Study of the Entrepreneurship in Universities as Learning Organization Based on Senge Model

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Nejad, Bahareh Azizi; Abbaszadeh, Mir Mohammad Seiied; Hassani, Mohammad; Bernousi, Iraj

2012-01-01

Learning organization and entrepreneurship are the most important issues that are focused on different themes in management. The purpose of present research was to study the relationship between learning organization elements and entrepreneurship among academic faculty members of the West Azarbaijan State Universities. The research method was…

Managing Change: Academic Libraries as Learning Organizations

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Sherry-Shiuan Su

2003-09-01

Full Text Available Designing libraries that can thrive in changing, chaotic environments is a continuous challenge for today’s managers. Academic libraries must now be agile, flexible, and able to adjust to the changing world. One system that can help managers in today’s environment is that of the learning organization. In these organizations, staff are encouraged to continuously learn new skills. However, for learning to be effective, the learning must result in improvements in the organization’s operations.The article will begin with the management issues of academic libraries in the changing environment, followed by the concept of learning organization; issues about leadership and learning organization, diversity and learning organization; changing technology and learning organization; and criteria for examining a learning library.[Article content in Chinese

Are Learning Organizations Pragmatic?

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Cavaleri, Steven A.

2008-01-01

Purpose: The purpose of this paper is to evaluate the future prospects of the popular concept known as the learning organization; to trace the influence of philosophical pragmatism on the learning organization and to consider its potential impact on the future; and to emphasize how pragmatic theories have shaped the development of Deming's total…

Employee competence in a learning organization

Directory of Open Access Journals (Sweden)

Anna Dziadkiewicz-Ilkowska

2009-12-01

Full Text Available The study shows the model of a learning organization as exemplified by a small business. In this kind of organization human resources are the key success factors and the "driving force" for intellectual and developmental potential that makes companies more creative and open to new ways of thinking about running and managing a business. This report shows that even micro and small enterprises can operate successfully successful on the market when they invest in knowledge development.

[Scale of organizational learning in schools. Organizational learning is a key element for the development of organizations].

Science.gov (United States)

López, Verónica; Ahumada, Luis; Olivares, Rodrigo; González, Alvaro

2012-05-01

Organizational learning is a key element for the development of organizations. School organizations are not exempt from this challenge and they currently face a highly dynamic and demanding context of education policies that emphasize the school's ability to learn. Thus, research on organizational learning in educational contexts requires valid instruments that are sensitive to the specifics of schools as organizations. In this study, we adapted and validated a scale of organizational learning in a sample of 119 Chilean municipal schools (N= 1,545). The results suggest a structural model made up of three factors: culture of learning, strategic clarity, and group learning. These factors predicted dimensions of educational achievement, as measured through the National Assessment System of Educational Achievement (SNED). Results are discussed in view of the literature on school improvement.

Reconstructing spatial organizations of chromosomes through manifold learning.

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Zhu, Guangxiang; Deng, Wenxuan; Hu, Hailin; Ma, Rui; Zhang, Sai; Yang, Jinglin; Peng, Jian; Kaplan, Tommy; Zeng, Jianyang

2018-02-02

Decoding the spatial organizations of chromosomes has crucial implications for studying eukaryotic gene regulation. Recently, chromosomal conformation capture based technologies, such as Hi-C, have been widely used to uncover the interaction frequencies of genomic loci in a high-throughput and genome-wide manner and provide new insights into the folding of three-dimensional (3D) genome structure. In this paper, we develop a novel manifold learning based framework, called GEM (Genomic organization reconstructor based on conformational Energy and Manifold learning), to reconstruct the three-dimensional organizations of chromosomes by integrating Hi-C data with biophysical feasibility. Unlike previous methods, which explicitly assume specific relationships between Hi-C interaction frequencies and spatial distances, our model directly embeds the neighboring affinities from Hi-C space into 3D Euclidean space. Extensive validations demonstrated that GEM not only greatly outperformed other state-of-art modeling methods but also provided a physically and physiologically valid 3D representations of the organizations of chromosomes. Furthermore, we for the first time apply the modeled chromatin structures to recover long-range genomic interactions missing from original Hi-C data. © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

PAL driven organizational learning theory and practices a light on learning journey of organizations

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Chuah, Kong

2015-01-01

Presenting an innovative concept and approach for organization management, this book serves to document an organization’s journey towards the ultimate goal of learning organization. This book also shares the experience on how a OL framework built on established learning theories, could be used effectively, overcoming many of the barriers in a real industrial setting. Utilizing a ready-to-use tool called Project Action Learning (PAL) to analyze real life case studies, the authors introduce a framework that allows teams of people to work and learn over the course of business projects. Equal emphasis is placed on the achievement of pre-set project outcomes and the learning objectives of the participants. In addition, a long term organizational learning strategy is put forward and the necessary supporting infrastructure, in the form of four ‘PAL Pillars’, is described. The concepts and development of the PAL driven Organizational Learning model are inspired by, and grounded in, Western and Eastern business ...

Learning organizations, internal marketing, and organizational commitment in hospitals.

Science.gov (United States)

Tsai, Yafang

2014-04-04

Knowledge capital is becoming more important to healthcare establishments, especially for hospitals that are facing changing societal and industrial patterns. Hospital staff must engage in a process of continual learning to improve their healthcare skills and provide a superior service to their patients. Internal marketing helps hospital administrators to improve the quality of service provided by nursing staff to their patients and allows hospitals to build a learning culture and enhance the organizational commitment of its nursing staff. Our empirical study provides nursing managers with a tool to allow them to initiate a change in the attitudes of nurses towards work, by constructing a new 'learning organization' and using effective internal marketing. A cross-sectional design was employed. Two hundred questionnaires were distributed to nurses working in either a medical centre or a regional hospital in Taichung City, Taiwan, and 114 valid questionnaires were returned (response rate: 57%). The entire process of distribution and returns was completed between 1 October and 31 October 2009. Hypothesis testing was conducted using structural equation modelling. A significant positive correlation was found between the existence of a 'learning organization', internal marketing, and organizational commitment. Internal marketing was a mediator between creating a learning organization and organizational commitment. Nursing managers may be able to apply the creation of a learning organization to strategies that can strengthen employee organizational commitment. Further, when promoting the creation of a learning organization, managers can coordinate their internal marketing practices to enhance the organizational commitment of nurses.

Moodle supporting problem-based, project-organized learning at Aalborg University

DEFF Research Database (Denmark)

Buus, Lillian; Møller, Brian; Enevoldsen, Lars Peter

and efficient learning model and a trademark of Aalborg University. In 2008 some study programs started using Moodle as their learning platform. In 2011 it was decided that Moodle should be the official learning management system for Aalborg University on-campus. At the presentation we would like to share some...... of the challenges we have encountered when implementing Moodle at Aalborg University whilst keeping the problem-based, project-organized model as the pedagogical foundation....

Design, Explanation, and Evaluation of Training Model Structures Based on Learning Organization--In the Cement Industry with a Nominal Production Capacity of Ten Thousand Tons

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Rahimian, Hamid; Kazemi, Mojtaba; Abbspour, Abbas

2017-01-01

This research aims to determine the effectiveness of training based on learning organization in the staff of cement industry with production capacity over ten thousand tons. The purpose of this study is to propose a training model based on learning organization. For this purpose, the factors of organizational learning were introduced by…

Communities of clinical practice: the social organization of clinical learning.

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Egan, Tony; Jaye, Chrystal

2009-01-01

The social organization of clinical learning is under-theorized in the sociological literature on the social organization of health care. Professional scopes of practice and jurisdictions are formally defined by professional principles and standards and reflected in legislation; however, these are mediated through the day-to-day clinical activities of social groupings of clinical teams. The activities of health service providers typically occur within communities of clinical practice. These are also major sites for clinical curriculum delivery, where clinical students learn not only clinical skills but also how to be health professionals. In this article, we apply Wenger's model of social learning within organizations to curriculum delivery within a health service setting. Here, social participation is the basis of learning. We suggest that it offers a powerful framework for recognizing and explaining paradox and incongruence in clinical teaching and learning, and also for recognizing opportunities, and devising means, to add value to students' learning experiences.

Learning Organization [reviewed article

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Antonoaie, N.

2014-06-01

Full Text Available “The essence of LOs is effective organizational learning, but relevant academic disciplines, such as economics, anthropology, and social psychology, all entail different assumptions about what this might actually mean. Assorted analytical approaches such as population ecology and sociotechnical systems theory offer distinctly different vocabularies for describing what the LO might be or what it might do.” [Snell, 2007] The learning organization (LO is an idealized vision of an organization where the structures, routines, and working practices are open to continuous adaptation and improvement, where the individuals and teams engage in continuous learning, where the norms and values are supportive of continuous learning, and where strategic decision making is informed by and responsive to relevant data analysis and feedback.

Strategic learning in healthcare organizations.

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O'Sullivan, M J

1999-01-01

There is no definitive blueprint for the healthcare organization involved in strategic learning. However, what distinguishes strategic learning institutions is their acknowledgment that they must discover their own paths and solutions rather than blindly follow a detailed strategic mandate from administration. Answers to their most critical implementation and adaptive questions will not flow down ready-made from above, but will be tailored to meet the requirements of their own particular situation. Strategic learning organizations have certain attributes in common in developing their own answers: They continuously experiment rather than seek final solutions. They favor improvisation over forecasts. They formulate new actions rather than defend past ones. They nurture change rather than permanence. They encourage creative conflict rather than tranquillity. They encourage questioning rather than compliance. They expose contradictions rather than hide them (Weick 1977). Most importantly, strategic learning organizations realize that successful strategic change is best undertaken as a process of learning (O'Sullivan 1999). Healthcare organizations can no longer afford the illusion of traditional strategic planning, with its emphasis on bureaucratic controls from the top to the bottom. They must embrace the fundamental truth that most change occurs through processes of learning that occur in many locations simultaneously throughout the organization. The initial step in discovering ways to improve the capability of healthcare organizations is to adapt continuously while fulfilling their mission. Healthcare leaders must create a shared vision of where an institution is heading rather than what the final destination will be, nurture a spirit of experimentation and discovery rather than close supervision and unbending control, and recognize that plans have to be continuously changed and adjusted. To learn means to face the unknown: to recognize that we do not possess all

The Organization of Informal Learning

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Rogoff, Barbara; Callanan, Maureen; Gutiérrez, Kris D.; Erickson, Frederick

2016-01-01

Informal learning is often treated as simply an alternative to formal, didactic instruction. This chapter discusses how the organization of informal learning differs across distinct settings but with important commonalities distinguishing informal learning from formal learning: Informal learning is nondidactic, is embedded in meaningful activity,…

Smart Residential Buildings as Learning Agent Organizations in the Internet of Things

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Schatten Markus

2014-03-01

Full Text Available Background: Smart buildings are one of the major application areas of technologies bound to embedded systems and the Internet of things. Such systems have to be adaptable and flexible in order to provide better services to its residents. Modelling such systems is an open research question. Herein, the question is approached using an organizational modelling methodology bound to the principles of the learning organization. Objectives: Providing a higher level of abstraction for understanding, developing and maintaining smart residential buildings in a more human understandable form. Methods/Approach: Organization theory provides us with the necessary concepts and methodology to approach complex organizational systems. Results: A set of principles for building learning agent organizations, a formalization of learning processes for agents, a framework for modelling knowledge transfer between agents and the environment, and a tailored organizational structure for smart residential buildings based on Nonaka’s hypertext organizational form. Conclusions: Organization theory is a promising field of research when dealing with complex engineering systems

Self-organized Learning Environments

DEFF Research Database (Denmark)

Dalsgaard, Christian; Mathiasen, Helle

2007-01-01

system actively. The two groups used the system in their own way to support their specific activities and ways of working. The paper concludes that self-organized learning environments can strengthen the development of students’ academic as well as social qualifications. Further, the paper identifies......The purpose of the paper is to discuss the potentials of using a conference system in support of a project based university course. We use the concept of a self-organized learning environment to describe the shape of the course. In the paper we argue that educational technology, such as conference...... systems, has a potential to support students’ development of self-organized learning environments and facilitate self-governed activities in higher education. The paper is based on an empirical study of two project groups’ use of a conference system. The study showed that the students used the conference...

Increasing the capacity to learn in organizations

International Nuclear Information System (INIS)

Barker Scott, B.

2007-01-01

This presentation outlines the process of learning in organizations. The learning cycle involves acquiring, applying, reflecting and generalizing. There are three levels of learning: organizational learning, team learning and individual learning. Organizational learning is learning that is embedded into the way we do things through process, norms, systems, structures, strategy etc. It concludes by suggesting that organization must generate ideas with impact and generalize ideas with impact

The Learning Organization: An Undelivered Promise.

Science.gov (United States)

Elkjaer, Bente

2001-01-01

Presents a case study on the development of a learning organization that did not last very long. Suggests that the reason for its demise was the way in which learning in the organization was understood and enacted. The case is evaluated against John Dewey's learning theory. (Contains 24 references.) (DDR)

Peranan Strategic Leadership terhadap Competitive Positioning melalui Organization Learning pada Perusahaan Non Manufaktur di Surabaya

OpenAIRE

Saputra, Lydia Kartika

2015-01-01

This study was accomplished to reveal the role of strategic leadership to competitive positioning through organization learning. Strategic leadership and organization learning owned and implemented within an organization can create even strengthen the competitive positioning of the organization. Through the dimensions each variable can indicate how far the role of strategic leadership and organization learning to competitive positioning.The analysis technique used was outer and inner model by...

Hybrid Model for e-Learning Quality Evaluation

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Suzana M. Savic

2012-02-01

Full Text Available E-learning is becoming increasingly important for the competitive advantage of economic organizations and higher education institutions. Therefore, it is becoming a significant aspect of quality which has to be integrated into the management system of every organization or institution. The paper examines e-learning quality characteristics, standards, criteria and indicators and presents a multi-criteria hybrid model for e-learning quality evaluation based on the method of Analytic Hierarchy Process, trend analysis, and data comparison.

Quality specifications in postgraduate medical e-learning: an integrative literature review leading to a postgraduate medical e-learning model.

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De Leeuw, R A; Westerman, Michiel; Nelson, E; Ket, J C F; Scheele, F

2016-07-08

E-learning is driving major shifts in medical education. Prioritizing learning theories and quality models improves the success of e-learning programs. Although many e-learning quality standards are available, few are focused on postgraduate medical education. We conducted an integrative review of the current postgraduate medical e-learning literature to identify quality specifications. The literature was thematically organized into a working model. Unique quality specifications (n = 72) were consolidated and re-organized into a six-domain model that we called the Postgraduate Medical E-learning Model (Postgraduate ME Model). This model was partially based on the ISO-19796 standard, and drew on cognitive load multimedia principles. The domains of the model are preparation, software design and system specifications, communication, content, assessment, and maintenance. This review clarified the current state of postgraduate medical e-learning standards and specifications. It also synthesized these specifications into a single working model. To validate our findings, the next-steps include testing the Postgraduate ME Model in controlled e-learning settings.

The Dialectical Development of "Storytelling" Learning Organizations: A Case Study of a Public Research University

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Hillon, Yue Cai; Boje, David M.

2017-01-01

Purpose: Calls for dialectical learning process model development in learning organizations have largely gone unheeded, thereby limiting conceptual understanding and application in the field. This paper aims to unify learning organization theory with a new understanding of Hegelian dialectics to trace the development of the storytelling learning…

Organizational Learning in Health Care Organizations

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Savithiri Ratnapalan

2014-02-01

Full Text Available The process of collective education in an organization that has the capacity to impact an organization’s operations, performance and outcomes is called organizational learning. In health care organizations, patient care is provided through one or more visible and invisible teams. These teams are composed of experts and novices from diverse backgrounds working together to provide coordinated care. The number of teams involved in providing care and the possibility of breakdowns in communication and coordinated care increases in direct proportion to sophisticated technology and treatment strategies of complex disease processes. Safe patient care is facilitated by individual professional learning; inter-professional team learning and system based organizational learning, which encompass modified context specific learning by multiple teams and team members in a health care organization. Organizational learning in health care systems is central to managing the learning requirements in complex interconnected dynamic systems where all have to know common background knowledge along with shared meta-knowledge of roles and responsibilities to execute their assigned functions, communicate and transfer the flow of pertinent information and collectively provide safe patient care. Organizational learning in health care is not a onetime intervention, but a continuing organizational phenomenon that occurs through formal and informal learning which has reciprocal association with organizational change. As such, organizational changes elicit organizational learning and organizational learning implements new knowledge and practices to create organizational changes.

Learning-based stochastic object models for characterizing anatomical variations

Science.gov (United States)

Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

2018-03-01

It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

Learning Organization Perceptions in Elementary Education in Terms of Teachers and the Effect of Learning Organization on Organizational Commitment

Science.gov (United States)

Erdem, Mustafa; Ucar, Ibrahim Halil

2013-01-01

In this study, it was tried to determine to what degree the learning organization predicted organizational commitment according to primary school teachers' perceptions. Descriptive survey model was used in this study and 429 teachers were chosen among 2387 teachers who worked in primary schools in Van in 2010-2011 education years and were included…

An Instructional Development Model for Global Organizations: The GOaL Model.

Science.gov (United States)

Hara, Noriko; Schwen, Thomas M.

1999-01-01

Presents an instructional development model, GOaL (Global Organization Localization), for use by global organizations. Topics include gaps in language, culture, and needs; decentralized processes; collaborative efforts; predetermined content; multiple perspectives; needs negotiation; learning within context; just-in-time training; and bilingual…

Lifelong learning of human actions with deep neural network self-organization.

Science.gov (United States)

Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

2017-12-01

Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

Science.gov (United States)

Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

2016-02-01

Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

Problem Solving Model for Science Learning

Science.gov (United States)

Alberida, H.; Lufri; Festiyed; Barlian, E.

2018-04-01

This research aims to develop problem solving model for science learning in junior high school. The learning model was developed using the ADDIE model. An analysis phase includes curriculum analysis, analysis of students of SMP Kota Padang, analysis of SMP science teachers, learning analysis, as well as the literature review. The design phase includes product planning a science-learning problem-solving model, which consists of syntax, reaction principle, social system, support system, instructional impact and support. Implementation of problem-solving model in science learning to improve students' science process skills. The development stage consists of three steps: a) designing a prototype, b) performing a formative evaluation and c) a prototype revision. Implementation stage is done through a limited trial. A limited trial was conducted on 24 and 26 August 2015 in Class VII 2 SMPN 12 Padang. The evaluation phase was conducted in the form of experiments at SMPN 1 Padang, SMPN 12 Padang and SMP National Padang. Based on the development research done, the syntax model problem solving for science learning at junior high school consists of the introduction, observation, initial problems, data collection, data organization, data analysis/generalization, and communicating.

Blended learning models for directing the self-learning activity of “Software Engineering” specialty students

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Vera V. Lyubchenko

2014-12-01

Full Text Available The adoption of Law of Ukraine “On Higher Education” (2014 involves the increase in students’ self-learning activity part in the curriculum. Therefore the self-learning activities’ arrangement in a way augmenting the result quality becomes a top priority task. This research objective consists in elaborating the scenario for organization of the students’ qualitative self-study, based on blended learning models. The author analyzes four blended learning models: the rotation model, flex-model, self-blend model and online driver model, and gives examples of their use. It is shown that first two models are the most suitable for full-time students. A general scenario for the use of blended learning models is described. Although the use of blended learning models causes several difficulties, it also essentially contributes into students’ self-study monitoring and control support.

Online Learning of Industrial Manipulators' Dynamics Models

DEFF Research Database (Denmark)

Polydoros, Athanasios

2017-01-01

, it was compared with multiple other state-of-the-art machine learning algorithms. Moreover, the thesis presents the application of the proposed learning method on robot control for achieving trajectory execution while learning the inverse dynamics models  on-the-fly . Also it is presented the application...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated.  In this thesis, is presented, a novel online machine learning approach  which is able to model both inverse and forward dynamics models of industrial manipulators....... The proposed method belongs to the class of deep learning and exploits the concepts of self-organization, recurrent neural networks and iterative multivariate Bayesian regression. It has been evaluated on multiple datasets captured from industrial robots while they were performing various tasks. Also...

