configuration. The process starts with a cubic eddy viscosity model (CEVM) developed for incompressible flows. It is fitted to limited experimental JIC data using shrinkage regression. The shrinkage process removes all the terms from the model, except an intercept, a linear term, and a quadratic one involving the square of the vorticity. The shrunk eddy viscositymore » model is implemented in an RANS simulator and calibrated, using vorticity measurements, to infer three parameters. The calibration is Bayesian and is solved using a Markov chain Monte Carlo (MCMC) method. A 3D probability density distribution for the inferred parameters is constructed, thus quantifying the uncertainty in the estimate. The phenomenal cost of using a 3D flow simulator inside an MCMC loop is mitigated by using surrogate models (“curve-fits”). A support vector machine classifier (SVMC) is used to impose our prior belief regarding parameter values, specifically to exclude nonphysical parameter combinations. The calibrated model is compared, in terms of its predictive skill, to simulations using uncalibrated linear and CEVMs. Finally, we find that the calibrated model, with one quadratic term, is more accurate than the uncalibrated simulator. The model is also checked at a flow condition at which the model was not calibrated.« less

Using Educational Games and Simulation Software in a Computer Science Course: Learning Achievements and Student Flow Experiences

ERIC Educational Resources Information Center

Liu, Tsung-Yu

2016-01-01

This study investigates how educational games impact on students' academic performance and multimedia flow experiences in a computer science course. A curriculum consists of five basic learning units, that is, the stack, queue, sort, tree traversal, and binary search tree, was conducted for 110 university students during one semester. Two groups…

Effects of Learning Support in Simulation-Based Physics Learning

ERIC Educational Resources Information Center

Chang, Kuo-En; Chen, Yu-Lung; Lin, He-Yan; Sung, Yao-Ting

2008-01-01

This paper describes the effects of learning support on simulation-based learning in three learning models: experiment prompting, a hypothesis menu, and step guidance. A simulation learning system was implemented based on these three models, and the differences between simulation-based learning and traditional laboratory learning were explored in…

Risky Business or Sharing the Load?--Social Flow in Collaborative Mobile Learning

ERIC Educational Resources Information Center

Ryu, Hokyoung; Parsons, David

2012-01-01

Mobile learning has been built upon the premise that we can transform traditional classroom or computer-based learning activities into a more ubiquitous and connected form of learning. Tentative outcomes from this assertion have been witnessed in many collaborative learning activities, but few analytic observations on what triggers this…

Affect and Learning: An Exploratory Look into the Role of Affect in Learning with AutoTutor

ERIC Educational Resources Information Center

Craig, Scotty D.; Graesser, Arthur C.; Sullins, Jeremiah; Gholson, Barry

2004-01-01

The role that affective states play in learning was investigated from the perspective of a constructivist learning framework. We observed six different affect states (frustration, boredom, flow, confusion, eureka and neutral) that potentially occur during the process of learning introductory computer literacy with AutoTutor, an intelligent…

SHIWA Services for Workflow Creation and Sharing in Hydrometeorolog

NASA Astrophysics Data System (ADS)

Terstyanszky, Gabor; Kiss, Tamas; Kacsuk, Peter; Sipos, Gergely

2014-05-01

Researchers want to run scientific experiments on Distributed Computing Infrastructures (DCI) to access large pools of resources and services. To run these experiments requires specific expertise that they may not have. Workflows can hide resources and services as a virtualisation layer providing a user interface that researchers can use. There are many scientific workflow systems but they are not interoperable. To learn a workflow system and create workflows may require significant efforts. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows developed in other workflow systems. To overcome it requires creating workflow interoperability solutions to allow workflow sharing. The FP7 'Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs' (SHIWA) project developed the Coarse-Grained Interoperability concept (CGI). It enables recycling and sharing workflows of different workflow systems and executing them on different DCIs. SHIWA developed the SHIWA Simulation Platform (SSP) to implement the CGI concept integrating three major components: the SHIWA Science Gateway, the workflow engines supported by the CGI concept and DCI resources where workflows are executed. The science gateway contains a portal, a submission service, a workflow repository and a proxy server to support the whole workflow life-cycle. The SHIWA Portal allows workflow creation, configuration, execution and monitoring through a Graphical User Interface using the WS-PGRADE workflow system as the host workflow system. The SHIWA Repository stores the formal description of workflows and workflow engines plus executables and data needed to execute them. It offers a wide-range of browse and search operations. To support non-native workflow execution the SHIWA Submission Service imports the workflow and workflow engine from the SHIWA Repository. This service either invokes locally or remotely pre-deployed workflow engines or submits workflow engines with the workflow to local or remote resources to execute workflows. The SHIWA Proxy Server manages certificates needed to execute the workflows on different DCIs. Currently SSP supports sharing of ASKALON, Galaxy, GWES, Kepler, LONI Pipeline, MOTEUR, Pegasus, P-GRADE, ProActive, Triana, Taverna and WS-PGRADE workflows. Further workflow systems can be added to the simulation platform as required by research communities. The FP7 'Building a European Research Community through Interoperable Workflows and Data' (ER-flow) project disseminates the achievements of the SHIWA project to build workflow user communities across Europe. ER-flow provides application supports to research communities within (Astrophysics, Computational Chemistry, Heliophysics and Life Sciences) and beyond (Hydrometeorology and Seismology) to develop, share and run workflows through the simulation platform. The simulation platform supports four usage scenarios: creating and publishing workflows in the repository, searching and selecting workflows in the repository, executing non-native workflows and creating and running meta-workflows. The presentation will outline the CGI concept, the SHIWA Simulation Platform, the ER-flow usage scenarios and how the Hydrometeorology research community runs simulations on SSP.

The Impact of Using SMS as Learning Support Tool on Students' Learning

ERIC Educational Resources Information Center

Gasaymeh, Al-Mothana M.; Aldalalah, Osamah M.

2013-01-01

This study aimed to investigate the impact of using Short Message Service (SMS) as learning support tool on students' learning in an introductory programming course. In addition, the study examined students' perceptions of the advantages and disadvantages of the use of SMS as a learning support tool in their class. The participants in this study…

Designing a Semantic Bliki System to Support Different Types of Knowledge and Adaptive Learning

ERIC Educational Resources Information Center

Huang, Shiu-Li; Yang, Chia-Wei

2009-01-01

Though blogs and wikis have been used to support knowledge management and e-learning, existing blogs and wikis cannot support different types of knowledge and adaptive learning. A case in point, types of knowledge vary greatly in category and viewpoints. Additionally, adaptive learning is crucial to improving one's learning performance. This study…

[Effects of Learning Activities on Application of Learning Portfolio in Nursing Management Course].

PubMed

Choi, So Eun; Kim, Eun A

2016-02-01

This study was conducted to examine effects of a learning portfolio by identifying the learning of nursing students taking a learning portfolio-utilized nursing management class. A non-equivalent control group pretest-posttest design was used. Participants were 83 senior students taking the nursing management course in one of the Departments of Nursing at 2 Universities. Experimental group (n=42) received a learning portfolio-utilized nursing management class 15 times over 15 weeks (3 hours weekly). Self-directed learning abilities, approaches to learning and learning flow of the participants were examined with self-report structured questionnaires. Data were collected between September 2 and December 16, 2014, and were analyzed using chi-square test, Fisher's exact test, independent t-test and ANCOVA with SPSS/PC version 21.0. After the intervention the experimental group showed significant increases in self-directed learning abilities, deep approaches to learning and learning flow compared to the control group. However, no significant difference was found between groups for surface approaches to learning. Learning activities using the learning portfolios could be effective in cultivating the learning competency for growth of knowledge, technology and professionalism by increasing personal concentration and organization ability of the nursing students so that they can react to the rapidly changing environment.

Scaling and pedotransfer in numerical simulations of flow and transport in soils

USDA-ARS?s Scientific Manuscript database

Flow and transport parameters of soils in numerical simulations need to be defined at the support scale of computational grid cells. Such support scale can substantially differ from the support scale in laboratory or field measurements of flow and transport parameters. The scale-dependence of flow a...

Machine Learning Interface for Medical Image Analysis.

PubMed

Zhang, Yi C; Kagen, Alexander C

2017-10-01

TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

Computational Analysis of Intra-Ventricular Flow Pattern Under Partial and Full Support of BJUT-II VAD.

PubMed

Zhang, Qi; Gao, Bin; Chang, Yu

2017-02-27

BACKGROUND Partial support, as a novel support mode, has been widely applied in clinical practice and widely studied. However, the precise mechanism of partial support of LVAD in the intra-ventricular flow pattern is unclear. MATERIAL AND METHODS In this study, a patient-specific left ventricular geometric model was reconstructed based on CT data. The intra-ventricular flow pattern under 3 simulated conditions - "heart failure", "partial support", and "full support" - were simulated by using fluid-structure interaction (FSI). The blood flow pattern, wall shear stress (WSS), time-average wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT) were calculated to evaluate the hemodynamic effects. RESULTS The results demonstrate that the intra-ventricular flow pattern is significantly changed by the support level of BJUT-II VAD. The intra-ventricular vortex was enhanced under partial support and was eliminated under full support, and the high OSI and RRT regions changed from the septum wall to the cardiac apex. CONCLUSIONS In brief, the support level of the BJUT-II VAD has significant effects on the intra-ventricular flow pattern. The partial support mode of BJUT-II VAD can enhance the intra-ventricular vortex, while the distribution of high OSI and RRT moved from the septum wall to the cardiac apex. Hence, the partial support mode of BJUT-II VAD can provide more benefit for intra-ventricular flow pattern.

Organizational Support in Online Learning Environments: Examination of Support Factors in Corporate Online Learning Implementation

ERIC Educational Resources Information Center

Schultz, Thomas L.; Correia, Ana-Paula

2015-01-01

This article explores the role of different types of support in corporate online learning programs. Most research has not specifically focused on all of the support factors required to provide a corporate online learning program, although many research studies address several in regards to the research outcome. An effort was made in this article…

Pleated metal bipolar assembly

DOEpatents

Wilson, Mahlon S.; Zawodzinski, Christine

2001-01-01

A thin low-cost bipolar plate for an electrochemical cell is formed from a polymer support plate with first flow channels on a first side of the support plate and second flow channels on a second side of the support plate, where the first flow channels and second flow channels have intersecting locations and have a depth effective to form openings through the support plate at the intersecting locations. A first foil of electrically conductive material is pressed into the first flow channels. A second foil of electrically conductive material pressed into the second flow channels so that electrical contact is made between the first and second foils at the openings through the support plate. A particular application of the bipolar plate is in polymer electrolyte fuel cells.

Unsteady flow sensing and optimal sensor placement using machine learning

NASA Astrophysics Data System (ADS)

Semaan, Richard

2016-11-01

Machine learning is used to estimate the flow state and to determine the optimal sensor placement over a two-dimensional (2D) airfoil equipped with a Coanda actuator. The analysis is based on flow field data obtained from 2D unsteady Reynolds averaged Navier-Stokes (uRANS) simulations with different jet blowing intensities and actuation frequencies, characterizing different flow separation states. This study shows how the "random forests" algorithm is utilized beyond its typical usage in fluid mechanics estimating the flow state to determine the optimal sensor placement. The results are compared against the current de-facto standard of maximum modal amplitude location and against a brute force approach that scans all possible sensor combinations. The results show that it is possible to simultaneously infer the state of flow and to determine the optimal sensor location without the need to perform proper orthogonal decomposition. Collaborative Research Center (CRC) 880, DFG.

Support for learning goes beyond academic support: Voices of students with Asperger's disorder and attention deficit hyperactivity disorder.

PubMed

Bolic Baric, Vedrana; Hellberg, Kristina; Kjellberg, Anette; Hemmingsson, Helena

2016-02-01

The purpose of this study was to describe and explore the experiences of support at school among young adults with Asperger's disorder and attention deficit hyperactivity disorder and also to examine what support they, in retrospect, described as influencing learning. Purposive sampling was used to enroll participants. Data were collected through semi-structured interviews with 13 young adults aged between 20 and 29 years. A qualitative analysis, based on interpreting people's experiences, was conducted by grouping and searching for patterns in data. The findings indicate that the participants experienced difficulties at school that included academic, social, and emotional conditions, all of which could influence learning. Support for learning included small groups, individualized teaching methods, teachers who cared, and practical and emotional support. These clusters together confirm the overall understanding that support for learning aligns academic and psychosocial support. In conclusion, academic support combined with psychosocial support at school seems to be crucial for learning among students with Asperger's disorder and attention deficit hyperactivity disorder. © The Author(s) 2015.

Hybrid E-Learning Tool TransLearning: Video Storytelling to Foster Vicarious Learning within Multi-Stakeholder Collaboration Networks

ERIC Educational Resources Information Center

van der Meij, Marjoleine G.; Kupper, Frank; Beers, Pieter J.; Broerse, Jacqueline E. W.

2016-01-01

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…

A focus group study of chiropractic students following international service learning experiences

PubMed Central

Boysen, James C.; Salsbury, Stacie A.; Derby, Dustin; Lawrence, Dana J.

2016-01-01

Objective: One objective of chiropractic education is to cultivate clinical confidence in novice practitioners. The purpose of this qualitative study was to describe how participation in a short-term international service learning experience changed perceptions of clinical confidence in senior chiropractic students. Methods: Seventeen senior chiropractic students participated in 4 moderated focus group sessions within 4 months after a clinical educational opportunity held in international settings. Participants answered standard questions on how this educational experience may have changed their clinical confidence. Two investigators performed qualitative thematic analysis of the verbatim transcripts to identify core concepts and supporting themes. Results: The core concept was transformation from an unsure student to a confident doctor. The service learning experience allowed students to deliver chiropractic treatment to patients in a real-world setting, engage in frequent repetitions of technical skills, perform clinical decision-making and care coordination, and communicate with patients and other health professionals. Students described increased clinical confidence in 9 competency areas organized within 3 domains: (1) chiropractic competencies including observation, palpation, and manipulation; (2) clinical competencies including problem solving, clinic flow, and decision-making; and (3) communication competencies, including patient communication, interprofessional communication, and doctor–patient relationship. Students recommended that future service learning programs include debriefing sessions similar to the experience offered by these focus groups to enhance student learning. Conclusion: Senior chiropractic students who participated in an international service learning program gained confidence and valuable practical experience in integrating their chiropractic, clinical, and communication skills for their future practices. PMID:27258817

Lifelong learning: Established concepts and evolving values.

PubMed

Talati, Jamsheer Jehangir

2014-03-01

To summarise the concepts critical for understanding the content and value of lifelong learning (LL). Ideas generated by personal experience were combined with those of philosophers, social scientists, educational institutions, governments and UNESCO, to facilitate an understanding of the importance of the basic concepts of LL. Autopoietic, continuous, self-determined, informal, vicarious, biographical, lifelong reflexive learning, from and for society, when supported by self-chosen formal courses, can build capacities and portable skills that allow useful responses to challenges and society's new structures of governance. The need for LL is driven by challenges. LL flows continuously in pursuit of one agenda, which could either be citizenship, as is conventional, or as this article proposes, health. LL cannot be wholly centred on vocation. Continuous medical education and continuous professional development, important in their own right, cannot supply all that is needed. LL aids society with its learning, and it requires an awareness of the environment and structures of society. It is heavily vicarious, draws on formal learning and relies for effectiveness on reflection, self-assessment and personal shaping of views of the world from different perspectives. Health is critical to rational thought and peace, and determines society's capacity to govern itself, and improve its health. LL should be reshaped to focus on health not citizenship. Therefore, embedding learning in society and environment is critical. Each urologist must develop an understanding of the numerous concepts in LL, of which 'biographicisation' is the seed that will promote innovative strategies.

Lifelong learning: Established concepts and evolving values

PubMed Central

Talati, Jamsheer Jehangir

2014-01-01

Objective To summarise the concepts critical for understanding the content and value of lifelong learning (LL). Methods Ideas generated by personal experience were combined with those of philosophers, social scientists, educational institutions, governments and UNESCO, to facilitate an understanding of the importance of the basic concepts of LL. Results Autopoietic, continuous, self-determined, informal, vicarious, biographical, lifelong reflexive learning, from and for society, when supported by self-chosen formal courses, can build capacities and portable skills that allow useful responses to challenges and society’s new structures of governance. The need for LL is driven by challenges. LL flows continuously in pursuit of one agenda, which could either be citizenship, as is conventional, or as this article proposes, health. LL cannot be wholly centred on vocation. Continuous medical education and continuous professional development, important in their own right, cannot supply all that is needed. LL aids society with its learning, and it requires an awareness of the environment and structures of society. It is heavily vicarious, draws on formal learning and relies for effectiveness on reflection, self-assessment and personal shaping of views of the world from different perspectives. Conclusion Health is critical to rational thought and peace, and determines society’s capacity to govern itself, and improve its health. LL should be reshaped to focus on health not citizenship. Therefore, embedding learning in society and environment is critical. Each urologist must develop an understanding of the numerous concepts in LL, of which ‘biographicisation’ is the seed that will promote innovative strategies. PMID:26019932

Informing Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles.

PubMed

Horne, Avril C; Szemis, Joanna M; Webb, J Angus; Kaur, Simranjit; Stewardson, Michael J; Bond, Nick; Nathan, Rory

2018-03-01

One important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.

Informing Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles

NASA Astrophysics Data System (ADS)

Horne, Avril C.; Szemis, Joanna M.; Webb, J. Angus; Kaur, Simranjit; Stewardson, Michael J.; Bond, Nick; Nathan, Rory

2018-03-01

One important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.

A Framework for a Computer System to Support Distributed Cooperative Learning

ERIC Educational Resources Information Center

Chiu, Chiung-Hui

2004-01-01

To develop a computer system to support cooperative learning among distributed students; developers should consider the foundations of cooperative learning. This article examines the basic elements that make cooperation work and proposes a framework for such computer supported cooperative learning (CSCL) systems. This framework is constituted of…

Relationships of People with Learning Disabilities in Ireland

ERIC Educational Resources Information Center

Bane, Geraldine; Deely, Marie; Donohoe, Brian; Dooher, Martin; Flaherty, Josephine; Iriarte, Edurne Garcia; Hopkins, Rob; Mahon, Ann; Minogue, Ger; Mc Donagh, Padraig; O'Doherty, Siobhain; Curry, Martin; Shannon, Stephen; Tierney, Edel; Wolfe, Marie

2012-01-01

This study explored the perspectives of people with learning disabilities on relationships and supports in the Republic of Ireland. A national research network consisting of 21 researchers with learning disabilities, 12 supporters, and 7 university researchers conducted the study. Researchers with learning disabilities and their supporters ran 16…

Building a community of practice for sustainability: strengthening learning and collective action of Canadian biosphere reserves through a national partnership.

PubMed

Reed, Maureen G; Godmaire, Hélène; Abernethy, Paivi; Guertin, Marc-André

2014-12-01

Deliberation, dialogue and systematic learning are now considered attributes of good practice for organizations seeking to advance sustainability. Yet we do not know whether organizations that span spatial scales and governance responsibilities can establish effective communities of practice to facilitate learning and action. The purpose of this paper is to generate a framework that specifies actions and processes of a community of practice designed to instill collective learning and action strategies across a multi-level, multi-partner network. The framework is then used to describe and analyze a partnership among practitioners of Canada's 16 UNESCO biosphere reserves, and additional researchers and government representatives from across Canada. The framework is a cycle of seven action steps, beginning and ending with reflecting on and evaluating present practice. It is supported by seven characteristics of collaborative environmental management that are used to gauge the success of the partnership. Our results show that the partnership successfully built trust, established shared norms and common interest, created incentives to participate, generated value in information sharing and willingness to engage, demonstrated effective flow of information, and provided leadership and facilitation. Key to success was the presence of a multi-lingual facilitator who could bridge cultural differences across regions and academia-practitioner expectations. The project succeeded in establishing common goals, setting mutual expectations and building relations of trust and respect, and co-creating knowledge. It is too soon to determine whether changes in practices that support sustainability will be maintained over the long term and without the help of an outside facilitator. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Use of Narrative: Gender Differences and Implications for Motivation and Learning in a Math Game. CRESST Report 804

ERIC Educational Resources Information Center

Bittick, Sarah Joy; Chung, Gregory K. W. K.

2011-01-01

The use of a narrative in educational contexts has been found to increase learners' experience of flow or absorption in a task. This increased experience of flow can in turn result in increased retention and learning outcomes. However, narrative can also be polarizing particularly in the male-dominated realm of video game play due to gender…

Designing a Moodle Course with the CADMOS Learning Design Tool

ERIC Educational Resources Information Center

Katsamani, Maria; Retalis, Symeon; Boloudakis, Michail

2012-01-01

CADMOS is a graphical learning design (LD) authoring tool that helps a teacher design a unit of learning in two layers: (i) the conceptual layer, which seems like a concept map and contains the learning activities with their associated learning resources and (ii) the flow layer, which contains the orchestration of these activities. One of CADMOS'…

Cognitive Tools for Assessment and Learning in a High Information Flow Environment.

ERIC Educational Resources Information Center

Lajoie, Susanne P.; Azevedo, Roger; Fleiszer, David M.

1998-01-01

Describes the development of a simulation-based intelligent tutoring system for nurses working in a surgical intensive care unit. Highlights include situative learning theories and models of instruction, modeling expertise, complex decision making, linking theories of learning to the design of computer-based learning environments, cognitive task…

Modeling long-term suspended-sediment export from an undisturbed forest catchment

NASA Astrophysics Data System (ADS)

Zimmermann, Alexander; Francke, Till; Elsenbeer, Helmut

2013-04-01

Most estimates of suspended sediment yields from humid, undisturbed, and geologically stable forest environments fall within a range of 5 - 30 t km-2 a-1. These low natural erosion rates in small headwater catchments (≤ 1 km2) support the common impression that a well-developed forest cover prevents surface erosion. Interestingly, those estimates originate exclusively from areas with prevailing vertical hydrological flow paths. Forest environments dominated by (near-) surface flow paths (overland flow, pipe flow, and return flow) and a fast response to rainfall, however, are not an exceptional phenomenon, yet only very few sediment yields have been estimated for these areas. Not surprisingly, even fewer long-term (≥ 10 years) records exist. In this contribution we present our latest research which aims at quantifying long-term suspended-sediment export from an undisturbed rainforest catchment prone to frequent overland flow. A key aspect of our approach is the application of machine-learning techniques (Random Forest, Quantile Regression Forest) which allows not only the handling of non-Gaussian data, non-linear relations between predictors and response, and correlations between predictors, but also the assessment of prediction uncertainty. For the current study we provided the machine-learning algorithms exclusively with information from a high-resolution rainfall time series to reconstruct discharge and suspended sediment dynamics for a 21-year period. The significance of our results is threefold. First, our estimates clearly show that forest cover does not necessarily prevent erosion if wet antecedent conditions and large rainfalls coincide. During these situations, overland flow is widespread and sediment fluxes increase in a non-linear fashion due to the mobilization of new sediment sources. Second, our estimates indicate that annual suspended sediment yields of the undisturbed forest catchment show large fluctuations. Depending on the frequency of large events, annual suspended-sediment yield varies between 74 - 416 t km-2 a-1. Third, the estimated sediment yields exceed former benchmark values by an order of magnitude and provide evidence that the erosion footprint of undisturbed, forested catchments can be undistinguishable from that of sustainably managed, but hydrologically less responsive areas. Because of the susceptibility to soil loss we argue that any land use should be avoided in natural erosion hotspots.

A deep learning framework for causal shape transformation.

PubMed

Lore, Kin Gwn; Stoecklein, Daniel; Davies, Michael; Ganapathysubramanian, Baskar; Sarkar, Soumik

2018-02-01

Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the common go-to architecture for exploiting sequential information where the output is dependent on a sequence of inputs. However, in most considered problems, the dependencies typically lie in the latent domain which may not be suitable for applications involving the prediction of a step-wise transformation sequence that is dependent on the previous states only in the visible domain with a known terminal state. We propose a hybrid architecture of convolution neural networks (CNN) and stacked autoencoders (SAE) to learn a sequence of causal actions that nonlinearly transform an input visual pattern or distribution into a target visual pattern or distribution with the same support and demonstrated its practicality in a real-world engineering problem involving the physics of fluids. We solved a high-dimensional one-to-many inverse mapping problem concerning microfluidic flow sculpting, where the use of deep learning methods as an inverse map is very seldom explored. This work serves as a fruitful use-case to applied scientists and engineers in how deep learning can be beneficial as a solution for high-dimensional physical problems, and potentially opening doors to impactful advance in fields such as material sciences and medical biology where multistep topological transformations is a key element. Copyright © 2017 Elsevier Ltd. All rights reserved.

Augmenting the senses: a review on sensor-based learning support.

PubMed

Schneider, Jan; Börner, Dirk; van Rosmalen, Peter; Specht, Marcus

2015-02-11

In recent years sensor components have been extending classical computer-based support systems in a variety of applications domains (sports, health, etc.). In this article we review the use of sensors for the application domain of learning. For that we analyzed 82 sensor-based prototypes exploring their learning support. To study this learning support we classified the prototypes according to the Bloom's taxonomy of learning domains and explored how they can be used to assist on the implementation of formative assessment, paying special attention to their use as feedback tools. The analysis leads to current research foci and gaps in the development of sensor-based learning support systems and concludes with a research agenda based on the findings.

Augmenting the Senses: A Review on Sensor-Based Learning Support

PubMed Central

Schneider, Jan; Börner, Dirk; van Rosmalen, Peter; Specht, Marcus

2015-01-01

In recent years sensor components have been extending classical computer-based support systems in a variety of applications domains (sports, health, etc.). In this article we review the use of sensors for the application domain of learning. For that we analyzed 82 sensor-based prototypes exploring their learning support. To study this learning support we classified the prototypes according to the Bloom's taxonomy of learning domains and explored how they can be used to assist on the implementation of formative assessment, paying special attention to their use as feedback tools. The analysis leads to current research foci and gaps in the development of sensor-based learning support systems and concludes with a research agenda based on the findings. PMID:25679313

Collaborative learning: A next step in the training of peer support providers.

PubMed

Cronise, Rita

2016-09-01

This column explores how peer support provider training is enhanced through collaborative learning. Collaborative learning is an approach that draws upon the "real life" experiences of individual learners and encompasses opportunities to explore varying perspectives and collectively construct solutions that enrich the practice of all participants. This description draws upon published articles and examples of collaborative learning in training and communities of practice of peer support providers. Similar to person-centered practices that enhance the recovery experience of individuals receiving services, collaborative learning enhances the experience of peer support providers as they explore relevant "real world" issues, offer unique contributions, and work together toward improving practice. Three examples of collaborative learning approaches are provided that have resulted in successful collaborative learning opportunities for peer support providers. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Students' Perceptions of Self-Directed Learning and Collaborative Learning with and without Technology

ERIC Educational Resources Information Center

Lee, K.; Tsai, P.-S.; Chai, C. S.; Koh, J. H. L.

2014-01-01

This study explored students' perceptions of self-directed learning (SDL) and collaborative learning (CL) with/without technology in an information and communications technology-supported classroom environment. The factors include SDL, CL, SDL supported by technology, and CL supported by technology. Based on the literature review, this study…

A Competence-Based Service for Supporting Self-Regulated Learning in Virtual Environments

ERIC Educational Resources Information Center

Nussbaumer, Alexander; Hillemann, Eva-Catherine; Gütl, Christian; Albert, Dietrich

2015-01-01

This paper presents a conceptual approach and a Web-based service that aim at supporting self-regulated learning in virtual environments. The conceptual approach consists of four components: 1) a self-regulated learning model for supporting a learner-centred learning process, 2) a psychological model for facilitating competence-based…

Successful Implementation of a Computer-Supported Collaborative Learning System in Teaching E-Commerce

ERIC Educational Resources Information Center

Ngai, E. W. T.; Lam, S. S.; Poon, J. K. L.