The learning organization and the level of consciousness

OpenAIRE

Chiva Gómez, Ricardo

2017-01-01

Purpose – The purpose of this paper is to analyze learning organization by comparing with other types of organizations. This typology is based on the levels of consciousness and relates each type of organization with a level of learning and an organizational structure. Design/methodology/approach – This is a conceptual paper based on the concept of levels of consciousness. Findings – The paper proposes that learning organization requires the highest level of consciousness. O...

The effect of nurses' use of the principles of learning organization on organizational effectiveness.

Science.gov (United States)

Jeong, Seok Hee; Lee, Taewha; Kim, In Sook; Lee, Myung Ha; Kim, Mi Ja

2007-04-01

This paper is a report of a study to describe the effect on organizational effectiveness of nurses' use of the principles of learning organization. Since Senge proposed the learning organization model in 1990, the principles of learning organization have been considered as a new organizational vision. However, there is little empirical evidence that shows how nurses' use of the principles of learning organization affects organizational effectiveness in healthcare settings. A cross-sectional survey was used and the data were collected in 2003. Participants were 629 professional nurses who had worked full-time for more than 1 year in the general units of nine tertiary medical hospitals in South Korea. A questionnaire was distributed to nurse managers of nine hospitals, who distributed it to 665 nurses, 635 of whom responded (response rate 95.5%). Six returns were discarded due to incomplete responses, leaving 629 for data analysis. There was a statistically significant positive relationship between nurses' use of the principles of learning organization and organizational effectiveness. Hierarchical multiple regression analysis revealed that the concept explained an additional 24.9% of organizational commitment and a further 22.6% of job satisfaction. The learning organization principles of shared vision and team learning were statistically significant predictors for organizational effectiveness. Individual nurses can use the principles of learning organization to enhance organizational effectiveness. Intervention programmes that integrate and strengthen shared vision and team learning may be useful to enhance organizational effectiveness. Further research is required to identify other factors related to the principles of learning organization.

Memetakan Perubahan Organisasi Dalam Desain Learning Organization Pada Usaha Kecil Menengah di Kota Malang

Directory of Open Access Journals (Sweden)

Sugeng Mulyono

2016-06-01

Full Text Available This research aims at analyzing the implementation of learning organization at small and medium enterprises (SMEs; the effects of learning organization on individuals’ ability; the effects of individuals’ ability on SMEs changes; and the effects of learning organization on changes of SMEs. The population of this research is all SMEs located in Malang and the samples are 298 SMEs taken through multi stages sampling. The primary data were collected using a questionare and interviews, whereas the secondary were obtain from relevant documents. The collected data were analyzed using descriptive and structural equational modelling (SEM. The results show that learning organization has a significant positive effect on individuals’ ability; the individuals’ ability has a significant positive effect on changes of SMEs; and learning organization has a significant positive effect on changes of SMEs, as indicated by C.R > 2 and value of P < 0,05.

Prediction of Employee Turnover in Organizations using Machine Learning Algorithms

OpenAIRE

Rohit Punnoose; Pankaj Ajit

2016-01-01

Employee turnover has been identified as a key issue for organizations because of its adverse impact on work place productivity and long term growth strategies. To solve this problem, organizations use machine learning techniques to predict employee turnover. Accurate predictions enable organizations to take action for retention or succession planning of employees. However, the data for this modeling problem comes from HR Information Systems (HRIS); these are typically under-funded compared t...

FEATURES OF ORGANIZATION OF BLENDED LEARNING IN PREPARATION OF FUTURE TEACHERS OF INFORMATICS

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Inna Stoliarenko

2015-10-01

Full Text Available The term "blended learning" described by domestic and foreign scientists is considered in the article. A number of advantages of blended learning have been marked out in comparison with traditional one: flexibility, learning personification, increase of motivation of students to training, variety of forms of arrangement of educational process and forms of presentation of teaching material and increase of efficiency of activity of the teacher. A set of key competencies a teacher should possess to support effective activity in the mixed educational environment has been analyzed. The scientists of the Learning Accelerator organization engaged in support of introduction of blended learning in American schools presented it. It is determined that its main difference from a teacher who uses traditional methods and training forms – desire to experiment, introducing various innovative pedagogical technologies in educational process to achieve maximum result. There is also a desire to create favorable conditions for successful learning of each student considering strong and weak sides. The scientists of Clayton Christensen Institute designed the models of organization of blended learning. These models were analyzed. Two expedient models for implementation in higher school, in particular, in preparation of future teachers of informatics have been defined: station rotation and "flipped classroom".

Limits of the Learning Organization: A Critical Look.

Science.gov (United States)

Fenwick, Tara J.

The development of the "learning organization" may be traced to three converging trends: the tradition of organizational development; economic shifts to globalization, deregulation, and information-based industry; and total quality management. Learning organizations are generally characterized as follows: organizations that create…

Analisis Tingkat Motivasi Siswa Dalam Pembelajaran IPA Model Advance Organizer Berbasis Proyek

Directory of Open Access Journals (Sweden)

Tasiwan -

2014-04-01

Full Text Available atur kemajuan (advance organizer berbasis proyek. Sampel penelitian dipilih secara acak. Pada kelas  eksperimen diterapkan model pembelajaran advance organizer berbasis proyek sedangkan pada kelas kontrol diterapkan pembelajaran langsung (direct instruction tanpa advance organizer. Sebelum pembelajaran di kelas, siswa eksperimen dikelompokkan menjadi 8 kelompok yang terdiri atas 4 – 5 siswa. Setiap kelompok ditugaskan untuk merealisasikan proyek bel listrik, rangkaian arus seri – paralel, dan tuas. Produk proyek digunakan dalam pembelajaran dikelas sebagai advance organizer. Data diperoleh melalui observasi partisipatif, penilaian produk, peta konsep, laporan eksperimen, dan angket. Instrumen motivasi menggunakan skala motivasi ARCS. Hasil penelitian menunjukkan bahwa kelas eksperimen memiliki tingkat motivasi lebih baik dalam aspek perhatian, relevansi, kepercayaan diri, dan kepuasan pembelajaran dengan rata – rata tingkat motivasi sebesar 77,20, sedangkan tanpa advance organizer berbasis proyek sebesar 71,10. Disarankan siswa diberikan kemandirian penuh dalam proyek. This study was conducted to analyze the level of student motivation in learning science through models of advance organizer  based project . Samples were selected at random . In the experimental class advance organizer applied learning model based on a class project while learning control direct instruction without advance organizer . Prior learning in the classroom , students are grouped into 8 experimental groups consisting of 4-5 students . Each group was assigned a project to realize an electric bell , the circuit current series - parallel , and lever . Products used in a learning class project as advance organizer . The data obtained through participant observation , assessment product , concept maps , experimental reports , and questionnaires . Motivation instrument using ARCS motivation scale . Results showed that the experimental class had better motivation level

Manager’s decision-making in organizations –empirical analysis of bureaucratic vs. learning approach

OpenAIRE

Jana Frenová; Daniela Hrehová; Eva Bolfíková

2010-01-01

The paper is focused on the study of manager’s decision-making with respect to the basic model of learning organization, presented by P. Senge as a system model of management. On one hand, the empirical research was conducted in connection with key dimensions of organizational learning such as: 1. system thinking, 2. personal mastery, 3. mental models, 4. team learning, 5. building shared vision and 6. dynamics causes. On the other hand, the research was connected with the analysis of the bur...

PENERAPAN MODEL PEMBELAJARAN ADVANCE ORGANIZER BERVISI SETS TERHADAP PENINGKATAN PENGUASAAN KONSEP KIMIA

Directory of Open Access Journals (Sweden)

Ilam Pratitis

2015-11-01

Full Text Available This study aims to determine the effect of the application of learning model with advance organizer envisions SETS to increase mastery of chemistry concepts in the high school in Semarang on buffer solution material. The design used in this research is the design of the control group non equivalent. Sampling was conducted with a purposive sampling technique, and obtained a XI 6 science grade as experimental class and class XI 5 science grade as control class. Data collection method used is the method of documentation, testing, observation, and questionnaires. The results showed that the average cognitive achievement of experimental class was 84, while the control class was 82. The result of data analysis showed that the effect of the application of learning model with advance organizer envisions SETS was able to increase the mastery of chemical concepts of 4%, with a correlation rate of 0.2. Based on the results, it can be concluded that the learning model with advance organizer envisions SETS had positive effect of increasing mastery of the concept of chemistry on buffer solution material. The advice given is learning model with organizer envisions SETS should also be applied to other chemistry materials. This is of course accompanied by a change in order to suit the needs of its effect on learning outcomes in the form of concept mastery of chemistry to be more increased.Keywords: Advance Organizer, Buffer Solution, Concept Mastery, SETS

Organizational Learning Culture, Learning Transfer Climate and Perceived Innovation in Jordanian Organizations

Science.gov (United States)

Bates, Reid; Khasawneh, Samer

2005-01-01

This paper examines the relationship between organizational learning culture, learning transfer climate, and organizational innovation. The objective was to test the ability of learning organization culture to account for variance in learning transfer climate and subsequent organizational innovation, and to examine the role of learning transfer…

Learning Organic Chemistry Through Natural Products

Indian Academy of Sciences (India)

Higher Learning. ... The Series on "learning Organic Chemistry Through Natural Products". Nature is a remarkable ... skeletal structure to the interior electronic configu- ration ... Among the advantages of this approach are the fact that unlike the.

Learning Organization and Innovative Behavior: The Mediating Effect of Work Engagement

Science.gov (United States)

Park, Yu Kyoung; Song, Ji Hoon; Yoon, Seung Won; Kim, Jungwoo

2014-01-01

Purpose: The purpose of this study is to investigate the mediating effect of work engagement on the relationship between learning organization and innovative behavior. Design/methodology/approach: This study used surveys as a data collection tool and implemented structural equation modeling for empirically testing the proposed research model.…

The "Organization" as an Interdisciplinary Learning Zone: Using a Strategic Game to Integrate Learning about Supply Chain Management and Advertising

Science.gov (United States)

Arora, Anshu Saxena

2012-01-01

Purpose: The research study seeks to explore the relationship among strategic gaming, the learning organization model and approach, and transfer of learning as key success strategies for improved individual and organizational performance and sustainable competitive advantage. This research aims to identify and elaborate on the strategic…

Research on Model of Student Engagement in Online Learning

Science.gov (United States)

Peng, Wang

2017-01-01

In this study, online learning refers students under the guidance of teachers through the online learning platform for organized learning. Based on the analysis of related research results, considering the existing problems, the main contents of this paper include the following aspects: (1) Analyze and study the current student engagement model.…

The Learning Organization and the Level of Consciousness

Science.gov (United States)

Chiva, Ricardo

2017-01-01

Purpose: The purpose of this paper is to analyze learning organization by comparing with other types of organizations. This typology is based on the levels of consciousness and relates each type of organization with a level of learning and an organizational structure. Design/methodology/approach: This is a conceptual paper based on the concept of…

Cross-organism learning method to discover new gene functionalities.

Science.gov (United States)

Domeniconi, Giacomo; Masseroli, Marco; Moro, Gianluca; Pinoli, Pietro

2016-04-01

Knowledge of gene and protein functions is paramount for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. Analyses for biomedical knowledge discovery greatly benefit from the availability of gene and protein functional feature descriptions expressed through controlled terminologies and ontologies, i.e., of gene and protein biomedical controlled annotations. In the last years, several databases of such annotations have become available; yet, these valuable annotations are incomplete, include errors and only some of them represent highly reliable human curated information. Computational techniques able to reliably predict new gene or protein annotations with an associated likelihood value are thus paramount. Here, we propose a novel cross-organisms learning approach to reliably predict new functionalities for the genes of an organism based on the known controlled annotations of the genes of another, evolutionarily related and better studied, organism. We leverage a new representation of the annotation discovery problem and a random perturbation of the available controlled annotations to allow the application of supervised algorithms to predict with good accuracy unknown gene annotations. Taking advantage of the numerous gene annotations available for a well-studied organism, our cross-organisms learning method creates and trains better prediction models, which can then be applied to predict new gene annotations of a target organism. We tested and compared our method with the equivalent single organism approach on different gene annotation datasets of five evolutionarily related organisms (Homo sapiens, Mus musculus, Bos taurus, Gallus gallus and Dictyostelium discoideum). Results show both the usefulness of the perturbation method of available annotations for better prediction model training and a great improvement of the cross-organism models with respect to the single-organism ones

Learning in Organizations - an Object Relations Perspective

DEFF Research Database (Denmark)

Andersen, Anders Siig

Learning in organizations – an object relations perspective As a researcher with a primary interest in the study of learning environments in organizations I have conducted a number of empirical research projects primarily concerning work places in the state sector. The aim of the research has been...... of organizations as learning environments for the employees. Theoretically I draw on object relations theory. Within this tradition the theoretical point of departure is twofold: the study of work conditions in hospitals carried out by Menzies (1975) and Hinschelwood & Skogstad (2000). With regard to the first...... positive and negative impact do they have with respect to the staff itself? With regard to Hinschelwood & Skogstad (2000) they are introduced to further develop and contrast Menzies’ theoretical ideas. Instead of only emphasizing the connection between the work organization and the defence techniques...

Profile of students’ learning styles in Sorogan-Bandongan organic chemistry lecture

Science.gov (United States)

Rinaningsih; Kadarohman, A.; Firman, H.; Sutoyo

2018-05-01

Individual-based independent curriculum as one of target of national education of Indonesia in XXI century can be achieved with the implementation of Sorogan-Bandongan model. This kind of learning model highly facilitates students in understanding various concepts with their own, respective learning styles. This research aims to perceive the effectiveness of Sorogan-Bandongan in increasing the mastery of concept in various learning styles. The samples of this research are students majoring in chemistry amounted to 31 students. Using pre-test and post-test instrument, data are analyzed in descriptive-qualitative method. Based on the result of the data analysis, it is found that 16% of students have mathematical/logical learning style, 22.6% naturalist, 9.7% visual/spatial, 13% kinesthetic, 6% linguistic, 13% intrapersonal, 9.7% interpersonal, and 10% musical. After the implementation of Sorogan-Bandongan model in the Organic Chemistry lectures, improvement of classical learning outcomes as 11,07 is obtained. Six out of eight learning styles of students experienced increase in mastery of concept, where 7 students have the naturalist learning style, 4 students experienced decrease in mastery of concept while 1 student is stagnant (0); meanwhile, 2 out of 4 students that have the interpersonal learning style experienced decrease in mastery of concept.

General informatics teaching with B-Learning teaching model

Directory of Open Access Journals (Sweden)

Nguyen The Dung

2018-03-01

Full Text Available Blended learning (B-learning, a combination of face-to-face teaching and E-learning-supported-teaching in an online course, and Information and Communication Technology (ICT tools have been studied in recent years. In addition, the use of this teaching model is effective in teaching and learning conditions in which some certain subjects are appropriate for the specific teaching context. As it has been a matter of concern of the universities in Vietnam today, deep studies related to this topic is crucial to be conducted. In this article, the process of developing online courses and organizing teaching for the General Informatics subject for first-year students at the Hue University of Education with B-learning teaching model will be presented. The combination of 60% face-to-face and 40% online learning.

Measuring organizational learning. Model testing in two Romanian universities

OpenAIRE

Alexandra Luciana Guţă

2014-01-01

The scientific literature associates organizational learning with superior organization performance. If we refer to the academic environment, we appreciate that it can develop and reach better levels of performance through changes driven from the inside. Thus, through this paper we elaborate on a conceptual model of organizational learning and we test the model on a sample of employees (university teachers and researchers) from two Romanian universities. The model comprises the process of org...

FACTORS INFLUENCING VICARIOUS LEARNING MECHANISM EFFECTIVENESS WITHIN ORGANIZATIONS

OpenAIRE

JOHN R. VOIT; COLIN G. DRURY

2013-01-01

As organizations become larger it becomes increasingly difficult to share lessons-learned across their disconnected units allowing individuals to learn vicariously from each other's experiences. This lesson-learned information is often unsolicited by the recipient group or individual and required an individual or group to react to the information to yield benefits for the organization. Data was collected using 39 interviews and 582 survey responses that proved the effects of information usefu...

Are All Hands-On Activities Equally Effective? Effect of Using Plastic Models, Organ Dissections, and Virtual Dissections on Student Learning and Perceptions

Science.gov (United States)

Lombardi, Sara A.; Hicks, Reimi E.; Thompson, Katerina V.; Marbach-Ad, Gili

2014-01-01

This study investigated the impact of three commonly used cardiovascular model-assisted activities on student learning and student attitudes and perspectives about science. College students enrolled in a Human Anatomy and Physiology course were randomly assigned to one of three experimental groups (organ dissections, virtual dissections, or…

Project based learning in organizations: towards a methodology for learning in groups

NARCIS (Netherlands)

Poell, R.F.; Krogt, F.J. van der

2003-01-01

This article introduces a methodology for employees in organizations to set up and carry out their own group learning projects. It is argued that employees can use project-based learning to make their everyday learning more systematic at times, without necessarily formalizing it. The article

Project-based learning in organizations : Towards a methodology for learning in groups

NARCIS (Netherlands)

Poell, R.F.; van der Krogt, F.J.

2003-01-01

This article introduces a methodology for employees in organizations to set up and carry out their own group learning projects. It is argued that employees can use project-based learning to make their everyday learning more systematic at times, without necessarily formalizing it. The article

Intergenerational learning in organizations

NARCIS (Netherlands)

dr. Donald Ropes

2013-01-01

Purpose – The purpose of this paper is to explore the concept of intergenerational learning as a way for organizations to deal with an ageing worker population in a positive and constructive way. Design/methodology/approach – The paper employs a thematic synthesis of qualitative literature and

Lessons Learned from 2 Decades of Modelling Forest Dead Organic Matter and Soil Carbon at the National Scale

Science.gov (United States)

Shaw, C.; Kurz, W. A.; Metsaranta, J.; Bona, K. A.; Hararuk, O.; Smyth, C.

2017-12-01

The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) is a forest carbon budget model that operates on individual stands. It is applied from regional to national-scales in Canada for national and international reporting of GHG emissions and removals and in support of analyses of forest sector mitigation options and other scientific and policy questions. This presentation will review the history and continuous improvement process of representations of dead organic matter (DOM) and soil carbon modelling. Early model versions in which dead organic matter (DOM) pools only included litter, downed deadwood and soil, to the current version where these pools are estimated separately to better compare model estimates against field measurements, or new pools have been added. Uncertainty analyses consistently point at soil C pools as large sources of uncertainty. With the new ground plot measurements from the National Forest Inventory, and with a newly compiled forest soil carbon database, we have recently completed a model data assimilation exercise that helped reduce parameter uncertainties. Lessons learned from the continuous improvement process will be summarised and we will discuss how model modification have led to improved representation of DOM and soil carbon dynamics. We conclude by suggesting future research priorities that can advance DOM and soil carbon modelling in Canadian forest ecosystems.

Learning Organization Dimensions of the Sri Lanka Army

Science.gov (United States)

Dahanayake, Nishada Dhananjaya; Gamlath, Sharmila

2013-01-01

Purpose: This study intends to investigate the extent to which the Sri Lanka Army can be described as a learning organization. Design/methodology/approach: The main tool of analysis used was the Dimensions of the Learning Organization Questionnaire (DLOQ) developed by Marsick and Watkins, with the exclusion of the sections on financial and…

Prototype-based models in machine learning.

Science.gov (United States)

Biehl, Michael; Hammer, Barbara; Villmann, Thomas

2016-01-01

An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of potentially high-dimensional, complex datasets. We discuss basic schemes of competitive vector quantization as well as the so-called neural gas approach and Kohonen's topology-preserving self-organizing map. Supervised learning in prototype systems is exemplified in terms of learning vector quantization. Most frequently, the familiar Euclidean distance serves as a dissimilarity measure. We present extensions of the framework to nonstandard measures and give an introduction to the use of adaptive distances in relevance learning. © 2016 Wiley Periodicals, Inc.

Learning in Youth Organizing

Science.gov (United States)

Kirshner, Ben

2014-01-01

This response identifies several strengths of the article, "Pushing the Boundaries: What Youth Organizers at Boston's Hyde Square Task Force Have to Teach Us about Civic Engagement" and draws connections to recent developments in sibling fields, including social and emotional learning and internet activism. These developments offer ideas…

Manager’s decision-making in organizations –empirical analysis of bureaucratic vs. learning approach

Directory of Open Access Journals (Sweden)

Jana Frenová

2010-06-01

Full Text Available The paper is focused on the study of manager’s decision-making with respect to the basic model of learning organization, presented by P. Senge as a system model of management. On one hand, the empirical research was conducted in connection with key dimensions of organizational learning such as: 1. system thinking, 2. personal mastery, 3. mental models, 4. team learning, 5. building shared vision and 6. dynamics causes. On the other hand, the research was connected with the analysis of the bureaucratic logic of decision-making process, characterized by non-functional stability, inflexibility, individualism, power, authority and hierarchy, centralization, vagueness, fragmentariness. The objective of the research was to analyse to what extent manager’s decision–making is based on bureaucratic tools or organizational learning in either complex problem-solving or non-problemsolving decision-making. (MANOVA, method of the repeated measure, intersubject factor – situation: 1. non problematic, 2. problematic. The conclusion of analysis is that there are significant differences in character of solving of problem situation and non-problem situation decision-making: the bureaucratic attributes of decision-making are more intensive in problematic situations while learning approach is more actual in non-problematic situations. The results of our analysis have shown that managers who apply the learning organization attributes in their decision-making. are more successful in problem-solving.

The MVP Model as an Organizing Framework for Neuroscience Findings Related to Learning

Science.gov (United States)

Zakrajsek, Todd M.

2017-01-01

This chapter describes the ways in which the MVP model relates to recent research on neuroscience and learning, and demonstrates how those relationships may be used to better understand physiological impacts on motivation, and to facilitate improved learning.

Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network.

Science.gov (United States)

Del Papa, Bruno; Priesemann, Viola; Triesch, Jochen

2017-01-01

Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions - matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model's performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN's spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences.

FACILITATING THE STATISTIC’S LEARNING: A B-LEARNING MODEL FOR OUR STUDENTS

Directory of Open Access Journals (Sweden)

Miguel Ángel Montero

2011-05-01

Full Text Available The experience which we count with in the university education, the development of the ICT (Information and Communications Technology, the integration in the ESSE, the new qualifications (or Grades and mainly the desire to improve push us to innovate and to put into practice new methodologies in the teaching and learning of the subjects of Mathematics and Statistic assigned to our department. These methods totally renovate the lecturer’s roll and the traditional teaching, introducing multimedia tools, support platforms and new resources that provide students an autonomy which before they did not have, modifying the organization of time and space, increasing modalities and strategies of teaching-learning-tutorization and therefore developing more flexible models. It is tried to facilitate the learning of these subjects, providing a model b-learning, a comple- ment or alternative to the attendance classes, reinforcing the student’s active self-training.

E-learning and the Educational Organizations Structure Reengineering (EOSR

Directory of Open Access Journals (Sweden)

Osama Alshara

2007-06-01

Full Text Available There are many calls for innovative learning methods that utilize advanced technologies. However, we will raise fundamental questions that look deep into the future of the educational organization. Can the educational institute survive without adapting learning technologies? Would the educational institute succeed in adapting new learning technologies without changing its organizational structure and processes? We claim that the answer to both questions is no. Our research will present the need for edu-cational institutes to incorporate learning technologies and focuses on the demand for the educational organization structure reengineering as a basic requirement for the suc-cess of incorporating learning technologies. Our study ex-plores the faculty requirements and policies and procedures of educational institutes in the UAE.The paper concludes with some discussions on findings from a case study of the need of educational organization struc-ture reengineering as a basic requirement for incorporating learning technologies.

Learning while (re)configuring: Business model innovation processes in established firms.

Science.gov (United States)

Berends, Hans; Smits, Armand; Reymen, Isabelle; Podoynitsyna, Ksenia

2016-08-01

This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: "drifting" starts with an emphasis on experiential learning and shifts later to cognitive search; "leaping," in contrast, starts with an emphasis on cognitive search and shifts later to experiential learning. Both drifting and leaping can result in radical business model innovations, while their occurrence depends on whether a new business model takes off from an existing model and when it goes into operation. We discuss the implications of these findings for theory on business models and organizational learning.

Crisis-induced learning in public sector organizations

NARCIS (Netherlands)

Deverell, E.C.

2010-01-01

How do public organizations manage crises? How do public organizations learn from crises? These seemingly basic questions still pose virtual puzzles for crisis management researchers. This dissertation sheds light on the problems regarding the lack of knowledge on how public organizations manage and

Intergenerational Learning in Organizations

Science.gov (United States)

Ropes, Donald

2013-01-01

Purpose: The purpose of this paper is to explore the concept of intergenerational learning as a way for organizations to deal with an ageing worker population in a positive and constructive way. Design/methodology/approach: The paper employs a thematic synthesis of qualitative literature and considers all types of sources including quantitative…

Global assessment of soil organic carbon stocks and spatial distribution of histosols: the Machine Learning approach

Science.gov (United States)

Hengl, Tomislav

2016-04-01

Preliminary results of predicting distribution of soil organic soils (Histosols) and soil organic carbon stock (in tonnes per ha) using global compilations of soil profiles (about 150,000 points) and covariates at 250 m spatial resolution (about 150 covariates; mainly MODIS seasonal land products, SRTM DEM derivatives, climatic images, lithological and land cover and landform maps) are presented. We focus on using a data-driven approach i.e. Machine Learning techniques that often require no knowledge about the distribution of the target variable or knowledge about the possible relationships. Other advantages of using machine learning are (DOI: 10.1371/journal.pone.0125814): All rules required to produce outputs are formalized. The whole procedure is documented (the statistical model and associated computer script), enabling reproducible research. Predicted surfaces can make use of various information sources and can be optimized relative to all available quantitative point and covariate data. There is more flexibility in terms of the spatial extent, resolution and support of requested maps. Automated mapping is also more cost-effective: once the system is operational, maintenance and production of updates are an order of magnitude faster and cheaper. Consequently, prediction maps can be updated and improved at shorter and shorter time intervals. Some disadvantages of automated soil mapping based on Machine Learning are: Models are data-driven and any serious blunders or artifacts in the input data can propagate to order-of-magnitude larger errors than in the case of expert-based systems. Fitting machine learning models is at the order of magnitude computationally more demanding. Computing effort can be even tens of thousands higher than if e.g. linear geostatistics is used. Many machine learning models are fairly complex often abstract and any interpretation of such models is not trivial and require special multidimensional / multivariable plotting and data mining

Learning Networks: connecting people, organizations, autonomous agents and learning resources to establish the emergence of effective lifelong learning

NARCIS (Netherlands)

Koper, Rob; Sloep, Peter

2003-01-01

Koper, E.J.R., Sloep, P.B. (2002) Learning Networks connecting people, organizations, autonomous agents and learning resources to establish the emergence of effective lifelong learning. RTD Programma into Learning Technologies 2003-2008. More is different… Heerlen, Nederland: Open Universiteit

A Model of Self-Organizing Head-Centered Visual Responses in Primate Parietal Areas

Science.gov (United States)

Mender, Bedeho M. W.; Stringer, Simon M.

2013-01-01

We present a hypothesis for how head-centered visual representations in primate parietal areas could self-organize through visually-guided learning, and test this hypothesis using a neural network model. The model consists of a competitive output layer of neurons that receives afferent synaptic connections from a population of input neurons with eye position gain modulated retinal receptive fields. The synaptic connections in the model are trained with an associative trace learning rule which has the effect of encouraging output neurons to learn to respond to subsets of input patterns that tend to occur close together in time. This network architecture and synaptic learning rule is hypothesized to promote the development of head-centered output neurons during periods of time when the head remains fixed while the eyes move. This hypothesis is demonstrated to be feasible, and each of the core model components described is tested and found to be individually necessary for successful self-organization. PMID:24349064

Learning while (re)configuring: Business model innovation processes in established firms

Science.gov (United States)

Berends, Hans; Smits, Armand; Reymen, Isabelle; Podoynitsyna, Ksenia

2016-01-01

This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: “drifting” starts with an emphasis on experiential learning and shifts later to cognitive search; “leaping,” in contrast, starts with an emphasis on cognitive search and shifts later to experiential learning. Both drifting and leaping can result in radical business model innovations, while their occurrence depends on whether a new business model takes off from an existing model and when it goes into operation. We discuss the implications of these findings for theory on business models and organizational learning. PMID:28596704

The Relationship between Learning Organization Dimensions and Library Performance

Science.gov (United States)

Haley, Qing Kong

2010-01-01

The purpose of this research was to examine the relationship between learning organization dimensions and academic library performance. It studied whether differences existed in learning organization dimensions given the predictor variables of performance indicators, library resources, and demographics of the academic library. This research…

Learning achievements of farmers during the transition to market-oriented organic agriculture in rural Uganda

Directory of Open Access Journals (Sweden)

Amos Owamani

2010-04-01

Full Text Available Organic agriculture requires farmers with the ability to develop profitable agro-enterprises on their own. By drawing on four years of experiences with the Enabling Rural Innovation approach in Uganda, we outline how smallholder farmers transition to organic agriculture and, at the same time, increase their entrepreneurial skills and competences through learning. In order to document this learning we operationalised the Kirkpatrick learning evaluation model, which subsequently informed the collection of qualitative data in two study sites. Our analysis suggests that the Enabling Rural Innovation approach helps farmers to develop essential capabilities for identifying organic markets and new organic commodities, for testing these organic commodities under varying organic farm management scenarios, and for negotiating contracts with organic traders. We also observed several obstacles that confront farmers’ transition to organic agriculture when using the Enabling Rural Innovation approach. These include the long duration of agronomic experimentation and seed multiplication, expensive organic certification procedures and the absence of adequate mechanism for farmers to access crop finance services. Despite prevailing obstacles we conclude that the Enabling Rural Innovation approach provides a starting point for farmers to develop entrepreneurial competences and profitable agro-enterprises on their own.

Learning of Cross-Sectional Anatomy Using Clay Models

Science.gov (United States)

Oh, Chang-Seok; Kim, Ji-Young; Choe, Yeon Hyeon

2009-01-01

We incorporated clay modeling into gross anatomy and neuro-anatomy courses to help students understand cross-sectional anatomy. By making clay models, cutting them and comparing cut surfaces to CT and MR images, students learned how cross-sectional two-dimensional images were created from three-dimensional structure of human organs. Most students…

Organizing Blended Learning for Students on the Basis of Learning Roadmaps

Science.gov (United States)

Andreeva, Nadezhda M.; Artyukhov, Ivan P.; Myagkova, Elena G.; Pak, Nikolay I.; Akkasynova, Zhamilya K.

2018-01-01

The relevance of the problem of organizing blended learning for students is related to the sharpening contradiction between the high potential of this educational technology and the poor methodological elaboration of its use in actual learning practice. With regard to this, the paper is aimed at providing grounds for the methodological system of…

Challenges of information security incident learning: An industrial case study in a Chinese healthcare organization.

Science.gov (United States)

He, Ying; Johnson, Chris

2017-12-01

Security incidents can have negative impacts on healthcare organizations, and the security of medical records has become a primary concern of the public. However, previous studies showed that organizations had not effectively learned lessons from security incidents. Incident learning as an essential activity in the "follow-up" phase of security incident response lifecycle has long been addressed but not given enough attention. This paper conducted a case study in a healthcare organization in China to explore their current obstacles in the practice of incident learning. We interviewed both IT professionals and healthcare professionals. The results showed that the organization did not have a structured way to gather and redistribute incident knowledge. Incident response was ineffective in cycling incident knowledge back to inform security management. Incident reporting to multiple stakeholders faced a great challenge. In response to this case study, we suggest the security assurance modeling framework to address those obstacles.

Are all hands-on activities equally effective? Effect of using plastic models, organ dissections, and virtual dissections on student learning and perceptions.

Science.gov (United States)

Lombardi, Sara A; Hicks, Reimi E; Thompson, Katerina V; Marbach-Ad, Gili

2014-03-01

This study investigated the impact of three commonly used cardiovascular model-assisted activities on student learning and student attitudes and perspectives about science. College students enrolled in a Human Anatomy and Physiology course were randomly assigned to one of three experimental groups (organ dissections, virtual dissections, or plastic models). Each group received a 15-min lecture followed by a 45-min activity with one of the treatments. Immediately after the lesson and then 2 mo later, students were tested on anatomy and physiology knowledge and completed an attitude survey. Students who used plastic models achieved significantly higher overall scores on both the initial and followup exams than students who performed organ or virtual dissections. On the initial exam, students in the plastic model and organ dissection treatments scored higher on anatomy questions than students who performed virtual dissections. Students in the plastic model group scored higher than students who performed organ dissections on physiology questions. On the followup exam, when asked anatomy questions, students in the plastic model group scored higher than dissection students and virtual dissection students. On attitude surveys, organ dissections had higher perceived value and were requested for inclusion in curricula twice as often as any other activity. Students who performed organ dissections were more likely than the other treatment groups to agree with the statement that "science is fun," suggesting that organ dissections may promote positive attitudes toward science. The findings of this study provide evidence for the importance of multiple types of hands-on activities in anatomy laboratory courses.

Relationships among Organizational Commitment, Job Satisfaction, and Learning Organization Culture in One Korean Private Organization

Science.gov (United States)

Lim, Taejo

2010-01-01

The purpose of this study is to identify dynamic relationships among organizational commitment, job satisfaction, and learning organization culture in a Korean private company. Using a sample of 669 employees from five subsidiaries of a Korean conglomerate, this research found that learning organization culture is moderately and positively related…

Learning Organizations. Studiu exploratoriu asupra Consiliilor Judeţene din România

Directory of Open Access Journals (Sweden)

Diana GHIURA

2012-12-01

Full Text Available This article is the result of an ample study centered on the concept of learning organizations, more precisely on the degree in which Romanian County Councils are learning organizations. In order to analyze this, a research instrument has been sent to every County Council. This tool has been developed by three Harvard professors: David A. Garvin, Amy C. Edmondson and Francesca Gino who also published, in 2008, an article in Harvard Business Review ‘Is Yours A Learning Organization?’. Their article is fundamental for this study. Approximately 26 out of 41 County Councils participated to the study and the findings are summarized in this article. The results were really interesting and according to them, Romanian County Councils are learning organizations only in terms of leadership that encourages learning. Regarding the other two blocks – learning environment and learning processes, the findings revealed that the County Councils act like learning organizations in a very small degree. As a consequence, the organizations that participated to the study still have many things to improve in order to become learning organizations.

The NHS as a learning organization: aspirations beyond the rainbow?

Science.gov (United States)

Timpson, J

1998-09-01

It is the intention of this paper to review the issues and challenges organizations face when aspiring to embrace and enact the tenets of a learning organization; and in particular the perceived impact on management strategy, structure and leadership styles. The paper is predicated on the premise that learning and knowledge act as vital strategic resources, crucial not only to organizations in terms of competitive advantage but to ethical enterprise per se. Modern life is characterized by change, against the backdrop of this continual turmoil, organizational learning has emerged as a dominant theme within contemporary management theory, with many commentators increasingly locating the capacity of an aspiring organization to accommodate the ethos of organizational learning, as the vital component in ensuring enduring efficiency, innovation and competitiveness. However, the utility of such learning needs to be scrutinized and evaluated in terms of service need and expectation. The paper will expand upon wider theoretical debates extant within the literature, by considering the concept and utility of the learning organization with specific reference to management reform extant within the British National Health Service (NHS). During the course of the review the various the theoretical positions contributing to the notion of the learning organization will be analysed, the practical ramifications of which will be examined in the context of reflective practice, clinical supervision and the wider cultural background of nursing and the NHS. The paper concludes that the NHS needs to reorientate management perspectives to focus attention more acutely on systems which are deliberately designed to facilitate shared learning, to unravel the ambiguities of organizational life, to affirm management belief in the nursing contribution and to achieve an as yet unrealized potential in terms of patient care and advanced nursing practice.

Learning by Doing versus Learning by Viewing: Three Experimental Comparisons of Learner-Generated versus Author-Provided Graphic Organizers

Science.gov (United States)

Stull, Andrew T.; Mayer, Richard E.

2007-01-01

Do students learn more deeply from a passage when they attempt to construct their own graphic organizers (i.e., learning by doing) than when graphic organizers are provided (i.e., learning by viewing)? In 3 experiments, learners were tested on retention and transfer after reading a passage with author-provided graphic organizers or when asked to…

Project organized Problem-based learning in Distance Education

DEFF Research Database (Denmark)

Jensen, Lars Peter; Helbo, Jan; Knudsen, Morten

2002-01-01

Project organized problem based learning is a successful concept for on-campus engineering education at Aalborg University. Recently this "Aalborg concept" has been used in networked distance education as well. This paper describes the experiences from two years of Internet-mediated project work...... in a new Master of Information Technology education. The main conclusions are, that the project work is a strong learning motivator, enhancing peer collaboration, for off-campus students as well. However, the concept cannot be directly transferred to off-campus learning. In this paper, the main problems...... experienced with group organized project work in distance education are described, and some possible solutions are listed....

Project-Organized Problem-Based Learning in Distance Education

DEFF Research Database (Denmark)

Jensen, Lars Peter; Helbo, Jan; Knudsen, Morten

2003-01-01

Project organized problem based learning is a successful concept for on-campus engineering education at Aalborg University. Recently this "Aalborg concept" has been used in networked distance education as well. This paper describes the experiences from two years of Internet-mediated project work...... in a new Master of Information Technology education. The main conclusions are, that the project work is a strong learning motivator, enhancing peer collaboration, for off-campus students as well. However, the concept cannot be directly transferred to off-campus learning. In this paper, the main problems...... experienced with group organized project work in distance education are described, and some possible solutions are listed....

Action errors, error management, and learning in organizations.

Science.gov (United States)

Frese, Michael; Keith, Nina

2015-01-03

Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.

Organic marketing initiatives and rural development - lessons learned for the organic industry

DEFF Research Database (Denmark)

Kristensen, Niels Heine; Kujala, Jouni

2005-01-01

Kujala J, Kristensen NH, (2005): Organic marketing initiatives and rural development - lessons learned for the organic industry. Article in "Organic farming for a new millennium - status and future challenges". Published by Nordic Association of Agricultural Scientists (NJF). Swedish University...... of Agricultural Sciences Alnarp, Sweden. NJF-Seminar 369, June 15-17, 2005. Electronic version available at www.njf.nu. ISSN 1653-2015...

Teaching Giants to Learn: Lessons from Army Learning in World War II

Science.gov (United States)

Visser, Max

2017-01-01

Purpose: This paper aims to discuss the "truism" that learning organizations cannot be large organizations and, conversely, that large organizations cannot be learning organizations. This paper analyzes learning in the German and US armies in the Second World War, based on a four-dimensional model of the learning organization.…

Implementation of Learning Organization Components in Ardabil Social Security Hospital

OpenAIRE

Azadeh Zirak

2015-01-01

This study aimed to investigate the implementation of learning organization characteristics based on Marquardt systematic model in Ardabil Social Security Hospital. The statistical population of this research was 234 male and female employees of Ardabil Social Security Hospital. For data collection, Marquardt questionnaire was used in the present study which its validity and reliability had been confirmed. Statistical analysis of hypotheses based on independent samples t-test showed that lear...

Learning Organizations in High Reliability Industries

International Nuclear Information System (INIS)

Schwalbe, D.; Wächter, C.

2016-01-01

Full text: Humans make mistakes. Sometimes we learn from them. In a high reliability organization we have to learn before an error leads to an incident (or even accident). Therefore the “human factor” is most important as most of the time the human is the last line of defense. The “human factor” is more than communication or leadership skills. At the end, it is the personal attitude. This attitude has to be safety minded. And this attitude has to be self-reflected continuously. Moreover, feedback from others is urgently needed to improve one’s personal skills daily and learn from our own experience as well as from others. (author

Preparing for the Learning Organization.

Science.gov (United States)

Salner, Marcia

1999-01-01

A seminar to prepare students for learning organizations was based on Perry's theory of intellectual and ethical development. Developmental assignments were designed to assist cognitive growth and self-awareness. Challenges arose from differences in group composition (younger or mixed-age students) and the ethics of attempting to alter students'…

Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

Science.gov (United States)

Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

2018-02-01

Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

Learning Organic Chemistry Through Natural Products

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 16; Issue 12. Learning Organic Chemistry Through Natural Products - Architectural Designs in Molecular Constructions. N R Krishnaswamy. Volume 16 Issue 12 December 2011 pp 1287-1293 ...