2013-01-01

This paper describes the successful application of a computer-supported collaborative learning system in teaching e-commerce. The authors created a teaching and learning environment for 39 local secondary schools to introduce e-commerce using a computer-supported collaborative learning system. This system is designed to equip students with…

Internal and External Factors Affecting Teachers' Adoption of Formative Assessment to Support Learning

ERIC Educational Resources Information Center

Izci, Kemal

2016-01-01

Assessment forms an important part of instruction. Assessment that aims to support learning is known as formative assessment and it contributes student's learning gain and motivation. However, teachers rarely use assessment formatively to aid their students' learning. Thus reviewing the factors that limit or support teachers' practices of…

Internal and External Factors Affecting Teachers' Adoption of Formative Assessment to Support Learning

ERIC Educational Resources Information Center

Izci, Kemal

2016-01-01

Assessment forms an important part of instruction. Assessment that aims to support learning is known as formative assessment and it contributes student's learning gain and motivation. However, teachers rarely use assessment formatively to aid their students' learning. Thus, reviewing the factors that limit or support teachers' practices of…

Triple Scheme of Learning Support Design for Scientific Discovery Learning Based on Computer Simulation: Experimental Research

ERIC Educational Resources Information Center

Zhang, Jianwei; Chen, Qi; Sun, Yanquing; Reid, David J.

2004-01-01

Learning support studies involving simulation-based scientific discovery learning have tended to adopt an ad hoc strategies-oriented approach in which the support strategies are typically pre-specified according to learners' difficulties in particular activities. This article proposes a more integrated approach, a triple scheme for learning…

Supporting Vocationally Oriented Learning in the High School Years: Rationale, Tasks, Challenges

ERIC Educational Resources Information Center

Halpern, Robert

2012-01-01

This article highlights the limitations of our current educational system in terms of vocational learning and highlights the role that vocational learning can play in supporting youth development and improving youth outcomes. It discusses the role that nonschool settings can play in supporting vocational learning and suggests strategies to improve…

The Impact of Leadership Support for Blended Learning on Teachers and Students

ERIC Educational Resources Information Center

Bodden-White, Michelle Marie

2015-01-01

This quantitative study examined the relationship between teachers' perceptions of leadership support for their use of a blended learning approach to teach math in fourth or fifth grade and their use of blended learning. The study also examined teachers' perceptions of leadership support for incorporating blended learning and student engagement.…

The Effects of Mobile-Computer-Supported Collaborative Learning: Meta-Analysis and Critical Synthesis

ERIC Educational Resources Information Center

Sung, Yao-Ting; Yang, Je-Ming; Lee, Han-Yueh

2017-01-01

One of the trends in collaborative learning is using mobile devices for supporting the process and products of collaboration, which has been forming the field of mobile-computer-supported collaborative learning (mCSCL). Although mobile devices have become valuable collaborative learning tools, evaluative evidence for their substantial…

Supporting new graduate professional development: a clinical learning framework.

PubMed

Fitzgerald, Cate; Moores, Alis; Coleman, Allison; Fleming, Jennifer

2015-02-01

New graduate occupational therapists are required to competently deliver health-care practices within complex care environments. An occupational therapy clinical education programme within a large public sector health service sought to investigate methods to support new graduates in their clinical learning and professional development. Three cycles of an insider action research approach each using the steps of planning, action, critical observation and reflection were undertaken to investigate new graduate learning strategies, develop a learning framework and pilot its utility. Qualitative research methods were used to analyse data gathered during the action research cycles. Action research identified variations in current practices to support new graduate learning and to the development of the Occupational Therapy Clinical Learning Framework (OTCLF). Investigation into the utility of the OTCLF revealed two themes associated with its implementation namely (i) contribution to learning goal development and (ii) compatibility with existing learning supports. The action research cycles aimed to review current practices to support new graduate learning. The learning framework developed encourages reflection to identify learning needs and the review, discussion of, and engagement in, goal setting and learning strategies. Preliminary evidence indicates that the OTCLF has potential as an approach to guide new graduate goal development supported by supervision. Future opportunity to implement a similar learning framework in other allied health professions was identified, enabling a continuation of the cyclical nature of enquiry, integral to this research approach within the workplace. © 2014 Occupational Therapy Australia.

A Data-Driven Approach to Develop Physically Sound Predictors: Application to Depth-Averaged Velocities and Drag Coefficients on Vegetated Flows

NASA Astrophysics Data System (ADS)

Tinoco, R. O.; Goldstein, E. B.; Coco, G.

2016-12-01

We use a machine learning approach to seek accurate, physically sound predictors, to estimate two relevant flow parameters for open-channel vegetated flows: mean velocities and drag coefficients. A genetic programming algorithm is used to find a robust relationship between properties of the vegetation and flow parameters. We use data published from several laboratory experiments covering a broad range of conditions to obtain: a) in the case of mean flow, an equation that matches the accuracy of other predictors from recent literature while showing a less complex structure, and b) for drag coefficients, a predictor that relies on both single element and array parameters. We investigate different criteria for dataset size and data selection to evaluate their impact on the resulting predictor, as well as simple strategies to obtain only dimensionally consistent equations, and avoid the need for dimensional coefficients. The results show that a proper methodology can deliver physically sound models representative of the processes involved, such that genetic programming and machine learning techniques can be used as powerful tools to study complicated phenomena and develop not only purely empirical, but "hybrid" models, coupling results from machine learning methodologies into physics-based models.

Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods

NASA Astrophysics Data System (ADS)

Cubuk, E. D.; Schoenholz, S. S.; Rieser, J. M.; Malone, B. D.; Rottler, J.; Durian, D. J.; Kaxiras, E.; Liu, A. J.

2015-03-01

We use machine-learning methods on local structure to identify flow defects—or particles susceptible to rearrangement—in jammed and glassy systems. We apply this method successfully to two very different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temperature. We also identify characteristics of flow defects that differentiate them from the rest of the sample. Our results show it is possible to discern subtle structural features responsible for heterogeneous dynamics observed across a broad range of disordered materials.

Shifts in the suitable habitat available for brown trout (Salmo trutta L.) under short-term climate change scenarios.

PubMed

Muñoz-Mas, R; Lopez-Nicolas, A; Martínez-Capel, F; Pulido-Velazquez, M

2016-02-15

The impact of climate change on the habitat suitability for large brown trout (Salmo trutta L.) was studied in a segment of the Cabriel River (Iberian Peninsula). The future flow and water temperature patterns were simulated at a daily time step with M5 models' trees (NSE of 0.78 and 0.97 respectively) for two short-term scenarios (2011-2040) under the representative concentration pathways (RCP 4.5 and 8.5). An ensemble of five strongly regularized machine learning techniques (generalized additive models, multilayer perceptron ensembles, random forests, support vector machines and fuzzy rule base systems) was used to model the microhabitat suitability (depth, velocity and substrate) during summertime and to evaluate several flows simulated with River2D©. The simulated flow rate and water temperature were combined with the microhabitat assessment to infer bivariate habitat duration curves (BHDCs) under historical conditions and climate change scenarios using either the weighted usable area (WUA) or the Boolean-based suitable area (SA). The forecasts for both scenarios jointly predicted a significant reduction in the flow rate and an increase in water temperature (mean rate of change of ca. -25% and +4% respectively). The five techniques converged on the modelled suitability and habitat preferences; large brown trout selected relatively high flow velocity, large depth and coarse substrate. However, the model developed with support vector machines presented a significantly trimmed output range (max.: 0.38), and thus its predictions were banned from the WUA-based analyses. The BHDCs based on the WUA and the SA broadly matched, indicating an increase in the number of days with less suitable habitat available (WUA and SA) and/or with higher water temperature (trout will endure impoverished environmental conditions ca. 82% of the days). Finally, our results suggested the potential extirpation of the species from the study site during short time spans. Copyright © 2015 Elsevier B.V. All rights reserved.

Decision support system for optimally managing water resources to meet multiple objectives in the Savannah River Basin

USGS Publications Warehouse

Roehl, Edwin A.; Conrads, Paul

2015-01-01

Managers of large river basins face conflicting demands for water resources such as wildlife habitat, water supply, wastewater assimilative capacity, flood control, hydroelectricity, and recreation. The Savannah River Basin, for example, has experienced three major droughts since 2000 that resulted in record low water levels in its reservoirs, impacting dependent economies for years. The Savannah River estuary contains two municipal water intakes and the ecologically sensitive freshwater tidal marshes of the Savannah National Wildlife Refuge. The Port of Savannah is the fourth busiest in the United States, and modifications to the harbor to expand ship traffic since the 1970s have caused saltwater to migrate upstream, reducing the freshwater marsh’s acreage more than 50 percent. A planned deepening of the harbor includes flow-alteration features to minimize further migration of salinity, whose effectiveness will only be known after all construction is completed.One of the challenges of large basin management is the optimization of water use through ongoing regional economic development, droughts, and climate change. This paper describes a model of the Savannah River Basin designed to continuously optimize regulated flow to meet prioritized objectives set by resource managers and stakeholders. The model was developed from historical data using machine learning, making it more accurate and adaptable to changing conditions than traditional models. The model is coupled to an optimization routine that computes the daily flow needed to most efficiently meet the water-resource management objectives. The model and optimization routine are packaged in a decision support system that makes it easy for managers and stakeholders to use. Simulation results show that flow can be regulated to substantially reduce salinity intrusions in the Savannah National Wildlife Refuge, while conserving more water in the reservoirs. A method for using the model to assess the effectiveness of the flow-alteration features after the deepening also is demonstrated.

Making Learning Support Contextually Responsive

ERIC Educational Resources Information Center

Dreyer, L.; Engelbrecht, P.; Swart, E.

2012-01-01

Research indicates that the success of inclusive education lies within the provision of adequate support for learners who experience barriers to learning in mainstream schools as well as in the changing roles of teachers and support services staff. The Western Cape Education Department (WCED) implemented a learning support model, designed to…

Voices from the Trenches: Faculty Perspectives on Support for Sustaining Service-Learning

ERIC Educational Resources Information Center

Lambright, Kristina T.; Alden, Allison F.

2012-01-01

Using data collected from three colleges, the authors examine how faculty members view the level of support for service-learning at their respective institutions. There is variation among the institutions in perceived instructor and administrator support for service-learning, availability of support services, and attitudes regarding consideration…

Web-Based Learning Support System

NASA Astrophysics Data System (ADS)

Fan, Lisa

Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

Social Media and Seamless Learning: Lessons Learned

ERIC Educational Resources Information Center

Panke, Stefanie; Kohls, Christian; Gaiser, Birgit

2017-01-01

The paper discusses best practice approaches and metrics for evaluation that support seamless learning with social media. We draw upon the theoretical frameworks of social learning theory, transfer learning (bricolage), and educational design patterns to elaborate upon different ideas for ways in which social media can support seamless learning.…

Contextualised Media for Learning

ERIC Educational Resources Information Center

de Jong, Tim; Specht, Marcus; Koper, Rob

2008-01-01

In this paper, we analyse how contextualised media can be used to support learning. Additionally, the advantages of contextualised learning and the types of learning that are fit to be supported are discussed. Our focus throughout the paper will be on lifelong learning, and the integration of formal and informal learning therein. However, we…

Co-Regulation of Learning in Computer-Supported Collaborative Learning Environments: A Discussion

ERIC Educational Resources Information Center

Chan, Carol K. K.

2012-01-01

This discussion paper for this special issue examines co-regulation of learning in computer-supported collaborative learning (CSCL) environments extending research on self-regulated learning in computer-based environments. The discussion employs a socio-cognitive perspective focusing on social and collective views of learning to examine how…

Understanding, Evaluating, and Supporting Self-Regulated Learning Using Learning Analytics

ERIC Educational Resources Information Center

Roll, Ido; Winne, Philip H.

2015-01-01

Self-regulated learning is an ongoing process rather than a single snapshot in time. Naturally, the field of learning analytics, focusing on interactions and learning trajectories, offers exciting opportunities for analyzing and supporting self-regulated learning. This special section highlights the current state of research at the intersection of…

Structural Relationships among Self-Regulated Learning, Learning Flow, Satisfaction, and Learning Persistence in Cyber Universities

ERIC Educational Resources Information Center

Joo, Young Ju; Joung, Sunyoung; Kim, Jiyeon

2014-01-01

Learning persistence in a cyber-learning environment is not only an index determining the success or failure of individual learners but also a source of important information to establish the management direction of educational programs in an organization. Accordingly, learners need to be motivated to continue to grow in order to ensure both…

How Competition in a Game-Based Science Learning Environment Influences Students' Learning Achievement, Flow Experience, and Learning Behavioral Patterns

ERIC Educational Resources Information Center

Chen, Ching-Huei; Liu, Jun-Han; Shou, Wen-Chuan

2018-01-01

Although educational games have become prevalent in recent research, only a limited number of studies have considered learners' learning behaviors while playing a science problem-solving game. Introducing a competitive element to game-based learning is promising; however, research has produced ambiguous results, indicating that more studies should…

Intrinsic Motivation of Chinese Learning in Predicting Online Learning Self-Efficacy and Flow Experience Relevant to Students' Learning Progress

ERIC Educational Resources Information Center

Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Lin, Pei-Hsin

2017-01-01

Students of Southeast Asian Heritage Learning Chinese (SSAHLC) in Taiwan have frequently demonstrated difficulty with traditional Chinese (a graphical character) radical recognition due to their limited exposure to the written language form since childhood. In this study, we designed a Chinese radical learning game (CRLG), which adopted a drill…

Probing High School Students' Cognitive Structures and Key Areas of Learning Difficulties on Ethanoic Acid Using the Flow Map Method

ERIC Educational Resources Information Center

Zhou, Qing; Wang, Tingting; Zheng, Qi

2015-01-01

The purpose of this study was primarily to explore high school students' cognitive structures and to identify their learning difficulties on ethanoic acid through the flow map method. The subjects of this study were 30 grade 1 students from Dong Yuan Road Senior High School in Xi'an, China. The interviews were conducted a week after the students…

A Study of the Relationships among Learning Styles, Participation Types, and Performance in Programming Language Learning Supported by Online Forums

ERIC Educational Resources Information Center

Shaw, Ruey-Shiang

2012-01-01

This study is focused on the relationships among learning styles, participation types, and learning performance for programming language learning supported by an online forum. Kolb's learning style inventory was used in this study to determine a learner's learning type: "Diverger", "Assimilator", "Converger", and "Accommodator". Social Learning…

A Research on the Generative Learning Model Supported by Context-Based Learning

ERIC Educational Resources Information Center

Ulusoy, Fatma Merve; Onen, Aysem Seda

2014-01-01

This study is based on the generative learning model which involves context-based learning. Using the generative learning model, we taught the topic of Halogens. This topic is covered in the grade 10 chemistry curriculum using activities which are designed in accordance with the generative learning model supported by context-based learning. The…

Invited Reaction: Influences of Formal Learning, Personal Learning Orientation, and Supportive Learning Environment on Informal Learning

ERIC Educational Resources Information Center

Cseh, Maria; Manikoth, Nisha N.

2011-01-01

As the authors of the preceding article (Choi and Jacobs, 2011) have noted, the workplace learning literature shows evidence of the complementary and integrated nature of formal and informal learning in the development of employee competencies. The importance of supportive learning environments in the workplace and of employees' personal learning…

NiftyNet: a deep-learning platform for medical imaging.

PubMed

Gibson, Eli; Li, Wenqi; Sudre, Carole; Fidon, Lucas; Shakir, Dzhoshkun I; Wang, Guotai; Eaton-Rosen, Zach; Gray, Robert; Doel, Tom; Hu, Yipeng; Whyntie, Tom; Nachev, Parashkev; Modat, Marc; Barratt, Dean C; Ourselin, Sébastien; Cardoso, M Jorge; Vercauteren, Tom

2018-05-01

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. The NiftyNet infrastructure provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on the TensorFlow framework and supports features such as TensorBoard visualization of 2D and 3D images and computational graphs by default. We present three illustrative medical image analysis applications built using NiftyNet infrastructure: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. The NiftyNet infrastructure enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Fuel cell assembly unit for promoting fluid service and electrical conductivity

DOEpatents

Jones, Daniel O.

1999-01-01

Fluid service and/or electrical conductivity for a fuel cell assembly is promoted. Open-faced flow channel(s) are formed in a flow field plate face, and extend in the flow field plate face between entry and exit fluid manifolds. A resilient gas diffusion layer is located between the flow field plate face and a membrane electrode assembly, fluidly serviced with the open-faced flow channel(s). The resilient gas diffusion layer is restrained against entering the open-faced flow channel(s) under a compressive force applied to the fuel cell assembly. In particular, a first side of a support member abuts the flow field plate face, and a second side of the support member abuts the resilient gas diffusion layer. The support member is formed with a plurality of openings extending between the first and second sides of the support member. In addition, a clamping pressure is maintained for an interface between the resilient gas diffusion layer and a portion of the membrane electrode assembly. Preferably, the support member is spikeless and/or substantially flat. Further, the support member is formed with an electrical path for conducting current between the resilient gas diffusion layer and position(s) on the flow field plate face.

The experiences of supporting learning in pairs of nursing students in clinical practice.

PubMed

Holst, Hanna; Ozolins, Lise-Lotte; Brunt, David; Hörberg, Ulrica

2017-09-01

The purpose of this study is to describe how supervisors experience supporting nursing students' learning in pairs on a Developing and Learning Care Unit in Sweden. The present study has been carried out with a Reflective Lifeworld Research (RLR) approach founded on phenomenology. A total of 25 lifeworld interviews were conducted with supervisors who had supervised pairs of students. The findings reveal how supervisors support students' learning in pairs through a reflective approach creating learning space in the encounter with patients, students and supervisors. Supervisors experience a movement that resembles balancing between providing support in learning together and individual learning. The findings also highlight the challenge in supporting both the pairs of students and being present in the reality of caring. In conclusion, the learning space has the potential of creating a relative level of independency in the interaction between pairs of students and their supervisor when the supervisor strives towards a reflective approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

Navigation assistance: a trade-off between wayfinding support and configural learning support.

PubMed

Münzer, Stefan; Zimmer, Hubert D; Baus, Jörg

2012-03-01

Current GPS-based mobile navigation assistance systems support wayfinding, but they do not support learning about the spatial configuration of an environment. The present study examined effects of visual presentation modes for navigation assistance on wayfinding accuracy, route learning, and configural learning. Participants (high-school students) visited a university campus for the first time and took a predefined assisted tour. In Experiment 1 (n = 84, 42 females), a presentation mode showing wayfinding information from eye-level was contrasted with presentation modes showing wayfinding information included in views that provided comprehensive configural information. In Experiment 2 (n = 48, 24 females), wayfinding information was included in map fragments. A presentation mode which always showed north on top of the device was compared with a mode which rotated according to the orientation of the user. Wayfinding accuracy (deviations from the route), route learning, and configural learning (direction estimates, sketch maps) were assessed. Results indicated a trade-off between wayfinding and configural learning: Presentation modes providing comprehensive configural information supported the acquisition of configural knowledge at the cost of accurate wayfinding. The route presentation mode supported wayfinding at the cost of configural knowledge acquisition. Both presentation modes based on map fragments supported wayfinding. Individual differences in visual-spatial working memory capacity explained a considerable portion of the variance in wayfinding accuracy, route learning, and configural learning. It is concluded that learning about an unknown environment during assisted navigation is based on the integration of spatial information from multiple sources and can be supported by appropriate visualization. PsycINFO Database Record (c) 2012 APA, all rights reserved.

The Effects of Self-Determination on Learning Outcomes in a Blended Learning

ERIC Educational Resources Information Center

Joo, Young Ju; Lim, Kyu Yon; Han, Sang Yoon; Ham, Yoo Kyoung; Kang, Aran

2013-01-01

The purpose of the paper is to examine whether the sub-constructs of self-determination, that is, learners' perceived level of autonomy, competence, and relatedness, predict learning flow, persistence, and achievement in a blended learning context. Participants are 102 adult learners who voluntarily registered for a Chinese language learning…

17 CFR 229.1114 - (Item 1114) Credit enhancement and other support, except for certain derivatives instruments.

Code of Federal Regulations, 2010 CFR

2010-04-01

... liable to provide payments representing 10% or more of the cash flow supporting any offered class of... liable to provide payments representing 10% or more, but less than 20%, of the cash flow supporting any... liable or contingently liable to provide payments representing 20% or more of the cash flow supporting...

Towards Greater Learner Control: Web Supported Project-Based Learning

ERIC Educational Resources Information Center

Guthrie, Cameron

2010-01-01

Project-based learning has been suggested as an appropriate pedagogy to prepare students in information systems for the realities of the business world. Web-based resources have been used to support such pedagogy with mixed results. The paper argues that the design of web-based learning support to cater to different learning styles may give…

The Job Is the Learning Environment: Performance-Centered Learning To Support Knowledge Worker Performance.

ERIC Educational Resources Information Center

Dickover, Noel T.

2002-01-01

Explains performance-centered learning (PCL), an approach to optimize support for performance on the job by making corporate assets available to knowledge workers so they can solve actual problems. Illustrates PCL with a Web site that provides just-in-time learning, collaboration, and performance support tools to improve performance at the…

Investigating Teacher Learning Supports in High School Biology Curricular Programs to Inform the Design of Educative Curriculum Materials

ERIC Educational Resources Information Center

Beyer, Carrie J.; Delgado, Cesar; Davis, Elizabeth A.; Krajcik, Joseph

2009-01-01

Reform efforts have emphasized the need to support teachers' learning about reform-oriented practices. Educative curriculum materials are one potential vehicle for promoting teacher learning about these practices. Educative curriculum materials include supports that are intended to promote both student "and" teacher learning. However, little is…

Families Support Their Children's Success in Science Learning by Influencing Interest and Self-efficacy

ERIC Educational Resources Information Center

Sha, Li; Schunn, Christian; Bathgate, Meghan; Ben-Eliyahu, Adar

2016-01-01

How is a child's successful participation in science learning shaped by their family's support? We focus on the critical time period of early adolescents, testing (i) whether the child's perception of family support is important for both choice preferences to participate in optional learning experiences and engagement during science learning, and…

Education Leaders' Guide to Transforming Student and Learning Supports. A Center Guide

ERIC Educational Resources Information Center

Center for Mental Health in Schools at UCLA, 2014

2014-01-01

New directions for student and learning supports are key to systemically addressing barriers to learning and teaching. The aim is to unify and then develop a comprehensive and equitable system of student/learning supports at every school. This guide incorporates years of research and prototype development and a variety of examples from…

Organizational Support for Action Learning in South Korean Organizations

ERIC Educational Resources Information Center

Cho, Yonjoo; Egan, Toby

2013-01-01

The purpose of this study was (1) to examine the impact of organizational support on employee learning and performance and (2) to elaborate on the context of organizational support for action learning in South Korean organizations. For this inquiry, two central questions were posed: What are employee reactions to organizational support for action…

Peer learning partnerships: exploring the experience of pre-registration nursing students.

PubMed

Christiansen, Angela; Bell, Amelia

2010-03-01

This paper explores the impact of a peer learning initiative developed to facilitate, purposefully, mutually supportive learning relationships between student nurses in the practice setting. Finding effective strategies to support learning in the practice setting has been the focus of professional concern for a considerable time. In the UK clinical mentorship is seen as pivotal to ensuring fitness to practice; however, recent debate on the nature of learning has revealed the clinical workplace as a rich learning environment where learning occurs not only through hierarchical relationships, but also from a network of peer relationships. Formalising peer relationships through peer assisted learning is increasingly suggested as a strategy to support workplace learning and support novice students' transition to the clinical setting. Despite the developing literature in this field there is limited understanding about how students experience facilitated peer relationships. An interpretive qualitative design. Focus group interviews were used to collect interactive and situated discourse from nursing students who had recently participated in peer learning partnerships (n = 54). Narrative data were analysed thematically. Findings suggest that active support from a fellow student reduced the feelings of social isolation experienced by novice students in initial clinical placements, helping them to deal more effectively with the challenges faced and reducing the factors that have an impact on attrition. In addition, the reciprocity of the peer learning partnerships facilitated understanding of mentorship and created a heightened sense of readiness for registration and professional practice. Peer learning partnerships facilitated by mentors in clinical practice can support the transition to nursing for first year students and can help more experienced students gain a confidence and a heightened readiness for mentorship and registered practice. Facilitated peer learning partnerships can enhance the student experience in the practice setting and can help maximise opportunities for learning and support. This suggests that peer assisted learning is a legitimate area for innovation and further research.

The pedagogical ebb and flow of human patient simulation: empowering through a process of fading support.

PubMed

Parker, Brian Corey; Myrick, Florence

2012-07-01

The use of the high-fidelity human patient simulator (HPS)-based clinical scenario in undergraduate nursing education is a powerful learning tool, well suited to modern nursing students' preference for immersive construction of knowledge through the provision of contextually rich reality-based practice and social discourse. The purpose of this study was to explore the social-psychological processes that occur within HPS-based clinical scenarios. Grounded theory method was used to study students and faculty sampled from a Western Canadian baccalaureate nursing program. The process of leveled coding generated a substantive theory that has the potential to enable educators to empower students through the use of fading support, a twofold process composed of adaptive scaffolding and dynamic assessment that challenges students to realistically self-regulate and transform their frame of reference for nursing practice, while limiting the threats that traditional HPS-based curriculum can impose. Copyright 2012, SLACK Incorporated.

Teaching Tectonics to Undergraduates with Web GIS

NASA Astrophysics Data System (ADS)

Anastasio, D. J.; Bodzin, A.; Sahagian, D. L.; Rutzmoser, S.

2013-12-01

Geospatial reasoning skills provide a means for manipulating, interpreting, and explaining structured information and are involved in higher-order cognitive processes that include problem solving and decision-making. Appropriately designed tools, technologies, and curriculum can support spatial learning. We present Web-based visualization and analysis tools developed with Javascript APIs to enhance tectonic curricula while promoting geospatial thinking and scientific inquiry. The Web GIS interface integrates graphics, multimedia, and animations that allow users to explore and discover geospatial patterns that are not easily recognized. Features include a swipe tool that enables users to see underneath layers, query tools useful in exploration of earthquake and volcano data sets, a subduction and elevation profile tool which facilitates visualization between map and cross-sectional views, drafting tools, a location function, and interactive image dragging functionality on the Web GIS. The Web GIS platform is independent and can be implemented on tablets or computers. The GIS tool set enables learners to view, manipulate, and analyze rich data sets from local to global scales, including such data as geology, population, heat flow, land cover, seismic hazards, fault zones, continental boundaries, and elevation using two- and three- dimensional visualization and analytical software. Coverages which allow users to explore plate boundaries and global heat flow processes aided learning in a Lehigh University Earth and environmental science Structural Geology and Tectonics class and are freely available on the Web.

Uninformative contexts support word learning for high-skill spellers.