Learning Organic Chemistry Through Natural Products

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 2. Learning Organic Chemistry Through Natural Products Determination of Absolute Stereochemistry. N R Krishnaswamy. Series Article Volume 1 Issue 2 February 1996 pp 40-46 ...

The Usage of E-Learning Model To Optimize Learning System In Higher Education by Using Dick and Carey Design Approach

Directory of Open Access Journals (Sweden)

Anak Agung Gde Satia Utama

2016-04-01

Full Text Available Nowadays many universities in the world apply technology enhanced learning in order to help learning activities. Due to the potentials technology enhanced learning offers, recent education using it and universities in particular are trying to apply it. One of the subjects of this research is The Accounting Department of Airlangga University in Surabaya. The idea of this research is to investigate the students about how they know deeply about e-learning system and learning objectives as a first step to conduct e-learning model. After the model completed, the next step is to prepare database learning. Entity Relationship Diagram (ERD can help to explain the model. The purpose of this research was done by using Dick and Carey Design Model. There are nine steps to conduct e-learning model. All steps can be categorized into three steps research: first is the introduction or empirical study, the next step is the design and the last is the feedback after the implementation. The methodology used in this research is using Qualitative Exploratory, by using questionnaire and interviews as data collection techniques. The analysis of the data shows organization requires information about e-learning content, user as a learning subject and information technology infrastructures. E-learning model as one of the alternative learning can help users to optimized learning.

Real-time modeling of primitive environments through wavelet sensors and Hebbian learning

Science.gov (United States)

Vaccaro, James M.; Yaworsky, Paul S.

1999-06-01

Modeling the world through sensory input necessarily provides a unique perspective for the observer. Given a limited perspective, objects and events cannot always be encoded precisely but must involve crude, quick approximations to deal with sensory information in a real- time manner. As an example, when avoiding an oncoming car, a pedestrian needs to identify the fact that a car is approaching before ascertaining the model or color of the vehicle. In our methodology, we use wavelet-based sensors with self-organized learning to encode basic sensory information in real-time. The wavelet-based sensors provide necessary transformations while a rank-based Hebbian learning scheme encodes a self-organized environment through translation, scale and orientation invariant sensors. Such a self-organized environment is made possible by combining wavelet sets which are orthonormal, log-scale with linear orientation and have automatically generated membership functions. In earlier work we used Gabor wavelet filters, rank-based Hebbian learning and an exponential modulation function to encode textural information from images. Many different types of modulation are possible, but based on biological findings the exponential modulation function provided a good approximation of first spike coding of `integrate and fire' neurons. These types of Hebbian encoding schemes (e.g., exponential modulation, etc.) are useful for quick response and learning, provide several advantages over contemporary neural network learning approaches, and have been found to quantize data nonlinearly. By combining wavelets with Hebbian learning we can provide a real-time front-end for modeling an intelligent process, such as the autonomous control of agents in a simulated environment.

Using a Metro Map Metaphor for organizing Web-based learning resources

DEFF Research Database (Denmark)

Grønbæk, Kaj; Bang, Tove; Hansen, Per Steen

2002-01-01

This paper briefly describes the WebNize system and how it applies a Metro Map metaphor for organizing guided tours in Web based resources. Then, experiences in using the Metro Map based tours in a Knowledge Sharing project at the library at Aarhus School of Business (ASB) in Denmark, are discussed...... is to create models for Intelligent Knowledge Solutions that can contribute to form the learning environments of the School in the 21st century. The WebNize system is used for sharing of knowledge through metro maps for specific subject areas made available in the Learning Resource Centre at ASB. The metro....... The Library has been involved in establishing a Learning Resource Center (LRC). The LRC serves as an exploratorium for the development and the testing of new forms of communication and learning, at the same time as it integrates the information resources of the electronic research library. The objective...

Organizing for Spaces and Dynamics of Multipolar Learning in Multinational Corporations

DEFF Research Database (Denmark)

Hull Kristensen, Peer; Lotz, Maja

Limited research has been conducted on how MNCs organize conditions and spaces for recursive learning to facilitate the practice of innovation across dispersed units as well as how organizational members at all levels may become involved in innovations through the engagement in ongoing multipolar...... learning dynamics. Based on longitudinal case studies in two MNCs this paper contributes with insights into how spaces and dynamics of multipolar learning are organized and governed across dispersed MNC units at the micro level of everyday work practices. The paper shows that it is possible to organize...... spaces and dynamics that can organize recursiveness and continuity in multipolar learning by way of experimentation with new coordination components and governance architectures. Against the previous literature, however, it becomes evident that these are not the outcome of spontaneous interactions...

The Interaction Model in iLearning Environments and its Use in the Smart Lab Concept

Directory of Open Access Journals (Sweden)

Yuliya Lyalina

2011-11-01

Full Text Available This paper identifies and discusses current trends and challenges, offers an overview of state-of-the-art technologies in the development of remote and smart laboratories, and introduces the iLearning interaction model. The use of the model allows reconstructing already- existing iLearning environments. The smart lab model is described for face-to-face, Mobile and Blended Learning. As a result, this allows offering new information technology that organizes the educational process according to learning type (face-to-face, hands-on learning, Life Long Learning, E-Learning, M-Learning, Blended learning, Game-based learning, etc.. The remote access Architecture and Interface for the multifunctional Smart Lab will be developed.

Organizational Learning Supported by Reference Architecture Models

DEFF Research Database (Denmark)

Nardello, Marco; Møller, Charles; Gøtze, John

2017-01-01

The wave of the fourth industrial revolution (Industry 4.0) is bringing a new vision of the manufacturing industry. In manufacturing, one of the buzzwords of the moment is “Smart production”. Smart production involves manufacturing equipment with many sensors that can generate and transmit large...... amounts of data. These data and information from manufacturing operations are however not shared in the organization. Therefore the organization is not using them to learn and improve their operations. To address this problem, the authors implemented in an Industry 4.0 laboratory an instance...... of an emerging technical standard specific for the manufacturing industry. Global manufacturing experts consider the Reference Architecture Model Industry 4.0 (RAMI4.0) as one of the corner stones for the implementation of Industry 4.0. The instantiation contributed to organizational learning in the laboratory...

Learning Organic Chemistry Through Natural Products

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 10. Learning Organic Chemistry Through Natural Products Architectural Designs in Molecular Constructions. N R Krishnaswamy. Series Article Volume 1 Issue 10 October 1996 pp 37-43 ...

Learning Organic Chemistry Through Natural Products

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 7. Learning Organic Chemistry Through Natural engine Products - Structure and Biological Functions. N R Krishnaswamy. Series Article Volume 1 Issue 7 July 1996 pp 23-30 ...

Students' use of social software in self-organized learning environment

DEFF Research Database (Denmark)

Mathiasen, Helle; Dalsgaard, Christian

2006-01-01

The paper will argue that new possibilities of digital media, especially social software, have a potential regarding development of self-organized learning environments and facilitating self-governed activities. Based on a sociological perspective, the paper will clarify the concepts of informal...... and formal learning used in this paper. It is argued that formal and informal conditions of learning can supplement each other within an educational setting. A formal setting of project work forms the basis of informal, selfgoverned activities of students. The paper will argue that social software tools can...... support students' self-governed activities and their development of self-organized learning environments....

Teaching organization theory for healthcare management: three applied learning methods.

Science.gov (United States)

Olden, Peter C

2006-01-01

Organization theory (OT) provides a way of seeing, describing, analyzing, understanding, and improving organizations based on patterns of organizational design and behavior (Daft 2004). It gives managers models, principles, and methods with which to diagnose and fix organization structure, design, and process problems. Health care organizations (HCOs) face serious problems such as fatal medical errors, harmful treatment delays, misuse of scarce nurses, costly inefficiency, and service failures. Some of health care managers' most critical work involves designing and structuring their organizations so their missions, visions, and goals can be achieved-and in some cases so their organizations can survive. Thus, it is imperative that graduate healthcare management programs develop effective approaches for teaching OT to students who will manage HCOs. Guided by principles of education, three applied teaching/learning activities/assignments were created to teach OT in a graduate healthcare management program. These educationalmethods develop students' competency with OT applied to HCOs. The teaching techniques in this article may be useful to faculty teaching graduate courses in organization theory and related subjects such as leadership, quality, and operation management.

Topological self-organization and prediction learning support both action and lexical chains in the brain.

Science.gov (United States)

Chersi, Fabian; Ferro, Marcello; Pezzulo, Giovanni; Pirrelli, Vito

2014-07-01

A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, the network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall. Copyright © 2014 Cognitive Science Society, Inc.

Leadership in learning organizations: a strategy for improvement.

Science.gov (United States)

Till, Alex; Amin, Maslah; McKimm, Judy

2016-11-02

The learning organization is a potential framework for managing transformational culture change and delivering high quality health care. It helps to shift the focus from the development of individuals as leaders to one which takes a 'whole organization' approach.

Reflexões sobre a subjetividade na gestão a partir do paradigma da organização que aprende Reflections about subjectivity in administration from learning organization model

Directory of Open Access Journals (Sweden)

Francisco Javier Uribe

2001-01-01

Full Text Available O artigo estabelece correlações entre subjetividade e gestão organizacional a partir do paradigma da organização que aprende, de Peter Senge. Os principais eixos analíticos do mesmo são o conceito de aprendizagem organizacional, como processo que articula a aprendizagem individual e social, através da comunicação, e o conceito de liderança, visto como capacidade social de moldar o futuro que depende da disseminação de qualidades e atitudes que dependem de características de natureza individual ou subjetiva.Correlations were established between subjectivity and organizational administration from Peter Senge's learning organization model. Their principal analytical issues comes from organization learning concept that articulates individual and social learning by communication and from the leadership concept considered as a social capacity to model the future dependent on attitudes and skills of individual or subjective nature.

Learning Organic Chemistry Through Natural Products

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Learning Organic Chemistry Through Natural Products From Molecular and Electronic Structures to Reactivity. N R Krishnaswamy. Series Article Volume 1 Issue 5 May 1996 pp 12-18 ...

Computational modeling of neural plasticity for self-organization of neural networks.

Science.gov (United States)

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Active Learning and Cooperative Learning in the Organic Chemistry Lecture Class

Science.gov (United States)

Paulson, Donald R.

1999-08-01

Faculty in the physical sciences are one of the academic groups least receptive to the use of active learning strategies and cooperative learning in their classrooms. This is particularly so in traditional lecture classes. It is the objective of this paper to show how effective these techniques can be in improving student performance in classes. The use of active learning strategies and cooperative learning groups in my organic chemistry lecture classes has increased the overall pass rate in my classes by an astounding 20-30% over the traditional lecture mode. This has been accomplished without any reduction in "standards". The actual methods employed are presented as well as a discussion of how I came to radically change the way I teach my classes.

Learning Organization Profile of Educational Hospitals in Iran: Practice of Organizational Interlocking Systems.

Science.gov (United States)

Mohebbifar, Rafat; Hashemi, Hassan Jahani; Rajaee, Roya; Najafi, Marziye; Etedal, Mahbobeh G H

2015-02-24

Organizational learning has been identified as necessary for different organizations to improve their performance in the changing and competitive environment. The main purpose of this research was to specify the learning organization profile of educational and health centers of Tehran and Qazvin Universities of Medical Sciences in Iran. The present research was conducted using a cross-sectional method in the academic year of 2013-2014. A staff of 530 from educational hospitals subordinated to Tehran and Qazvin universities of medical sciences participated in the research. The participants were selected using stratified random sampling. That is to say, a random sample of a proportionate size was selected from each hospital. The instrument for data collection was a Likert-scale questionnaire involving 50 items. The statistical techniques of ANOVA, t-test, Chi-square, correlation coefficients (Pearson and Spearman), and regression were utilized to analyze the data. All of them were performed using the Statistical Package for Social Sciences (SPSS) 16.0 for windows. the results indicated that 449 of participants (84.7%) had a B.S. degree and 78 of them (14.7%) had an M.S. or a Ph.D. degree. Among the fivefold dimensions of "Learning Organization" model (Learning, Organization, People, Knowledge, and Technology) in comparison of the two universities, the "people" dimension was the highest-rated dimension with the mean rating of 25.71±8.36 and the "learning" dimension was the lowest-rated dimension with the mean of 25.35±8.04. Comparison between the two universities yielded the result that educational hospitals in Tehran University of medical sciences with the rating of 126.56 had a more complete profile than that of educational hospitals in Qazvin university of medical sciences with the rating of 122.23. The hospitals of the two above-mentioned universities were, to a great extent, far from the characteristics of Learning Organization. In light of the massive mission

Development of methodological principles for organization of students’ independent work in the e-learning system

Directory of Open Access Journals (Sweden)

Олександр Іванович Пушкар

2016-10-01

Full Text Available The concept of organization of professional competence formation of students’ independent work in e-learning is proposed in the article. Implementation of the proposed model of competence formation in e-learning is done on the example of multimedia complex for discipline "Processes of publishing and printing". Selection of the most important components for each competence is made on the basis of Saaty method

The Model of Blended Learning and Its Use at Foreign Language Teaching

OpenAIRE

A. A. Kudysheva; A. N. Kudyshev

2013-01-01

In present article the model of Blended Learning, its advantage at foreign language teaching, and also some problems that can arise during its use are considered. The Blended Learning is a special organization of learning, which allows to combine classroom work and modern technologies in electronic distance teaching environment. Nowadays a lot of European educational institutions and companies use such technology. Through this method: student gets the opportunity to learn in a group (classroo...

Gender-Equal Organizations as a Prerequisite for Workplace Learning

Science.gov (United States)

Johansson, Kristina; Abrahamsson, Lena

2018-01-01

Purpose: This paper aims to explore how gendering of the learning environment acts to shape the design and outcome of workplace learning. The primary intention is to reflect on the idea of gender-equal organizations as a prerequisite for workplace learning. Design/methodology/approach: A review of literature relating to gender and workplace…

Adapting to managed care by becoming a learning organization.

Science.gov (United States)

O'Sullivan, M J

1999-03-01

In the tumultuous and chaotic environment of managed health care, hospital-based mental health providers need to change in fundamental ways. The traditional view of mental health organizations is a professional-bureaucratic one where actions and outcomes of planning are thought to be highly predictable. The author proposes an alternative paradigm for viewing mental health provider organizations, one based on learning theory, which accepts that the future is unknowable because of its complexity and the probabilistic nature of the world. Within this perspective, mental health care providers need to become "learning organizations" to successfully adapt to the new and evolving conditions.

Learning while (re-)configuring: business model innovation processes in established firms

NARCIS (Netherlands)

Berends, J.J.; Smits, A.; Reymen, I.M.M.J.; Podoynitsyna, K.S.

2016-01-01

This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: “drifting”

Sustaining Change in a Learning Organization

Science.gov (United States)

Steenekamp, K.; Botha, G.; Moloi, K. C.

2012-01-01

This article looks at how the application of the concept of a "learning organisation" can be used at a specific organisation in South Africa to change the work performance of its employees. We do this by exploring different theories, models and definitions of organisational learning, learning organisation, organisational knowledge and…

Teaching giants to learn: Lessons from army learning in World War II

NARCIS (Netherlands)

Visser, M.

2017-01-01

PURPOSE - This paper aims to discuss the “truism” that learning organizations cannot be large organizations and, conversely, that large organizations cannot be learning organizations. This paper analyzes learning in the German and US armies in the Second World War, based on a four-dimensional model

The development of learning materials based on core model to improve students’ learning outcomes in topic of Chemical Bonding

Science.gov (United States)

Avianti, R.; Suyatno; Sugiarto, B.

2018-04-01

This study aims to create an appropriate learning material based on CORE (Connecting, Organizing, Reflecting, Extending) model to improve students’ learning achievement in Chemical Bonding Topic. This study used 4-D models as research design and one group pretest-posttest as design of the material treatment. The subject of the study was teaching materials based on CORE model, conducted on 30 students of Science class grade 10. The collecting data process involved some techniques such as validation, observation, test, and questionnaire. The findings were that: (1) all the contents were valid, (2) the practicality and the effectiveness of all the contents were good. The conclusion of this research was that the CORE model is appropriate to improve students’ learning outcomes for studying Chemical Bonding.

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

Science.gov (United States)

Cuperlovic-Culf, Miroslava

2018-01-11

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

Science.gov (United States)

Cuperlovic-Culf, Miroslava

2018-01-01

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies. PMID:29324649

An access to care center as a learning organization.

Science.gov (United States)

Parris, U

2000-01-01

The Durham Access to Care (DATC) is one of the new streamlined vehicles for the delivery of integrated home-based and community-based health services across Ontario. Management and staff in this change transition have undertaken to become a learning organization. To implement this visionary process leadership qualities and style is key. This article gives a brief account of DATC and its move to becoming a learning organization and the author's observational reflections of an effective leadership style.

Situated learning theory: adding rate and complexity effects via Kauffman's NK model.

Science.gov (United States)

Yuan, Yu; McKelvey, Bill

2004-01-01

For many firms, producing information, knowledge, and enhancing learning capability have become the primary basis of competitive advantage. A review of organizational learning theory identifies two approaches: (1) those that treat symbolic information processing as fundamental to learning, and (2) those that view the situated nature of cognition as fundamental. After noting that the former is inadequate because it focuses primarily on behavioral and cognitive aspects of individual learning, this paper argues the importance of studying learning as interactions among people in the context of their environment. It contributes to organizational learning in three ways. First, it argues that situated learning theory is to be preferred over traditional behavioral and cognitive learning theories, because it treats organizations as complex adaptive systems rather than mere information processors. Second, it adds rate and nonlinear learning effects. Third, following model-centered epistemology, it uses an agent-based computational model, in particular a "humanized" version of Kauffman's NK model, to study the situated nature of learning. Using simulation results, we test eight hypotheses extending situated learning theory in new directions. The paper ends with a discussion of possible extensions of the current study to better address key issues in situated learning.

Electrochemical model of the polyaniline based organic memristive device

International Nuclear Information System (INIS)

Demin, V. A.; Erokhin, V. V.; Kashkarov, P. K.; Kovalchuk, M. V.

2014-01-01

The electrochemical organic memristive device with polyaniline active layer is a stand-alone device designed and realized for reproduction of some synapse properties in the innovative electronic circuits, including the neuromorphic networks capable for learning. In this work, a new theoretical model of the polyaniline memristive is presented. The developed model of organic memristive functioning was based on the detailed consideration of possible electrochemical processes occuring in the active zone of this device. Results of the calculation have demonstrated not only the qualitative explanation of the characteristics observed in the experiment but also the quantitative similarities of the resultant current values. It is shown how the memristive could behave at zero potential difference relative to the reference electrode. This improved model can establish a basis for the design and prediction of properties of more complicated circuits and systems (including stochastic ones) based on the organic memristive devices

Finding the Intersection of the Learning Organization and Learning Transfer: The Significance of Leadership

Science.gov (United States)

Kim, Jun Hee; Callahan, Jamie L.

2013-01-01

Purpose: This article aims to develop a conceptual framework delineating the key dimension of the learning organization which significantly influences learning transfer. Design/methodology/approach: The conceptual framework was developed by analyzing previous studies and synthesizing the results associated with the following four relationships:…

The Development of Inquiry Learning Materials to Complete Content Life System Organization in Junior High School Students

Science.gov (United States)

Mayasari, F.; Raharjo; Supardi, Z. A. I.

2018-01-01

This research aims to develop the material eligibility to complete the inquiry learning of student in the material organization system of junior high school students. Learning materials developed include syllabi, lesson plans, students’ textbook, worksheets, and learning achievement test. This research is the developmental research which employ Dick and Carey model to develop learning material. The experiment was done in Junior High School 4 Lamongan regency using One Group Pretest-Posttest Design. The data collection used validation, observation, achievement test, questionnaire administration, and documentation. Data analysis techniques used quantitative and qualitative descriptive.The results showed that the developed learning material was valid and can be used. Learning activity accomplished with good category, where student activities were observed. The aspects of attitudes were observed during the learning process are honest, responsible, and confident. Student learning achievement gained an average of 81, 85 in complete category, with N-Gain 0, 75 for a high category. The activities and student response to learning was very well categorized. Based on the results, this researcher concluded that the device classified as feasible of inquiry-based learning (valid, practical, and effective) system used on the material organization of junior high school students.

Collecting lessons learned : How project-based organizations in the oil and gas industry learn from their projects

NARCIS (Netherlands)

Buttler, T.

2016-01-01

Project-based organizations collect lessons learned in order to improve the performance of projects. They aim to repeat successes by using positive lessons learned, and to avoid repeating negative experiences by using negative lessons learned. Cooke-Davies (2002) claimed that the ability to learn

Impact of Learning Organization Culture on Performance in Higher Education Institutions

Science.gov (United States)

Ponnuswamy, Indra; Manohar, Hansa Lysander

2016-01-01

In this paper, an adapted version of the Dimensions of Learning Organization Questionnaire (DLOQ) was employed to investigate the perception of academic staff on learning organization culture in Indian higher education institutions. The questionnaire was sent to 700 faculty members of different universities using a non-probability purposive…

Learning with hierarchical-deep models.

Science.gov (United States)

Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

2013-08-01

We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

Do organizations spend wisely on employees? Effects of training and development investments on learning and innovation in organizations.

Science.gov (United States)

Sung, Sun Young; Choi, Jin Nam

2014-04-01

The present study examines the effects of training and development on organizational innovation. We specifically suggest that the training and development investments of an organization affect its innovative performance by promoting various learning practices. We empirically tested our hypothesis by using time-lagged, multi-source data collected from 260 Korean companies that represent diverse industries. Our analysis showed that corporate expenditure for internal training predicts interpersonal and organizational learning practices, which, in turn, increase innovative performance. The data also revealed that the positive relationship between interpersonal and organizational learning practices and innovative performance is stronger within organizations that have stronger innovative climates. By contrast, investment in employee development through financial support for education outside an organization poses a significant negative effect on its innovative performance and no significant effect on learning practices. The present study provides a plausible explanation for a mechanism through which the investment of an organization in employees enhances its innovative performance. Copyright © 2013 The Authors.

Do organizations spend wisely on employees? Effects of training and development investments on learning and innovation in organizations

Science.gov (United States)

Sung, Sun Young; Choi, Jin Nam

2014-01-01

The present study examines the effects of training and development on organizational innovation. We specifically suggest that the training and development investments of an organization affect its innovative performance by promoting various learning practices. We empirically tested our hypothesis by using time-lagged, multi-source data collected from 260 Korean companies that represent diverse industries. Our analysis showed that corporate expenditure for internal training predicts interpersonal and organizational learning practices, which, in turn, increase innovative performance. The data also revealed that the positive relationship between interpersonal and organizational learning practices and innovative performance is stronger within organizations that have stronger innovative climates. By contrast, investment in employee development through financial support for education outside an organization poses a significant negative effect on its innovative performance and no significant effect on learning practices. The present study provides a plausible explanation for a mechanism through which the investment of an organization in employees enhances its innovative performance. Copyright © 2013 The Authors. PMID:25598576

Learning Organic Chemistry Through Natural Products

Indian Academy of Sciences (India)

SERIES I ARTICLE. Learning Organic Chemistry. Through Natural Products. 2. Determination of Absolute Stereochemistry. N R Krishnaswamy was initiated into the world of natural products by T R. Seshadri at University of. Delhi and has carried on the glorious traditions of his mentor. He has taught at Bangalore University,.

Model-based machine learning.

Science.gov (United States)

Bishop, Christopher M

2013-02-13

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

Preparing for Organisational Learning by HK Infrastructure Project Joint Ventures Organizations.

Science.gov (United States)

Walker, Derek H. T.; Johannes, Derick S.

2003-01-01

Interviews with nine Hong Kong managers involved in joint ventures with other organizations focused on the organizational learning aspects of collaboration: attitudes toward interorganizational learning, acquisition of knowledge assets, and learning motivation. An important motivation for developing alliances was to learn from each other, fill…

MODEL OF COLLABORATIVE COURSES DEVELOPMENT IN DISTANCE LEARNING PLATFORMS

Directory of Open Access Journals (Sweden)

Dmytro S. Morozov

2015-02-01

Full Text Available The research paper outlines the problem of organization collaboration of users group on creation distance learning courses. The article contains analysis of the courses data structure. According to proposed structure the model of developer’s collaboration on creating distance learning courses based on basic principles of source code management was proposed. The article also provides result of research on necessary tools for collaborative development of courses in distance learning platforms. According to the requirements of flexibility and simplicity of access to system for any level educational institutions, technological decisions on granting permissions on performing basic operations on course elements and providing to user moderation’s privileges were proposed.

THE EFFECT OF LEARNING ORGANIZATIONS ON PSYCHOLOGICAL EMPOWERMENT: A RESEARCH IN PUBLIC SECTOR

OpenAIRE

Duygu TOPLU; Meltem AKCA

2013-01-01

Persistence of an organization and its adaptation to changing environment is very crucial in organizational context. The organizations which give necessary importance to their employees’ needs and foster their willingness to learn, are expected to be more succesful than others. The purpose of this study is to investigate the effects of learning organizations’ characteristics on psychological empowerment. Within this context, first the relationship between learning organization and psychologic...

An Hourly Streamflow Forecasting Model Coupled with an Enforced Learning Strategy

Directory of Open Access Journals (Sweden)

Ming-Chang Wu

2015-10-01

Full Text Available Floods, one of the most significant natural hazards, often result in loss of life and property. Accurate hourly streamflow forecasting is always a key issue in hydrology for flood hazard mitigation. To improve the performance of hourly streamflow forecasting, a methodology concerning the development of neural network (NN based models with an enforced learning strategy is proposed in this paper. Firstly, four different NNs, namely back propagation network (BPN, radial basis function network (RBFN, self-organizing map (SOM, and support vector machine (SVM, are used to construct streamflow forecasting models. Through the cross-validation test, NN-based models with superior performance in streamflow forecasting are detected. Then, an enforced learning strategy is developed to further improve the performance of the superior NN-based models, i.e., SOM and SVM in this study. Finally, the proposed flow forecasting model is obtained. Actual applications are conducted to demonstrate the potential of the proposed model. Moreover, comparison between the NN-based models with and without the enforced learning strategy is performed to evaluate the effect of the enforced learning strategy on model performance. The results indicate that the NN-based models with the enforced learning strategy indeed improve the accuracy of hourly streamflow forecasting. Hence, the presented methodology is expected to be helpful for developing improved NN-based streamflow forecasting models.

Relationship between Organizational Learning and Workplace Bullying in Learning Organizations

Science.gov (United States)

Korkmaz, Mehmet; Cemaloglu, Necati

2010-01-01

The purpose of this research is to define the relationship between features of a learning organization in formal educational institutions in Turkey, specifically primary schools, and workplace bullying of teachers in these institutions. The scope and sampling group of the research are teachers in primary schools. Two different scales are used in…

Globalizing the Intelligent Organization: Learning Organizations, Smart Workers, (Not So) Clever Countries and the Sociological Imagination.

Science.gov (United States)

Clegg, Stewart

1999-01-01

Contrasts exploratory learning with exploitative learning to argue for the importance of both and not just the latter. Discusses a case for organization studies that situates itself within a classical tradition of sociology. (CCM)

Perry's Scheme of Intellectual and Epistemological Development as a Framework for Describing Student Difficulties in Learning Organic Chemistry

Science.gov (United States)

Grove, Nathaniel P.; Bretz, Stacey Lowery

2010-01-01

We have investigated student difficulties with the learning of organic chemistry. Using Perry's Model of Intellectual Development as a framework revealed that organic chemistry students who function as dualistic thinkers struggle with the complexity of the subject matter. Understanding substitution/elimination reactions and multi-step syntheses is…

Hebbian learning in a model with dynamic rate-coded neurons: an alternative to the generative model approach for learning receptive fields from natural scenes.

Science.gov (United States)

Hamker, Fred H; Wiltschut, Jan

2007-09-01

Most computational models of coding are based on a generative model according to which the feedback signal aims to reconstruct the visual scene as close as possible. We here explore an alternative model of feedback. It is derived from studies of attention and thus, probably more flexible with respect to attentive processing in higher brain areas. According to this model, feedback implements a gain increase of the feedforward signal. We use a dynamic model with presynaptic inhibition and Hebbian learning to simultaneously learn feedforward and feedback weights. The weights converge to localized, oriented, and bandpass filters similar as the ones found in V1. Due to presynaptic inhibition the model predicts the organization of receptive fields within the feedforward pathway, whereas feedback primarily serves to tune early visual processing according to the needs of the task.

The impact of managers' perceptions of learning organizations on innovation in healthcare: sample of Turkey.

Science.gov (United States)

Ugurluoglu, Ozgur; Ugurluoglu Aldogan, Ece; Dilmac, Elife

2013-01-01

Organizational learning is the process of increasing effective organizational activities through knowledge and understanding. Innovation is the creation of any product, service or process, which is new to a business unit. Significant amount of research on organizational learning place a central meaning on the fact that there is a positive relationship between organizational learning and innovation. Both organizational learning and innovation are essential for organizations to prepare for change. The aim of this study is to determine to what extent the identified learning organization dimensions are associated with innovation. The study used a quantitative non-experimental design employing statistical analysis via multiple regression and correlation methods to identify the relationships between the variables examined. Because the research was conducted in a non-experimental way, learning organization dimensions are referred to as predictor variables, and innovation is referred to as the criterion variable. Watkins and Marsick's Dimensions of the Learning Organization Questionnaire was used in the study. Questionnaires were distributed to 498 hospital managers and, 243 valid responses were used in this study. Therefore, 243 hospital managers working at 250 Ministry of Health (public) hospitals across Turkey participated in the study. Results demonstrate that there are significant and positive correlations between learning organization dimensions and innovation. Intercorrelations between learning organization dimensions and correlations between learning organization dimensions and innovation were average and high, respectively. Results further indicate that the dimensions of the learning organizations explained 66.5% of the variance for the innovation. Copyright © 2012 John Wiley & Sons, Ltd.

Learning versus correct models: influence of model type on the learning of a free-weight squat lift.

Science.gov (United States)

McCullagh, P; Meyer, K N

1997-03-01

It has been assumed that demonstrating the correct movement is the best way to impart task-relevant information. However, empirical verification with simple laboratory skills has shown that using a learning model (showing an individual in the process of acquiring the skill to be learned) may accelerate skill acquisition and increase retention more than using a correct model. The purpose of the present study was to compare the effectiveness of viewing correct versus learning models on the acquisition of a sport skill (free-weight squat lift). Forty female participants were assigned to four learning conditions: physical practice receiving feedback, learning model with model feedback, correct model with model feedback, and learning model without model feedback. Results indicated that viewing either a correct or learning model was equally effective in learning correct form in the squat lift.

Student Organizations as Avenues for Leader Learning and Development.

Science.gov (United States)

Sessa, Valerie I; Alonso, Nicole; Farago, Pamela; Schettino, Gaynell; Tacchi, Kelcie; Bragger, Jennifer D

2017-09-01

This chapter describes theory and research demonstrating that the experiences students have within student organizations, and the people with whom they interact within those organizations, are powerful triggers for leader learning and development. © 2017 Wiley Periodicals, Inc., A Wiley Company.

Extending the 4I Organizational Learning Model: Information Sources, Foraging Processes and Tools

Directory of Open Access Journals (Sweden)

Tracy A. Jenkin

2013-08-01

Full Text Available The continued importance of organizational learning has recently led to several calls for further developing the theory. This article addresses these calls by extending Crossan, Lane and White’s (1999 4I model to include a fifth process, information foraging, and a fourth level, the tool. The resulting 5I organizational learning model can be generalized to a number of learning contexts, especially those that involve understanding and making sense of data and information. Given the need for organizations to both innovate and increase productivity, and the volumes of data and information that are available to support both, the 5I model addresses an important organizational issue.

Learning to Act: Qualitative Learning of Deterministic Action Models

DEFF Research Database (Denmark)

Bolander, Thomas; Gierasimczuk, Nina

2017-01-01

In this article we study learnability of fully observable, universally applicable action models of dynamic epistemic logic. We introduce a framework for actions seen as sets of transitions between propositional states and we relate them to their dynamic epistemic logic representations as action...... in the limit (inconclusive convergence to the right action model). We show that deterministic actions are finitely identifiable, while arbitrary (non-deterministic) actions require more learning power—they are identifiable in the limit. We then move on to a particular learning method, i.e. learning via update......, which proceeds via restriction of a space of events within a learning-specific action model. We show how this method can be adapted to learn conditional and unconditional deterministic action models. We propose update learning mechanisms for the afore mentioned classes of actions and analyse...

Spiking neurons in a hierarchical self-organizing map model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells.

Directory of Open Access Journals (Sweden)

Praveen K Pilly

Full Text Available Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning grid cells with hexagonal grid firing fields of multiple spatial scales and place cells with one or more firing fields that match neurophysiological data about these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous

EFFECT OF INQUIRY LEARNING MODEL AND MOTIVATION ON PHYSICS OUTCOMES LEARNING STUDENTS

Directory of Open Access Journals (Sweden)

Dahlia Megawati Pardede

2016-06-01

Full Text Available The purposes of the research are: (a to determine differences in learning outcomes of students with Inquiry Training models and conventional models, (b to determine differences in physics learning outcomes of students who have high motivation and low motivation, (c to determine the interaction between learning models with the level of motivation in improving student Physics learning outcomes. The results were found: (a there are differences in physical students learning outcomes are taught by Inquiry Training models and conventional models. (b learning outcomes of students who are taught by Inquiry Learning Model Training better than student learning outcomes are taught with conventional model. (c there is a difference in student's learning outcomes that have high motivation and low motivation. (d Student learning outcomes that have a high motivation better than student learning outcomes than have a low motivation. (e there is interaction between learning and motivation to student learning outcomes. Learning outcomes of students who are taught by the model is influenced also by the motivation, while learning outcomes of students who are taught with conventional models are not affected by motivation.

Organizational Support for Action Learning in South Korean Organizations

Science.gov (United States)

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…

Reporting intellectual capital in health care organizations: specifics, lessons learned, and future research perspectives.

Science.gov (United States)

Veltri, Stefania; Bronzetti, Giovanni; Sicoli, Graziella

2011-01-01

This article analyzes the concept of intellectual capital (IC) in the health sector sphere by studying the case of a major nonprofit research organization in this sector, which has for some time been publishing IC reports. In the last few years, health care organizations have been the object of great attention in the implementation and transfer of managerial models and tools; however, there is still a lack of attention paid to the strategic management of IC as a fundamental resource for supporting and enhancing performance improvement dynamics. The main aim of this article is to examine the IC reporting model used by the Center of Molecular Medicine (CMM), a Swedish health organization which is an outstanding benchmark in reporting its IC. We also consider the specifics of IC reporting for health organizations, the lessons learned by analyzing CMM's IC reporting, and future perspectives for research.

Room-temperature and temperature-dependent QSRR modelling for predicting the nitrate radical reaction rate constants of organic chemicals using ensemble learning methods.

Science.gov (United States)

Gupta, S; Basant, N; Mohan, D; Singh, K P

2016-07-01

Experimental determinations of the rate constants of the reaction of NO3 with a large number of organic chemicals are tedious, and time and resource intensive; and the development of computational methods has widely been advocated. In this study, we have developed room-temperature (298 K) and temperature-dependent quantitative structure-reactivity relationship (QSRR) models based on the ensemble learning approaches (decision tree forest (DTF) and decision treeboost (DTB)) for predicting the rate constant of the reaction of NO3 radicals with diverse organic chemicals, under OECD guidelines. Predictive powers of the developed models were established in terms of statistical coefficients. In the test phase, the QSRR models yielded a correlation (r(2)) of >0.94 between experimental and predicted rate constants. The applicability domains of the constructed models were determined. An attempt has been made to provide the mechanistic interpretation of the selected features for QSRR development. The proposed QSRR models outperformed the previous reports, and the temperature-dependent models offered a much wider applicability domain. This is the first report presenting a temperature-dependent QSRR model for predicting the nitrate radical reaction rate constant at different temperatures. The proposed models can be useful tools in predicting the reactivities of chemicals towards NO3 radicals in the atmosphere, hence, their persistence and exposure risk assessment.

Capstone Teaching Models: Combining Simulation, Analytical Intuitive Learning Processes, History and Effectiveness

Science.gov (United States)

Reid, Maurice; Brown, Steve; Tabibzadeh, Kambiz

2012-01-01

For the past decade teaching models have been changing, reflecting the dynamics, complexities, and uncertainties of today's organizations. The traditional and the more current active models of learning have disadvantages. Simulation provides a platform to combine the best aspects of both types of teaching practices. This research explores the…

Komparasi Pemahaman Konsep Bangun Datar Siswa Antara Yang Diajar Dengan Model Pembelajaran Advance Organizer Dengan Peta Konsep Dan Model Pembelajaran Yang Mengadopsi Teori Van Hiele Pada Kelas VII SMPN 2 Sinjai Timur

Directory of Open Access Journals (Sweden)

Edi Syukri

2016-02-01

perbedaan pemahaman konsep bangun datar siswa antara yang diajar dengan model pembelajaran advance organizer dengan peta konsep dan model pembelajaran yag mengadopsi teori Van Hiele.Kata kunci: Pendekatan saintifik, Keterampilan proses sains, Hasil belajar kognitif biologi. ABSTRACTThe type of this research is experimental research that aims to: (1 know the learning outcomes, activities, and responses of students to advance organizer learning model with concept maps and learning models that adopt Van Hiele theory on the subject of wake up, especially quadrilateral class VII SMPN 2 Sinjai East, (2 to know how to understand the concept of students' wake up between those taught by advance organizer learning model with concept map and learning model adopting Van Hiele theory. The population in this study were all students of class VII of SMPN 2 Sinjai Timur and the sample consisted of two classes namely class VII-A and class VII-C, both as an experimental class was selected using purposive random sampling technique. The data collected consisted of data on student learning outcomes, student activity data in learning, and student response data on the device and learning. The results showed that the score of students' mathematics learning outcomes in experimental class 1 with mean of 20,36 and standard deviation 2,164 reach classical completeness equal to 89,29%, and student activity in learning is in the active category and student response to device and its learning is positive. In general, it is concluded that advanced organizer learning model with concept map to be applied in class VII SMPN 2 Sinjai Timur with quite effective category. Score of student learning outcomes in experiment class 2 with mean of 20,63 and standard deviation 2,589 reach classical completeness equal to 88,89% and student activity in learning is inactive category and student response to device and its learning is positive. It is generally concluded that the learning model adopting Van Hiele's theory to

The Game Enhanced Learning Model

DEFF Research Database (Denmark)

Reng, Lars; Schoenau-Fog, Henrik

2016-01-01

will describe the levels of the model, which is based on our experience in teaching professional game development at university level. Furthermore, we have been using the model to inspire numerous educators to improve their students’ motivation and skills. The model presents various game-based learning...... activities, and depicts their required planning and expected outcome through eight levels. At its lower levels, the model contains the possibilities of using stand-alone analogue and digital games as teachers, utilizing games as a facilitator of learning activities, exploiting gamification and motivating......In this paper, we will introduce the Game Enhanced learning Model (GEM), which describes a range of gameoriented learning activities. The model is intended to give an overview of the possibilities of game-based learning in general and all the way up to purposive game productions. In the paper, we...

Acid-Base Learning Outcomes for Students in an Introductory Organic Chemistry Course

Science.gov (United States)

Stoyanovich, Carlee; Gandhi, Aneri; Flynn, Alison B.

2015-01-01

An outcome-based approach to teaching and learning focuses on what the student demonstrably knows and can do after instruction, rather than on what the instructor teaches. This outcome-focused approach can then guide the alignment of teaching strategies, learning activities, and assessment. In organic chemistry, mastery of organic acid-base…

Student Modeling and Machine Learning

OpenAIRE

Sison , Raymund; Shimura , Masamichi

1998-01-01

After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...