PubMed

Eskenazi, Michael A; Swischuk, Natascha K; Folk, Jocelyn R; Abraham, Ashley N

2018-04-30

The current study investigated how high-skill spellers and low-skill spellers incidentally learn words during reading. The purpose of the study was to determine whether readers can use uninformative contexts to support word learning after forming a lexical representation for a novel word, consistent with instance-based resonance processes. Previous research has found that uninformative contexts damage word learning; however, there may have been insufficient exposure to informative contexts (only one) prior to exposure to uninformative contexts (Webb, 2007; Webb, 2008). In Experiment 1, participants read sentences with one novel word (i.e., blaph, clurge) embedded in them in three different conditions: Informative (six informative contexts to support word learning), Mixed (three informative contexts followed by three uninformative contexts), and Uninformative (six uninformative contexts). Experiment 2 added a new condition with only three informative contexts to further clarify the conclusions of Experiment 1. Results indicated that uninformative contexts can support word learning, but only for high-skill spellers. Further, when participants learned the spelling of the novel word, they were more likely to learn the meaning of that word. This effect was much larger for high-skill spellers than for low-skill spellers. Results are consistent with the Lexical Quality Hypothesis (LQH) in that high-skill spellers form stronger orthographic representations which support word learning (Perfetti, 2007). Results also support an instance-based resonance process of word learning in that prior informative contexts can be reactivated to support word learning in future contexts (Bolger, Balass, Landen, & Perfetti, 2008; Balass, Nelson, & Perfetti, 2010; Reichle & Perfetti, 2003). (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The Relationships among Group Size, Participation, and Performance of Programming Language Learning Supported with Online Forums

ERIC Educational Resources Information Center

Shaw, Ruey-Shiang

2013-01-01

This study examined the relationships among group size, participation, and learning performance factors when learning a programming language in a computer-supported collaborative learning (CSCL) context. An online forum was used as the CSCL environment for learning the Microsoft ASP.NET programming language. The collaborative-learning experiment…

Using Wikis as a Support and Assessment Tool in Collaborative Digital Game-Based Learning Environments

ERIC Educational Resources Information Center

Samur, Yavuz

2011-01-01

In computer-supported collaborative learning (CSCL) environments, there are many researches done on collaborative learning activities; however, in game-based learning environments, more research and literature on collaborative learning activities are required. Actually, both game-based learning environments and wikis enable us to use new chances…

An Ontology to Support the Classification of Learning Material in an Organizational Learning Environment: An Evaluation

ERIC Educational Resources Information Center

Valaski, Joselaine; Reinehr, Sheila; Malucelli, Andreia

2017-01-01

Purpose: The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a specific knowledge area. Design/methodology/approach: An ontology for recommending learning material was integrated in the organizational learning environment…

Mobile Affordances and Learning Theories in Supporting and Enhancing Learning

ERIC Educational Resources Information Center

MacCallum, Kathryn; Day, Stephanie; Skelton, David; Verhaart, Michael

2017-01-01

Mobile technology promises to enhance and better support students' learning. The exploration and adoption of appropriate pedagogies that enhance learning is crucial for the wider adoption of mobile learning. An increasing number of studies have started to address how existing learning theory can be used to underpin and better frame mobile learning…

Pressurized water reactor flow skirt apparatus

DOEpatents

Kielb, John F.; Schwirian, Richard E.; Lee, Naugab E.; Forsyth, David R.

2016-04-05

A pressurized water reactor vessel having a flow skirt formed from a perforated cylinder structure supported in the lower reactor vessel head at the outlet of the downcomer annulus, that channels the coolant flow through flow holes in the wall of the cylinder structure. The flow skirt is supported at a plurality of circumferentially spaced locations on the lower reactor vessel head that are not equally spaced or vertically aligned with the core barrel attachment points, and the flow skirt employs a unique arrangement of hole patterns that assure a substantially balanced pressure and flow of the coolant over the entire underside of the lower core support plate.

Learning Strategies in Web-Supported Collaborative Project

ERIC Educational Resources Information Center

ChanLin, Lih-Juan

2012-01-01

Web-based learning promotes computer-mediated interaction and student-centred learning in most higher education institutions. To fulfil their academic requirements, students develop appropriate strategies to support learning. Purposes of this study were to: (1) examine the relationship between students study strategies (assessed by Learning and…

Apparatus for measuring fluid flow

DOEpatents

Smith, Jack E.; Thomas, David G.

1984-01-01

Flow measuring apparatus includes a support loop having strain gages mounted thereon and a drag means which is attached to one end of the support loop and which bends the sides of the support loop and induces strains in the strain gages when a flow stream impacts thereon.

Apparatus for measuring fluid flow

DOEpatents

Smith, J.E.; Thomas, D.G.

Flow measuring apparatus includes a support loop having strain gages mounted thereon and a drag means which is attached to one end of the support loop and which bends the sides of the support loop and induces strains in the strain gages when a flow stream impacts thereon.

Evaluation of Algorithms for a Miles-in-Trail Decision Support Tool

NASA Technical Reports Server (NTRS)

Bloem, Michael; Hattaway, David; Bambos, Nicholas

2012-01-01

Four machine learning algorithms were prototyped and evaluated for use in a proposed decision support tool that would assist air traffic managers as they set Miles-in-Trail restrictions. The tool would display probabilities that each possible Miles-in-Trail value should be used in a given situation. The algorithms were evaluated with an expected Miles-in-Trail cost that assumes traffic managers set restrictions based on the tool-suggested probabilities. Basic Support Vector Machine, random forest, and decision tree algorithms were evaluated, as was a softmax regression algorithm that was modified to explicitly reduce the expected Miles-in-Trail cost. The algorithms were evaluated with data from the summer of 2011 for air traffic flows bound to the Newark Liberty International Airport (EWR) over the ARD, PENNS, and SHAFF fixes. The algorithms were provided with 18 input features that describe the weather at EWR, the runway configuration at EWR, the scheduled traffic demand at EWR and the fixes, and other traffic management initiatives in place at EWR. Features describing other traffic management initiatives at EWR and the weather at EWR achieved relatively high information gain scores, indicating that they are the most useful for estimating Miles-in-Trail. In spite of a high variance or over-fitting problem, the decision tree algorithm achieved the lowest expected Miles-in-Trail costs when the algorithms were evaluated using 10-fold cross validation with the summer 2011 data for these air traffic flows.

The cerebellum and visual perceptual learning: evidence from a motion extrapolation task.

PubMed

Deluca, Cristina; Golzar, Ashkan; Santandrea, Elisa; Lo Gerfo, Emanuele; Eštočinová, Jana; Moretto, Giuseppe; Fiaschi, Antonio; Panzeri, Marta; Mariotti, Caterina; Tinazzi, Michele; Chelazzi, Leonardo

2014-09-01

Visual perceptual learning is widely assumed to reflect plastic changes occurring along the cerebro-cortical visual pathways, including at the earliest stages of processing, though increasing evidence indicates that higher-level brain areas are also involved. Here we addressed the possibility that the cerebellum plays an important role in visual perceptual learning. Within the realm of motor control, the cerebellum supports learning of new skills and recalibration of motor commands when movement execution is consistently perturbed (adaptation). Growing evidence indicates that the cerebellum is also involved in cognition and mediates forms of cognitive learning. Therefore, the obvious question arises whether the cerebellum might play a similar role in learning and adaptation within the perceptual domain. We explored a possible deficit in visual perceptual learning (and adaptation) in patients with cerebellar damage using variants of a novel motion extrapolation, psychophysical paradigm. Compared to their age- and gender-matched controls, patients with focal damage to the posterior (but not the anterior) cerebellum showed strongly diminished learning, in terms of both rate and amount of improvement over time. Consistent with a double-dissociation pattern, patients with focal damage to the anterior cerebellum instead showed more severe clinical motor deficits, indicative of a distinct role of the anterior cerebellum in the motor domain. The collected evidence demonstrates that a pure form of slow-incremental visual perceptual learning is crucially dependent on the intact cerebellum, bearing the notion that the human cerebellum acts as a learning device for motor, cognitive and perceptual functions. We interpret the deficit in terms of an inability to fine-tune predictive models of the incoming flow of visual perceptual input over time. Moreover, our results suggest a strong dissociation between the role of different portions of the cerebellum in motor versus non-motor functions, with only the posterior lobe being responsible for learning in the perceptual domain. Copyright © 2014. Published by Elsevier Ltd.

Design requirements, challenges, and solutions for high-temperature falling particle receivers

NASA Astrophysics Data System (ADS)

Christian, Joshua; Ho, Clifford

2016-05-01

Falling particle receivers (FPR) utilize small particles as a heat collecting medium within a cavity receiver structure. Previous analysis for FPR systems include computational fluid dynamics (CFD), analytical evaluations, and experiments to determine the feasibility and achievability of this CSP technology. Sandia National Laboratories has fabricated and tested a 1 MWth FPR that consists of a cavity receiver, top hopper, bottom hopper, support structure, particle elevator, flux target, and instrumentation. Design requirements and inherent challenges were addressed to enable continuous operation of flowing particles under high-flux conditions and particle temperatures over 700 °C. Challenges include being able to withstand extremely high temperatures (up to 1200°C on the walls of the cavity), maintaining particle flow and conveyance, measuring temperatures and mass flow rates, filtering out debris, protecting components from direct flux spillage, and measuring irradiance in the cavity. Each of the major components of the system is separated into design requirements, associated challenges and corresponding solutions. The intent is to provide industry and researchers with lessons learned to avoid pitfalls and technical problems encountered during the development of Sandia's prototype particle receiver system at the National Solar Thermal Test Facility (NSTTF).

Mechanisms and Effects of Transcranial Direct Current Stimulation

PubMed Central

Giordano, James; Bikson, Marom; Kappenman, Emily S.; Clark, Vincent P.; Coslett, H. Branch; Hamblin, Michael R.; Hamilton, Roy; Jankord, Ryan; Kozumbo, Walter J.; McKinley, R. Andrew; Nitsche, Michael A.; Reilly, J. Patrick; Richardson, Jessica; Wurzman, Rachel

2017-01-01

The US Air Force Office of Scientific Research convened a meeting of researchers in the fields of neuroscience, psychology, engineering, and medicine to discuss most pressing issues facing ongoing research in the field of transcranial direct current stimulation (tDCS) and related techniques. In this study, we present opinions prepared by participants of the meeting, focusing on the most promising areas of research, immediate and future goals for the field, and the potential for hormesis theory to inform tDCS research. Scientific, medical, and ethical considerations support the ongoing testing of tDCS in healthy and clinical populations, provided best protocols are used to maximize safety. Notwithstanding the need for ongoing research, promising applications include enhancing vigilance/attention in healthy volunteers, which can accelerate training and support learning. Commonly, tDCS is used as an adjunct to training/rehabilitation tasks with the goal of leftward shift in the learning/treatment effect curves. Although trials are encouraging, elucidating the basic mechanisms of tDCS will accelerate validation and adoption. To this end, biomarkers (eg, clinical neuroimaging and findings from animal models) can support hypotheses linking neurobiological mechanisms and behavioral effects. Dosage can be optimized using computational models of current flow and understanding dose–response. Both biomarkers and dosimetry should guide individualized interventions with the goal of reducing variability. Insights from other applied energy domains, including ionizing radiation, transcranial magnetic stimulation, and low-level laser (light) therapy, can be prudently leveraged. PMID:28210202

Learning Support Centers and International Tutor Training Program Certification: An Interview with Rick A. Sheets

ERIC Educational Resources Information Center

Walker, Luann

2016-01-01

This article presents an interview with Rick A. Sheets, who has been working in learning assistance, faculty training, and technology support for over 30 years. He collaborated with Frank Christ as the co-founder and webmaster of the Learning Support Centers in Higher Education (LSCHE) website, a resource established in 1996 for learning center…

Supporting Self-Regulated Learning in Computer-Based Learning Environments: Systematic Review of Effects of Scaffolding in the Domain of Science Education

ERIC Educational Resources Information Center

Devolder, A.; van Braak, J.; Tondeur, J.

2012-01-01

Despite the widespread assumption that students require scaffolding support for self-regulated learning (SRL) processes in computer-based learning environments (CBLEs), there is little clarity as to which types of scaffolds are most effective. This study offers a literature review covering the various scaffolds that support SRL processes in the…

Parents Supporting Learning: A Non-Intensive Intervention Supporting Literacy and Numeracy in the Home Learning Environment

ERIC Educational Resources Information Center

Niklas, Frank; Cohrssen, Caroline; Tayler, Collette

2016-01-01

In Australia, emphasis in early childhood education policy is placed on the importance of the role of the family as a child's first educator, and finding effective ways to raise the effectiveness of parents in supporting children's learning, development and well-being. International studies demonstrate that the home learning environment (HLE)…

Challenge of Supporting Vocational Learning: Empowering Collaboration in a Scripted 3D Game--How Does Teachers' Real-Time Orchestration Make a Difference?

ERIC Educational Resources Information Center

Hamalainen, Raija; Oksanen, Kimmo

2012-01-01

Along with the development of new technologies, orchestrating computer-supported collaborative learning (CSCL) has become a topic of discussion because new learning spaces challenge teacher to support collaborative learning in new ways. However, despite the optimistic notions of teachers' orchestration in CSCL situations, there are still no…

Support for Learning with Computer Simulations: Giving Hints, Supporting Learning Processes, and Providing Hypotheses.

ERIC Educational Resources Information Center

Njoo, Melanie; de Jong, Ton

This paper contains the results of a study on the importance of discovery learning using computer simulations. The purpose of the study was to identify what constitutes discovery learning and to assess the effects of instructional support measures. College students were observed working with an assignment and a computer simulation in the domain of…

Student Attitudes toward Learning, Level of Pre-Knowledge and Instruction Type in a Computer-Simulation: Effects on Flow Experiences and Perceived Learning Outcomes

ERIC Educational Resources Information Center

Winberg, T. Mikael; Hedman, Leif

2008-01-01

Attitudes toward learning (ATL) have been shown to influence students' learning outcomes. However, there is a lack of knowledge about the ways in which the interaction between ATL, the learning situation, and the level of students' prior knowledge influence affective reactions and conceptual change. In this study, a simulation of acid-base…

Compressive sensing based machine learning strategy for characterizing the flow around a cylinder with limited pressure measurements

NASA Astrophysics Data System (ADS)

Bright, Ido; Lin, Guang; Kutz, J. Nathan

2013-12-01

Compressive sensing is used to determine the flow characteristics around a cylinder (Reynolds number and pressure/flow field) from a sparse number of pressure measurements on the cylinder. Using a supervised machine learning strategy, library elements encoding the dimensionally reduced dynamics are computed for various Reynolds numbers. Convex L1 optimization is then used with a limited number of pressure measurements on the cylinder to reconstruct, or decode, the full pressure field and the resulting flow field around the cylinder. Aside from the highly turbulent regime (large Reynolds number) where only the Reynolds number can be identified, accurate reconstruction of the pressure field and Reynolds number is achieved. The proposed data-driven strategy thus achieves encoding of the fluid dynamics using the L2 norm, and robust decoding (flow field reconstruction) using the sparsity promoting L1 norm.

Flow in E-learning: What Drives It and Why It Matters

ERIC Educational Resources Information Center

Rodríguez-Ardura, Inma; Meseguer-Artola, Antoni

2017-01-01

This paper seeks to explain why some individuals sink further into states of flow than others, and what effects flow has in the context of a virtual education environment. Our findings--gathered from both questionnaire and behavioural data--reveal that flow states are elicited by the e-learners' senses of controlling the virtual education…

Wikis and Collaborative Learning in Higher Education

ERIC Educational Resources Information Center

Zheng, Binbin; Niiya, Melissa; Warschauer, Mark

2015-01-01

While collaborative learning and collaborative writing can be of great value to student learning, the implementation of a technology-supported collaborative learning environment is a challenge. With their built-in features for supporting collaborative writing and social communication, wikis are a promising platform for collaborative learning;…

Go with the Flow: Examining the Effects of Engagement Using Flow Theory and Its Relationship to Achievement and Performance in the 3-Dimensional Virtual Learning Environment of Second Life

ERIC Educational Resources Information Center

Cooper, Karen E.

2009-01-01

Virtual Worlds have become an attractive platform for work, play, and learning. Businesses, including the public sector and academia, are increasingly investing their time, money, and attention to understanding the value of virtual worlds as a productivity tool. For example, educators are leading the way with research in Second Life, one of the…

Information Infrastructure, Information Environments, and Long-Term Collaboration

NASA Astrophysics Data System (ADS)

Baker, K. S.; Pennington, D. D.

2009-12-01

Information infrastructure that supports collaborative science is a complex system of people, organizational arrangements, and tools that require co-management. Contemporary studies are exploring how to establish and characterize effective collaborative information environments. Collaboration depends on the flow of information across the human and technical system components through mechanisms that create linkages, both conceptual and technical. This transcends the need for requirements solicitation and usability studies, highlighting synergistic interactions between humans and technology that can lead to emergence of group level cognitive properties. We consider the ramifications of placing priority on establishing new metaphors and new types of learning environments located near-to-data-origin for the field sciences. In addition to changes in terms of participant engagement, there are implications in terms of innovative contributions to the design of information systems and data exchange. While data integration occurs in the minds of individual participants, it may be facilitated by collaborative thinking and community infrastructure. Existing learning frameworks - from Maslow’s hierarchy of needs to organizational learning - require modification and extension if effective approaches to decentralized information management and systems design are to emerge. Case studies relating to data integration include ecological community projects: development of cross-disciplinary conceptual maps and of a community unit registry.

Collaborative Multimedia Learning: Influence of a Social Regulatory Support on Learning Performance and on Collaboration

ERIC Educational Resources Information Center

Acuña, Santiago Roger; López-Aymes, Gabriela

2016-01-01

This paper analyzes the effects of a support aimed at favoring the social regulatory processes in a computer-supported collaborative learning (CSCL) environment, specifically in a comprehension task of a multimedia text about Psychology of Communication. This support, named RIDE (Saab, van Joolingen, & van Hout-Wolters, 2007; 2012), consists…

Features of Effective Professional Learning: A Case Study of the Implementation of a System-Based Professional Learning Model

ERIC Educational Resources Information Center

Labone, Elizabeth; Long, Janette

2016-01-01

The impact of quality teaching on student learning has led to an increased focus on professional learning to support and improve teacher practice. Review of the literature on effective professional learning suggests six elements that support sustained change in teacher practice; namely, focus, learning components, feedback, collaborative…

Designing Mobile Learning Environments to Support Teacher-Led Field Trips within Informal Learning Environments

ERIC Educational Resources Information Center

Hawkins, Donald S.

2016-01-01

Mobile devices have become increasingly more visible within classrooms and informal learning spaces. The purpose of this dissertation is to examine the impact of mobile learning (m-learning) tools to support student learning during teacher-led field trips. Specifically, the research questions for this study are: (a) What conditions affect student…

Comparison of Machine Learning methods for incipient motion in gravel bed rivers

NASA Astrophysics Data System (ADS)

Valyrakis, Manousos

2013-04-01

Soil erosion and sediment transport of natural gravel bed streams are important processes which affect both the morphology as well as the ecology of earth's surface. For gravel bed rivers at near incipient flow conditions, particle entrainment dynamics are highly intermittent. This contribution reviews the use of modern Machine Learning (ML) methods implemented for short term prediction of entrainment instances of individual grains exposed in fully developed near boundary turbulent flows. Results obtained by network architectures of variable complexity based on two different ML methods namely the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are compared in terms of different error and performance indices, computational efficiency and complexity as well as predictive accuracy and forecast ability. Different model architectures are trained and tested with experimental time series obtained from mobile particle flume experiments. The experimental setup consists of a Laser Doppler Velocimeter (LDV) and a laser optics system, which acquire data for the instantaneous flow and particle response respectively, synchronously. The first is used to record the flow velocity components directly upstream of the test particle, while the later tracks the particle's displacements. The lengthy experimental data sets (millions of data points) are split into the training and validation subsets used to perform the corresponding learning and testing of the models. It is demonstrated that the ANFIS hybrid model, which is based on neural learning and fuzzy inference principles, better predicts the critical flow conditions above which sediment transport is initiated. In addition, it is illustrated that empirical knowledge can be extracted, validating the theoretical assumption that particle ejections occur due to energetic turbulent flow events. Such a tool may find application in management and regulation of stream flows downstream of dams for stream restoration, implementation of sustainable practices in river and estuarine ecosystems and design of stable river bed and banks.

Analysis of student’s scientific attitude behaviour change effects blended learning supported by I-spring Suite 8 application

NASA Astrophysics Data System (ADS)

Budiharti, Rini; Waras, N. S.

2018-05-01

This article aims to describe the student’s scientific attitude behaviour change as treatment effect of Blended Learning supported by I-Spring Suite 8 application on the material balance and the rotational dynamics. Blended Learning models is learning strategy that integrate between face-to-face learning and online learning by combination of various media. Blended Learning model supported I-Spring Suite 8 media setting can direct learning becomes interactive. Students are guided to actively interact with the media as well as with other students to discuss getting the concept by the phenomena or facts presented. The scientific attitude is a natural attitude of students in the learning process. In interactive learning, scientific attitude is so needed. The research was conducted using a model Lesson Study which consists of the stages Plan-Do-Check-Act (PDCA) and applied to the subject of learning is students at class XI MIPA 2 of Senior High School 6 Surakarta. The validity of the data used triangulation techniques of observation, interviews and document review. Based on the discussion, it can be concluded that the use of Blended Learning supported media I-Spring Suite 8 is able to give the effect of changes in student behaviour on all dimensions of scientific attitude that is inquisitive, respect the data or fact, critical thinking, discovery and creativity, open minded and cooperation, and perseverance. Display e-learning media supported student worksheet makes the students enthusiastically started earlier, the core until the end of learning

MoLeNET Mobile Learning Conference 2009: Research Papers

ERIC Educational Resources Information Center

Guy Parker, Ed.

2010-01-01

The Mobile Learning Network (MoLeNET) is a unique collaborative approach to encouraging, supporting, expanding and promoting mobile learning, primarily in English post-14 education and training, via supported shared cost mobile learning projects. Collaboration at national level involves participating institutions and the Learning and Skills…

Supporting Learning from Illustrated Texts: Conceptualizing and Evaluating a Learning Strategy

ERIC Educational Resources Information Center

Schlag, Sabine; Ploetzner, Rolf

2011-01-01

Texts and pictures are often combined in order to improve learning. Many students, however, have difficulty to appropriately process text-picture combinations. We have thus conceptualized a learning strategy which supports learning from illustrated texts. By inducing the processes of information selection, organization, integration, and…

Learning and Language: Supporting Group Work so Group Work Supports Learning

ERIC Educational Resources Information Center

Mylett, Terri; Gluck, Russell

2005-01-01

This paper reports on developments in teaching and learning for first year employment relations students at the University of Wollongong based on creating conditions of learning informed by Vygotsky's "zone of proximal development" theory. Essentially, this meant emphasising collaborative learning (group work) in the lecture theatre and…

A blended learning approach to teaching CVAD care and maintenance.

PubMed

Hainey, Karen; Kelly, Linda J; Green, Audrey

2017-01-26

Nurses working within both acute and primary care settings are required to care for and maintain central venous access devices (CVADs). To support these nurses in practice, a higher education institution and local health board developed and delivered CVAD workshops, which were supported by a workbook and competency portfolio. Following positive evaluation of the workshops, an electronic learning (e-learning) package was also introduced to further support this clinical skill in practice. To ascertain whether this blended learning approach to teaching CVAD care and maintenance prepared nurses for practice, the learning package was evaluated through the use of electronic questionnaires. Results highlighted that the introduction of the e-learning package supported nurses' practice, and increased their confidence around correct clinical procedures.

e-Learning competency for practice nurses: an evaluation report.

PubMed

Heartfield, Marie; Morello, Andrea; Harris, Melanie; Lawn, Sharon; Pols, Vincenza; Stapleton, Carolyn; Battersby, Malcolm

2013-01-01

Practice nurses in Australia are now funded to facilitate chronic condition management, including self-management support. Chronic disease management requires an established rapport, support and proactivity between general practitioners, patients and the practice nurses. To achieve this, training in shared decision making is needed. e-Learning supports delivery and achievement of such policy outcomes, service improvements and skill development. However, e-learning effectiveness for health care professionals' is determined by several organisational, economic, pedagogical and individual factors, with positive e-learning experience linked closely to various supports. This paper reinforces previous studies showing nurses' expanding role across general practice teams and reports on some of the challenges of e-learning. Merely providing practice nurses with necessary information via web-based learning systems does not ensure successful learning or progress toward improving health outcomes for patients.

Transferring learning from faculty development to the classroom.

PubMed

Rock, Kim Z

2014-12-01

This study’s purpose was to better understand the transfer of learning by uncovering how various factors supported the integration of health information technology knowledge and skills gleaned from the Health Resources and Services Administration–funded faculty development programs into nursing education curricula. Through interviews with 20 participants from four programs, this study confirmed the importance of findings related to faculty, program, and work environment characteristics for supporting successful transfer of learning and substantiates a variety of other transfer-of-learning research. New or seldom discussed supportive individual characteristics were found, including leadership abilities, lifelong learning, ability to recognize limitations, persistence, creativity, and risk taking. The importance of networking, diversity of perspectives, postconference support, and teams in program designs were found to positively influence transfer. The variety of supportive factors and barriers in the participants’ work environments strengthens the assertions that transfer may be context dependent. Findings provided insight for recommendations to improve learning transfer. Copyright 2014, SLACK Incorporated.

Shaping Solutions from Learnings in PAIs: A Blueprint

ERIC Educational Resources Information Center

Dosanjh, Nawtej; Jha, Pushkar P.

2016-01-01

Purpose: The paper outlines a portal that facilitates learning through sharing of experiences. This flow is between experience sharers and solution seekers in the domain of poverty alleviation interventions (PAIs). Practitioners working on PAIs are often confined to searching from within "lessons learned" repositories and also from…

Labeled Postings for Asynchronous Interaction

ERIC Educational Resources Information Center

ChanLin, Lih-Juan; Chen, Yong-Ting; Chan, Kung-Chi

2009-01-01

The Internet promotes computer-mediated communications, and so asynchronous learning network systems permit more flexibility in time, space, and interaction than synchronous mode of learning. The key point of asynchronous learning is the materials for web-aided teaching and the flow of knowledge. This research focuses on improving online…

Distributed learning and multi-objectivity in traffic light control

NASA Astrophysics Data System (ADS)

Brys, Tim; Pham, Tong T.; Taylor, Matthew E.

2014-01-01

Traffic jams and suboptimal traffic flows are ubiquitous in modern societies, and they create enormous economic losses each year. Delays at traffic lights alone account for roughly 10% of all delays in US traffic. As most traffic light scheduling systems currently in use are static, set up by human experts rather than being adaptive, the interest in machine learning approaches to this problem has increased in recent years. Reinforcement learning (RL) approaches are often used in these studies, as they require little pre-existing knowledge about traffic flows. Distributed constraint optimisation approaches (DCOP) have also been shown to be successful, but are limited to cases where the traffic flows are known. The distributed coordination of exploration and exploitation (DCEE) framework was recently proposed to introduce learning in the DCOP framework. In this paper, we present a study of DCEE and RL techniques in a complex simulator, illustrating the particular advantages of each, comparing them against standard isolated traffic actuated signals. We analyse how learning and coordination behave under different traffic conditions, and discuss the multi-objective nature of the problem. Finally we evaluate several alternative reward signals in the best performing approach, some of these taking advantage of the correlation between the problem-inherent objectives to improve performance.