A MODEL OF MANAGEMENT STRATEGY FOR A QUALITY LEARNING IN ISLAMIC HIGHER EDUCATION (IHE

Directory of Open Access Journals (Sweden)

Ara Hidayat

2016-03-01

Full Text Available The quality of Islamic education is generally influenced by several factors, among other things: leadership, organizational culture, lecturercompetence versus faculty student ratio, dynamic curriculum, library collections and learning facilities. The factors above are most likely to influence and impact the quality of education process in general. Developing a model of management strategy for quality learning is a minimal effort to improve quality graduates of a university. The model was developed on the basis of the following theories: (1 transformative leadership (Tichy and Devana (1997, (2 strategy of learning organization, (Peter (2002, and (3 a quality-based management (Griffin, 2004. Furthermore, the model shares the following characteristics: (1 a quality learning emerges from an effective and efficient management of academic service; (2 developing management of a quality learning is continuous lecture development; (3 lecture plays an important role in developing a quality learning; (4 a quality learning stipulates that a leader be loyal and committed to their job, wise and have a sense of democracy.

A Conceptual Framework for Mentoring in a Learning Organization

Science.gov (United States)

Klinge, Carolyn M.

2015-01-01

The purpose of this article is to provide a conceptual framework for mentoring as an added component of a learning organization in the context of adult learning and development theories. Mentoring is traditionally a process in which an experienced person (the mentor) guides another person (the mentee or protégé) in the development of her or his…

Institutional Narcissism, Arrogant Organization Disorder and Interruptions in Organizational Learning

Science.gov (United States)

Godkin, Lynn; Allcorn, Seth

2009-01-01

Purpose: This article aims to present an alternative approach to diagnosing behavioral barriers to organizational learning. Design/methodology/approach: The paper juxtaposes interruptions in organizational learning with characteristics of narcissism and arrogant organization disorder. Psychoanalytically informed theory and DSM-IV criteria are…

Problems in the Deployment of Learning Networks In Small Organizations

NARCIS (Netherlands)

Shankle, Dean E.; Shankle, Jeremy P.

2006-01-01

Please, cite this publication as: Shankle, D.E., & Shankle, J.P. (2006). Problems in the Deployment of Learning Networks In Small Organizations. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence Conference. March 30th-31st, Sofia, Bulgaria:

Learning for Sustainability Among Faith-Based Organizations in Kenya

Science.gov (United States)

Moyer, Joanne M.; Sinclair, A. John; Diduck, Alan P.

2014-08-01

The complex and unpredictable contexts in which environmental and development work take place require an adaptable, learning approach. Faith-based organizations (FBOs) play a significant role in sustainability work around the world, and provide a unique setting in which to study learning. This paper explores individual learning for sustainability within two FBOs engaged in sustainability work in Kenya. Learning outcomes covered a broad range of areas, including the sustainability framework, environment/conservation, skills, community work, interpersonal engagement, and personal and faith development. These outcomes were acquired through embodied experience and activity, facilitation by the workplace, interpersonal interaction, personal reflection, and Bible study and worship. Grounded categories were compared to learning domains and processes described by Mezirow's transformative learning theory. The findings indicate that for learning in the sustainability field, instrumental learning and embodied learning processes are particularly important, and consequently they require greater attention in the theory when applied in this field.

MACHINE LEARNING FOR THE SELF-ORGANIZATION OF DISTRIBUTED SYSTEMS IN ECONOMIC APPLICATIONS

Directory of Open Access Journals (Sweden)

Jerzy Balicki

2017-03-01

Full Text Available In this paper, an application of machine learning to the problem of self-organization of distributed systems has been discussed with regard to economic applications, with particular emphasis on supervised neural network learning to predict stock investments and some ratings of companies. In addition, genetic programming can play an important role in the preparation and testing of several financial information systems. For this reason, machine learning applications have been discussed because some software applications can be automatically constructed by genetic programming. To obtain a competitive advantage, machine learning can be used for the management of self-organizing cloud computing systems performing calculations for business. Also the use of selected economic self-organizing distributed systems has been described, including some testing methods of predicting borrower reliability. Finally, some conclusions and directions for further research have been proposed.

Adult Learning and Organizations.

Science.gov (United States)

Dailey, Nancy

1984-01-01

The author argues that most work environments still conform to a hierarchical, bureaucratic pattern--an outdated system. She urges a move to a more andragogical model. The author discusses bureaucratic structure, organizational culture, the influence of leadership, the quality of learning at the workplace, and the employer-employee relationship.…

Interconnected growing self-organizing maps for auditory and semantic acquisition modeling

Directory of Open Access Journals (Sweden)

Mengxue eCao

2014-03-01

Full Text Available Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic--semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners; a reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1 I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2 clear auditory and semantic boundaries can be found in the network representation; (3 cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4 reinforcing-by-link training leads to well-perceived auditory--semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model.

Becoming a Learning Organization Through Dynamic Business Process Management

Directory of Open Access Journals (Sweden)

Marek Szelągowski

2014-01-01

Full Text Available As customers demand easier access to individualized products and services, companies now face an ongoing problem of how to deliver flexible and innovative solutions while maintaining efficiency and competitiveness. In this environment, the only sustainable form of competitive advantage rests in the ability to learn faster than the competition (de Geus, 1988. The article returns to the somewhat forgotten concept of the learning organization and explores how its principles can be applied with the use of dynamic business process management (dynamic BPM. Enabling in this concept individual or team-based limited experimentation and providing conditions for learning though experience in the course of performing business processes allows for the constant creation of practical knowledge. This article provides examples of how dynamic BPM facilitates the constant creation and verification of practical knowledge, with the aim of improving and adapting processes to maintain the competitive advantage of the organization.

Graphic Organizers and Students with Learning Disabilities: A Meta-Analysis

Science.gov (United States)

Dexter, Douglas D.; Hughes, Charles A.

2011-01-01

This meta-analysis reviews experimental and quasi-experimental studies in which upper-elementary, intermediate, and secondary students with learning disabilities learned from graphic organizers. Following an exhaustive search for studies meeting specified design criteria, 55 standardized mean effect sizes were extracted from 16 articles involving…

Charting the energy landscape of metal/organic interfaces via machine learning

Science.gov (United States)

Scherbela, Michael; Hörmann, Lukas; Jeindl, Andreas; Obersteiner, Veronika; Hofmann, Oliver T.

2018-04-01

The rich polymorphism exhibited by inorganic/organic interfaces is a major challenge for materials design. In this work, we present a method to efficiently explore the potential energy surface and predict the formation energies of polymorphs and defects. This is achieved by training a machine learning model on a list of only 100 candidate structures that are evaluated via dispersion-corrected density functional theory (DFT) calculations. We demonstrate the power of this approach for tetracyanoethylene on Ag(100) and explain the anisotropic ordering that is observed experimentally.

The Influence of Pintrich's Self-Regulated Learning Model on Elementary Teacher Candidates in a Life Science Course

Science.gov (United States)

Çetin, Baris

2017-01-01

The purpose of this research was to determine whether the use of activities based on Pintrich's self-regulated learning model effect the self-regulated learning perceptions of elementary teacher candidates within a Life Science course. The research was organized in accordance with the quasi-experimental designs model. This study was conducted…

Towards a semantic learning model fostering learning object reusability

OpenAIRE

Fernandes , Emmanuel; Madhour , Hend; Wentland Forte , Maia; Miniaoui , Sami

2005-01-01

We try in this paper to propose a domain model for both author's and learner's needs concerning learning objects reuse. First of all, we present four key criteria for an efficient authoring tool: adaptive level of granularity, flexibility, integration and interoperability. Secondly, we introduce and describe our six-level Semantic Learning Model (SLM) designed to facilitate multi-level reuse of learning materials and search by defining a multi-layer model for metadata. Finally, after mapping ...

Piaget and Organic Chemistry: Teaching Introductory Organic Chemistry through Learning Cycles

Science.gov (United States)

Libby, R. Daniel

1995-07-01

This paper describes the first application of the Piaget-based learning cycle technique (Atkin & Karplus, Sci. Teach. 1962, 29, 45-51) to an introductory organic chemistry course. It also presents the step-by-step process used to convert a lecture course into a discussion-based active learning course. The course is taught in a series of learning cycles. A learning cycle is a three phase process that provides opportunities for students to explore new material and work with an instructor to recognize logical patterns in data, and devise and test hypotheses. In this application, the first phase, exploration, involves out-of-class student evaluation of data in attempts to identify significant trends and develop hypotheses that might explain the trends in terms of fundamental scientific principles. In the second phase, concept invention, the students and instructor work together in-class to evaluate student hypotheses and find concepts that work best in explaining the data. The third phase, application, is an out-of-class application of the concept to new situations. The development of learning cycles from lecture notes is presented as an 8 step procedure. The process involves revaluation and restructuring of the course material to maintain a continuity of concept development according to the instructor's logic, dividing topics into individual concepts or techniques, and refocusing the presentation in terms of large numbers of examples that can serve as data for students in their exploration and application activities. A sample learning cycle and suggestions for ways of limited implementation of learning cycles into existing courses are also provided.

The Emergence of the Open Networked ``i-Learning'' Model

Science.gov (United States)

Elia, Gianluca

The most significant forces that are changing the business world and the society behaviors in this beginning of the twenty-first century can be identified into the globalization of the economy, technological evolution and convergence, change of the workers' expectations, workplace diversity and mobility, and mostly, knowledge and learning as major organizational assets. But which type of ­learning dynamics must be nurtured and pursued within the organizations, today, in order to generate valuable knowledge and its effective applications? After a brief discussion on the main changes observable in management, ICT and society/workplace in the last years, this chapter aims to answer to this question, through the proposition of the “Π-shaped” profile (a new professional archetype for leading change), and through the discussion of the open networked “i-Learning” model (a new framework to “incubate” innovation in learning processes). Actually, the “i” stands for “innovation” (to highlight the nature of the impact on traditional ­learning model), but also it stands for “incubation” (to underline the urgency to have new environments in which incubating new professional profiles). Specifically, the main key characteristics at the basis of the innovation of the learning processes will be ­presented and described, by highlighting the managerial, technological and societal aspects of their nature. A set of operational guidelines will be also ­provided to ­activate and sustain the innovation process, so implementing changes in the strategic dimensions of the model. Finally, the “i-Learning Radar” is presented as an operational tool to design, communicate and control an “i-Learning experience”. This tool is represented by a radar diagram with six strategic dimensions of a ­learning initiative.

27 CFR 22.104 - Educational organizations, colleges of learning, and scientific universities.

Science.gov (United States)

2010-04-01

..., colleges of learning, and scientific universities. 22.104 Section 22.104 Alcohol, Tobacco Products and... OF TAX-FREE ALCOHOL Use of Tax-Free Alcohol § 22.104 Educational organizations, colleges of learning... income tax under 26 U.S.C. 501(a). (b) Colleges of learning. Colleges of learning, for the purposes of...

Multiple organ definition in CT using a Bayesian approach for 3D model fitting

Science.gov (United States)

Boes, Jennifer L.; Weymouth, Terry E.; Meyer, Charles R.

1995-08-01

Organ definition in computed tomography (CT) is of interest for treatment planning and response monitoring. We present a method for organ definition using a priori information about shape encoded in a set of biometric organ models--specifically for the liver and kidney-- that accurately represents patient population shape information. Each model is generated by averaging surfaces from a learning set of organ shapes previously registered into a standard space defined by a small set of landmarks. The model is placed in a specific patient's data set by identifying these landmarks and using them as the basis for model deformation; this preliminary representation is then iteratively fit to the patient's data based on a Bayesian formulation of the model's priors and CT edge information, yielding a complete organ surface. We demonstrate this technique using a set of fifteen abdominal CT data sets for liver surface definition both before and after the addition of a kidney model to the fitting; we demonstrate the effectiveness of this tool for organ surface definition in this low-contrast domain.

Examining Asymmetrical Relationships of Organizational Learning Antecedents: A Theoretical Model

Directory of Open Access Journals (Sweden)

Ery Tri Djatmika

2016-02-01

Full Text Available Global era is characterized by highly competitive advantage market demand. Responding to the challenge of rapid environmental changes, organizational learning is becoming a strategic way and solution to empower people themselves within the organization in order to create a novelty as valuable positioning source. For research purposes, determining the influential antecedents that affect organizational learning is vital to understand research-based solutions given for practical implications. Accordingly, identification of variables examined by asymmetrical relationships is critical to establish. Possible antecedent variables come from organizational and personal point of views. It is also possible to include a moderating one. A proposed theoretical model of asymmetrical effects of organizational learning and its antecedents is discussed in this article.

A strategic systems perspective of organizational learning theory: models for a case study at the Jet Propulsion Laboratory

Science.gov (United States)

Neece, O.

2000-01-01

Organizational learning is an umbrella term that covers a variety of topics including; learning curves, productivity, organizational memory, organizational forgetting, knowledge transfer, knowledge sharing and knowledge creation. This treatise will review some of these theories in concert with a model of how organizations learn.

Learning About Climate and Atmospheric Models Through Machine Learning

Science.gov (United States)

Lucas, D. D.

2017-12-01

From the analysis of ensemble variability to improving simulation performance, machine learning algorithms can play a powerful role in understanding the behavior of atmospheric and climate models. To learn about model behavior, we create training and testing data sets through ensemble techniques that sample different model configurations and values of input parameters, and then use supervised machine learning to map the relationships between the inputs and outputs. Following this procedure, we have used support vector machines, random forests, gradient boosting and other methods to investigate a variety of atmospheric and climate model phenomena. We have used machine learning to predict simulation crashes, estimate the probability density function of climate sensitivity, optimize simulations of the Madden Julian oscillation, assess the impacts of weather and emissions uncertainty on atmospheric dispersion, and quantify the effects of model resolution changes on precipitation. This presentation highlights recent examples of our applications of machine learning to improve the understanding of climate and atmospheric models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Learning Organic Chemistry Through Natural Products -12 ...

Indian Academy of Sciences (India)

Higher Learning. Generations of students would vouch for the fact that he has the uncanny ability to present the chemistry of natural products logically and with feeling. The most interesting chemical aspect of a molecule is its. reactivHy pattern. NR Krishnaswamy. In this part of the series, dynamic organic chemistry and.

Organic Determinants of Learning and Behavioral Disorders.

Science.gov (United States)

Philpott, William H.; And Others

Theories regarding organic determinants of learning and behavior disorders are reviewed historically. Cases illustrating how a bio-ecologic examination can isolate the substances to which a person reacts and some of the reasons for those reactions are presented; and the role of various disorders in relation to the central nervous system is…

A Collaborative Model for Ubiquitous Learning Environments

Science.gov (United States)

Barbosa, Jorge; Barbosa, Debora; Rabello, Solon

2016-01-01

Use of mobile devices and widespread adoption of wireless networks have enabled the emergence of Ubiquitous Computing. Application of this technology to improving education strategies gave rise to Ubiquitous e-Learning, also known as Ubiquitous Learning. There are several approaches to organizing ubiquitous learning environments, but most of them…

Learning from erroneous models using SCYDynamics

NARCIS (Netherlands)

Mulder, Y.G.; Bollen, Lars; de Jong, Anthonius J.M.

2014-01-01

Dynamic phenomena are common in science education. Students can learn about such system dynamic processes through model based learning activities. This paper describes a study on the effects of a learning from erroneous models approach using the learning environment SCYDynamics. The study compared

Problem Based Learning

DEFF Research Database (Denmark)

de Graaff, Erik; Guerra, Aida

, the key principles remain the same everywhere. Graaff & Kolmos (2003) identify the main PBL principles as follows: 1. Problem orientation 2. Project organization through teams or group work 3. Participant-directed 4. Experiental learning 5. Activity-based learning 6. Interdisciplinary learning and 7...... model and in general problem based and project based learning. We apply the principle of teach as you preach. The poster aims to outline the visitors’ workshop programme showing the results of some recent evaluations.......Problem-Based Learning (PBL) is an innovative method to organize the learning process in such a way that the students actively engage in finding answers by themselves. During the past 40 years PBL has evolved and diversified resulting in a multitude in variations in models and practices. However...

Learning in manufacturing organizations : what factors predict effectiveness?

NARCIS (Netherlands)

Shipton, H.; Dawson, J.; West, M.A.; Patterson, M.G.

2002-01-01

This paper argues that it is possible to identify factors which pre-dispose organizations to adopt effective learning strategies and processes. It is hypothesized that effective OL is associated with: profitability, environmental uncertainty, structure, approach to HRM and quality orientation. The

Restaurants as Learning Organizations: A Multiple-Site Case Study of U.S. Non-Chain Restaurants

Science.gov (United States)

Boccia, Mark

2016-01-01

This study investigated the construct of the learning organization in the restaurant industry. Descriptive accounts of learning were gleaned from face-to-face interviews, focus groups, observations, document analysis, and data from the Dimensions of the Learning Organization Questionnaire (DLOQ) from 52 participants employed in three US…

The formation and development of corporate culture of learning organization: efficiency assessment

Directory of Open Access Journals (Sweden)

T. O. Tolstykh

2017-01-01

Full Text Available In modern conditions of digitalization of the economy, its integration with the policy society questions of formation and development of corporate culture of the learning organisation are of particular relevance. Digital transformation of business dictates the need for the emergence and development of learning organizations, creating and preserving knowledge. In this situation, the openness of issues of assessment of efficiency of processes of formation and development defines the importance of the proposed research. Corporate culture is regarded by most scholars as the most important internal resource of the organization, able to provide her with stability in a crisis and give impetus to the development and transition to qualitatively different levels of the life cycle. This position assumes that a strong corporate culture should be aimed at building a learning organization, able to quickly adapt to changes in the external and internal environment. This article examines the issue of assessment of efficiency of corporate culture; it is shown that in addition to the empirical, sociological methods and qualitative approach to evaluation, is acceptable investment approach. This option appears when you use the aggregate target-oriented and project management methods, which allows in a systematic manner to carry out the formation and development of corporate culture. The assessment should be subject to software development activities and (or development of the corporate culture of a learning organization. In evidence to draw conclusions on the example of agricultural companies, a calculation of the economic efficiency of the program of formation of corporate culture of a learning organization. Calculation of net discounted income, the net present value of the project, profitability index, project profitability, payback period. This confirms the social and economic effects of the proposed program on the formation of corporate culture of independent

The Learning Organization Dimensions and Their Impact on Organizational Performance: Orange Jordan as a Case Study

Directory of Open Access Journals (Sweden)

Farid M. Qawasmeh

2013-12-01

Full Text Available The objective of this study is to measure the impact of learning organization's seven key dimensions (continuous learning opportunities, inquiry and dialogue, employee empowerment, establish systems to capture and share learning, connect the organization to its environment, collaboration and team learning, strategic leadership on organizational performance in Jordan Telecom. It also aims to figure out the type and magnitude of correlation among these seven dimensions as well as to assess the credibility of the questionnaire in a different context such as the Arab business environment. The sample size was (312 employees in this case study. The study results are as follows: The status of the learning organization dimensions was moderate (3.44 out of 5 on 5-step Likert scale. A positive statistical correlation exists among the seven learning organization dimensions as well as a positive statistical correlation with organizational performance. The questionnaire proved to be suitable in the Arab business context. Finally, the study recommends that organizations must consider the seven learning organizations’ dimensions due to their role in enhancing organizational performance and assuring a competitive edge.

Community Based Learning and Civic Engagement: Informal Learning among Adult Volunteers in Community Organizations

Science.gov (United States)

Mundel, Karsten; Schugurensky, Daniel

2008-01-01

Many iterations of community based learning employ models, such as consciousness raising groups, cultural circles, and participatory action research. In all of them, learning is a deliberate part of an explicit educational activity. This article explores another realm of community learning: the informal learning that results from volunteering in…

Aging, neurogenesis, and caloric restriction in different model organisms.

Science.gov (United States)

Arslan-Ergul, Ayca; Ozdemir, A Tugrul; Adams, Michelle M

2013-08-01

Brain aging is a multifactorial process that is occurring across multiple cognitive domains. A significant complaint that occurs in the elderly is a decrement in learning and memory ability. Both rodents and zebrafish exhibit a similar problem with memory during aging. The neurobiological changes that underlie this cognitive decline are complex and undoubtedly influenced by many factors. Alterations in the birth of new neurons and neuron turnover may contribute to age-related cognitive problems. Caloric restriction is the only non-genetic intervention that reliably increases life span and healthspan across multiple organisms although the molecular mechanisms are not well-understood. Recently the zebrafish has become a popular model organism for understanding the neurobiological consequences but to date very little work has been performed. Similarly, few studies have examined the effects of dietary restriction in zebrafish. Here we review the literature related to memory decline, neurogenesis, and caloric restriction across model organisms and suggest that zebrafish has the potential to be an important animal model for understanding the complex interactions between age, neurobiological changes in the brain, and dietary regimens or their mimetics as interventions.