Influence of an Integrated Learning Diagnosis and Formative Assessment-Based Personalized Web Learning Approach on Students' Learning Performances and Perceptions

ERIC Educational Resources Information Center

Wongwatkit, Charoenchai; Srisawasdi, Niwat; Hwang, Gwo-Jen; Panjaburee, Patcharin

2017-01-01

The advancement of computer and communication technologies has enabled students to learn across various real-world contexts with supports from the learning system. In the meantime, researchers have emphasized the necessity of providing personalized learning guidance or support by considering individual students' status and needs in order to…

The Impacts of Network Centrality and Self-Regulation on an E-Learning Environment with the Support of Social Network Awareness

ERIC Educational Resources Information Center

Lin, Jian-Wei; Huang, Hsieh-Hong; Chuang, Yuh-Shy

2015-01-01

An e-learning environment that supports social network awareness (SNA) is a highly effective means of increasing peer interaction and assisting student learning by raising awareness of social and learning contexts of peers. Network centrality profoundly impacts student learning in an SNA-related e-learning environment. Additionally,…

Some Thoughts on "Using Learning Progressions to Design Vertical Scales That Support Coherent Inferences about Student Growth"

ERIC Educational Resources Information Center

Kingston, Neal M.; Broaddus, Angela; Lao, Hongling

2015-01-01

Briggs and Peck (2015) have written a thought-provoking article on the use of learning progressions in the design of vertical scales that support inferences about student growth. Organized learning models, including learning trajectories, learning progressions, and learning maps have been the subject of research for many years, but more recently…

Personal Learning Environments, Social Media, and Self-Regulated Learning: A Natural Formula for Connecting Formal and Informal Learning

ERIC Educational Resources Information Center

Dabbagh, Nada; Kitsantas, Anastasia

2012-01-01

A Personal Learning Environment or PLE is a potentially promising pedagogical approach for both integrating formal and informal learning using social media and supporting student self-regulated learning in higher education contexts. The purpose of this paper is to (a) review research that support this claim, (b) conceptualize the connection…

An Adaptive Navigation Support System for Conducting Context-Aware Ubiquitous Learning in Museums

ERIC Educational Resources Information Center

Chiou, Chuang-Kai; Tseng, Judy C. R.; Hwang, Gwo-Jen; Heller, Shelly

2010-01-01

In context-aware ubiquitous learning, students are guided to learn in the real world with personalized supports from the learning system. As the learning resources are realistic objects in the real world, certain physical constraints, such as the limitation of stream of people who visit the same learning object, the time for moving from one object…

Autonomy Supported, Learner-Controlled or System-Controlled Learning in Hypermedia Environments and the Influence of Academic Self-Regulation Style

ERIC Educational Resources Information Center

Gorissen, Chantal J. J.; Kester, Liesbeth; Brand-Gruwel, Saskia; Martens, Rob

2015-01-01

This study focuses on learning in three different hypermedia environments that either support autonomous learning, learner-controlled learning or system-controlled learning and explores the mediating role of academic self-regulation style (ASRS; i.e. a macro level of motivation) on learning. This research was performed to gain more insight in the…

Computer-Supported Collaborative Learning in Higher Education

ERIC Educational Resources Information Center

Roberts, Tim, Ed.

2005-01-01

"Computer-Supported Collaborative Learning in Higher Education" provides a resource for researchers and practitioners in the area of computer-supported collaborative learning (also known as CSCL); particularly those working within a tertiary education environment. It includes articles of relevance to those interested in both theory and practice in…

Mobile and Online Learning Journal: Effects on Apprentices' Reflection in Vocational Education and Training

ERIC Educational Resources Information Center

Mauroux, Laetitia; Könings, Karen D.; Zufferey, Jessica Dehler; Gurtner, Jean-Luc

2014-01-01

While learning journals (LJs) have been shown to support self-regulated learning strategies, reflection and learning outcomes in academic contexts, few studies have investigated their relevance in vocational education. A mobile and online learning journal (MOLJ) was developed to support reflection on workplace experiences. However, acceptance of…

Applying a Framework for Student Modeling in Exploratory Learning Environments: Comparing Data Representation Granularity to Handle Environment Complexity

ERIC Educational Resources Information Center

Fratamico, Lauren; Conati, Cristina; Kardan, Samad; Roll, Ido

2017-01-01

Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments. Thus, providing adaptive support has great potential to help improve student learning with these rich activities. Providing adaptive support requires a…

Evaluating the Acceptability and Usability of EASEL: A Mobile Application That Supports Guided Reflection for Experiential Learning Activities

ERIC Educational Resources Information Center

Schnepp, Jerry; Rogers, Christian

2017-01-01

Aim/Purpose: To examine the early perceptions (acceptability) and usability of EASEL (Education through Application-Supported Experiential Learning), a mobile platform that delivers reflection prompts and content before, during, and after an experiential learning activity. Background: Experiential learning is an active learning approach in which…

Investigating Learning through Work: Learning Environment Scale & User Guide to the Provider. Support Document

ERIC Educational Resources Information Center

Hawke, Geof; Chappell, Clive

2008-01-01

This Support Document was produced by the authors based on their research for the report, "Investigating Learning through Work: The Development of the 'Provider Learning Environment Scale'" (ED503392). It provides readers with a complete copy of the "Provider Learning Environment Scale" (version 2.0); and an accompanying user…

Game-Based Learning in an OpenSim-Supported Virtual Environment on Perceived Motivational Quality of Learning

ERIC Educational Resources Information Center

Kim, Heesung; Ke, Fengfeng; Paek, Insu

2017-01-01

This experimental study was intended to examine whether game-based learning (GBL) that encompasses four particular game characteristics (challenges, a storyline, immediate rewards and the integration of game-play with learning content) in an OpenSimulator-supported virtual reality learning environment can improve perceived motivational quality of…

Flight Systems Integration and Test

NASA Technical Reports Server (NTRS)

Wright, Michael R.

2011-01-01

Topics to be Covered in this presentation are: (1) Integration and Test (I&T) Planning (2) Integration and Test Flows (3) Overview of Typical Mission I&T (4) Supporting Elements (5) Lessons-Learned and Helpful Hints (6) I&T Mishaps and Failures (7) The Lighter Side of I&T and (8) Small-Group Activity. This presentation highlights a typical NASA "in-house" I&T program (1) For flight systems that are developed by NASA at a space flight center (like GSFC) (2) Requirements well-defined: qualification/acceptance, documentation, configuration management. (3) Factors: precedents, human flight, risk-aversion ("failure-phobia"), taxpayer dollars, jobs and (4) Some differences among NASA centers, but generally a resource-intensive process

Quantitative experiments to explain the change of seasons

NASA Astrophysics Data System (ADS)

Testa, Italo; Busarello, Gianni; Puddu, Emanuella; Leccia, Silvio; Merluzzi, Paola; Colantonio, Arturo; Moretti, Maria Ida; Galano, Silvia; Zappia, Alessandro

2015-03-01

The science education literature shows that students have difficulty understanding what causes the seasons. Incorrect explanations are often due to a lack of knowledge about the physical mechanisms underlying this phenomenon. To address this, we present a module in which the students engage in quantitative measurements with a photovoltaic panel to explain changes to the sunray flow on Earth’s surface over the year. The activities also provide examples of energy transfers between the incoming radiation and the environment to introduce basic features of Earth’s climate. The module was evaluated with 45 secondary school students (aged 17-18) and a pre-/post-test research design. Analysis of students’ learning outcomes supports the effectiveness of the proposed activities.

Issues Management Process Course # 38401

DOE Office of Scientific and Technical Information (OSTI.GOV)

Binion, Ula Marie

The purpose of this training it to advise Issues Management Coordinators (IMCs) on the revised Contractor Assurance System (CAS) Issues Management (IM) process. Terminal Objectives: Understand the Laboratory’s IM process; Understand your role in the Laboratory’s IM process. Learning Objectives: Describe the IM process within the context of the CAS; Describe the importance of implementing an institutional IM process at LANL; Describe the process flow for the Laboratory’s IM process; Apply the definition of an issue; Use available resources to determine initial screening risk levels for issues; Describe the required major process steps for each risk level; Describe the personnelmore » responsibilities for IM process implementation; Access available resources to support IM process implementation.« less

The Personal Digital Library (PDL)-based e-learning: Using the PDL as an e-learning support tool

NASA Astrophysics Data System (ADS)

Deng, Xiaozhao; Ruan, Jianhai

The paper describes a support tool for learners engaged in e-learning, the Personal Digital Library (PDL). The characteristics and functionality of the PDL are presented. Suggested steps for constructing and managing a PDL are outlined and discussed briefly. The authors believe that the PDL as a support tool of e-learning will be important and essential in the future.

Supporting Learning through the Use of Self-Reflection Blogs: A Study of the Experience of Blended Learning Students in the United Arab Emirates

ERIC Educational Resources Information Center

Isakovic, Adrienne A.; McNaught, Allan

2013-01-01

This exploratory study seeks to examine how the use of student-written blogs support student learning through the student perspective. The blogs were introduced to provide support in four distinct areas: as a medium for facilitating learning; as a medium for interactivity; as a medium for metacognitive thought and reflection; and as a learning…

Evaluation of the Implementation of Professional Learning Communities and the Impact on Student Achievement

ERIC Educational Resources Information Center

Bostic, Cristi M.

2013-01-01

This dissertation evaluated the implementation of professional learning communities in a large suburban school district in North Carolina. The presence of shared and supportive leadership, shared values and vision, collective learning and application, shared personal practice, supportive conditions for relationships, and supportive conditions for…

Flexibility in Macro-Scripts for Computer-Supported Collaborative Learning

ERIC Educational Resources Information Center

Dillenbourg, P.; Tchounikine, P.

2007-01-01

In the field of computer-supported collaborative learning (CSCL), scripts are designed to support collaboration among distant learners or co-present learners whose interactions are (at least partially) mediated by a computer. The rationale of scripts is to structure collaborative learning processes in order to trigger group interactions that may…

Multiple Mice Based Collaborative One-to-One Learning

ERIC Educational Resources Information Center

Infante, Cristian; Hidalgo, Pedro; Nussbaum, Miguel; Alarcon, Rosa; Gottlieb, Andres

2009-01-01

Exchange is a collaborative learning application, originally developed for wirelessly interconnected Pocket PCs, that provides support for students and a teacher performing a face-to-face computer supported collaborative learning (CSCL) activity in a Single Input/Single Display (SISD) mode. We extend the application to support a single display…

Social Knowledge Awareness Map for Computer Supported Ubiquitous Learning Environment

ERIC Educational Resources Information Center

El-Bishouty, Moushir M.; Ogata, Hiroaki; Rahman, Samia; Yano, Yoneo

2010-01-01

Social networks are helpful for people to solve problems by providing useful information. Therefore, the importance of mobile social software for learning has been supported by many researches. In this research, a model of personalized collaborative ubiquitous learning environment is designed and implemented in order to support learners doing…

A Unified Model of Student Engagement in Classroom Learning and Classroom Learning Environment: One Measure and One Underlying Construct

ERIC Educational Resources Information Center

Cavanagh, Robert F.

2015-01-01

This study employed the capabilities-expectations model of engagement in classroom learning based on bio-ecological frameworks of intellectual development and flow theory. According to the capabilities-expectations model, engagement requires a balance between the capabilities of a student for learning in a particular situation and what is expected…

EGameFlow: A Scale to Measure Learners' Enjoyment of E-Learning Games

ERIC Educational Resources Information Center

Fu, Fong-Ling; Su, Rong-Chang; Yu, Sheng-Chin

2009-01-01

In an effective e-learning game, the learner's enjoyment acts as a catalyst to encourage his/her learning initiative. Therefore, the availability of a scale that effectively measures the enjoyment offered by e-learning games assist the game designer to understanding the strength and flaw of the game efficiently from the learner's points of view.…

Continuous-Flow Left Ventricular Assist Device Support Improves Myocardial Supply:Demand in Chronic Heart Failure.

PubMed

Soucy, Kevin G; Bartoli, Carlo R; Phillips, Dustin; Giridharan, Guruprasad A; Sobieski, Michael A; Wead, William B; Dowling, Robert D; Wu, Zhongjun J; Prabhu, Sumanth D; Slaughter, Mark S; Koenig, Steven C

2017-06-01

Continuous-flow left ventricular assist devices (CF LVADs) are rotary blood pumps that improve mean blood flow, but with potential limitations of non-physiological ventricular volume unloading and diminished vascular pulsatility. In this study, we tested the hypothesis that left ventricular unloading with increasing CF LVAD flow increases myocardial flow normalized to left ventricular work. Healthy (n = 8) and chronic ischemic heart failure (IHF, n = 7) calves were implanted with CF LVADs. Acute hemodynamics and regional myocardial blood flow were measured during baseline (LVAD off, clamped), partial (2-4 L/min) and full (>4 L/min) LVAD support. IHF calves demonstrated greater reduction of cardiac energy demand with increasing LVAD support compared to healthy calves, as calculated by rate-pressure product. Coronary artery flows (p < 0.05) and myocardial blood flow (left ventricle (LV) epicardium and myocardium, p < 0.05) decreased with increasing LVAD support in normal calves. In the IHF model, blood flow to the septum, LV, LV epicardium, and LV myocardium increased significantly with increasing LVAD support when normalized to cardiac energy demand (p < 0.05). In conclusion, myocardial blood flow relative to cardiac demand significantly increased in IHF calves, thereby demonstrating that CF LVAD unloading effectively improves cardiac supply and demand ratio in the setting of ischemic heart failure.

Testing a Conception of How School Leadership Influences Student Learning

ERIC Educational Resources Information Center

Leithwood, Kenneth; Patten, Sarah; Jantzi, Doris

2010-01-01

Purpose: This article describes and reports the results of testing a new conception of how leadership influences student learning ("The Four Paths"). Framework: Leadership influence is conceptualized as flowing along four paths (Rational, Emotions, Organizational, and Family) toward student learning. Each path is populated by multiple…

Constant Change: The Ever-Evolving Personal Learning Environment

ERIC Educational Resources Information Center

Torres Kompen, Ricardo; Monguet, Josep Ma.; Brigos, Miguel

2015-01-01

There are several definitions for the term "personal learning environment" (PLE); in this article, PLE refers to a group of web technologies, with various degrees of integration and interaction, that helps users and learners manage the flow of information that relates to the learning process, the creation of knowledge, and the…

Cage Painting within the Fifth Discipline of Learning Organisations

ERIC Educational Resources Information Center

Rimmington, Glyn M.; Alagic, Mara

2009-01-01

Learning organisations face new challenges in the 21st century. Increased flow of trade in commodities, manufactured goods and information as well as mobility of people have led to increased global interdependence, interconnectedness and cultural diversity. People and teams within learning organisations have become globally distributed with the…

Technology Support for Discussion Based Learning: From Computer Supported Collaborative Learning to the Future of Massive Open Online Courses

ERIC Educational Resources Information Center

Rosé, Carolyn Penstein; Ferschke, Oliver

2016-01-01

This article offers a vision for technology supported collaborative and discussion-based learning at scale. It begins with historical work in the area of tutorial dialogue systems. It traces the history of that area of the field of Artificial Intelligence in Education as it has made an impact on the field of Computer-Supported Collaborative…

How task characteristics and social support relate to managerial learning: empirical evidence from Dutch home care.

PubMed

Ouweneel, A P Else; Taris, Toon W; Van Zolingen, Simone J; Schreurs, Paul J G

2009-01-01

Researchers have revealed that managers profit most from informal and on-the-job learning. Moreover, research has shown that task characteristics and social support affect informal learning. On the basis of these insights, the authors examined the effects of task characteristics (psychological job demands, job control) and social support from the supervisor and colleagues on informal on-the-job learning among 1588 managers in the Dutch home-care sector. A regression analysis revealed that high demands, high control, and high colleague and supervisor support were each associated with high levels of informal learning. The authors found no evidence for statistical interactions among the effects of these concepts. They concluded that to promote managers' informal workplace learning, employers should especially increase job control.

Learning in the tutorial group: a balance between individual freedom and institutional control.

PubMed

McAllister, Anita; Aanstoot, Janna; Hammarström, Inger Lundeborg; Samuelsson, Christina; Johannesson, Eva; Sandström, Karin; Berglind, Ulrika

2014-01-01

The study investigates factors in problem-based learning tutorial groups which promote or inhibit learning. The informants were tutors and students from speech-language pathology and physiotherapy programmes. Semi-structured focus-group interviews and individual interviews were used. Results revealed three themes: Responsibility. Time and Support. Under responsibility, the delicate balance between individual and institutional responsibility and control was shown. Time included short and long-term perspectives on learning. Under support, supporting documents, activities and personnel resources were mentioned. In summary, an increased control by the program and tutors decreases student's motivation to assume responsibility for learning. Support in tutorial groups needs to adapt to student progression and to be well aligned to tutorial work to have the intended effect. A lifelong learning perspective may help students develop a meta-awareness regarding learning that could make tutorial work more meaningful.

Examining Motivational Orientation and Learning Strategies in Computer-Supported Self-Directed Learning (CS-SDL) for Mathematics: The Perspective of Intrinsic and Extrinsic Goals

ERIC Educational Resources Information Center

Lao, Andrew Chan-Chio; Cheng, Hercy N. H.; Huang, Mark C. L.; Ku, Oskar; Chan, Tak-Wai

2017-01-01

One-to-one technology, which allows every student to receive equal access to learning tasks through a personal computing device, has shown increasing potential for self-directed learning in elementary schools. With computer-supported self-directed learning (CS-SDL), students may set their own learning goals through the suggestions of the system…

Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.

PubMed

Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke

2016-01-01

Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned.

Ryan King | NREL

Science.gov Websites

research focuses on optimization and machine learning applied to complex energy systems and turbulent flows techniques to improve wind plant design and controls and developed a new data-driven machine learning closure

Achieving change through mutual development: supported online learning and the evolving roles of health and information professionals.

PubMed

Bury, Rachel; Martin, Lindsey; Roberts, Sue

2006-12-01

Major changes in health care, within an information- and technology-rich age, are impacting significantly on health professionals and upon their education and training. Health information professionals-in both the National Health Service (NHS) and higher education (HE) contexts-are consequently developing their roles, skills and partnerships to meet the needs of flexible education and training. This article explores one facet of this-supported online learning and its impact on role development. A case study approach was taken, aiming to explore how academics, health information professionals and learning technologists are developing supported online learning to explicitly address the e-literacy and information needs of health students within the context of NHS frameworks for education. This was contextualized by a literature review. The case study explores and discusses three dynamics--(i) The use of supported online learning tools by future health-care professionals throughout their professional training to ensure they have the appropriate e-literacy skills; (ii) the use of supported online learning by current health professionals to enable them to adapt to the changing environment; (iii) the development of the health information professional, and particularly their role within multi-disciplinary teams working with learning technologists and health professionals, to enable them to design and deliver supported online learning. The authors argue that, in this specific case study, health information professionals are key to the development of supported online learning. They are working successfully in collaboration and their roles are evolving to encompass learning and teaching activities in a wider context. There are consequently several lessons to be drawn in relation to professional education and role development.

Assessment of (Computer-Supported) Collaborative Learning

ERIC Educational Resources Information Center

Strijbos, J. -W.

2011-01-01

Within the (Computer-Supported) Collaborative Learning (CS)CL research community, there has been an extensive dialogue on theories and perspectives on learning from collaboration, approaches to scaffold (script) the collaborative process, and most recently research methodology. In contrast, the issue of assessment of collaborative learning has…

Social cognitive theory, metacognition, and simulation learning in nursing education.

PubMed

Burke, Helen; Mancuso, Lorraine

2012-10-01

Simulation learning encompasses simple, introductory scenarios requiring response to patients' needs during basic hygienic care and during situations demanding complex decision making. Simulation integrates principles of social cognitive theory (SCT) into an interactive approach to learning that encompasses the core principles of intentionality, forethought, self-reactiveness, and self-reflectiveness. Effective simulation requires an environment conducive to learning and introduces activities that foster symbolic coding operations and mastery of new skills; debriefing builds self-efficacy and supports self-regulation of behavior. Tailoring the level of difficulty to students' mastery level supports successful outcomes and motivation to set higher standards. Mindful selection of simulation complexity and structure matches course learning objectives and supports progressive development of metacognition. Theory-based facilitation of simulated learning optimizes efficacy of this learning method to foster maturation of cognitive processes of SCT, metacognition, and self-directedness. Examples of metacognition that are supported through mindful, theory-based implementation of simulation learning are provided. Copyright 2012, SLACK Incorporated.

Lifelong Learning Organisers: Requirements for Tools for Supporting Episodic and Semantic Learning

ERIC Educational Resources Information Center

Vavoula, Giasemi; Sharples, Mike

2009-01-01

We propose Lifelong Learning Organisers (LLOs) as tools to support the capturing, organisation and retrieval of personal learning experiences, resources and notes, over a range of learning topics, at different times and places. The paper discusses general requirements for the design of LLOs based on findings from a diary-based study of everyday…

Representative Model of the Learning Process in Virtual Spaces Supported by ICT

ERIC Educational Resources Information Center

Capacho, José

2014-01-01

This paper shows the results of research activities for building the representative model of the learning process in virtual spaces (e-Learning). The formal basis of the model are supported in the analysis of models of learning assessment in virtual spaces and specifically in Dembo´s teaching learning model, the systemic approach to evaluating…

Learning to Support Learning Together: An Experience with the Soft Systems Methodology

ERIC Educational Resources Information Center

Sanchez, Adolfo; Mejia, Andres

2008-01-01

An action research approach called soft systems methodology (SSM) was used to foster organisational learning in a school regarding the role of the learning support department within the school and its relation with the normal teaching-learning activities. From an initial situation of lack of coordination as well as mutual misunderstanding and…

Development of a Peer-Assisted Learning Strategy in Computer-Supported Collaborative Learning Environments for Elementary School Students

ERIC Educational Resources Information Center

Tsuei, Mengping

2011-01-01

This study explores the effects of Electronic Peer-Assisted Learning for Kids (EPK), on the quality and development of reading skills, peer interaction and self-concept in elementary students. The EPK methodology uses a well-developed, synchronous computer-supported, collaborative learning system to facilitate students' learning in Chinese. We…

Supporting Case-Based Learning in Information Security with Web-Based Technology

ERIC Educational Resources Information Center

He, Wu; Yuan, Xiaohong; Yang, Li

2013-01-01

Case-based learning has been widely used in many disciplines. As an effective pedagogical method, case-based learning is also being used to support teaching and learning in the domain of information security. In this paper, we demonstrate case-based learning in information security by sharing our experiences in using a case study to teach security…

Analysis of an Interactive Technology Supported Problem-Based Learning STEM Project Using Selected Learning Sciences Interest Areas (SLSIA)

ERIC Educational Resources Information Center

Kumar, David Devraj

2017-01-01

This paper reports an analysis of an interactive technology-supported, problem-based learning (PBL) project in science, technology, engineering and mathematics (STEM) from a Learning Sciences perspective using the Selected Learning Sciences Interest Areas (SLSIA). The SLSIA was adapted from the "What kinds of topics do ISLS [International…

The Effects of Different Computer-Supported Collaboration Scripts on Students' Learning Processes and Outcome in a Simulation-Based Collaborative Learning Environment

ERIC Educational Resources Information Center

Wieland, Kristina

2010-01-01

Students benefit from collaborative learning activities, but they do not automatically reach desired learning outcomes when working together (Fischer, Kollar, Mandl, & Haake, 2007; King, 2007). Learners need instructional support to increase the quality of collaborative processes and individual learning outcomes. The core challenge is to find…

Teaching Verbal Chains Using Flow Diagrams and Texts

ERIC Educational Resources Information Center

Holliday, William G.

1976-01-01

A discussion of the recent diagram and attention theory and research surprisingly suggests that a single flow diagram with instructive questions constitutes an effective learning medium in terms of verbal chaining. (Author)

Deep learning beyond Lefschetz thimbles

NASA Astrophysics Data System (ADS)

Alexandru, Andrei; Bedaque, Paulo F.; Lamm, Henry; Lawrence, Scott

2017-11-01

The generalized thimble method to treat field theories with sign problems requires repeatedly solving the computationally expensive holomorphic flow equations. We present a machine learning technique to bypass this problem. The central idea is to obtain a few field configurations via the flow equations to train a feed-forward neural network. The trained network defines a new manifold of integration which reduces the sign problem and can be rapidly sampled. We present results for the 1 +1 dimensional Thirring model with Wilson fermions on sizable lattices. In addition to the gain in speed, the parametrization of the integration manifold we use avoids the "trapping" of Monte Carlo chains which plagues large-flow calculations, a considerable shortcoming of the previous attempts.

Academic Outcomes among a Sample of Learning Support Community College Students

ERIC Educational Resources Information Center

Skinner, Amy D.

2014-01-01

This research examined the relationship between placement in a learning support college program and subsequent academic outcomes. The sample consisted of 275 entering freshmen students who were enrolled in the Learning Support reading courses in the fall of 2005. Data were collected from the Gordon College Office of Institutional Research. The…

SELF (Supports for Early Learning Foundations): A Non-Directed Model Demonstration Project. Final Report.

ERIC Educational Resources Information Center

Harrison, Holly

This final report describes achievements and activities of Project SELF (Supports for Early Learning Foundations), a federally funded project in New Mexico which developed, evaluated, and replicated an innovative model that provides strategies for early interventionists and families to support early learning foundations. The project identified…

Special Education in General Education Classrooms: Cooperative Teaching Using Supportive Learning Activities.

ERIC Educational Resources Information Center

Johnson, Robin R.; And Others

1995-01-01

Supportive learning activities were implemented in a multiple-baseline time series design across four fifth-grade classrooms to evaluate the effects of a cooperative teaching alternative (supportive learning) on teaching behavior, the behavior and grades of general and special education students, and the opinions of general education teachers.…

Interaction Analysis for Supporting Students' Self-Regulation during Blog-Based CSCL Activities

ERIC Educational Resources Information Center

Michailidis, Nikolaos; Kapravelos, Efstathios; Tsiatsos, Thrasyvoulos

2018-01-01

Self-regulated learning is an important means of supporting students' self-awareness and self-regulation level so as to enhance their motivation and engagement. Interaction Analysis (IA) contributes to this end, and its use in studying learning dynamics involved in asynchronous Computer-Supported Collaborative Learning (CSCL) activities has…

Examining Institutional Support for Student Learning Assessment at Historically Black Colleges and Universities

ERIC Educational Resources Information Center

Overton, Doris Anntoinette

2010-01-01

This study examined institutional support for student learning assessment initiatives at accredited four-year historically Black colleges and universities. Three domains and one construct of institutional support for learning assessment were the foci of this two-part study (i.e., organizational and administrative practices and policies, the…

Different Futures of Adaptive Collaborative Learning Support

ERIC Educational Resources Information Center

Rummel, Nikol; Walker, Erin; Aleven, Vincent

2016-01-01

In this position paper we contrast a Dystopian view of the future of adaptive collaborative learning support (ACLS) with a Utopian scenario that--due to better-designed technology, grounded in research--avoids the pitfalls of the Dystopian version and paints a positive picture of the practice of computer-supported collaborative learning 25 years…

Internal and External Regulation to Support Knowledge Construction and Convergence in Computer Supported Collaborative Learning (CSCL)

ERIC Educational Resources Information Center

Romero, Margarida; Lambropoulos, Niki

2011-01-01

Computer Supported Collaborative Learning (CSCL) activities aim to promote collaborative knowledge construction and convergence. During the CSCL activity, the students should regulate their learning activity, at the individual and collective level. This implies an organisation cost related to the coordination of the activity with the team-mates…

Supporting Distance Learners for Collaborative Problem Solving.

ERIC Educational Resources Information Center

Verdejo, M. F.; Barros, B.; Abad, M. T.