Graphic Organizers for Secondary Students with Learning Disabilities

Science.gov (United States)

Singleton, Sabrina M.; Filce, Hollie Gabler

2015-01-01

Research suggests students with learning disabilities often have trouble connecting new and prior knowledge, distinguishing essential and nonessential information, and applying comprehension strategies (DiCecco & Gleason, 2002; Vaughn & Edmonds, 2006). Graphic organizers have been suggested as tools educators can use to facilitate critical…

Visual Perceptual Learning and Models.

Science.gov (United States)

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

THE DYNAMIC MODEL FOR CONTROL OF STUDENT’S LEARNING INDIVIDUAL TRAJECTORY

Directory of Open Access Journals (Sweden)

A. A. Mitsel

2015-01-01

Full Text Available In connection with the transition of the educational system to a competence-oriented approach, the problem of learning outcomes assessment and creating an individual learning trajectory of a student has become relevant. Its solution requires the application of modern information technologies. The third generation of Federal state educational standards of higher professional education (FSES HPE defines the requirements for the results of Mastering the basic educational programs (BEP. According to FSES HPE up to 50% of subjects have a variable character, i.e. depend on the choice of a student. It significantly influences on the results of developing various competencies. The problem of forming student’s learning trajectory is analyzed in general and the choice of an individual direction was studied in details. Various methods, models and algorithms of the student’s individual learning trajectory formation were described. The analysis of the model of educational process organization in terms of individual approach makes it possible to develop a decision support system (DSS. DSS is a set of interrelated programs and data used for analysis of situation, development of alternative solutions and selection of the most acceptable alternative. DSSs are often used when building individual learning path, because this task can be considered as a discrete multi-criteria problem, creating a significant burden on the decision maker. A new method of controlling the learning trajectory has been developed. The article discusses problem statement and solution of determining student’s optimal individual educational trajectory as a dynamic model of learning trajectory control, which uses score assessment to construct a sequence of studied subjects. A new model of management learning trajectory is based on dynamic models for tracking the reference trajectory. The task can be converted to an equivalent model of linear programming, for which a reliable solution

The Socialization of Newcomers into Organizations: Integrating Learning and Social Exchange Processes

Science.gov (United States)

Korte, Russell F.

2007-01-01

Traditional views of socialization focus primarily on the passive learning by the newcomer of the expectations of the organization. Theorizing and research on cognitive learning and social exchange indicate that the socialization process is vastly more complex. This paper views socialization through the lenses of cognitive learning and social…

Characteristics of health care organizations associated with learning and development: lessons from a pilot study.

Science.gov (United States)

Nyström, Monica

2009-01-01

Characteristics of health care organizations associated with an ability to learn from experiences and to develop and manage change were explored in this study. Understanding of these characteristics is necessary to identify factors influencing success in learning from the past and achieving future health care quality objectives. A literature review of the quality improvement, strategic organizational development and change management, organizational learning, and microsystems fields identified 20 organizational characteristics, grouped under (a) organizational systems, (b) key actors, and (c) change management processes. Qualitative methods, using interviews, focus group reports, and archival records, were applied to find associations between identified characteristics and 6 Swedish health care units externally evaluated as delivering high-quality care. Strong support for a characteristic was defined as units having more than 4 sources describing the characteristic as an important success factor. Eighteen characteristics had strong support from at least 2 units. The strongest evidence was found for the following: (i) key actors have long-term commitment, provide support, and make sense of ambiguous situations; (ii) organizational systems encourage employee commitment, participation, and involvement; and (iii) change management processes are employed systematically. Based on the results, a new model of "characteristics associated with learning and development in health care organizations" is proposed.

Individual Learning Accounts and Other Models of Financing Lifelong Learning

Science.gov (United States)

Schuetze, Hans G.

2007-01-01

To answer the question "Financing what?" this article distinguishes several models of lifelong learning as well as a variety of lifelong learning activities. Several financing methods are briefly reviewed, however the principal focus is on Individual Learning Accounts (ILAs) which were seen by some analysts as a promising model for…

Teaching Economics: A Cooperative Learning Model.

Science.gov (United States)

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…

Lessons that Last: Former Youth Organizers' Reflections on What and How They Learned

Science.gov (United States)

Conner, Jerusha

2014-01-01

This study examines the learning outcomes and learning environment of a youth organizing program that has been effective in promoting individual as well as social change. Drawing on interviews with 25 former youth organizers from the program, this study explores the lessons that stay with them as they transition to young adulthood and the factors…

Learning Organic Chemistry Through Natural Products A Practical ...

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 9. Learning Organic Chemistry Through Natural Products A Practical Approach. N R Krishnaswamy. Series Article Volume 1 Issue 9 September 1996 pp 25-33. Fulltext. Click here to view fulltext PDF. Permanent link:

76 FR 50224 - Medicare Program; Accountable Care Organization Accelerated Development Learning Sessions; Center...

Science.gov (United States)

2011-08-12

...] Medicare Program; Accountable Care Organization Accelerated Development Learning Sessions; Center for... (CMS). This two-day training session is the second Accelerated Development Learning Session (ADLS.... Through Accelerated Development Learning Sessions (ADLS), the Innovation Center will test whether...

What’s about Peer Tutoring Learning Model?

Science.gov (United States)

Muthma'innah, M.

2017-09-01

Mathematics learning outcomes in Indonesia in general is still far from satisfactory. One effort that could be expected to solve the problem is to apply the model of peer tutoring learning in mathematics. This study aims to determine whether the results of students’ mathematics learning can be enhanced through peer tutoring learning models. This type of research is the study of literature, so that the method used is to summarize and analyze the results of relevant research that has been done. Peer tutoring learning model is a model of learning in which students learn in small groups that are grouped with different ability levels, all group members to work together and help each other to understand the material. By paying attention to the syntax of the learning, then learning will be invaluable peer tutoring for students who served as teachers and students are taught. In mathematics, the implementation of this learning model can make students understand each other mathematical concepts and help students in solving mathematical problems that are poorly understood, due to the interaction between students in learning. Then it will be able to improve learning outcomes in mathematics. The impact, it can be applied in mathematics learning.

Modelling unsupervised online-learning of artificial grammars: linking implicit and statistical learning.

Science.gov (United States)

Rohrmeier, Martin A; Cross, Ian

2014-07-01

Humans rapidly learn complex structures in various domains. Findings of above-chance performance of some untrained control groups in artificial grammar learning studies raise questions about the extent to which learning can occur in an untrained, unsupervised testing situation with both correct and incorrect structures. The plausibility of unsupervised online-learning effects was modelled with n-gram, chunking and simple recurrent network models. A novel evaluation framework was applied, which alternates forced binary grammaticality judgments and subsequent learning of the same stimulus. Our results indicate a strong online learning effect for n-gram and chunking models and a weaker effect for simple recurrent network models. Such findings suggest that online learning is a plausible effect of statistical chunk learning that is possible when ungrammatical sequences contain a large proportion of grammatical chunks. Such common effects of continuous statistical learning may underlie statistical and implicit learning paradigms and raise implications for study design and testing methodologies. Copyright © 2014 Elsevier Inc. All rights reserved.

Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective

Science.gov (United States)

Lytras, Miltiadis, Ed.; Naeve, Ambjorn, Ed.

2005-01-01

In the context of Knowledge Society, the convergence of knowledge and learning management is a critical milestone. "Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective" provides state-of-the art knowledge through a balanced theoretical and technological discussion. The semantic web perspective…

Inquiry based learning as didactic model in distant learning

NARCIS (Netherlands)

Rothkrantz, L.J.M.

2015-01-01

Recent years many universities are involved in development of Massive Open Online Courses (MOOCs). Unfortunately an appropriate didactic model for cooperated network learning is lacking. In this paper we introduce inquiry based learning as didactic model. Students are assumed to ask themselves

Model brain based learning (BBL and whole brain teaching (WBT in learning

Directory of Open Access Journals (Sweden)

Baiq Sri Handayani

2017-08-01

Full Text Available The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL and the model of Whole Brain Teaching (WBT. The purposes of this article are to obtain information related to (1 the brain’s natural learning system, (2 analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3 explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1 the brain’s natural learning system are: (a the nerves in each hemisphere do not work independently, (b doing more activities can connect more brain nerves, (c the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2 the characteristics of BBL and WBT are: (a BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3 the typical

Implications of Complexity and Chaos Theories for Organizations that Learn

Science.gov (United States)

Smith, Peter A. C.

2003-01-01

In 1996 Hubert Saint-Onge and Smith published an article ("The evolutionary organization: avoiding a Titanic fate", in The Learning Organization, Vol. 3 No. 4), based on their experience at the Canadian Imperial Bank of Commerce (CIBC). It was established at CIBC that change could be successfully facilitated through blended application…

A New Mobile Learning Adaptation Model

OpenAIRE

Mohamd Hassan Hassan; Jehad Al-Sadi

2009-01-01

This paper introduces a new model for m- Learning context adaptation due to the need of utilizing mobile technology in education. Mobile learning; m-Learning for short; in considered to be one of the hottest topics in the educational community, many researches had been done to conceptualize this new form of learning. We are presenting a promising design for a model to adapt the learning content in mobile learning applications in order to match the learner context, preferences and the educatio...

Analysis of the Effect of Sequencing Lecture and Laboratory Instruction on Student Learning and Motivation Towards Learning Chemistry in an Organic Chemistry Lecture Course

Science.gov (United States)

Pakhira, Deblina

2012-01-01

Exposure to organic chemistry concepts in the laboratory can positively affect student performance, learning new chemistry concepts and building motivation towards learning chemistry in the lecture. In this study, quantitative methods were employed to assess differences in student performance, learning, and motivation in an organic chemistry…

Effect Of Inquiry Learning Model And Motivation On Physics Outcomes Learning Students

OpenAIRE

Pardede, Dahlia Megawati; Manurung, Sondang Rina

2016-01-01

The purposes of the research are: (a) to determine differences in learning outcomes of students with Inquiry Training models and conventional models, (b) to determine differences in physics learning outcomes of students who have high motivation and low motivation, (c) to determine the interaction between learning models with the level of motivation in improving student Physics learning outcomes. The results were found: (a) there are differences in physical students learning outcomes are taugh...

76 FR 66931 - Medicare Program; Accountable Care Organization Accelerated Development Learning Sessions; Center...

Science.gov (United States)

2011-10-28

...] Medicare Program; Accountable Care Organization Accelerated Development Learning Sessions; Center for... Services (CMS). This two-day training session is the third and final Accelerated Development Learning... the quality of care for beneficiaries. Through Accelerated Development Learning Sessions (ADLS), the...

A survey on the effects of knowledge management on organizational learning: A case study of technical and vocational training organization

Directory of Open Access Journals (Sweden)

Naser Azad

2014-04-01

Full Text Available This paper presents an empirical investigation to study the effects of knowledge management on organizational learning. The study is held in headquarter of technical and vocational training organization in city of Tehran, Iran. The proposed study measures the effects of concept of management, management, knowledge tools, measurement, change management and knowledge content on organizational learning. The study designs a questionnaire in Likert scale and selects a sample of 313 people randomly from 1680 people who work for this organization in city of Tehran, Iran. Using structural equation modeling, the study has detected a positive and meaningful relationship with knowledge management on organizational learning. In our survey, knowledge content is the most important factor followed by change management.

Evaluation of quality of pedagogic model for blended learning on course “Life safety”

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M. V. Legan

2016-01-01

Full Text Available The article is devoted to evaluating the quality of the pedagogical model for the students’ blended learning on the course «Health and Safety». A choice of the used technologies, forms, active and interactive methods in the learning process, learning tools is made; a new generation of multi-media resources is developed; the quality of teaching evaluation by blended learning model according to the process approach is carried out.The purpose of the study was to assess the quality blended learning model with different ratios of classroom and e-learning component of students on the course “Health and Safety”.Two groups of students were involved in the experiment:1st experimental group (152 persons were the students of all areas of training, learning on the course “Health and Safety”, using a blended approach. E-learning technologies were used to provide the access to information resources (electronic educational-methodical complex on discipline, placed in the electronic educational environment of the University, the organization of self-study, sending the lecturer coursework and examinations, passing the intermediate and final testing for the purpose of monitoring assessment of the knowledge quality. This kind of blended learning models («with a web-enabled learning» is characterized by the addition of electronic educational resources without reducing the hours of a traditional component.2nd experimental group: (164 persons – students enrolled in the course «Health and Safety» in the blended learning model. Students have been using the distance technology for self-study according to the curriculum – 80% of university hours. Personal communication («face to face» was with the lecturer during the session.We have tested two groups of students who participated in the experiment (final control via a module testing electronic environment. In order to assess the quality of blended learning model we used a process approach. An

BLENDED LEARNING AND FEATURES OF THE USE OF THE ROTATION MODEL IN THE EDUCATIONAL PROCESS

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Tkachuk H.

2017-12-01

Full Text Available The article analyzes of the problem of blended learning in higher education institutions. In particular, the article analyzes the legislative documents about the implementation of information technologies in the educational process, strategies for higher education, the introduction of distance learning, that determine importance of blended learning. The author also analyzes the concept of blended learning based on the definitions that are considered in the scientific and pedagogical literature. That analysis determines the ambiguity and incorrectness of the different definitions. It was proposed author's definition for this term. For order to identify the benefits of blended learning, it was analyzed of the positive and negative aspects of all technologies that are combined in the system of blended learning. Based on the analysis of different learning models, it was determined that the most optimal models is the station rotation model and the flipped classroom. The article provides an example of the use of a combination of these models for learning the topic "Computer Structure" by the students of the direction of training "Informatics". The education session was taking place in several stages and involves changing the five stations. Based on the conducted research was identified the general didactic and methodical principles of organization of blended learning.

Evaluation of Learning Processes in an Organic Chemistry Course.

Science.gov (United States)

Maroto, B.; Camusso, C.; Cividini, M.

1997-01-01

Reviews a subjective exercise completed by students at the end of each of six units in an introductory organic chemistry course. Argues that instruction should be shaped by Ausubel's concept of meaningful learning. (DDR)

A CONCEPTUAL MODEL FOR EFFECTIVE DISTANCE LEARNING IN HIGHER A CONCEPTUAL MODEL FOR EFFECTIVE DISTANCE LEARNING IN HIGHER A CONCEPTUAL MODEL FOR EFFECTIVE DISTANCE LEARNING IN HIGHER EDUCATION

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Mehran FARAJOLLAHI

2010-07-01

Full Text Available The present research aims at presenting a conceptual model for effective distance learning in higher education. Findings of this research shows that an understanding of the technological capabilities and learning theories especially constructive theory and independent learning theory and communicative and interaction theory in Distance learning is an efficient factor in the planning of effective Distance learning in higher education. Considering the theoretical foundations of the present research, in the effective distance learning model, the learner is situated at the center of learning environment. For this purpose, the learner needs to be ready for successful learning and the teacher has to be ready to design the teaching- learning activities when they initially enter the environment. In the present model, group and individual active teaching-learning approach, timely feedback, using IT and eight types of interactions have been designed with respect to theoretical foundations and current university missions. From among the issues emphasized in this model, one can refer to the Initial, Formative and Summative evaluations. In an effective distance learning environment, evaluation should be part of the learning process and the feedback resulting from it should be used to improve learning. For validating the specified features, the opinions of Distance learning experts in Payame Noor, Shiraz, Science and Technology and Amirkabir Universities have been used which verified a high percentage of the statistical sample of the above mentioned features.

STEM based learning to facilitate middle school students’ conceptual change, creativity and collaboration in organization of living system topic

Science.gov (United States)

Rustaman, N. Y.; Afianti, E.; Maryati, S.

2018-05-01

A study using one group pre-post-test experimental design on Life organization system topic was carried out to investigate student’s tendency in learning abstract concept, their creativity and collaboration in designing and producing cell models through STEM-based learning. A number of seventh grade students in Cianjur district were involved as research subjects (n=34). Data were collected using two tier test for tracing changes in student conception before and after the application of STEM-based learning, and rubrics in creativity design (adopted from Torrance) and product on cell models (individually, in group), and rubric for self-assessment and observed skills on collaboration adapted from Marzano’s for life-long learning. Later the data obtained were analyzed qualitatively by interpreting the tendency of data presented in matrix sorted by gender. Research findings showed that the percentage of student’s scientific concept mastery is moderate in general. Their creativity in making a cell model design varied in category (expressing, emergent, excellent, not yet evident). Student’s collaboration varied from excellent, fair, good, less once, to less category in designing cell model. It was found that STEM based learning can facilitate students conceptual change, creativity and collaboration.

Transforming practice organizations to foster lifelong learning and commitment to medical professionalism.

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Frankford, D M; Patterson, M A; Konrad, T R

2000-07-01

Practice organizations will increasingly engage in activities that are the functional equivalents of continuing medical education. The authors maintain that if these activities are properly structured within practice organizations, they can become powerful engines of socialization to enhance physicians' lifelong learning and commitment to medical professionalism. They propose that this promise can be realized if new or reformed practice organizations combine education and service delivery and institutionalize processes of individual and collective reflection. The resulting "institutions of reflective practice" would be ones of collegial, experiential, reflective lifelong learning concerning the technical and normative aspects of medical work. They would extend recent methods of medical education such as problem-based learning into the practice setting and draw on extant methods used in complex organizations to maximize the advantages and minimize the disadvantages that practice organizations typically present for adult learning. As such, these institutions would balance the potentially conflicting organizational needs for, on the one hand, (1) self-direction, risk taking, and creativity; (2) specialization; and (3) collegiality; and, on the other hand, (4) organizational structure, (5) coordination of division of labor, and (6) hierarchy. Overall, this institutionalization of reflective practice would enrich practice with education and education with practice, and accomplish the ideals of what the authors call "responsive medical professionalism." The medical profession would both contribute and be responsive to social values, and medical work would be valued intrinsically and as central to practitioners' self-identity and as a contribution to the public good.

Learning classification models with soft-label information.

Science.gov (United States)

Nguyen, Quang; Valizadegan, Hamed; Hauskrecht, Milos

2014-01-01

Learning of classification models in medicine often relies on data labeled by a human expert. Since labeling of clinical data may be time-consuming, finding ways of alleviating the labeling costs is critical for our ability to automatically learn such models. In this paper we propose a new machine learning approach that is able to learn improved binary classification models more efficiently by refining the binary class information in the training phase with soft labels that reflect how strongly the human expert feels about the original class labels. Two types of methods that can learn improved binary classification models from soft labels are proposed. The first relies on probabilistic/numeric labels, the other on ordinal categorical labels. We study and demonstrate the benefits of these methods for learning an alerting model for heparin induced thrombocytopenia. The experiments are conducted on the data of 377 patient instances labeled by three different human experts. The methods are compared using the area under the receiver operating characteristic curve (AUC) score. Our AUC results show that the new approach is capable of learning classification models more efficiently compared to traditional learning methods. The improvement in AUC is most remarkable when the number of examples we learn from is small. A new classification learning framework that lets us learn from auxiliary soft-label information provided by a human expert is a promising new direction for learning classification models from expert labels, reducing the time and cost needed to label data.

Correlation Between Blended Learning Model With The Perspective Of Learning Effectiveness For Nursing Student

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Susila Sumartiningsih

2015-06-01

Full Text Available ABSTRACT The learning model is one of the enabling factors that influence the achievement of students. That students have a good learning outcomes the lecturer must choose appropriate learning models. But in fact not all lecturers choose the most appropriate learning model with the demands of learning outcomes and student characteristics.The study design was descriptive quantitative correlation. Total population of 785 the number of samples are 202 were taken by purposive sampling. Techniques of data collection is done by cross-sectional and then processed through the Spearman test. The results showed no significant relationship between classroom lecture method in the context of blended learning models to study the effectiveness perspective the p value of 0.001. There is a significant relationship between e-learning methods in the context of blended learning models with perspective of activities study of nursing students the p value of 0.028. There is a significant relationship between learning model of blended learning with the perspective of nursing students learning effectiveness p value 0.167. Researchers recommend to future researchers conduct more research on the comparison between the effectiveness of the learning model based on student learning centers with the e-learning models and its impact on student achievement of learning competencies as well as to the implications for other dimensions of learning outcomes and others.