This paper describes a computer-supported environment designed to facilitate distance learning through collaborative problem-solving. The goal is to encourage distance learning students to work together, in order to promote both learning of collaboration and learning through collaboration. Collaboration is defined as working together on a common…

Technology Supported Learning and Teaching: A Staff Perspective

ERIC Educational Resources Information Center

O'Donoghue, John, Ed.

2006-01-01

"Technology Supported Learning and Teaching: A Staff Perspective" presents accounts and case studies of first-hand experience in developing, implementing, or evaluating learning technologies. This book highlights the many areas in which practitioners are attempting to implement learning technologies and reflects themes of current topical interest.…

Wiki-Based Rapid Prototyping for Teaching-Material Design in E-Learning Grids

ERIC Educational Resources Information Center

Shih, Wen-Chung; Tseng, Shian-Shyong; Yang, Chao-Tung

2008-01-01

Grid computing environments with abundant resources can support innovative e-Learning applications, and are promising platforms for e-Learning. To support individualized and adaptive learning, teachers are encouraged to develop various teaching materials according to different requirements. However, traditional methodologies for designing teaching…

Learning across Levels

ERIC Educational Resources Information Center

Stahl, Gerry

2013-01-01

The theme of this year's Computer-Supported Collaborative Learning (CSCL) 2013 conference--"To see the world 'and' a grain of sand: Learning across levels of space, time and scale"--targets a provocative challenge for CSCL, namely that the interactions of collaborative learning be understood, supported and analysed at multiple levels. As the…

Global Learning in England: Baseline Analysis of the Global Learning Programme Whole School Audit 2013-14. Research Paper No. 15 for the Global Learning Programme

ERIC Educational Resources Information Center

Hunt, Frances; Cara, Olga

2015-01-01

The Global Learning Programme in England is an initiative aimed at supporting the teaching and learning of global learning in schools in England at Key Stage 2 and Key Stage 3. It is a five-year national programme of support to schools to enhance their provision of global learning. Specifically, the GLP-E works with teachers to enhance their…

Using large-scale flow experiments to rehabilitate Colorado River ecosystem function in Grand Canyon: Basis for an adaptive climate-resilient strategy: Chapter 17

USGS Publications Warehouse

Melis, Theodore S.; Pine, William E.; Korman, Josh; Yard, Michael D.; Jain, Shaleen; Pulwarty, Roger S.; Miller, Kathleen; Hamlet, Alan F.; Kenney, Douglas S.; Redmond, Kelly T.

2016-01-01

Adaptive management of Glen Canyon Dam is improving downstream resources of the Colorado River in Glen Canyon National Recreation Area and Grand Canyon National Park. The Glen Canyon Dam Adaptive Management Program (AMP), a federal advisory committee of 25 members with diverse special interests tasked to advise the U.S. Department of the Interior), was established in 1997 in response to the 1992 Grand Canyon Protection Act. Adaptive management assumes that ecosystem responses to management policies are inherently complex and unpredictable, but that understanding and management can be improved through monitoring. Best known for its high-flow experiments intended to benefit physical and biological resources by simulating one aspect of pre-dam conditions—floods, the AMP promotes collaboration among tribal, recreation, hydropower, environmental, water and other natural resource management interests. Monitoring has shown that high flow experiments move limited new tributary sand inputs below the dam from the bottom of the Colorado River to shorelines; rebuilding eroded sandbars that support camping areas and other natural and cultural resources. Spring-timed high flows have also been shown to stimulate aquatic productivity by disturbing the river bed below the dam in Glen Canyon. Understanding about how nonnative tailwater rainbow trout (Oncorhynchus mykiss), and downstream endangered humpback chub (Gila cypha) respond to dam operations has also increased, but this learning has mostly posed “surprise” adaptation opportunities to managers. Since reoperation of the dam to Modified Low Fluctuating Flows in 1996, rainbow trout now benefit from more stable daily flows and high spring releases, but possibly at a risk to humpback chub and other native fishes downstream. In contrast, humpback chub have so far proven robust to all flows, and native fish have increased under the combination of warmer river temperatures associated with reduced storage in Lake Powell, and a system-wide reduction in trout from 2000-06, possibly due to several years of natural reproduction under limited food supply. Uncertainties about dam operations and ecosystem responses remain, including how native and nonnative fish will interact and respond to possible increased river temperatures under drier basin conditions. Ongoing assessment of operating policies by the AMP’s diverse stakeholders represents a major commitment to the river’s valued resources, while surprise learning opportunities can also help identify a resilient climate-change strategy for co-managing nonnative and endangered native fish, sandbar habitats and other river resources in a region with already complex and ever-increasing water demands.

Teachers' experiences of teaching in a blended learning environment.

PubMed

Jokinen, Pirkko; Mikkonen, Irma

2013-11-01

This paper considers teachers' experiences of teaching undergraduate nursing students in a blended learning environment. The basic idea of the study programme was to support students to reflect on theory and practice, and provide with access to expert and professional knowledge in real-life problem-solving and decision making. Learning was organised to support learning in and about work: students worked full-time and this provided excellent opportunities for learning both in practice, online and face-to-face sessions. The aim of the study was to describe teachers' experiences of planning and implementing teaching and learning in a blended-learning-based adult nursing programme. The research method was qualitative, and the data were collected by three focus group interviews, each with four to six participants. The data were analysed using qualitative content analysis. The results show that the blended learning environment constructed by the combination of face-to-face learning and learning in practice with technology-mediated learning creates challenges that must be taken into consideration when planning and implementing blended teaching and learning. However, it provides good opportunities to enhance students' learning in and about work. This is because such programmes support student motivation through the presence of "real-life" and their relevance to the students' own places of work. Nevertheless, teachers require knowledge of different pedagogical approaches; they need professional development support in redesigning teaching and learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Effect of Blended Learning and Social Media-Supported Learning on the Students' Attitude and Self-Directed Learning Skills in Science Education

ERIC Educational Resources Information Center

Akgunduz, Devrim; Akinoglu, Orhan

2016-01-01

The main purpose of this study is to investigate the effect of blended learning and social media supported learning on the students' attitude and self-directed learning skills in Science Education. This research took place with the 7th grade 74 students attending to a primary school in Kadikoy, Istanbul and carried out "Our Body Systems"…

A Cybernetic Design Methodology for 'Intelligent' Online Learning Support

NASA Astrophysics Data System (ADS)

Quinton, Stephen R.

The World Wide Web (WWW) provides learners and knowledge workers convenient access to vast stores of information, so much that present methods for refinement of a query or search result are inadequate - there is far too much potentially useful material. The problem often encountered is that users usually do not recognise what may be useful until they have progressed some way through the discovery, learning, and knowledge acquisition process. Additional support is needed to structure and identify potentially relevant information, and to provide constructive feedback. In short, support for learning is needed. The learning envisioned here is not simply the capacity to recall facts or to recognise objects. The focus is on learning that results in the construction of knowledge. Although most online learning platforms are efficient at delivering information, most do not provide tools that support learning as envisaged in this chapter. It is conceivable that Web-based learning environments can incorporate software systems that assist learners to form new associations between concepts and synthesise information to create new knowledge. This chapter details the rationale and theory behind a research study that aims to evolve Web-based learning environments into 'intelligent thinking' systems that respond to natural language human input. Rather than functioning simply as a means of delivering information, it is argued that online learning solutions will 1 day interact directly with students to support their conceptual thinking and cognitive development.

Slowly Shifting a Culture of Teaching in Higher Education: A Case Study of Biology Instructors' Micro-Processes of Collaborative Inquiry into Teaching and Learning

NASA Astrophysics Data System (ADS)

Neuwald, Anuschka

The Vision and Change reports (American Association for the Advancement of Science, 2011, 2013) have identified a need for change in undergraduate biology education, emphasizing student learning of content knowledge and competencies. Missing from this report and larger efforts to improve undergraduate education (Brainard, 2007; Henderson et al., 2011; Sunal et al., 2001) are guidelines for how to support instructors' professional learning to change teaching practices. I am exploring one possible support structure by studying a group of seven biology instructors that are engaged in a collaborative process over two semesters. This process is modeled after Lesson Study (Lewis et al., 2006), a form of cyclical inquiry-based professional learning activities. The purpose of this qualitative case study is to examine the micro-processes of this collaboration and how these micro-processes afford and limit the ability to change one's teaching practices. Wenger's (1998) concept of "community of practice" provides a theoretical framework for data analysis. I view an instructor's professional learning as social and situated, involving negotiation of new meanings, boundaries, and participation as part of an on-going collaboration. Data analysis shows that negotiation of meaning, characterized by friction and dissonance, is a normal part of the micro-processes of collaborative group work. There are three friction points that are intertwined and influence each other: 1) rhythmic ebb and flow of negotiation about a common professional goal for the instructors and a common learning goal for undergraduates in biology, 2) pressure of time to produce an outcome, and 3) grappling with collective agency, authority and capacity. I argue that these friction points are necessary and important for understanding the micro-processes of negotiation in a collaborative process. Furthermore, this study contributes to literature examining how the use of collaborative processes that are often counter-cultural to higher education norms and expectations will likely be necessary for instructional changes shared by educators in higher education (Henderson et al., 2011; Sunal et al., 2011; Wiemann et al., 2010). This case study sheds light on the messiness and hard work of professional learning that is necessary if we are serious about changing teaching practices in higher education.

GeoBus: bringing Earth science learning to secondary schools in the UK

NASA Astrophysics Data System (ADS)

Robinson, Ruth; Roper, Kathryn; Pike, Charlotte

2015-04-01

GeoBus (www.geobus.org.uk) is an educational outreach project that was developed in 2012 by the Department of Earth and Environmental Sciences at the University of St Andrews, and it is sponsored jointly by industry and the UK Research Councils (NERC and EPSRC). The aims of GeoBus are to support the teaching of Earth Science in secondary (middle and high) schools by providing teaching support to schools that have no or little expertise of teaching Earth science, to share the outcomes of new science research and the experiences of young researchers with school pupils, and to provide a bridge between industry, higher education institutions, research councils and schools. Since its launch, GeoBus has visited over 160 different schools across the length and breadth of Scotland. Almost 35,000 pupils will have been involved in experiential Earth science learning activities by April 2015, including many in remote and disadvantaged regions. The challenge with secondary school experiential learning as outreach is that activities need to be completed in either 50 or 80 minutes to fit within the school timetables in the UK, and this can limit the amount of hands-on activities that pupils undertake in one session. However, it is possible to dedicate a whole or half day of linked activities to Earth science learning within the Scotland Curriculum for Excellence, and this provides a long enough period to undertake field work, conduct group projects, or complete more complicated experiments. GeoBus has developed a suite of workshops that all involve experiential learning and are targeted for shorter and longer time slots, and the lessons learned in developing and refining these workshops to maximise the learning achieved will be presented. A key aim of GeoBus is to incorporate research outcomes directly into workshops, and to involve early career researchers in project development. One example that is currently in progress is a set of hydrology workshops that focus on the water cycle, groundwater flow and aqueous geochemistry arising from a 3rd year PhD student's research. One workshop will include some fieldwork which is an important part of the Scottish curriculum, and hydrology provides the ideal platform for pupils to develop their investigative skills, and collect and manipulate field data. Our presentation will provide examples of these hands-on GeoBus activities that introduce basic concepts in hydrology and hydrogeology.

The World Climate Exercise: Is (Simulated) Experience Our Best Teacher?

NASA Astrophysics Data System (ADS)

Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

2015-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

'The challenge to take charge of life with long-term illness': nurses' experiences of supporting patients' learning with the didactic model.

PubMed

Andersson, Susanne; Svanström, Rune; Ek, Kristina; Rosén, Helena; Berglund, Mia

2015-12-01

The aim of this implementation study is to describe nurses' experiences of supporting patient learning using the model called 'The challenge to take charge of life with long-term illness'. Supporting patient learning for those suffering from a long-term illness is a complex art in nursing. Genuine learning occurs at a deep and existential level. If the patient's resistance to illness can be challenged and reflected upon, the patient may take charge of his/her life. The project lasted for 2 years and was initiated by a former patient on an assisted haemodialysis ward and involved 14 registered nurses. The project began with a session to review patients' learning and the didactic model. Monthly reflective meetings and group supervisions were held that focused on the nurses' experiences of supporting patient learning. Notes were written during these reflective meetings and group sessions. Data collected from interviews, notes and written stories were subjected to phenomenological analysis. Three aspects of nurses' experiences of the learning support approach were assessed: To have the courage to listen sincerely, a movement from providing information to supporting learning, and to let the patient indicate the direction. The approach resulted in an increased focus on genuine dialogue and the courage to encourage patients to take charge of their health process. The changes in nurses' approach to learning support reveal that they shift from providing information on the disease, illness and treatment to strengthening and supporting the patient in making decisions and taking responsibility. For nurses, the change entails accepting the patient's goals and regarding their own role as supportive rather than controlling. The didactic model and involved supervision contributed to the change in the nurses' approach. The didactic model might be useful in caring for persons with long-term illness, making the care more person-centred and enhancing the patient's self-care ability. © 2015 John Wiley & Sons Ltd.

The effects of different learning environments on students' motivation for learning and their achievement.

PubMed

Baeten, Marlies; Dochy, Filip; Struyven, Katrien

2013-09-01

Research in higher education on the effects of student-centred versus lecture-based learning environments generally does not take into account the psychological need support provided in these learning environments. From a self-determination theory perspective, need support is important to study because it has been associated with benefits such as autonomous motivation and achievement. The purpose of the study is to investigate the effects of different learning environments on students' motivation for learning and achievement, while taking into account the perceived need support. First-year student teachers (N= 1,098) studying a child development course completed questionnaires assessing motivation and perceived need support. In addition, a prior knowledge test and case-based assessment were administered. A quasi-experimental pre-test/post-test design was set up consisting of four learning environments: (1) lectures, (2) case-based learning (CBL), (3) alternation of lectures and CBL, and (4) gradual implementation with lectures making way for CBL. Autonomous motivation and achievement were higher in the gradually implemented CBL environment, compared to the CBL environment. Concerning achievement, two additional effects were found; students in the lecture-based learning environment scored higher than students in the CBL environment, and students in the gradually implemented CBL environment scored higher than students in the alternated learning environment. Additionally, perceived need support was positively related to autonomous motivation, and negatively to controlled motivation. The study shows the importance of gradually introducing students to CBL, in terms of their autonomous motivation and achievement. Moreover, the study emphasizes the importance of perceived need support for students' motivation. © 2012 The British Psychological Society.

GP supervisors' experience in supporting self-regulated learning: a balancing act.

PubMed

Sagasser, Margaretha H; Kramer, Anneke W M; van Weel, Chris; van der Vleuten, Cees P M

2015-08-01

Self-regulated learning is essential for professional development and lifelong learning. As self-regulated learning has many inaccuracies, the need to support self-regulated learning has been recommended. Supervisors can provide such support. In a prior study trainees reported on the variation in received supervisor support. This study aims at exploring supervisors' perspectives. The aim is to explore how supervisors experience self-regulated learning of postgraduate general practitioners (GP) trainees and their role in this, and what helps and hinders them in supervising. In a qualitative study using a phenomenological approach, we interviewed 20 supervisors of first- and third-year postgraduate GP trainees. Supervisors recognised trainee activity in self-regulated learning and adapted their coaching style to trainee needs, occasionally causing conflicting emotions. Supervisors' beliefs regarding their role, trainees' role and the usefulness of educational interventions influenced their support. Supervisors experienced a relation between patient safety, self-regulated learning and trainee capability to learn. Supervisor training was helpful to exchange experience and obtain advice. Supervisors found colleagues helpful in sharing supervision tasks or in calibrating judgments of trainees. Busy practice occasionally hindered the supervisory process. In conclusion, supervisors adapt their coaching to trainees' self-regulated learning, sometimes causing conflicting emotions. Patient safety and entrustment are key aspects of the supervisory process. Supervisors' beliefs about their role and trainees' role influence their support. Supervisor training is important to increase awareness of these beliefs and the influence on their behaviour, and to improve the use of educational instruments. The results align with findings from other (medical) education, thereby illustrating its relevance.

Ice Flows: A Game-based Learning approach to Science Communication

NASA Astrophysics Data System (ADS)

Le Brocq, Anne

2017-04-01

Game-based learning allows people to become immersed in an environment, and learn how the system functions and responds to change through playing a game. Science and gaming share a similar characteristic: they both involve learning and understanding the rules of the environment you are in, in order to achieve your objective. I will share experiences of developing and using the educational game "Ice Flows" for science communication. The game tasks the player with getting a penguin to its destination, through controlling the size of the ice sheet via ocean temperature and snowfall. Therefore, the game aims to educate the user about the environmental controls on the behaviour of the ice sheet, whilst they are enjoying playing a game with penguins. The game was funded by a NERC Large Grant entitled "Ice shelves in a warming world: Filchner Ice Shelf system, Antarctica", so uses data from the Weddell Sea sector of the West Antarctic Ice Sheet to generate unique levels. The game will be easily expandable to other regions of Antarctica and beyond, with the ultimate aim of giving a full understanding to the user of different ice flow regimes across the planet.

A baker's dozen of new particle flows for nonlinear filters, Bayesian decisions and transport

NASA Astrophysics Data System (ADS)

Daum, Fred; Huang, Jim

2015-05-01

We describe a baker's dozen of new particle flows to compute Bayes' rule for nonlinear filters, Bayesian decisions and learning as well as transport. Several of these new flows were inspired by transport theory, but others were inspired by physics or statistics or Markov chain Monte Carlo methods.

Building Common Ground for Environmental Flows using Traditional Techniques and Novel Engagement Approaches.

PubMed

Mott Lacroix, Kelly E; Xiu, Brittany C; Megdal, Sharon B

2016-04-01

Despite increased understanding of the science of environmental flows, identification and implementation of effective environmental flow policies remains elusive. Perhaps the greatest barrier to implementing flow policies is the framework for water management. An alternative management approach is needed when legal rights for environmental flows do not exist, or are ineffective at protecting ecosystems. The research presented here, conducted in the U.S. state of Arizona, provides an empirical example of engagement to promote social learning as an approach to finding ways to provide water for the environment where legal rights for environmental flows are inadequate. Based on our engagement process we propose that identifying and then building common ground require attention to the process of analyzing qualitative data and the methods for displaying complex information, two aspects not frequently discussed in the social learning or stakeholder engagement literature. The results and methods from this study can help communities develop an engagement process that will find and build common ground, increase stakeholder involvement, and identify innovative solutions to provide water for the environment that reflect the concerns of current water users.

Shifting the Balance in First-Year Learning Support: From Staff Instruction to Peer-Learning Primacy

ERIC Educational Resources Information Center

van der Meer, Jacques; Scott, Carole

2008-01-01

Effective response to the learning needs of first-year students is a contested issue. In many learning support centres the dominant approach to developing student learning skills is through generic or tailored workshops and/or individual consultations. Although there is a place for these activities, we argue that the balance should be shifted…

The Impact of Supported and Annotated Mobile Learning on Achievement and Cognitive Load

ERIC Educational Resources Information Center

Shadiev, Rustam; Hwang, Wu-Yuin; Huang, Yueh-Min; Liu, Tzu-Yu

2015-01-01

We designed activities for learning English as a foreign language in a mobile learning environment with familiar authentic support for this study. Students learned at school and then applied their newly gained knowledge to solve daily life problems by first using a tablet to take pictures of objects they wished to learn about, then describing them…

Parental Support and Enjoyment of Learning in Mathematics: Does Change in Parental Support Predict Change in Enjoyment of Learning?

ERIC Educational Resources Information Center

Buff, Alex; Reusser, Kurt; Dinkelmann, Iris

2017-01-01

Positive and negative emotions are ubiquitous in everyday school life, and can foster or impair processes of learning and achievement. However, learning- and achievement-related emotions are not based solely on experiences from respective situations in the school context. Rather, experiences outside of school, e.g. learning at home, are also…

Examining the Roles of Blended Learning Approaches in Computer-Supported Collaborative Learning (CSCL) Environments: A Delphi Study

ERIC Educational Resources Information Center

So, Hyo-Jeong; Bonk, Curtis J.

2010-01-01

In this study, a Delphi method was used to identify and predict the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments. The Delphi panel consisted of experts in online learning from different geographic regions of the world. This study discusses findings related to (a) pros and cons of blended…

The Soft-Skills Learning Triangle: A Learning Model for Supporting Online Management & Leadership Development

ERIC Educational Resources Information Center

Adams, Jean

2010-01-01

The purpose of this paper is to present the Soft-skills Learning Triangle (SLT)--a model created to help coaches, mentors, and educators understand how web-technologies can be used to support management learning and soft-skills development. SLT emerged as part of a larger action-learning research project--the NewMindsets Management Education…

Digital Systems Supporting Cognition and Exploratory Learning in Twenty-First Century: Guest Editorial

ERIC Educational Resources Information Center

Spector, J. Michael; Ifenthaler, Dirk; Sampson, Demetrios G.

2016-01-01

Digital systems and digital technologies are globally investigated for their potential to transform learning, teaching and assessment towards offering unique learning experiences to the twenty-first century learners. This Special Issue on "Digital systems supporting cognition and exploratory learning in twenty-first century" aims to…

Adaptive Units of Learning and Educational Videogames

ERIC Educational Resources Information Center

Moreno-Ger, Pablo; Thomas, Pilar Sancho; Martinez-Ortiz, Ivan; Sierra, Jose Luis; Fernandez-Manjon, Baltasar

2007-01-01

In this paper, we propose three different ways of using IMS Learning Design to support online adaptive learning modules that include educational videogames. The first approach relies on IMS LD to support adaptation procedures where the educational games are considered as Learning Objects. These games can be included instead of traditional content…

841 Square Miles of Commitment: Districtwide Plan Makes Professional Learning a Priority

ERIC Educational Resources Information Center

Slabine, Nancy Ames

2012-01-01

Without adequate time and resources, it is impossible for school districts and schools to support professional learning that leads to effective teaching practices, supportive leadership, and improved student results. That's why one of the seven new standards in Learning Forward's Standards for Professional Learning focuses specifically on…

Digital Game-Based Learning Supports Student Motivation, Cognitive Success, and Performance Outcomes

ERIC Educational Resources Information Center

Woo, Jeng-Chung

2014-01-01

Traditional multimedia learning is primarily based on the cognitive load concept of information processing theory. Recent digital game-based learning (DGBL) studies have focused on exploring content support for learning motivation and related game characteristics. Motivation, volition, and performance (MVP) theory indicates that cognitive load and…

Supporting Adaptive Learning Pathways through the Use of Learning Analytics: Developments, Challenges and Future Opportunities

ERIC Educational Resources Information Center

Mavroudi, Anna; Giannakos, Michail; Krogstie, John

2018-01-01

Learning Analytics (LA) and adaptive learning are inextricably linked since they both foster technology-supported learner-centred education. This study identifies developments focusing on their interplay and emphasises insufficiently investigated directions which display a higher innovation potential. Twenty-one peer-reviewed studies are…

Supporting and Evaluating Transitional Learning for International University Students

ERIC Educational Resources Information Center

Owens, Alison

2011-01-01

In 2007, as part of its response to the continuing diversification of students, Central Queensland University introduced a for-credit undergraduate course, "The Principles of University Learning", focusing on "learning to learn" in the Australian university context. The aim was to support the transition of learners with diverse…

Operating Characteristics of the Implicit Learning System Supporting Serial Interception Sequence Learning

ERIC Educational Resources Information Center

Sanchez, Daniel J.; Reber, Paul J.

2012-01-01

The memory system that supports implicit perceptual-motor sequence learning relies on brain regions that operate separately from the explicit, medial temporal lobe memory system. The implicit learning system therefore likely has distinct operating characteristics and information processing constraints. To attempt to identify the limits of the…

Lifting the Status of Learning Support Teachers

ERIC Educational Resources Information Center

Kusuma-Powell, Ochan; Powell, William

2016-01-01

Status, the perception of one's standing in relation to others in a group, negatively influence learning. Status issue have implications for educating students with special learning needs: Both these students and the learning support or special education teachers who serve them often hold low status in a school community. Like adults, children…

Mobile Adaptive Communication Support for Vocabulary Acquisition

ERIC Educational Resources Information Center

Epp, Carrie Demmans

2014-01-01

This work explores the use of an adaptive mobile tool for language learning. A school-based deployment study showed that the tool supported learning. A second study is being conducted in informal learning environments. Current work focuses on building models that increase our understanding of the relationship between application usage and learning.

Factors Affecting M-Learners' Course Satisfaction and Learning Persistence

ERIC Educational Resources Information Center

Joo, Young Ju; Joung, Sunyoung; Lim, Eugene; Kim, Hae Jin

2014-01-01

This study investigated whether college students' self-efficacy, level of learning strategy use, academic burnout, and school support predict course satisfaction and learning persistence. To this end, self-efficacy, level of learning strategy use, academic burnout, and school support were used as prediction variables, and course satisfaction and…

The Dynamics of Flowing Waters.

ERIC Educational Resources Information Center

Mattingly, Rosanna L.

1987-01-01

Describes a series of activities designed to help students understand the dynamics of flowing water. Includes investigations into determining water discharge, calculating variable velocities, utilizing flood formulas, graphing stream profiles, and learning about the water cycle. (TW)

The Design of Immersive English Learning Environment Using Augmented Reality

ERIC Educational Resources Information Center

Li, Kuo-Chen; Chen, Cheng-Ting; Cheng, Shein-Yung; Tsai, Chung-Wei

2016-01-01

The study uses augmented reality (AR) technology to integrate virtual objects into the real learning environment for language learning. The English AR classroom is constructed using the system prototyping method and evaluated by semi-structured in-depth interviews. According to the flow theory by Csikszenmihalyi in 1975 along with the immersive…

The Effect of Simulation Games on the Learning of Computational Problem Solving

ERIC Educational Resources Information Center

Liu, Chen-Chung; Cheng, Yuan-Bang; Huang, Chia-Wen

2011-01-01

Simulation games are now increasingly applied to many subject domains as they allow students to engage in discovery processes, and may facilitate a flow learning experience. However, the relationship between learning experiences and problem solving strategies in simulation games still remains unclear in the literature. This study, thus, analyzed…

Closed Circuit? Flow, Influence and the Liquid Management of Learning and Skills

ERIC Educational Resources Information Center

Beighton, Christian

2017-01-01

A new discourse is being deployed by the English learning and skills sector's new professional body, the Education and Training Foundation (ETF). This discourse repositions learning within a specific vision of corporate expectations. With a focus on deregulation in the sector and employer engagement, this repositioning deploys the terminology and…

Creating Electronic Learning Environments: Games, Flow, and the User Interface.

ERIC Educational Resources Information Center

Jones, Marshall G.

A difficult task in creating rich, exploratory interactive learning environments is building an environment that is truly engaging. Engagement can be defined as the nexus of intrinsic knowledge and/or interest and external stimuli that promote the initial interest in, and continued use of a computer-based learning environment. Complete and total…

A Structural Equation Model of Predictors of Online Learning Retention

ERIC Educational Resources Information Center

Lee, Youngju; Choi, Jaeho

2013-01-01

This study examined the effects of internal academic locus of control (ALOC), learning strategies, flow experience, and student satisfaction on student retention in online learning courses. A total number of 282 adult students at the Korea National Open University participated in the study by completing an online survey adopted from previous…

Visual Perspectives within Educational Computer Games: Effects on Presence and Flow within Virtual Immersive Learning Environments

ERIC Educational Resources Information Center

Scoresby, Jon; Shelton, Brett E.

2011-01-01

The mis-categorizing of cognitive states involved in learning within virtual environments has complicated instructional technology research. Further, most educational computer game research does not account for how learning activity is influenced by factors of game content and differences in viewing perspectives. This study is a qualitative…

Optimization of the axial compressor flow passage to reduce the circumferential distortion

NASA Astrophysics Data System (ADS)

Popov, G.; Kolmakova, D.; Shklovets, A.; Ermakov, A.

2015-08-01

This work is motivated by the necessity to reduce the effects of the flow circumferential distortion in the flow passage of the aircraft gas turbine engine (GTE). In previous research, the authors have proposed the approaches to decrease of the flow circumferential distortion arising from the mid-support racks of GTE compressor and having a negative impact on the blade rows, located upstream. In particular, the idea of introducing the circumferentially non-uniform blade pitch and profile stagger angle of guide vanes located in front of the support was contributed in order to redistribute the flow and decrease the dynamic stresses in the rotor wheel of the same stage. During the research presented in this paper, another principal of reduction of the flow circumferential distortion was chosen. Firstly, the variants of upgrading the existing support racks were found. Secondly, the new design of support was offered. Both the first and the second version of the support design variation took into account the availability of technological and structural limitations associated with the location of oil pipes, springs and others elements in the support racks. Investigations of modified design showed that the support with altered racks provides a reduction of dynamic stresses by 20% at resonance with the most dangerous harmonic, and the new design of support can give the decrease of 30%.

Choroidal microcirculation in patients with rotary cardiac assist device.

PubMed

Polska, Elzbieta; Schima, Heinrich; Wieselthaler, Georg; Schmetterer, Leopold

2007-06-01

In recent years, fully implanted rotary blood pumps have been used for long-term cardiac assist in patients with end-stage heart failure. With these pumps, the pulsatility of arterial blood flow and arterial pressure pulse is considerably reduced. Effects on end-organ perfusion, particularly microcirculation, have been assessed. The ocular choroid offers a unique opportunity to study the pulsatile component of blood flow by measurement of fundus pulsation amplitude (FPA) as well as the microcirculation by laser Doppler flowmetry. Both techniques were applied in three male patients with rotary pumps (MicroMed DeBakey VAD), in whom pump velocity was adjusted to four levels of flow between individual minimal need and maximal support. In addition, blood flow velocities in the ophthalmic artery (peak, end-diastolic and mean flow velocity--PSV, EDV and MFV, respectively) were measured using color Doppler imaging. Systolic blood pressure increased by 6 to 22 mm Hg with increasing support. At maximal support FPA was reduced by -60% to -52% as compared with minimal pump support. Blood flow in the choroidal microvasculature, however, did not show relevant changes. A reduction in PSV (-31%, range -47% to -21%) and a pronounced rise in EDV (+93%, range +28% to +147%) was observed, whereas MFV was independent of pump flow. Our data indicate that mean choroidal blood flow is maintained when pump support is varied within therapeutic values, whereas the ratio of pulsatile to non-pulsatile choroidal flow changes. This study shows that, in patients with ventricular assist devices, a normal perfusion rate in the ocular microcirculation is maintained over a wide range of support conditions.

Comparing brain activity patterns during spontaneous exploratory and cue-instructed learning using single photon-emission computed tomography (SPECT) imaging of regional cerebral blood flow in freely behaving rats.

PubMed

Mannewitz, A; Bock, J; Kreitz, S; Hess, A; Goldschmidt, J; Scheich, H; Braun, Katharina

2018-05-01

Learning can be categorized into cue-instructed and spontaneous learning types; however, so far, there is no detailed comparative analysis of specific brain pathways involved in these learning types. The aim of this study was to compare brain activity patterns during these learning tasks using the in vivo imaging technique of single photon-emission computed tomography (SPECT) of regional cerebral blood flow (rCBF). During spontaneous exploratory learning, higher levels of rCBF compared to cue-instructed learning were observed in motor control regions, including specific subregions of the motor cortex and the striatum, as well as in regions of sensory pathways including olfactory, somatosensory, and visual modalities. In addition, elevated activity was found in limbic areas, including specific subregions of the hippocampal formation, the amygdala, and the insula. The main difference between the two learning paradigms analyzed in this study was the higher rCBF observed in prefrontal cortical regions during cue-instructed learning when compared to spontaneous learning. Higher rCBF during cue-instructed learning was also observed in the anterior insular cortex and in limbic areas, including the ectorhinal and entorhinal cortexes, subregions of the hippocampus, subnuclei of the amygdala, and the septum. Many of the rCBF changes showed hemispheric lateralization. Taken together, our study is the first to compare partly lateralized brain activity patterns during two different types of learning.

The Effects of a Concept Map-Based Support Tool on Simulation-Based Inquiry Learning

ERIC Educational Resources Information Center

Hagemans, Mieke G.; van der Meij, Hans; de Jong, Ton

2013-01-01

Students often need support to optimize their learning in inquiry learning environments. In 2 studies, we investigated the effects of adding concept-map-based support to a simulation-based inquiry environment on kinematics. The concept map displayed the main domain concepts and their relations, while dynamic color coding of the concepts displayed…

The Relationship between Social-Emotional Learning Ability and Perceived Social Support in Gifted Students

ERIC Educational Resources Information Center

Ogurlu, Üzeyir; Sevgi-Yalin, Hatun; Yavuz-Birben, Fazilet

2018-01-01

This study aimed to examine the relationship between social-emotional learning skills and perceived social support of gifted students. Based on this relationship, the authors also examined to what extent social and emotional learning skills were predictive of social support. In addition, gender variables were compared in social and emotional…

Understanding Evaluation of Learning Support in Mathematics and Statistics

ERIC Educational Resources Information Center

MacGillivray, Helen; Croft, Tony

2011-01-01

With rapid and continuing growth of learning support initiatives in mathematics and statistics found in many parts of the world, and with the likelihood that this trend will continue, there is a need to ensure that robust and coherent measures are in place to evaluate the effectiveness of these initiatives. The nature of learning support brings…

Special Educational Needs in Mainstream Secondary School Physical Education: Learning Support Assistants Have Their Say

ERIC Educational Resources Information Center

Maher, Anthony John

2016-01-01

Learning support assistants (LSAs) gained more political and academic attention in Britain after Estelle Morris announced that schools of the future would include more trained staff to support learning to higher standards. LSAs, thus, should form an integral part of the culture of all school departments in Britain, including physical education…

Technology Trends in Mobile Computer Supported Collaborative Learning in Elementary Education from 2009 to 2014

ERIC Educational Resources Information Center

Carapina, Mia; Boticki, Ivica

2015-01-01

This paper analyses mobile computer supported collaborative learning in elementary education worldwide focusing on technology trends for the period from 2009 to 2014. The results present representation of device types used to support collaborative activities, their distribution per users (1:1 or 1:m) and if students are learning through or around…

Professional Vision of Classroom Management and Learning Support in Science Classrooms--Does Professional Vision Differ across General and Content-Specific Classroom Interactions?

ERIC Educational Resources Information Center

Steffensky, Mirjam; Gold, Bernadette; Holdynski, Manfred; Möller, Kornelia

2015-01-01

The present study investigates the internal structure of professional vision of in-service teachers and student teachers with respect to classroom management and learning support in primary science lessons. Classroom management (including monitoring, managing momentum, and rules and routines) and learning support (including cognitive activation…

Supporting Doctoral Students through the Personalisation of a Graduate Virtual Research Environment

ERIC Educational Resources Information Center

Costello, Robert

2016-01-01

This paper offers a case study in which a traditional Learning Management System (LMS) was enhanced through learning theories and web-based technologies to support the development of doctoral students. The model being used here, can address and support a personalised learning approach to assist postgraduate students, as part of matching their…

Motivation, Stress and Learning Support Assistants: An Examination of Staff Perceptions at a Rural Secondary School

ERIC Educational Resources Information Center

Hammett, Neil; Burton, Neil

2005-01-01

The context of this study is an "improving" 11?18 secondary school in a small English market town, where the role of Learning Support Assistants (LSAs) is being developed as prime supporters of the renewed emphasis on improving teaching and learning processes. National initiatives, including the teachers workload agreement and national…

Learning Support Policy for Mathematics in Irish Primary Schools: Equal Access but Unequal Needs

ERIC Educational Resources Information Center

Travers, Joseph

2010-01-01

This paper critiques learning-support policy for mathematics in Irish primary schools. The key policy question addressed is how equitable the development of the learning-support service has been in addressing low achievement in mathematics in designated schools compared to non-designated schools. The core argument developed is that there is a link…

Student Success Rate in Online Learning Support Classes Compared to Traditional Classes

ERIC Educational Resources Information Center

Pope, Holly

2013-01-01

West Georgia Technical College (WGTC) did not offer online learning support courses and was losing students to other colleges that offered those courses online. Adding to this problem, online learning support class sections were not being added without sufficient proof that students could receive the same level of education in an online section as…

Designing Computer-Supported Collaborative Learning at Work for Rural It Workers: Learning Ensembles and Geographic Isolation

ERIC Educational Resources Information Center

Goggins, Sean P.

2014-01-01

This paper presents the results of a 9-month ethnographic and action research study of rural technology workers where computer support for collaborative learning through workplace technologies was introduced to a US-based technology firm. Throughout the implementation of this support and participation, issues related to geographic isolation are…

Instructional Theory for Using a Class Wiki to Support Collaborative Learning in Higher Education

ERIC Educational Resources Information Center

Lin, Chun-Yi

2013-01-01

The purpose of this study was to develop an instructional theory for using a class wiki to support collaborative learning in higher education. Although wikis have been identified in theory as one of the most powerful emerging technologies to support collaborative learning, challenges have been revealed in a number of studies regarding student…

Mobile Apps to Support and Assess Foreign Language Learning

ERIC Educational Resources Information Center

Berns, Anke; Palomo-Duarte, Manuel; Dodero, Juan Manuel; Ruiz-Ladrón, Juan Miguel; Márquez, Andrea Calderón

2015-01-01

In the last two decades there have been many attempts to integrate all kinds of mobile devices and apps to support formal as well as informal learning processes. However, most of the available apps still support mainly individual learning, using mobile devices to deliver content rather than providing learners with the opportunity to interact with…

ICT-Supported Learning for Inclusion of People with Special Needs: Review of Seven Educational Technology Journals, 1970-2011

ERIC Educational Resources Information Center

Istenic Starcic, Andreja; Bagon, Spela

2014-01-01

Research and development of information and communication technology (ICT)-supported learning for people with disabilities has not received adequate attention. It is also difficult to access research findings and developments in this field. Under the ENABLE Network of ICT Supported Learning for Disabled People (2011-2014) project, an emerging…

Evaluating the Impact of Instructional Support Using Data Mining and Process Mining: A Micro-Level Analysis of the Effectiveness of Metacognitive Prompts

ERIC Educational Resources Information Center

Sonnenberg, Christoph; Bannert, Maria

2016-01-01

In computer-supported learning environments, the deployment of self-regulatory skills represents an essential prerequisite for successful learning. Metacognitive prompts are a promising type of instructional support to activate students' strategic learning activities. However, despite positive effects in previous studies, there are still a large…

Learning Support and Academic Achievement among Malaysian Adolescents: The Mediating Role of Student Engagement

ERIC Educational Resources Information Center

Jelas, Zalizan M.; Azman, Norzaini; Zulnaidi, Hutkemri; Ahmad, Nor Aniza

2016-01-01

The aim of this study was to examine the associations between learning support, student engagement and academic achievement among adolescents. We also examined the extent to which affective, behavioural and cognitive engagement play a mediating role in students' perceived learning support from parents, teachers and peers, and contribute to their…

Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia.

PubMed

Ansari, Mozafar; Othman, Faridah; Abunama, Taher; El-Shafie, Ahmed

2018-04-01

The function of a sewage treatment plant is to treat the sewage to acceptable standards before being discharged into the receiving waters. To design and operate such plants, it is necessary to measure and predict the influent flow rate. In this research, the influent flow rate of a sewage treatment plant (STP) was modelled and predicted by autoregressive integrated moving average (ARIMA), nonlinear autoregressive network (NAR) and support vector machine (SVM) regression time series algorithms. To evaluate the models' accuracy, the root mean square error (RMSE) and coefficient of determination (R 2 ) were calculated as initial assessment measures, while relative error (RE), peak flow criterion (PFC) and low flow criterion (LFC) were calculated as final evaluation measures to demonstrate the detailed accuracy of the selected models. An integrated model was developed based on the individual models' prediction ability for low, average and peak flow. An initial assessment of the results showed that the ARIMA model was the least accurate and the NAR model was the most accurate. The RE results also prove that the SVM model's frequency of errors above 10% or below - 10% was greater than the NAR model's. The influent was also forecasted up to 44 weeks ahead by both models. The graphical results indicate that the NAR model made better predictions than the SVM model. The final evaluation of NAR and SVM demonstrated that SVM made better predictions at peak flow and NAR fit well for low and average inflow ranges. The integrated model developed includes the NAR model for low and average influent and the SVM model for peak inflow.

Permaculture in higher education: Teaching sustainability through action learning

NASA Astrophysics Data System (ADS)

Battisti, Bryce Thomas

This is a case study of the use of Action Learning (AL) theory to teach and confer degrees in Permaculture and other forms of sustainability at the newly formed Gaia University International (GUI). In Chapter Two I argue that GUI, as an institution of higher learning, is organized to provide support for learning. The goal of the university structure is to provide students, called Associates, with a vehicle for accumulation of credit towards a bachelor's degree. This organizational structure is necessary, but insufficient for AL because Associates need more than an organization to provide and coordinate their degree programs. In other words, just because the network of university structures are organized in ways that make AL possible and convenient, it does not necessarily follow that Action Learning will occur for any individual Associate. The support structures within GUI's degrees are discussed in Chapter Three. To a greater or lesser degree GUI provides support for personal learning among Associates as advisors and advisees with the goal of helping Associates complete and document the outcomes of world-change projects. The support structures are necessary, but not sufficient for AL because the personal learning process occurring for each Associate requires transformative reflection. Additionally, because Associates' attrition rate is very high, many Associates do not remain enrolled in GUI long enough to benefit from the support structures. At the simplest organizational level I discuss the reflection process conducted in the patterned interactions of assigned learning groups called Guilds (Chapter Four). These groups of Associates work to provide each other with the best possible environment for personal learning through reflection. As its Associates experience transformative reflection, GUI is able to help elevate the quality of world-change efforts in the Permaculture community. Provided the organizational and support structures are in place, this reflection process is both necessary and sufficient for AL. By this I mean that if transformative reflection is occurring in Guild meetings, and is supported by a system of advisors, reviewers and support people within a university organized to give credit for Action Learning, then Action Learning will occur for individual Associates.

Twelve tips for utilizing principles of learning to support medical education.

PubMed

Cutting, Maris F; Saks, Norma Susswein

2012-01-01

Research in the cognitive sciences on learning and memory conducted across a range of domains, settings, and age groups has resulted in the identification and formulation of a set of generic learning principles. These learning principles have proven relevant and applicable to a wide range of learning situations in a variety of settings, and can be useful in supporting medical education. They can provide guidance to medical students for efficient and effective study, and can be helpful to faculty to support instructional planning and decisions relating to curriculum. This article discusses evidence-based principles of learning and their relationship to effective learning, teaching, pedagogy and curriculum development. We reviewed important principles of learning to determine those most relevant to improving medical student learning, guiding faculty toward more effective teaching, and in designing a curriculum. Our analysis has resulted in the articulation of key learning principles and specific strategies that are broadly applicable to medical school learning, teaching, and instructional planning. The twelve tips highlight principles of learning that can be effectively applied in the complex learning environment of medical education.

The Influence of Need-Supportive Teacher Behavior on the Motivation of Students with Congenital Deafblindness

ERIC Educational Resources Information Center

Haakma, Ineke; Janssen, Marleen; Minnaert, Alexander

2017-01-01

Introduction: Research has indicated that need-supportive learning environments positively influence students' motivation. According to self-determination theory, a need-supportive learning environment is one in which teachers provide structure, autonomy support, and involvement, and thereby support their students' psychological needs for…

Reflections on providing sport science support for athletes with learning difficulties.

PubMed

Hills, Laura; Utley, Andrea

2010-01-01

To highlight the benefits and the need for sport science support for athletes with learning difficulties, and to reflect on our experience of working with the GB squad for athletes with learning difficulties. A review of key and relevant literature is presented, followed by a discussion of the sport science support provision and the issues that emerged in working with athletes with learning difficulties. Pre- and post- physiological tests along with evaluations of athletes' potential to benefit from sport psychology support were conducted. The aim of these tests was to provide information for the athletes and the coaches on fitness levels, to use this information to plan future training, and to identify how well the performance could be enhanced. A case study is presented for one athlete, who had competed in distance events. The focus is the psychological support that was provided. It is clear that athletes with learning difficulties require the same type of sports science support as their mainstream peers. However, sport scientists will need to consider ways to extend their practice in order to provide the appropriate level of support.

Supporting Learners to Succeed: A Thematic Report by Education Scotland on Behalf of the Scottish Funding Council on Provision of Services Delivered by Scotland's Colleges to Support Learners to Succeed in Their Learning. Transforming Lives through Learning

ERIC Educational Resources Information Center

Education Scotland, 2014

2014-01-01

This report focuses on the actions taken by colleges to help learners resolve issues which are affecting their ability to turn up for classes, engage fully in learning and undertake assessments successfully. It explains the range of services and the relationships colleges have with other external bodies to provide support for learning. This report…

Supporting those who work and learn: A phenomenological research study.

PubMed

Thurgate, Claire

2018-02-01

With a shift in the United Kingdom's National Health Service to organisational learning and the local introduction of the Assistant Practitioner role to support the nursing workforce there was a broad need to understand the lived experiences of those who work and learn. Hermeneutic phenomenology was the chosen methodology. A purposive sample of eight trainee assistant practitioners, four matrons, seven mentors and the practice development nurse participated in conversational interviews at intermittent points in the journey. A stepped process of analysis produced three over-arching super-ordinate themes which indicated that the transition to assistant practitioner is non-linear and complex necessitating a change in knowledge and behaviour and the workplace culture must enable learning and role development. This paper focuses on supporting the journey which encompassed learning at university and learning in the workplace. Participants' stories demonstrated the presence of knowledgeable mentors and a learning culture enabled new roles to be supported. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Web 2.0 systems supporting childhood chronic disease management: design guidelines based on information behaviour and social learning theories.

PubMed

Ekberg, Joakim; Ericson, Leni; Timpka, Toomas; Eriksson, Henrik; Nordfeldt, Sam; Hanberger, Lena; Ludvigsson, Johnny

2010-04-01

Self-directed learning denotes that the individual is in command of what should be learned and why it is important. In this study, guidelines for the design of Web 2.0 systems for supporting diabetic adolescents' every day learning needs are examined in light of theories about information behaviour and social learning. A Web 2.0 system was developed to support a community of practice and social learning structures were created to support building of relations between members on several levels in the community. The features of the system included access to participation in the culture of diabetes management practice, entry to information about the community and about what needs to be learned to be a full practitioner or respected member in the community, and free sharing of information, narratives and experience-based knowledge. After integration with the key elements derived from theories of information behaviour, a preliminary design guideline document was formulated.

A collaborative framework for Distributed Privacy-Preserving Support Vector Machine learning.

PubMed

Que, Jialan; Jiang, Xiaoqian; Ohno-Machado, Lucila

2012-01-01

A Support Vector Machine (SVM) is a popular tool for decision support. The traditional way to build an SVM model is to estimate parameters based on a centralized repository of data. However, in the field of biomedicine, patient data are sometimes stored in local repositories or institutions where they were collected, and may not be easily shared due to privacy concerns. This creates a substantial barrier for researchers to effectively learn from the distributed data using machine learning tools like SVMs. To overcome this difficulty and promote efficient information exchange without sharing sensitive raw data, we developed a Distributed Privacy Preserving Support Vector Machine (DPP-SVM). The DPP-SVM enables privacy-preserving collaborative learning, in which a trusted server integrates "privacy-insensitive" intermediary results. The globally learned model is guaranteed to be exactly the same as learned from combined data. We also provide a free web-service (http://privacy.ucsd.edu:8080/ppsvm/) for multiple participants to collaborate and complete the SVM-learning task in an efficient and privacy-preserving manner.

Student Support in E-Learning Courses in Higher Education--Insights from a Metasynthesis "A Pedagogy of Panic Attacks"

ERIC Educational Resources Information Center

Minnaar, A.

2011-01-01

E-learning includes the use of the internet for accessing learning materials, interacting with learning content and with instructors and students to obtain support during the learning process in order to gain knowledge and personal meaning and to grow. It occurs when students have electronic access to resources and where they are in regular online…

The Role of Student-Generated Externalizations in Strategic Multimedia Learning and How Current (Web-)Technology Fails to Support Learner Engagement

ERIC Educational Resources Information Center

Ploetzner, Rolf; Fillisch, Benjamin; Gewald, Patrick-André; Ruf, Tatjana

2016-01-01

In two studies, we investigated how learning strategies can support learning from multimedia. In the first study, 112 students learned from a web-based learning environment. On the basis of a strategy, one group of students took typewritten notes. The second group of students wrote a summary. Producing typewritten notes did not benefit learning…

Polyport atmospheric gas sampler

DOEpatents

Guggenheim, S. Frederic

1995-01-01

An atmospheric gas sampler with a multi-port valve which allows for multi, sequential sampling of air through a plurality of gas sampling tubes mounted in corresponding gas inlet ports. The gas sampler comprises a flow-through housing which defines a sampling chamber and includes a gas outlet port to accommodate a flow of gases through the housing. An apertured sample support plate defining the inlet ports extends across and encloses the sampling chamber and supports gas sampling tubes which depend into the sampling chamber and are secured across each of the inlet ports of the sample support plate in a flow-through relation to the flow of gases through the housing during sampling operations. A normally closed stopper means mounted on the sample support plate and operatively associated with each of the inlet ports blocks the flow of gases through the respective gas sampling tubes. A camming mechanism mounted on the sample support plate is adapted to rotate under and selectively lift open the stopper spring to accommodate a predetermined flow of gas through the respective gas sampling tubes when air is drawn from the housing through the outlet port.

Sequential Learning and Recognition of Comprehensive Behavioral Patterns Based on Flow of People

NASA Astrophysics Data System (ADS)

Gibo, Tatsuya; Aoki, Shigeki; Miyamoto, Takao; Iwata, Motoi; Shiozaki, Akira

Recently, surveillance cameras have been set up everywhere, for example, in streets and public places, in order to detect irregular situations. In the existing surveillance systems, as only a handful of surveillance agents watch a large number of images acquired from surveillance cameras, there is a possibility that they may miss important scenes such as accidents or abnormal incidents. Therefore, we propose a method for sequential learning and the recognition of comprehensive behavioral patterns in crowded places. First, we comprehensively extract a flow of people from input images by using optical flow. Second, we extract behavioral patterns on the basis of change-point detection of the flow of people. Finally, in order to recognize an observed behavioral pattern, we draw a comparison between the behavioral pattern and previous behavioral patterns in the database. We verify the effectiveness of our approach by placing a surveillance camera on a campus.

Future climate scenarios and rainfall--runoff modelling in the Upper Gallego catchment (Spain).

PubMed

Bürger, C M; Kolditz, O; Fowler, H J; Blenkinsop, S

2007-08-01

Global climate change may have large impacts on water supplies, drought or flood frequencies and magnitudes in local and regional hydrologic systems. Water authorities therefore rely on computer models for quantitative impact prediction. In this study we present kernel-based learning machine river flow models for the Upper Gallego catchment of the Ebro basin. Different learning machines were calibrated using daily gauge data. The models posed two major challenges: (1) estimation of the rainfall-runoff transfer function from the available time series is complicated by anthropogenic regulation and mountainous terrain and (2) the river flow model is weak when only climate data are used, but additional antecedent flow data seemed to lead to delayed peak flow estimation. These types of models, together with the presented downscaled climate scenarios, can be used for climate change impact assessment in the Gallego, which is important for the future management of the system.

Catechin treatment improves cerebrovascular flow-mediated dilation and learning abilities in atherosclerotic mice

PubMed Central

Drouin, Annick; Bolduc, Virginie; Thorin-Trescases, Nathalie; Bélanger, Élisabeth; Fernandes, Priscilla; Baraghis, Edward; Lesage, Frédéric; Gillis, Marc-Antoine; Villeneuve, Louis; Hamel, Edith; Ferland, Guylaine; Thorin, Eric

2013-01-01

Severe dyslipidemia and the associated oxidative stress could accelerate the age-related decline in cerebrovascular endothelial function and cerebral blood flow (CBF), leading to neuronal loss and impaired learning abilities. We hypothesized that a chronic treatment with the polyphenol catechin would prevent endothelial dysfunction, maintain CBF responses, and protect learning abilities in atherosclerotic (ATX) mice. We treated ATX (C57Bl/6-LDLR−/− hApoB+/+; 3 mo old) mice with catechin (30 mg·kg−1·day−1) for 3 mo, and C57Bl/6 [wild type (WT), 3 and 6 mo old] mice were used as controls. ACh- and flow-mediated dilations (FMD) were recorded in pressurized cerebral arteries. Basal CBF and increases in CBF induced by whisker stimulation were measured by optical coherence tomography and Doppler, respectively. Learning capacities were evaluated with the Morris water maze test. Compared with 6-mo-old WT mice, cerebral arteries from 6-mo-old ATX mice displayed a higher myogenic tone, lower responses to ACh and FMD, and were insensitive to NOS inhibition (P < 0.05), suggesting endothelial dysfunction. Basal and increases in CBF were lower in 6-mo-old ATX than WT mice (P < 0.05). A decline in the learning capabilities was also observed in ATX mice (P < 0.05). Catechin 1) reduced cerebral superoxide staining (P < 0.05) in ATX mice, 2) restored endothelial function by reducing myogenic tone, improving ACh- and FMD and restoring the sensitivity to nitric oxide synthase inhibition (P < 0.05), 3) increased the changes in CBF during stimulation but not basal CBF, and 4) prevented the decline in learning abilities (P < 0.05). In conclusion, catechin treatment of ATX mice prevents cerebrovascular dysfunctions and the associated decline in learning capacities. PMID:21186270

Unpacking the Roles of the Facilitator in Higher Education Professional Learning Communities

ERIC Educational Resources Information Center

Margalef, Leonor; Pareja Roblin, Natalie

2016-01-01

Facilitators are central for the success of professional learning communities (PLCs). Yet, their specific roles in supporting teacher learning remain still largely underexplored. To address this gap, the current multiple case study examines the roles of 4 university PLC facilitators, the strategies they used to support teacher learning, and the…

Experiential Learning Methods, Simulation Complexity and Their Effects on Different Target Groups

ERIC Educational Resources Information Center

Kluge, Annette

2007-01-01

This article empirically supports the thesis that there is no clear and unequivocal argument in favor of simulations and experiential learning. Instead the effectiveness of simulation-based learning methods depends strongly on the target group's characteristics. Two methods of supporting experiential learning are compared in two different complex…

Exploring Students' Language Awareness through Intercultural Communication in Computer-Supported Collaborative Learning

ERIC Educational Resources Information Center

Yang, Yu-Fen

2013-01-01

Students seldom think about language unless they are instructed to do so or are made to do so during learning activities. To arouse students' awareness while learning English for Specific Purposes (ESP), this study formed a computer-supported collaborative learning (CSCL) community to engage teachers and students from different domains and…

Reflecting on Quality Learning in a Student Writing Experience Supported by Technology.

ERIC Educational Resources Information Center

Ellis, Robert

With rapid developments in information technology in society being mirrored in the use of new learning technologies in universities, research into the quality of technologically-supported learning is essential. To date, research into new learning technologies has provided us with valuable knowledge that includes the theories behind their design,…

The Place of Game-Based Learning in an Age of Austerity

ERIC Educational Resources Information Center

Whitton, Nicola

2012-01-01

Digital games have the potential to create active and engaging environments for learning, supporting problem-solving, communication and group activities, as well as providing a forum for practice and learning through failure. The use of game techniques such as gradually increasing levels of difficulty and contextual feedback support learning, and…

Informal Learning with PDAs and Smartphones

ERIC Educational Resources Information Center

Clough, G.; Jones, A.C.; Mcandrew, P.; Scanlon, E.

2008-01-01

There has been increasing interest in informal learning in recent years alongside interest in how such learning can be supported by technology. However, relatively little is known about the extent to which adults make use of their own mobile devices to support informal learning. In this study, a survey was used to investigate whether, and to what…

Exploring How Creating Stop-Motion Animations Supports Student Teachers in Learning to Teach Science

ERIC Educational Resources Information Center

Wishart, Jocelyn

2017-01-01

This article reports on an exploration of teaching and learning through creating rudimentary stop-motion animations set up to identify how learning opportunities involving stop-motion animations can support student learning and science teacher education. Participants were student teachers, volunteers representing both secondary and primary school…

Six Characteristics of Nutrition Education Videos That Support Learning and Motivation to Learn

ERIC Educational Resources Information Center

Ramsay, Samantha A.; Holyoke, Laura; Branen, Laurel J.; Fletcher, Janice

2012-01-01

Objective: To identify characteristics in nutrition education video vignettes that support learning and motivation to learn about feeding children. Methods: Nine focus group interviews were conducted with child care providers in child care settings from 4 states in the western United States: California, Idaho, Oregon, and Washington. At each focus…

The Effects of Different Learning Environments on Students' Motivation for Learning and Their Achievement

ERIC Educational Resources Information Center

Baeten, Marlies; Dochy, Filip; Struyven, Katrien

2013-01-01

Background: Research in higher education on the effects of student-centred versus lecture-based learning environments generally does not take into account the psychological need support provided in these learning environments. From a self-determination theory perspective, need support is important to study because it has been associated with…

Content and Language Integrated Learning by Interaction. Fremdsprachendidaktik inhalts-und lernerorientiert. Volume 26

ERIC Educational Resources Information Center

Kupetz, Rita, Ed.; Becker, Carmen, Ed.

2014-01-01

Content and Language Integrated Learning (CLIL) is an established approach to support multilingualism in Europe by teaching various school subjects in an additional language. The practices used, however, vary considerably. Our book considers this diversity by looking at CLIL scenarios, defined as learning environments supporting content learning,…

A FAQ-Based e-Learning Environment to Support Japanese Language Learning

ERIC Educational Resources Information Center

Liu, Yuqin; Yin, Chengjiu; Ogata, Hiroaki; Qiao, Guojun; Yano, Yoneo

2011-01-01

In traditional classes, having many questions from learners is important because these questions indicate difficult points for learners and for teachers. This paper proposes a FAQ-based e-Learning environment to support Japanese language learning that focuses on learner questions. This knowledge sharing system enables learners to interact and…

Seamless Support: Technology Enhanced Learning in Open Distance Learning at NWU

ERIC Educational Resources Information Center

Esterhuizen, Hennie

2015-01-01

Frantic attempts of investing in technology to demonstrate willingness to educate for the knowledge society may result in failure to address the real requirements. This paper presents the main features of a framework for integrating Technology Enhanced Learning in Open Distance Learning at North-West University, South Africa. Support towards…

Not Blogging, Drinking: Peer Learning, Sociality and Intercultural Learning in Study Abroad

ERIC Educational Resources Information Center

Tonkin, Kati; Bourgault du Coudray, Chantal

2016-01-01

Research into study abroad students' intercultural learning has demonstrated a need to provide pedagogical support before, during and after the study abroad experience. This article reports on the authors' efforts to support the in-country learning of Australian study abroad students through an online guided reflection exercise (blog) with a…

A Model for Discussing the Quality of Technology-Enhanced Learning in Blended Learning Programmes

ERIC Educational Resources Information Center

Casanova, Diogo; Moreira, António

2017-01-01

This paper presents a comprehensive model for supporting informed and critical discussions concerning the quality of Technology-Enhanced Learning in Blended Learning programmes. The model aims to support discussions around domains such as how institutions are prepared, the participants' background and expectations, the course design, and the…

Achieving Complex Learning Outcomes through Adoption of a Pedagogical Perspective: A Model for Computer Technology Delivered Instruction

ERIC Educational Resources Information Center

Bellard, Breshanica

2018-01-01

Professionals responsible for the delivery of education and training using technology systems and platforms can facilitate complex learning through application of relevant strategies, principles and theories that support how learners learn and that support how curriculum should be designed in a technology based learning environment. Technological…

Designing for Interaction: Six Steps to Designing Computer-Supported Group-Based Learning

ERIC Educational Resources Information Center

Strijbos, J. W.; Martens, R. L.; Jochems, W. M. G.

2004-01-01

At present, the design of computer-supported group-based learning (CSGBL) is often based on subjective decisions regarding tasks, pedagogy and technology, or concepts such as "cooperative learning" and "collaborative learning." Critical review reveals these concepts as insufficiently substantial to serve as a basis for CSGBL design. Furthermore,…

Variable volume combustor with aerodynamic support struts

DOEpatents

Ostebee, Heath Michael; Johnson, Thomas Edward; Stewart, Jason Thurman; Keener, Christopher Paul

2017-03-07

The present application provides a combustor for use with a gas turbine engine. The combustor may include a number of micro-mixer fuel nozzles and a fuel injection system for providing a flow of fuel to the micro-mixer fuel nozzles. The fuel injection system may include a number of support struts supporting the fuel nozzles and providing the flow of fuel therethrough. The support struts may include an aerodynamic contoured shape so as to distribute evenly a flow of air to the micro-mixer fuel nozzles.

Take-Home Experiments in Undergraduate Fluid Mechanics Education

NASA Astrophysics Data System (ADS)

Cimbala, John

2007-11-01

Hands-on take-home experiments, assigned as homework, are useful as supplements to traditional in-class demonstrations and laboratories. Students borrow the equipment from the department's equipment room, and perform the experiment either at home or in the student lounge or student shop work area. Advantages include: (1) easy implementation, especially for large classes, (2) low cost and easy duplication of multiple units, (3) no loss of lecture time since the take-home experiment is self-contained with all necessary instructions, and (4) negligible increase in student or teaching assistant work load since the experiment is assigned as a homework problem in place of a traditional pen and paper problem. As an example, a pump flow take-home experiment was developed, implemented, and assessed in our introductory junior-level fluid mechanics course at Penn State. The experimental apparatus consists of a bucket, tape measure, submersible aquarium pump, tubing, measuring cup, and extension cord. We put together twenty sets at a total cost of less than 20 dollars per set. Students connect the tube to the pump outlet, submerge the pump in water, and measure the volume flow rate produced at various outflow elevations. They record and plot volume flow rate as a function of outlet elevation, and compare with predictions based on the manufacturer's pump performance curve (head versus volume flow rate) and flow losses. The homework assignment includes an online pre-test and post-test to assess the change in students' understanding of the principles of pump performance. The results of the assessment support a significant learning gain following the completion of the take-home experiment.

Physicians' preferences for asthma guidelines implementation.

PubMed

Kang, Min-Koo; Kim, Byung-Keun; Kim, Tae-Wan; Kim, Sae-Hoon; Kang, Hye-Ryun; Park, Heung-Woo; Chang, Yoon-Seok; Kim, Sun-Sin; Min, Kyung-Up; Kim, You-Young; Cho, Sang-Heon

2010-10-01

Patient care based on asthma guidelines is cost-effective and leads to improved treatment outcomes. However, ineffective implementation strategies interfere with the use of these recommendations in clinical practice. This study investigated physicians' preferences for asthma guidelines, including content, supporting evidence, learning strategies, format, and placement in the clinical workplace. We obtained information through a questionnaire survey. The questionnaire was distributed to physicians attending continuing medical education courses and sent to other physicians by airmail, e-mail, and facsimile. A total of 183 physicians responded (male to female ratio, 2.3:1; mean age, 40.4±9.9 years); 89.9% of respondents were internists or pediatricians, and 51.7% were primary care physicians. Physicians preferred information that described asthma medications, classified the disease according to severity and level of control, and provided methods of evaluation/treatment/monitoring and management of acute exacerbation. The most effective strategies for encouraging the use of the guidelines were through continuing medical education and discussions with colleagues. Physicians required supporting evidence in the form of randomized controlled trials and expert consensus. They preferred that the guidelines be presented as algorithms or flow charts/flow diagrams on plastic sheets, pocket cards, or in electronic medical records. This study identified the items of the asthma guidelines preferred by physicians in Korea. Asthma guidelines with physicians' preferences would encourage their implementation in clinical practice.

Enhancing Collaborative Learning through Dynamic Forms of Support: The Impact of an Adaptive Domain-Specific Support Strategy

ERIC Educational Resources Information Center

Karakostas, A.; Demetriadis, S.

2011-01-01

Research on computer-supported collaborative learning (CSCL) has strongly emphasized the value of providing student support of either fixed (e.g. collaboration scripts) or dynamic form (e.g. adaptive supportive interventions). Currently, however, there is not sufficient evidence corroborating the potential of adaptive support methods to improve…

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

Supporting student nurses in practice with additional online communication tools.

PubMed

Morley, Dawn A

2014-01-01

Student nurses' potential isolation and difficulties of learning on placement have been well documented and, despite attempts to make placement learning more effective, evidence indicates the continuing schism between formal learning at university and situated learning on placement. First year student nurses, entering placement for the first time, are particularly vulnerable to the vagaries of practice. During 2012 two first year student nurse seminar groups (52 students) were voluntarily recruited for a mixed method study to determine the usage of additional online communication support mechanisms (Facebook, wiki, an email group and traditional methods of support using individual email or phone) while undertaking their first five week clinical placement. The study explores the possibility of strengthening clinical learning and support by promoting the use of Web 2.0 support groups for student nurses. Results indicate a high level of interactivity in both peer and academic support in the use of Facebook and a high level of interactivity in one wiki group. Students' qualitative comments voice an appreciation of being able to access university and peer support whilst working individually on placement. Recommendations from the study challenge universities to use online communication tools already familiar to students to complement the support mechanisms that exist for practice learning. This is tempered by recognition of the responsibility of academics to ensure their students are aware of safe and effective online communication. Copyright © 2013 Elsevier Ltd. All rights reserved.

Conversational Agents in E-Learning

NASA Astrophysics Data System (ADS)

Kerry, Alice; Ellis, Richard; Bull, Susan

This paper discusses the use of natural language or 'conversational' agents in e-learning environments. We describe and contrast the various applications of conversational agent technology represented in the e-learning literature, including tutors, learning companions, language practice and systems to encourage reflection. We offer two more detailed examples of conversational agents, one which provides learning support, and the other support for self-assessment. Issues and challenges for developers of conversational agent systems for e-learning are identified and discussed.

Polymer Stress-Gradient Induced Migration in Thin Film Flow Over Topography

NASA Astrophysics Data System (ADS)

Tsouka, Sophia; Dimakopoulos, Yiannis; Tsamopoulos, John

2014-11-01

We consider the 2D, steady film flow of a dilute polymer solution over a periodic topography. We examine how the distribution of polymer in the planarization of topographical features is affected by flow intensity and physical properties. The thermodynamically acceptable, Mavrantzas-Beris two-fluid Hamiltonian model is used for polymer migration. The resulting system of differential equations is solved via the mixed FE method combined with an elliptic grid generation scheme. We present numerical results for polymer concentration, stress, velocity and flux of components as a function of the non-dimensional parameters of the problem (Deborah, Peclet, Reynolds and Capillary numbers, ratio of solvent viscosity to total liquid viscosity and geometric features of the topography). Polymer migration to the free surface is enhanced when the cavity gets steeper and deeper. This increases the spatial extent of the polymer depletion layer and induces strong banding in the stresses away from the substrate wall, especially in low polymer concentration. Macromolecules with longer relaxation times are predicted to migrate towards the free surface more easily, while high surface tension combined with a certain range of Reynolds numbers affects the free surface deformations. Work supported by the General Secretariat of Research & Technology of Greece through the program ``Excellence'' (Grant No. 1918) in the framework ``Education and Lifelong Learning'' co-funded by the ESF.

Coupling of Noah-MP and the High Resolution CI-WATER ADHydro Hydrological Model

NASA Astrophysics Data System (ADS)

Moreno, H. A.; Goncalves Pureza, L.; Ogden, F. L.; Steinke, R. C.

2014-12-01

ADHydro is a physics-based, high-resolution, distributed hydrological model suitable for simulating large watersheds in a massively parallel computing environment. It simulates important processes such as: rainfall and infiltration, snowfall and snowmelt in complex terrain, vegetation and evapotranspiration, soil heat flux and freezing, overland flow, channel flow, groundwater flow and water management. For the vegetation and evapotranspiration processes, ADHydro uses the validated community land surface model (LSM) Noah-MP. Noah-MP uses multiple options for key land-surface hydrology and was developed to facilitate climate predictions with physically based ensembles. This presentation discusses the lessons learned in coupling Noah-MP to ADHydro. Noah-MP is delivered with a main driver program and not as a library with a clear interface to be called from other codes. This required some investigation to determine the correct functions to call and the appropriate parameter values. ADHydro runs Noah-MP as a point process on each mesh element and provides initialization and forcing data for each element. Modeling data are acquired from various sources including the Soil Survey Geographic Database (SSURGO), the Weather Research and Forecasting (WRF) model, and internal ADHydro simulation states. Despite these challenges in coupling Noah-MP to ADHydro, the use of Noah-MP provides the benefits of a supported community code.

Science for Managing Riverine Ecosystems: Actions for the USGS Identified in the Workshop "Analysis of Flow and Habitat for Instream Aquatic Communities"

USGS Publications Warehouse

Bencala, Kenneth E.; Hamilton, David B.; Petersen, James H.

2006-01-01

Federal and state agencies need improved scientific analysis to support riverine ecosystem management. The ability of the USGS to integrate geologic, hydrologic, chemical, geographic, and biological data into new tools and models provides unparalleled opportunities to translate the best riverine science into useful approaches and usable information to address issues faced by river managers. In addition to this capability to provide integrated science, the USGS has a long history of providing long-term and nationwide information about natural resources. The USGS is now in a position to advance its ability to provide the scientific support for the management of riverine ecosystems. To address this need, the USGS held a listening session in Fort Collins, Colorado in April 2006. Goals of the workshop were to: 1) learn about the key resource issues facing DOI, other Federal, and state resource management agencies; 2) discuss new approaches and information needs for addressing these issues; and 3) outline a strategy for the USGS role in supporting riverine ecosystem management. Workshop discussions focused on key components of a USGS strategy: Communications, Synthesis, and Research. The workshop identified 3 priority actions the USGS can initiate now to advance its capabilities to support integrated science for resource managers in partner government agencies and non-governmental organizations: 1) Synthesize the existing science of riverine ecosystem processes to produce broadly applicable conceptual models, 2) Enhance selected ongoing instream flow projects with complementary interdisciplinary studies, and 3) Design a long-term, watershed-scale research program that will substantively reinvent riverine ecosystem science. In addition, topical discussion groups on hydrology, geomorphology, aquatic habitat and populations, and socio-economic analysis and negotiation identified eleven important complementary actions required to advance the state of the science and to develop the tools for supporting decisions on riverine ecosystem management. These eleven actions lie within the continuum of Communications, Synthesis, and Research.

Gaming science: the "Gamification" of scientific thinking.

PubMed

Morris, Bradley J; Croker, Steve; Zimmerman, Corinne; Gill, Devin; Romig, Connie

2013-09-09

Science is critically important for advancing economics, health, and social well-being in the twenty-first century. A scientifically literate workforce is one that is well-suited to meet the challenges of an information economy. However, scientific thinking skills do not routinely develop and must be scaffolded via educational and cultural tools. In this paper we outline a rationale for why we believe that video games have the potential to be exploited for gain in science education. The premise we entertain is that several classes of video games can be viewed as a type of cultural tool that is capable of supporting three key elements of scientific literacy: content knowledge, process skills, and understanding the nature of science. We argue that there are three classes of mechanisms through which video games can support scientific thinking. First, there are a number of motivational scaffolds, such as feedback, rewards, and flow states that engage students relative to traditional cultural learning tools. Second, there are a number of cognitive scaffolds, such as simulations and embedded reasoning skills that compensate for the limitations of the individual cognitive system. Third, fully developed scientific thinking requires metacognition, and video games provide metacognitive scaffolding in the form of constrained learning and identity adoption. We conclude by outlining a series of recommendations for integrating games and game elements in science education and provide suggestions for evaluating their effectiveness.

Gaming science: the “Gamification” of scientific thinking

PubMed Central

Morris, Bradley J.; Croker, Steve; Zimmerman, Corinne; Gill, Devin; Romig, Connie

2013-01-01

Science is critically important for advancing economics, health, and social well-being in the twenty-first century. A scientifically literate workforce is one that is well-suited to meet the challenges of an information economy. However, scientific thinking skills do not routinely develop and must be scaffolded via educational and cultural tools. In this paper we outline a rationale for why we believe that video games have the potential to be exploited for gain in science education. The premise we entertain is that several classes of video games can be viewed as a type of cultural tool that is capable of supporting three key elements of scientific literacy: content knowledge, process skills, and understanding the nature of science. We argue that there are three classes of mechanisms through which video games can support scientific thinking. First, there are a number of motivational scaffolds, such as feedback, rewards, and flow states that engage students relative to traditional cultural learning tools. Second, there are a number of cognitive scaffolds, such as simulations and embedded reasoning skills that compensate for the limitations of the individual cognitive system. Third, fully developed scientific thinking requires metacognition, and video games provide metacognitive scaffolding in the form of constrained learning and identity adoption. We conclude by outlining a series of recommendations for integrating games and game elements in science education and provide suggestions for evaluating their effectiveness. PMID:24058354

The Learning Thermometer: Closing the Loop between Teaching, Learning, Wellbeing and Support in Universities

ERIC Educational Resources Information Center

Stallman, Helen M.; King, Sharron

2016-01-01

The increasing awareness and impact of mental health problems in university students in addition to a need for objective measures of teaching quality provide the impetus for a new approach to supporting students. There is a need for more effective tools that integrate the institutional silos of teaching, learning, support, and wellbeing to help…

High School Teachers Use of Writing to Support Students' Learning: A National Survey

ERIC Educational Resources Information Center

Gillespie, Amy; Graham, Steve; Kiuhara, Sharlene; Hebert, Michael

2014-01-01

A random sample of language arts, social studies, science, and math high school teachers from across the United States were surveyed about their use of writing to support student learning. Four out of every five teachers reported they used writing to support student learning, applying on average 24 different writing activities across the school…

Support for Self-Regulation in Learning Complex Topics from Multimedia Explanations: Do Learners Need Extensive or Minimal Support?

ERIC Educational Resources Information Center

Rodicio, Hector Garcia; Sanchez, Emilio; Acuna, Santiago R.

2013-01-01

Acquiring complex conceptual knowledge requires learners to self-regulate their learning by planning, monitoring, and adjusting the process but they find it difficult to do so. In one experiment, we examined whether learners need broad systems of support for self-regulation or whether they are also able to learn with more economical support…

Implementing Action Research and Professional Learning Communities in a Professional Development School Setting to Support Teacher Candidate Learning

ERIC Educational Resources Information Center

Shanks, Joyce

2016-01-01

The paper reviews teacher candidates' use of action research and the Professional Learning Community (PLC) concept to support their work in their pre-student teaching field experience. In this research study, teacher candidates are involved in a professional development school relationship that uses action research and PLCs to support candidate…

An Analysis of Conceptual Flow Patterns and Structures in the Physics Classroom

ERIC Educational Resources Information Center

Eshach, Haim

2010-01-01

The aim of the current research is to characterize the conceptual flow processes occurring in whole-class dialogic discussions with a high level of interanimation; in the present case, of a high-school class learning about image creation on plane mirrors. Using detailed chains of interaction and conceptual flow discourse maps--both developed for…

Transforming clinical imaging and 3D data for virtual reality learning objects: HTML5 and mobile devices implementation.

PubMed

Trelease, Robert B; Nieder, Gary L

2013-01-01

Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android tablets. This article describes complementary methods for creating comparable, multiplatform VR learning objects in the new HTML5 standard format, circumventing platform-specific limitations imposed by the QuickTime VR multimedia file format. Multiple types or "dimensions" of anatomical information can be embedded in such learning objects, supporting different kinds of online learning applications, including interactive atlases, examination questions, and complex, multi-structure presentations. Such HTML5 VR learning objects are usable on new mobile devices that do not support QuickTime VR, as well as on personal computers. Furthermore, HTML5 VR learning objects can be embedded in "ebook" document files, supporting the development of new types of electronic textbooks on mobile devices that are increasingly popular and self-adopted for mobile learning. © 2012 American Association of Anatomists.

The Transformative Experience in Engineering Education

NASA Astrophysics Data System (ADS)

Goodman, Katherine Ann

This research evaluates the usefulness of transformative experience (TE) in engineering education. With TE, students 1) apply ideas from coursework to everyday experiences without prompting (motivated use); 2) see everyday situations through the lens of course content (expanded perception); and 3) value course content in new ways because it enriches everyday affective experience (affective value). In a three-part study, we examine how engineering educators can promote student progress toward TE and reliably measure that progress. For the first study, we select a mechanical engineering technical elective, Flow Visualization, that had evidence of promoting expanded perception of fluid physics. Through student surveys and interviews, we compare this elective to the required Fluid Mechanics course. We found student interest in fluids fell into four categories: complexity, application, ubiquity, and aesthetics. Fluid Mechanics promotes interest from application, while Flow Visualization promotes interest based in ubiquity and aesthetics. Coding for expanded perception, we found it associated with students' engineering identity, rather than a specific course. In our second study, we replicate atypical teaching methods from Flow Visualization in a new design course: Aesthetics of Design. Coding of surveys and interviews reveals that open-ended assignments and supportive teams lead to increased ownership of projects, which fuels risk-taking, and produces increased confidence as an engineer. The third study seeks to establish parallels between expanded perception and measurable perceptual expertise. Our visual expertise experiment uses fluid flow images with both novices and experts (students who had passed fluid mechanics). After training, subjects sort images into laminar and turbulent categories. The results demonstrate that novices learned to sort the flow stimuli in ways similar to subjects in prior perceptual expertise studies. In contrast, the experts' significantly better results suggest they are accessing conceptual fluids knowledge to perform this new, visual task. The ability to map concepts onto visual information is likely a necessary step toward expanded perception. Our findings suggest that open-ended aesthetic experiences with engineering content unexpectedly support engineering identity development, and that visual tasks could be developed to measure conceptual understanding, promoting expanded perception. Overall, we find TE a productive theoretical framework for engineering education research.

Diversity of devices along with diversity of data formats as a new challenge in global teaching and learning system

NASA Astrophysics Data System (ADS)

Sultana, Razia; Christ, Andreas; Meyrueis, Patrick

2014-07-01

The popularity of mobile communication devices is increasing day by day among students, especially for e-learning activities. "Always-ready-to-use" feature of mobile devices is a key motivation for students to use it even in a short break for a short time. This leads to new requirements regarding learning content presentation, user interfaces, and system architecture for heterogeneous devices. To support diverse devices is not enough to establish global teaching and learning system, it is equally important to support various formats of data along with different sort of devices having different capabilities in terms of processing power, display size, supported data formats, operating system, access method of data etc. Not only the existing data formats but also upcoming data formats, such as due to research results in the area of optics and photonics, virtual reality etc should be considered. This paper discusses the importance, risk and challenges of supporting heterogeneous devices to provide heterogeneous data as a learning content to make global teaching and learning system literally come true at anytime and anywhere. We proposed and implemented a sustainable architecture to support device and data format independent learning system.

Concept-Based Learning in Clinical Experiences: Bringing Theory to Clinical Education for Deep Learning.

PubMed

Nielsen, Ann

2016-07-01

Concept-based learning is used increasingly in nursing education to support the organization, transfer, and retention of knowledge. Concept-based learning activities (CBLAs) have been used in clinical education to explore key aspects of the patient situation and principles of nursing care, without responsibility for total patient care. The nature of best practices in teaching and the resultant learning are not well understood. The purpose of this multiple-case study research was to explore and describe concept-based learning in the context of clinical education in inpatient settings. Four clinical groups (each a case) were observed while they used CBLAs in the clinical setting. Major findings include that concept-based learning fosters deep learning, connection of theory with practice, and clinical judgment. Strategies used to support learning, major teaching-learning foci, and preconditions for concept-based teaching and learning will be described. Concept-based learning is promising to support integration of theory with practice and clinical judgment through application experiences with patients. [J Nurs Educ. 2016;55(7):365-371.]. Copyright 2016, SLACK Incorporated.

PBL and beyond: trends in collaborative learning.

PubMed

Pluta, William J; Richards, Boyd F; Mutnick, Andrew

2013-01-01

Building upon the disruption to lecture-based methods triggered by the introduction of problem-based learning, approaches to promote collaborative learning are becoming increasingly diverse, widespread and generally well accepted within medical education. Examples of relatively new, structured collaborative learning methods include team-based learning and just-in-time teaching. Examples of less structured approaches include think-pair share, case discussions, and the flipped classroom. It is now common practice in medical education to employ a range of instructional approaches to support collaborative learning. We believe that the adoption of such approaches is entering a new and challenging era. We define collaborate learning by drawing on the broader literature, including Chi's ICAP framework that emphasizes the importance of sustained, interactive explanation and elaboration by learners. We distinguish collaborate learning from constructive, active, and passive learning and provide preliminary evidence documenting the growth of methods that support collaborative learning. We argue that the rate of adoption of collaborative learning methods will accelerate due to a growing emphasis on the development of team competencies and the increasing availability of digital media. At the same time, the adoption collaborative learning strategies face persistent challenges, stemming from an overdependence on comparative-effectiveness research and a lack of useful guidelines about how best to adapt collaborative learning methods to given learning contexts. The medical education community has struggled to consistently demonstrate superior outcomes when using collaborative learning methods and strategies. Despite this, support for their use will continue to expand. To select approaches with the greatest utility, instructors must carefully align conditions of the learning context with the learning approaches under consideration. Further, it is critical that modifications are made with caution and that instructors verify that modifications do not impede the desired cognitive activities needed to support meaningful collaborative learning.

Using a Smartphone App and Coaching Group Sessions to Promote Residents' Reflection in the Workplace.

PubMed

Könings, Karen D; van Berlo, Jean; Koopmans, Richard; Hoogland, Henk; Spanjers, Ingrid A E; ten Haaf, Jeroen A; van der Vleuten, Cees P M; van Merriënboer, Jeroen J G

2016-03-01

Reflecting on workplace-based experiences is necessary for professional development. However, residents need support to raise their awareness of valuable moments for learning and to thoughtfully analyze those learning moments afterwards. From October to December 2012, the authors held a multidisciplinary six-week postgraduate training module focused on general competencies. Residents were randomly assigned to one of four conditions with varying degrees of reflection support; they were offered (1) a smartphone app, (2) coaching group sessions, (3) a combination of both, or (4) neither type of support. The app allowed participants to capture in real time learning moments as a text note, audio recording, picture, or video. Coaching sessions held every two weeks aimed to deepen participants' reflection on captured learning moments. Questionnaire responses and reflection data were compared between conditions to assess the effects of the app and coaching sessions on intensity and frequency of reflection. Sixty-four residents participated. App users reflected more often, captured more learning moments, and reported greater learning progress than nonapp users. Participants who attended coaching sessions were more alert to learning moments and pursued more follow-up learning activities to improve on the general competencies. Those who received both types of support were most alert to these learning moments. A simple mobile app for capturing learning moments shows promise as a tool to support workplace-based learning, especially when combined with coaching sessions. Future research should evaluate these tools on a broader scale and in conjunction with residents' and students' personal digital portfolios.

A statistical learning strategy for closed-loop control of fluid flows

NASA Astrophysics Data System (ADS)

Guéniat, Florimond; Mathelin, Lionel; Hussaini, M. Yousuff

2016-12-01

This work discusses a closed-loop control strategy for complex systems utilizing scarce and streaming data. A discrete embedding space is first built using hash functions applied to the sensor measurements from which a Markov process model is derived, approximating the complex system's dynamics. A control strategy is then learned using reinforcement learning once rewards relevant with respect to the control objective are identified. This method is designed for experimental configurations, requiring no computations nor prior knowledge of the system, and enjoys intrinsic robustness. It is illustrated on two systems: the control of the transitions of a Lorenz'63 dynamical system, and the control of the drag of a cylinder flow. The method is shown to perform well.

Development and validation of a learning progression for change of seasons, solar and lunar eclipses, and moon phases

NASA Astrophysics Data System (ADS)

Testa, Italo; Galano, Silvia; Leccia, Silvio; Puddu, Emanuella

2015-12-01

In this paper, we report about the development and validation of a learning progression about the Celestial Motion big idea. Existing curricula, research studies on alternative conceptions about these phenomena, and students' answers to an open questionnaire were the starting point to develop initial learning progressions about change of seasons, solar and lunar eclipses, and Moon phases; then, a two-tier multiple choice questionnaire was designed to validate and improve them. The questionnaire was submitted to about 300 secondary students of different school levels (14 to 18 years old). Item response analysis and curve integral method were used to revise the hypothesized learning progressions. Findings support that spatial reasoning is a key cognitive factor for building an explanatory framework for the Celestial Motion big idea, but also suggest that causal reasoning based on physics mechanisms underlying the phenomena, as light flux laws or energy transfers, may significantly impact a students' understanding. As an implication of the study, we propose that the teaching of the three discussed astronomy phenomena should follow a single teaching-learning path along the following sequence: (i) emphasize from the beginning the geometrical aspects of the Sun-Moon-Earth system motion; (ii) clarify consequences of the motion of the Sun-Moon-Earth system, as the changing solar radiation flow on the surface of Earth during the revolution around the Sun; (iii) help students moving between different reference systems (Earth and space observer's perspective) to understand how Earth's rotation and revolution can change the appearance of the Sun and Moon. Instructional and methodological implications are also briefly discussed.

Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models.

PubMed

AlDahoul, Nouar; Md Sabri, Aznul Qalid; Mansoor, Ali Mohammed

2018-01-01

Human detection in videos plays an important role in various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they are highly susceptible to dynamical events such as illumination changes, camera jitter, and variations in object sizes. On the other hand, the proposed feature learning approaches are cheaper and easier because highly abstract and discriminative features can be produced automatically without the need of expert knowledge. In this paper, we utilize automatic feature learning methods which combine optical flow and three different deep models (i.e., supervised convolutional neural network (S-CNN), pretrained CNN feature extractor, and hierarchical extreme learning machine) for human detection in videos captured using a nonstatic camera on an aerial platform with varying altitudes. The models are trained and tested on the publicly available and highly challenging UCF-ARG aerial dataset. The comparison between these models in terms of training, testing accuracy, and learning speed is analyzed. The performance evaluation considers five human actions (digging, waving, throwing, walking, and running). Experimental results demonstrated that the proposed methods are successful for human detection task. Pretrained CNN produces an average accuracy of 98.09%. S-CNN produces an average accuracy of 95.6% with soft-max and 91.7% with Support Vector Machines (SVM). H-ELM has an average accuracy of 95.9%. Using a normal Central Processing Unit (CPU), H-ELM's training time takes 445 seconds. Learning in S-CNN takes 770 seconds with a high performance Graphical Processing Unit (GPU).

Effects of teacher autonomy support and students' autonomous motivation on learning in physical education.

PubMed

Shen, Bo; McCaughtry, Nate; Martin, Jeffrey; Fahlman, Mariane

2009-03-01

This study applied self-determination theory to investigate the effects of students' autonomous motivation and their perceptions of teacher autonomy support on need satisfaction adjustment, learning achievement, and cardiorespiratory fitness over a 4-month personal conditioning unit. Participants were 253 urban adolescents (121 girls and 132 boys, ages = 12-14 years). Based on a series of multiple regression analyses, perceived autonomy support by teachers significantly predicted students'need satisfaction adjustment and led to learning achievement, especially for students who were not autonomously motivated to learn in physical education. In turn, being more autonomous was directly associated with cardiorespiratory fitness enhancement. The findings suggest that shifts in teaching approaches toward providing more support for students' autonomy and active involvement hold promise for enhancing learning.

Using Data to Support Teaching and Learning

ERIC Educational Resources Information Center

Palucki Blake, Laura

2017-01-01

This chapter discusses principles that support using data about teaching and learning and offers several strategies particularly well suited for use by institutional researchers at small colleges in helping faculty, staff, and administrators use data on student learning for improvement.

Convergent Technologies in Distance Learning Delivery.

ERIC Educational Resources Information Center

Wheeler, Steve

1999-01-01

Describes developments in British education in distance learning technologies. Highlights include networking the rural areas; communication, community, and paradigm shifts; digital compression techniques and telematics; Web-based material delivered over the Internet; system flexibility; social support; learning support; videoconferencing; and…

Facility Activation and Characterization for IPD Turbopump Testing at NASA Stennis Space Center

NASA Technical Reports Server (NTRS)

Sass, J. P.; Pace, J. S.; Raines, N. G.; Meredith, T. O.; Taylor, S. A.; Ryan, H. M.

2005-01-01

The Integrated Powerhead Demonstrator (IPD) is a 250K lbf (1.1 MN) thrust cryogenic hydrogen/oxygen engine technology demonstrator that utilizes a full flow staged combustion engine cycle. The Integrated Powerhead Demonstrator (IPD) is, in part, supported by NASA. IPD is also supported through the Department of Defense's Integrated High Payoff Rocket Propulsion Technology (IHPRPT) program, which seeks to increase the performance and capability of today's state-of-the-art rocket propulsion systems while decreasing costs associated with military and commercial access to space. The primary industry participants include Boeing-Rocketdyne and GenCorp Aerojet. The IPD Program recently achieved two major milestones. The first was the successful completion of the IPD Oxidizer Turbopump (OTP) hot-fire test project at the NASA John C. Stennis Space Center (SSC) E-1 test facility in June 2003. A total of nine IPD Workhorse Preburner tests were completed, and subsequently 12 IPD OTP hot-fire tests were completed. The second major milestone was the successful completion of the IPD Fuel Turbopump (FTP) cold-flow test project at the NASA SSC E-1 test facility in November 2003. A total of six IPD FTP cold-flow tests were completed. The next phase of development involves IPD integrated engine system testing also at the NASA SSC E-1 test facility scheduled to begin in early 2005. Following and overview of the NASA SSC E-1 test facility, this paper addresses the facility aspects pertaining to the activation and testing of the IPD oxidizer and fuel turbopumps. In addition, some of the facility challenges encountered and the lessons learned during the test projects shall be detailed.

Retracted: Nurses learning in the workplace: a comparison of workplace attributes in acute care settings in Australia and Singapore.

PubMed

Chan, S W; Chan, M F; Lee, S-Y; Henderson, A

2014-03-01

Workplaces need to foster teaching and learning interactions so staff collaborate and learn from each other. Internationally, many countries provide support to graduates and experienced staff to foster engagement necessary for learning and quality care. Workplace attributes can differ across countries depending on managerial, contextual, social and policy issues. This study compared workplace attributes of two Australian hospitals with a Singaporean hospital. A representative sample of nurses in two acute care facilities in Australia (n = 203) and a comparable facility in Singapore (n = 154) during 2010 and 2011 responded to a survey requesting demographic data and responses about workplace attributes. Attributes were determined through validated tools that measure staff perception of support when facilitating others learning (Support Instrument for Nurses Facilitating the Learning of Others) and the clinical learning organizational culture (Clinical Learning Organizational Culture Survey). Results indicated Singaporean nurses rated perception of acknowledgement, workload management and teamwork support in facilitating learners in their hospital as significantly better than the Australian cohort despite similar provisions for support and development. There were no significant differences across the two sites in the clinical learning culture. Analysis across three health facilities only provides a snapshot. Targeting more facilities would assist in confirming the extent of reported trends. Findings indicate differences in nurses' perceptions of support when facilitating learners. Further exploration of Singaporean nurses' increased perceptions of support is worthy. Clinical learning organizational culture findings across Australian and Singaporean acute care facilities suggest common attributes within the nursing profession that transcend contextual factors, for example, a strong sense of task accomplishment. Nurses across both countries demonstrate strengths in accomplishing tasks but less so in recognizing nurses' contributions that may also impact nurses' influence in the practice context. As these attributes are common, nursing can collectively lobby and develop policy, thereby strengthening their cause to be recognized. © 2014 International Council of Nurses.

Let's Get Physical: Teaching Physics through Gymnastics

ERIC Educational Resources Information Center

Sojourner, Elena J.; Burgasser, Adam J.; Weise, Eric D.

2018-01-01

The concept of embodied learning--that we can learn with our bodies and with our minds--is a well-established concept in physics and math education research, and includes symbolic understanding (e.g., gestures that track how students think or facilitate learning to model complex systems of energy flow) as well as the literal experience of…

Lifelong Learning in the Public Interest.

ERIC Educational Resources Information Center

Kurland, Norman D.

In this paper, the author notes that lifelong learning is at the confluence of a number of separate streams from the recent past, each of which flows into the broad concept of lifelong learning and brings its own set of concerns that have helped generate a need to consider where the streams are going. These streams, or educational areas, are…

Developing and Evaluating Gamifying Learning System by Using Flow-Based Model

ERIC Educational Resources Information Center

Su, Chung-Ho; Hsaio, Kai-Chong

2015-01-01

Game-based learning is an effective learning method, whose performance depends on the quality of the educational game. Due to versatile game environments with complex backgrounds, evaluations are not easy to implement. Consequently, it is difficult for educators to determine to what degree a game may be qualified. This study proposes a novel,…

Action Learning in an SME: Appetite Comes with Eating

ERIC Educational Resources Information Center

Hauser, Bernhard

2009-01-01

This account describes action learning in a small to medium-size enterprise (SME) that operates as a local power utility on an established market that is currently going through a process of radical transformation. The task of the action learning set was to improve the flow of information to employees about the evolving framework in which the…

Information flow through threespine stickleback networks without social transmission

PubMed Central

Atton, N.; Hoppitt, W.; Webster, M. M.; Galef, B. G.; Laland, K. N.

2012-01-01

Social networks can result in directed social transmission of learned information, thus influencing how innovations spread through populations. Here we presented shoals of threespine sticklebacks (Gasterosteous aculeatus) with two identical foraging tasks and applied network-based diffusion analysis (NBDA) to determine whether the order in which individuals in a social group contacted and solved the tasks was affected by the group's network structure. We found strong evidence for a social effect on discovery of the foraging tasks with individuals tending to discover a task sooner when others in their group had previously done so, and with the spread of discovery of the foraging tasks influenced by groups' social networks. However, the same patterns of association did not reliably predict spread of solution to the tasks, suggesting that social interactions affected the time at which the tasks were discovered, but not the latency to its solution following discovery. The present analysis, one of the first applications of NBDA to a natural animal system, illustrates how NBDA can lead to insight into the mechanisms supporting behaviour acquisition that more conventional statistical approaches might miss. Importantly, we provide the first compelling evidence that the spread of novel behaviours can result from social learning in the absence of social transmission, a phenomenon that we refer to as an untransmitted social effect on learning. PMID:22896644

The impact of programmatic assessment on student learning: theory versus practice.

PubMed

Heeneman, Sylvia; Oudkerk Pool, Andrea; Schuwirth, Lambert W T; van der Vleuten, Cees P M; Driessen, Erik W

2015-05-01

It is widely acknowledged that assessment can affect student learning. In recent years, attention has been called to 'programmatic assessment', which is intended to optimise both learning functions and decision functions at the programme level of assessment, rather than according to individual methods of assessment. Although the concept is attractive, little research into its intended effects on students and their learning has been conducted. This study investigated the elements of programmatic assessment that students perceived as supporting or inhibiting learning, and the factors that influenced the active construction of their learning. The study was conducted in a graduate-entry medical school that implemented programmatic assessment. Thus, all assessment information, feedback and reflective activities were combined into a comprehensive, holistic programme of assessment. We used a qualitative approach and interviewed students (n = 17) in the pre-clinical phase of the programme about their perceptions of programmatic assessment and learning approaches. Data were scrutinised using theory-based thematic analysis. Elements from the comprehensive programme of assessment, such as feedback, portfolios, assessments and assignments, were found to have both supporting and inhibiting effects on learning. These supporting and inhibiting elements influenced students' construction of learning. Findings showed that: (i) students perceived formative assessment as summative; (ii) programmatic assessment was an important trigger for learning, and (iii) the portfolio's reflective activities were appreciated for their generation of knowledge, the lessons drawn from feedback, and the opportunities for follow-up. Some students, however, were less appreciative of reflective activities. For these students, the elements perceived as inhibiting seemed to dominate the learning response. The active participation of learners in their own learning is possible when learning is supported by programmatic assessment. Certain features of the comprehensive programme of assessment were found to influence student learning, and this influence can either support or inhibit students' learning responses. © 2015 John Wiley & Sons Ltd.

Understanding evaluation of learning support in mathematics and statistics

NASA Astrophysics Data System (ADS)

MacGillivray, Helen; Croft, Tony

2011-03-01

With rapid and continuing growth of learning support initiatives in mathematics and statistics found in many parts of the world, and with the likelihood that this trend will continue, there is a need to ensure that robust and coherent measures are in place to evaluate the effectiveness of these initiatives. The nature of learning support brings challenges for measurement and analysis of its effects. After briefly reviewing the purpose, rationale for, and extent of current provision, this article provides a framework for those working in learning support to think about how their efforts can be evaluated. It provides references and specific examples of how workers in this field are collecting, analysing and reporting their findings. The framework is used to structure evaluation in terms of usage of facilities, resources and services provided, and also in terms of improvements in performance of the students and staff who engage with them. Very recent developments have started to address the effects of learning support on the development of deeper approaches to learning, the affective domain and the development of communities of practice of both learners and teachers. This article intends to be a stimulus to those who work in mathematics and statistics support to gather even richer, more valuable, forms of data. It provides a 'toolkit' for those interested in evaluation of learning support and closes by referring to an on-line resource being developed to archive the growing body of evidence.

Sounding Out Science: Incorporating Audio Technology to Assist Students with Learning Differences in Science Education

NASA Astrophysics Data System (ADS)

Gomes, Clement V.

With the current focus to have all students reach scientific literacy in the U.S, there exists a need to support marginalized students, such as those with Learning Disabilities/Differences (LD), to reach the same educational goals as their mainstream counterparts. This dissertation examines the benefits of using audio assistive technology on the iPad to support LD students to achieve comprehension of science vocabulary and semantics. This dissertation is composed of two papers, both of which include qualitative information supported by quantified data. The first paper, titled Using Technology to Overcome Fundamental Literacy Constraints for Students with Learning Differences to Achieve Scientific Literacy, provides quantified evidence from pretest and posttest analysis that audio technology can be beneficial for seventh grade LD students when learning new and unfamiliar science content. Analysis of observations and student interviews support the findings. The second paper, titled Time, Energy, and Motivation: Utilizing Technology to Ease Science Understanding for Students with Learning Differences, supports the importance of creating technology that is clear, audible, and easy for students to use so they benefit and desire to utilize the learning tool. Multiple correlation of Likert Survey analysis was used to identify four major items and was supported with analysis from observations of and interviews with students, parents, and educators. This study provides useful information to support the rising number of identified LD students and their parents and teachers by presenting the benefits of using audio assistive technology to learn science.

Using tablets to support self-regulated learning in a longitudinal integrated clerkship.

PubMed

Archbold Hufty Alegría, Dylan; Boscardin, Christy; Poncelet, Ann; Mayfield, Chandler; Wamsley, Maria

2014-01-01

Introduction The need to train physicians committed to learning throughout their careers has prompted medical schools to encourage the development and practice of self-regulated learning by students. Longitudinal integrated clerkships (LICs) require students to exercise self-regulated learning skills. As mobile tools, tablets can potentially support self-regulation among LIC students. Methods We provided 15 LIC students with tablet computers with access to the electronic health record (EHR), to track their patient cohort, and a multiplatform online notebook, to support documentation and retrieval of self-identified clinical learning issues. Students received a 1-hour workshop on the relevant features of the tablet and online notebook. Two focus groups with the students were used to evaluate the program, one early and one late in the year and were coded by two raters. Results Students used the tablet to support their self-regulated learning in ways that were unique to their learning styles and increased access to resources and utilization of down-time. Students who used the tablet to self-monitor and target learning demonstrated the utility of tablets as learning tools. Conclusions LICs are environments rich in opportunity for self-regulated learning. Tablets can enhance students' ability to develop and employ self-regulatory skills in a clinical context.

Using tablets to support self-regulated learning in a longitudinal integrated clerkship.

PubMed

Alegría, Dylan Archbold Hufty; Boscardin, Christy; Poncelet, Ann; Mayfield, Chandler; Wamsley, Maria

2014-01-01

The need to train physicians committed to learning throughout their careers has prompted medical schools to encourage the development and practice of self-regulated learning by students. Longitudinal integrated clerkships (LICs) require students to exercise self-regulated learning skills. As mobile tools, tablets can potentially support self-regulation among LIC students. We provided 15 LIC students with tablet computers with access to the electronic health record (EHR), to track their patient cohort, and a multiplatform online notebook, to support documentation and retrieval of self-identified clinical learning issues. Students received a 1-hour workshop on the relevant features of the tablet and online notebook. Two focus groups with the students were used to evaluate the program, one early and one late in the year and were coded by two raters. Students used the tablet to support their self-regulated learning in ways that were unique to their learning styles and increased access to resources and utilization of down-time. Students who used the tablet to self-monitor and target learning demonstrated the utility of tablets as learning tools. LICs are environments rich in opportunity for self-regulated learning. Tablets can enhance students' ability to develop and employ self-regulatory skills in a clinical context.

Using tablets to support self-regulated learning in a longitudinal integrated clerkship

PubMed Central

Alegría, Dylan Archbold Hufty; Boscardin, Christy; Poncelet, Ann; Mayfield, Chandler; Wamsley, Maria

2014-01-01

Introduction The need to train physicians committed to learning throughout their careers has prompted medical schools to encourage the development and practice of self-regulated learning by students. Longitudinal integrated clerkships (LICs) require students to exercise self-regulated learning skills. As mobile tools, tablets can potentially support self-regulation among LIC students. Methods We provided 15 LIC students with tablet computers with access to the electronic health record (EHR), to track their patient cohort, and a multiplatform online notebook, to support documentation and retrieval of self-identified clinical learning issues. Students received a 1-hour workshop on the relevant features of the tablet and online notebook. Two focus groups with the students were used to evaluate the program, one early and one late in the year and were coded by two raters. Results Students used the tablet to support their self-regulated learning in ways that were unique to their learning styles and increased access to resources and utilization of down-time. Students who used the tablet to self-monitor and target learning demonstrated the utility of tablets as learning tools. Conclusions LICs are environments rich in opportunity for self-regulated learning. Tablets can enhance students’ ability to develop and employ self-regulatory skills in a clinical context. PMID:24646438

Informal learning processes in support of clinical service delivery in a service-oriented community pharmacy.

PubMed

Patterson, Brandon J; Bakken, Brianne K; Doucette, William R; Urmie, Julie M; McDonough, Randal P

The evolving health care system necessitates pharmacy organizations' adjustments by delivering new services and establishing inter-organizational relationships. One approach supporting pharmacy organizations in making changes may be informal learning by technicians, pharmacists, and pharmacy owners. Informal learning is characterized by a four-step cycle including intent to learn, action, feedback, and reflection. This framework helps explain individual and organizational factors that influence learning processes within an organization as well as the individual and organizational outcomes of those learning processes. A case study of an Iowa independent community pharmacy with years of experience in offering patient care services was made. Nine semi-structured interviews with pharmacy personnel revealed initial evidence in support of the informal learning model in practice. Future research could investigate more fully the informal learning model in delivery of patient care services in community pharmacies. Copyright © 2016 Elsevier Inc. All rights reserved.

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

The evolution of social learning mechanisms and cultural phenomena in group foragers.

PubMed

van der Post, Daniel J; Franz, Mathias; Laland, Kevin N

2017-02-10

Advanced cognitive abilities are widely thought to underpin cultural traditions and cumulative cultural change. In contrast, recent simulation models have found that basic social influences on learning suffice to support both cultural phenomena. In the present study we test the predictions of these models in the context of skill learning, in a model with stochastic demographics, variable group sizes, and evolved parameter values, exploring the cultural ramifications of three different social learning mechanisms. Our results show that that simple forms of social learning such as local enhancement, can generate traditional differences in the context of skill learning. In contrast, we find cumulative cultural change is supported by observational learning, but not local or stimulus enhancement, which supports the idea that advanced cognitive abilities are important for generating this cultural phenomenon in the context of skill learning. Our results help to explain the observation that animal cultures are widespread, but cumulative cultural change might be rare.

A pattern-based analysis of clinical computer-interpretable guideline modeling languages.

PubMed

Mulyar, Nataliya; van der Aalst, Wil M P; Peleg, Mor

2007-01-01

Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines. The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration. We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly, or not at all. PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support basic control-flow patterns, cancellation patterns, and some advance branching and synchronization patterns. None support multiple instances patterns. They offer varying levels of support for synchronizing merge patterns and state-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns. CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.

Utilization of Virtual Server Technology in Mission Operations

NASA Technical Reports Server (NTRS)

Felton, Larry; Lankford, Kimberly; Pitts, R. Lee; Pruitt, Robert W.

2010-01-01

Virtualization provides the opportunity to continue to do "more with less"---more computing power with fewer physical boxes, thus reducing the overall hardware footprint, power and cooling requirements, software licenses, and their associated costs. This paper explores the tremendous advantages and any disadvantages of virtualization in all of the environments associated with software and systems development to operations flow. It includes the use and benefits of the Intelligent Platform Management Interface (IPMI) specification, and identifies lessons learned concerning hardware and network configurations. Using the Huntsville Operations Support Center (HOSC) at NASA Marshall Space Flight Center as an example, we demonstrate that deploying virtualized servers as a means of managing computing resources is applicable and beneficial to many areas of application, up to and including flight operations.

Virtualization in the Operations Environments

NASA Technical Reports Server (NTRS)

Pitts, Lee; Lankford, Kim; Felton, Larry; Pruitt, Robert

2010-01-01

Virtualization provides the opportunity to continue to do "more with less"---more computing power with fewer physical boxes, thus reducing the overall hardware footprint, power and cooling requirements, software licenses, and their associated costs. This paper explores the tremendous advantages and any disadvantages of virtualization in all of the environments associated with software and systems development to operations flow. It includes the use and benefits of the Intelligent Platform Management Interface (IPMI) specification, and identifies lessons learned concerning hardware and network configurations. Using the Huntsville Operations Support Center (HOSC) at NASA Marshall Space Flight Center as an example, we demonstrate that deploying virtualized servers as a means of managing computing resources is applicable and beneficial to many areas of application, up to and including flight operations.

Embedded Systems and TensorFlow Frameworks as Assistive Technology Solutions.

PubMed

Mulfari, Davide; Palla, Alessandro; Fanucci, Luca

2017-01-01

In the field of deep learning, this paper presents the design of a wearable computer vision system for visually impaired users. The Assistive Technology solution exploits a powerful single board computer and smart glasses with a camera in order to allow its user to explore the objects within his surrounding environment, while it employs Google TensorFlow machine learning framework in order to real time classify the acquired stills. Therefore the proposed aid can increase the awareness of the explored environment and it interacts with its user by means of audio messages.

The Effects of Computer-Supported Inquiry-Based Learning Methods and Peer Interaction on Learning Stellar Parallax

ERIC Educational Resources Information Center

Ruzhitskaya, Lanika

2011-01-01

The presented research study investigated the effects of computer-supported inquiry-based learning and peer interaction methods on effectiveness of learning a scientific concept. The stellar parallax concept was selected as a basic, and yet important in astronomy, scientific construct, which is based on a straightforward relationship of several…

Enhancing E-Learning through Teacher Support: Two Experiences

ERIC Educational Resources Information Center

Gaudioso, E.; Hernandez-del-Olmo, F.; Montero, M.

2009-01-01

Teachers in e-learning play a crucial role as facilitators of the students' learning experiences. To this end, a teacher needs to monitor, understand and evaluate the activity of the students in the course. What is more, e-learning can be enhanced if tools for supporting teachers in this task are provided. In this paper, two experiences are…

Using Context-Aware Ubiquitous Learning to Support Students' Understanding of Geometry

ERIC Educational Resources Information Center

Crompton, Helen

2015-01-01

In this study, context-aware ubiquitous learning was used to support 4th grade students as they learn angle concepts. Context-aware ubiquitous learning was provided to students primarily through the use of iPads to access real-world connections and a Dynamic Geometry Environment. Gravemeijer and van Eerde's (2009), design-based research (DBR)…

Introducing Adaptivity Features to a Regular Learning Management System to Support Creation of Advanced eLessons

ERIC Educational Resources Information Center

Komlenov, Zivana; Budimac, Zoran; Ivanovic, Mirjana

2010-01-01

In order to improve the learning process for students with different pre-knowledge, personal characteristics and preferred learning styles, a certain degree of adaptability must be introduced to online courses. In learning environments that support such kind of functionalities students can explicitly choose different paths through course contents…

Motivation in a Computer-Supported Collaborative Learning Scenario and Its Impact on Learning Activities and Knowledge Acquisition

ERIC Educational Resources Information Center

Schoor, Cornelia; Bannert, Maria

2011-01-01

Addressing a drawback in current research on computer-supported collaborative learning (CSCL), this study investigated the influence of motivation on learning activities and knowledge acquisition during CSCL. Participants' (N = 200 university students) task was to develop a handout for which they had first an individual preparing phase followed by…

Supporting Children's Learning: A Guide for Teaching Assistants

ERIC Educational Resources Information Center

Overall, Lyn

2007-01-01

Are you looking for a book that explains all the key ideas on how children learn and how best to support children in that learning? Covering all major themes, this book offers: (1) An introduction to main theories of learning and development from birth to primary including brain and emotional and social development; (2) An introduction to what…

A Web-Based Educational Setting Supporting Individualized Learning, Collaborative Learning and Assessment

ERIC Educational Resources Information Center

Gogoulou, Agoritsa; Gouli, Evangelia; Grigoriadou, Maria; Samarakou, Maria; Chinou, Dionisia

2007-01-01

In this paper, we present a web-based educational setting, referred to as SCALE (Supporting Collaboration and Adaptation in a Learning Environment), which aims to serve learning and assessment. SCALE enables learners to (i) work on individual and collaborative activities proposed by the environment with respect to learners' knowledge level, (ii)…