Perceptual Organization of Visual Structure Requires a Flexible Learning Mechanism

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Aslin, Richard N.

2011-01-01

Bhatt and Quinn (2011) provide a compelling and comprehensive review of empirical evidence that supports the operation of principles of perceptual organization in young infants. They also have provided a comprehensive list of experiences that could serve to trigger the learning of at least some of these principles of perceptual organization, and…

THE USE OF BLENDED LEARNING MODELS IN THE PROCESS OF FOREIGN LANGUAGE LEARNING

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Oleksandra Bezverkha

2017-09-01

Full Text Available In the article, the acute problem of implementation of pedagogical innovations and online technologies into the educational process is analyzed. The article explores the advantages of blended learning as a latter-day educational program in comparison with traditional campus learning. Blended learning is regarded worldwide as the combination of classroom face-to-face sessions with interactive learning opportunities created online. The purpose of the article is to identify blended learning transformational potential impacting students and teachers by ensuring a more personalized learning experience. The concept of blended learning, as a means to enhance foreign language teaching and learning in the classroom during the traditional face-to-face interaction between a teacher and a student, combined with computer-mediated activities, is examined. In the article, the main classification of blended learning models is established. There are four main blended learning models which include both face-to-face instruction time and online learning: Rotation Model, Flex Model, A La Carte Model, and Enriched Virtual Model. Once implemented successfully, a blended model can take advantage of both brick-and-mortar and digital worlds, providing significant benefits for the educational establishments and learners. To integrate any of the blended learning models, a teacher can create online activities that enable learners to explore the topic online at home, and then develop face-to-face interactions to dig deeper into the subject matter at the lesson. The use of blended learning models in order to expand educational opportunities for students while the foreign language acquisition, by increasing the availability and flexibility of education, taking into account student individual learning needs, with some element of student control over time, place and pace, is explored. The realization of blended learning models in regards to age and physiological peculiarities of

Video Killed the Radio Star, but Has Google Killed the Learning Organization?

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Peters, John; Snowden, Kate

2008-01-01

Purpose: The purpose of this paper is to reflect on the journal and organizational learning over the years. Design/methodology/approach: The approach adopted is that of providing a viewpoint perspective to look at the concept of the learning organization. Findings: By looking at organizational learning partly from the perspective of a publisher,…

The Impact of the Learning Organization Environment on the Organizational Learning Process in the Korean Business Context

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Song, Ji Hoon; Jeung, Chang-Wook; Cho, Sei Hyoung

2011-01-01

Purpose: The primary purposes of the current paper are to: provide theoretically clear concepts of the learning organization (LO) and organizational learning (OL) process; and empirically test the relationships among research constructs--environmental aspects of the LO and three types of OL processes at the levels of individual, group/team, and…

Learning Organization Models and Their Application to the U.S. Army

Science.gov (United States)

2016-06-01

acquiring, and transferring knowledge , and at modifying its behavior to reflect new knowledge and insights.” This definition highlights that learning has... knowledge can be used. 21 6. We actively share information with our customers to obtain their ideas to learn and improve services and products. 7...seek learning partners among customers , vendors, and suppliers. Knowledge Management: Acquisition, Creation, Storage and Retrieval, and Transfer and

Transformative Learning Factors to Enhance Integral Healthy Organizations

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Thavinpipatkul, Chanchai; Ratana-Ubol, Archanya; Charungkaittikul, Suwithida

2016-01-01

This article focuses on how organizations search for the key factors to develop integral changes and determine broader and higher transcendental learning skills in order to achieve healthy and sustainable organizational growth more effectively and efficiently. This study employed qualitative approaches. The research method used is an in-depth…

Students’ mathematical learning in modelling activities

DEFF Research Database (Denmark)

Kjeldsen, Tinne Hoff; Blomhøj, Morten

2013-01-01

Ten years of experience with analyses of students’ learning in a modelling course for first year university students, led us to see modelling as a didactical activity with the dual goal of developing students’ modelling competency and enhancing their conceptual learning of mathematical concepts i...... create and help overcome hidden cognitive conflicts in students’ understanding; that reflections within modelling can play an important role for the students’ learning of mathematics. These findings are illustrated with a modelling project concerning the world population....

The Aalborg model

DEFF Research Database (Denmark)

Kolmos, Anette; Fink, Flemming Kobberøe; Krogh, Lone

2004-01-01

The article descibes the concept of problem-based learning and project-organized learning with focus on the Aalborg PBL model.......The article descibes the concept of problem-based learning and project-organized learning with focus on the Aalborg PBL model....

Integrated Model for E-Learning Acceptance

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Ramadiani; Rodziah, A.; Hasan, S. M.; Rusli, A.; Noraini, C.

2016-01-01

E-learning is not going to work if the system is not used in accordance with user needs. User Interface is very important to encourage using the application. Many theories had discuss about user interface usability evaluation and technology acceptance separately, actually why we do not make it correlation between interface usability evaluation and user acceptance to enhance e-learning process. Therefore, the evaluation model for e-learning interface acceptance is considered important to investigate. The aim of this study is to propose the integrated e-learning user interface acceptance evaluation model. This model was combined some theories of e-learning interface measurement such as, user learning style, usability evaluation, and the user benefit. We formulated in constructive questionnaires which were shared at 125 English Language School (ELS) students. This research statistics used Structural Equation Model using LISREL v8.80 and MANOVA analysis.

Vicarious learning from human models in monkeys.

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Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

2012-01-01

We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

Developing a Matrix Organization to Unify Learning Support Services.

Science.gov (United States)

Clarke, John H.; Mansfield, Barry K.

1988-01-01

Describes use of matrix management to organize learning support services on a college campus. Claims matrix management, which links support services from academic and student affairs, increases access, improves accountability, and encourages new programs. (Author/ABL)

Project-organized collaborative learning in distance engineering education

DEFF Research Database (Denmark)

Knudsen, Morten; Bajard, C.; Helbo, Jan

2003-01-01

Transferring a successful on-campus project-organized learning method to distance continued education is complicated by the fact, that the target group as well as the learning environment and forms of communication are fundamentally different. The Master of Industrial Information Technology...... distance education has been selected for experiments with utilization of new information and commu-nication technology and didactic adjustments to make this transfer from on-campus to off-campus a successful endeavor. The adjustments, as well as the assessment of their effect, are based on a system......-atic monitoring and evaluation of the first year, and subsequent reflections by students and teachers....

Toward A Dual-Learning Systems Model of Speech Category Learning

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Bharath eChandrasekaran

2014-07-01

Full Text Available More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article we describe a neurobiologically-constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. We find an age related deficit in reflective-optimal but not reflexive-optimal auditory category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, uni-dimensional rules to more complex, reflexive, multi-dimensional rules. In a second application we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions.

A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

OpenAIRE

Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon

2013-01-01

Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...

Learning Markov Decision Processes for Model Checking

DEFF Research Database (Denmark)

Mao, Hua; Chen, Yingke; Jaeger, Manfred

2012-01-01

. The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation......Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm...... on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system...

Peer-to-Peer Learning and the Army Learning Model

Science.gov (United States)

2012-06-08

education will be delivered to the current and future force. This thesis examined the salient areas proposed by the ALM and its impact on P2P learning ...The Army Learning Model is the new educational model that develops adaptive leaders in an era of persistent conflict. Life-long, individual

Model-observer similarity, error modeling and social learning in rhesus macaques.

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Elisabetta Monfardini

Full Text Available Monkeys readily learn to discriminate between rewarded and unrewarded items or actions by observing their conspecifics. However, they do not systematically learn from humans. Understanding what makes human-to-monkey transmission of knowledge work or fail could help identify mediators and moderators of social learning that operate regardless of language or culture, and transcend inter-species differences. Do monkeys fail to learn when human models show a behavior too dissimilar from the animals' own, or when they show a faultless performance devoid of error? To address this question, six rhesus macaques trained to find which object within a pair concealed a food reward were successively tested with three models: a familiar conspecific, a 'stimulus-enhancing' human actively drawing the animal's attention to one object of the pair without actually performing the task, and a 'monkey-like' human performing the task in the same way as the monkey model did. Reward was manipulated to ensure that all models showed equal proportions of errors and successes. The 'monkey-like' human model improved the animals' subsequent object discrimination learning as much as a conspecific did, whereas the 'stimulus-enhancing' human model tended on the contrary to retard learning. Modeling errors rather than successes optimized learning from the monkey and 'monkey-like' models, while exacerbating the adverse effect of the 'stimulus-enhancing' model. These findings identify error modeling as a moderator of social learning in monkeys that amplifies the models' influence, whether beneficial or detrimental. By contrast, model-observer similarity in behavior emerged as a mediator of social learning, that is, a prerequisite for a model to work in the first place. The latter finding suggests that, as preverbal infants, macaques need to perceive the model as 'like-me' and that, once this condition is fulfilled, any agent can become an effective model.

E-learning policies, practices and challenges in two Norwegian organizations.

Science.gov (United States)

Welle-Strand, Anne; Thune, Taran

2003-05-01

This article reports a pilot study on the uses of technology to enable learning within a formal educational setting in a higher education institution and within a corporation. These two Norwegian cases were selected due to their commitment to technology-enabled learning, as expressed in policy and strategy documents. The aim was to investigate the commitment and actual use of information and communications technology (ICT) for learning as well as what key actors think are the major challenges for successful large scale implementation of ICT for learning. The findings indicate that there is insufficient follow-up on e-learning policies and that there is a general lack of strategic direction and leadership in this area. The key challenges respondents highlight relate to the need for a systematic and pedagogical approach to e-learning in which three equally important considerations must be balanced: organization, pedagogy and technology. Key perspectives of a coherent pedagogical and organizational framework for planning e-learning are discussed.

Vicarious learning from human models in monkeys.

Directory of Open Access Journals (Sweden)

Rossella Falcone

Full Text Available We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

Learning to Learn: towards a Relational and Transformational Model of Learning for Improved Integrated Care Delivery

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John Diamond

2013-06-01

Full Text Available Health and social care systems are implementing fundamental changes to organizational structures and work practices in an effort to achieve integrated care. While some integration initiatives have produced positive outcomes, many have not. We reframe the concept of integration as a learning process fueled by knowledge exchange across diverse professional and organizational communities. We thus focus on the cognitive and social dynamics of learning in complex adaptive systems, and on learning behaviours and conditions that foster collective learning and improved collaboration. We suggest that the capacity to learn how to learn shapes the extent to which diverse professional groups effectively exchange knowledge and self-organize for integrated care delivery.

Construction and Evaluation of Scenarios as a Learning Strategy through Modelling-Simulation

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Juan Luis Peñaloza Figueroa

2014-12-01

Full Text Available From a systemic perspective and in the context of an increasing generalization in the use of new technologies and the change in the educational paradigm -which emphasizes guided and autonomous learning-, the learning strategy should be routed to join logical reasoning and instrumental skills (software. The inclusion of new computing and communication resources to the learning process turns them into teaching tools, which makes it possible to organize the teaching and learning process in a different way. The design of these new scenarios of study has important implications to the way information is processed, to the different levels of learning (descriptive, explanatory or analytical ones and to the way knowledge is acquired and evaluated. In addition, that design takes into account the greater student-content, student-student and student-teacher interactivities, always emphasizing guided independent learning. Thus, the construction, analysis and evaluation of scenarios through models and simulation are the strategy that best suits the current learning style followed by students.

Evolution of co-management: role of knowledge generation, bridging organizations and social learning.

Science.gov (United States)

Berkes, Fikret

2009-04-01

Over a period of some 20 years, different aspects of co-management (the sharing of power and responsibility between the government and local resource users) have come to the forefront. The paper focuses on a selection of these: knowledge generation, bridging organizations, social learning, and the emergence of adaptive co-management. Co-management can be considered a knowledge partnership. Different levels of organization, from local to international, have comparative advantages in the generation and mobilization of knowledge acquired at different scales. Bridging organizations provide a forum for the interaction of these different kinds of knowledge, and the coordination of other tasks that enable co-operation: accessing resources, bringing together different actors, building trust, resolving conflict, and networking. Social learning is one of these tasks, essential both for the co-operation of partners and an outcome of the co-operation of partners. It occurs most efficiently through joint problem solving and reflection within learning networks. Through successive rounds of learning and problem solving, learning networks can incorporate new knowledge to deal with problems at increasingly larger scales, with the result that maturing co-management arrangements become adaptive co-management in time.

Learning in AN Oscillatory Cortical Model

Science.gov (United States)

Scarpetta, Silvia; Li, Zhaoping; Hertz, John

We study a model of generalized-Hebbian learning in asymmetric oscillatory neural networks modeling cortical areas such as hippocampus and olfactory cortex. The learning rule is based on the synaptic plasticity observed experimentally, in particular long-term potentiation and long-term depression of the synaptic efficacies depending on the relative timing of the pre- and postsynaptic activities during learning. The learned memory or representational states can be encoded by both the amplitude and the phase patterns of the oscillating neural populations, enabling more efficient and robust information coding than in conventional models of associative memory or input representation. Depending on the class of nonlinearity of the activation function, the model can function as an associative memory for oscillatory patterns (nonlinearity of class II) or can generalize from or interpolate between the learned states, appropriate for the function of input representation (nonlinearity of class I). In the former case, simulations of the model exhibits a first order transition between the "disordered state" and the "ordered" memory state.

EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

OpenAIRE

Hayati .; Retno Dwi Suyanti

2013-01-01

The objective in this research: (1) Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2) Determine the level of motivation to learn in affects physics student learning outcomes. (3) Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all s...

Student Perceptions of Online Homework Use for Formative Assessment of Learning in Organic Chemistry

Science.gov (United States)

Richards-Babb, Michelle; Curtis, Reagan; Georgieva, Zornitsa; Penn, John H.

2015-01-01

Use of online homework as a formative assessment tool for organic chemistry coursework was examined. Student perceptions of online homework in terms of (i) its ranking relative to other course aspects, (ii) their learning of organic chemistry, and (iii) whether it improved their study habits and how students used it as a learning tool were…

Semantic Maps Capturing Organization Knowledge in e-Learning

Science.gov (United States)

Mavridis, Androklis; Koumpis, Adamantios; Demetriadis, Stavros N.

e-learning, shows much promise in accessibility and opportunity to learn, due to its asynchronous nature and its ability to transmit knowledge fast and effectively. However without a universal standard for online learning and teaching, many systems are proclaimed as “e-learning-compliant”, offering nothing more than automated services for delivering courses online, providing no additional enhancement to reusability and learner personalization. Hence, the focus is not on providing reusable and learner-centered content, but on developing the technology aspects of e-learning. This current trend has made it crucial to find a more refined definition of what constitutes knowledge in the e-learning context. We propose an e-learning system architecture that makes use of a knowledge model to facilitate continuous dialogue and inquiry-based knowledge learning, by exploiting the full benefits of the semantic web as a medium capable for supplying the web with formalized knowledge.

EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

Directory of Open Access Journals (Sweden)

Hayati .

2013-06-01

Full Text Available The objective in this research: (1 Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2 Determine the level of motivation to learn in affects physics student learning outcomes. (3 Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all students in class XI SMA Negeri 1 T.P Sunggal Semester I 2012/2013. The sample of this research was consisted of two classes with a sample of 70 peoples who are determined by purposive sampling, the IPA XI-2 as a class experiment using a model-based multimedia learning Training Inquiry as many as 35 peoples and XI IPA-3 as a control class using learning model Inquiry Training 35 peoples. Hypotheses were analyzed using the GLM at significant level of 0.05 using SPSS 17.0 for Windows. Based on data analysis and hypothesis testing conducted found that: (1 Training Inquiry-based multimedia learning model in improving student learning outcomes rather than learning model physics Inquiry Training. (2 The results of studying physics students who have high motivation to learn better than students who have a low learning motivation. (3 From this research there was an interaction between learning model inquiry-based multimedia training and motivation to study on learning outcomes of students.

Implications of Multimodal Learning Models for foreign language teaching and learning

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Miguel Farías

2011-04-01

Full Text Available This literature review article approaches the topic of information and communications technologies from the perspective of their impact on the language learning process, with particular emphasis on the most appropriate designs of multimodal texts as informed by models of multimodal learning. The first part contextualizes multimodality within the fields of discourse studies, the psychology of learning and CALL; the second, deals with multimodal conceptions of reading and writing by discussing hypertextuality and literacy. A final section outlines the possible implications of multimodal learning models for foreign language teaching and learning.

PENGGUNAAN MODEL PROBLEM BASED LEARNING BERBANTUAN E-LEARNING TERHADAP KEMANDIRIAN BELAJAR MAHASISWA

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Jusep Saputra

2017-11-01

Full Text Available Self-regulated learning of learners can be achieved, if in the process of learning mathematics provides an open opportunity for students to learn independently. This research is a mixed method type embedded design, which aims to do studies focused on the use of the Problem Based Learning (PBL model assisted e-learning to student self-regulated learning. Sample selection is done on the purposive sampling and was taken 2 class contracting courses of school math III. Class A numbered 50 members, 24 the superior group and 26 the low group, given the treatment with PBL models assisted e-learning and class B numbered 50, 27 the superior group and 23 the low group, with expository. Instruments used in this research is self-regulated learning questionnaire with Likert scale. Based on data analysis we concluded that (1 Self-regulated learning of superior and low student who obtains aided PBL models assisted e-learning is better than self-regulated learning of superior and low superior students who obtain expository.

Brain Research: Implications for Learning.

Science.gov (United States)

Soares, Louise M.; Soares, Anthony T.

Brain research has illuminated several areas of the learning process: (1) learning as association; (2) learning as reinforcement; (3) learning as perception; (4) learning as imitation; (5) learning as organization; (6) learning as individual style; and (7) learning as brain activity. The classic conditioning model developed by Pavlov advanced…

Vicarious Learning from Human Models in Monkeys

OpenAIRE

Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

2012-01-01

We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was app...

Differently Structured Advance Organizers Lead to Different Initial Schemata and Learning Outcomes

Science.gov (United States)

Gurlitt, Johannes; Dummel, Sebastian; Schuster, Silvia; Nuckles, Matthias

2012-01-01

Does the specific structure of advance organizers influence learning outcomes? In the first experiment, 48 psychology students were randomly assigned to three differently structured advance organizers: a well-structured, a well-structured and key-concept emphasizing, and a less structured advance organizer. These were followed by a sorting task, a…

The Learning Organization and Some Other Modern Theories of Management

International Nuclear Information System (INIS)

Sugarman, Barry

2003-01-01

In the first part, Dr Sugarman reviewed several recent theories of management and their relevance to NPP management. These theories encompass basic aspects like bureaucracy, un-bureaucracy, quality and excellence, re-engineering, knowledge management, emotional intelligence and learning organisation. Dr Sugarman discussed evolution from the Old Paradigm (Bureaucracy) to the New One (Learning Organization), defining the main aspects of both models, that can be summarises primarily in regards to strategy and structure. In terms of strategy, the new paradigm moves away from being largely inflexible to a much more dynamic environment whereby innovation is encouraged as opposed to performing in the prescribed manner whether suitable or not. The structural changes in the new model are also evident. There has been a marked move away from a hierarchical 'top down' approach to a much flatter structure that encourages less empire building and more openness between teams of various. This ensures a much greater understanding by the whole organisation of what is happening. Dr Sugarman centred his talk on the new model and how this has affected the development of the current situation. The Learning Organisation, according to the definition of Peter Senge in The Fifth Discipline (1990), is an organisation where people continually expand their capacity to create results they truly desire, and where the people are continually learning how to learn together. The movements behind increasing quality introduced a new model into industry based on Production, where workers became responsible for quality assurance instead of quality controls being reviewed by inspectors. All the employees share responsibility for learning how to improve continuously. That means, complete involvement of all staff. Following on from this, the Quality Revolution made appearance and was driven by extra attention to the customer. Out-sourcing became common and the 'Internal customer' became more common. All

Human Economy and Entrepreneurial Learning in a Voluntary Organization

DEFF Research Database (Denmark)

Revsbech, Christine

2014-01-01

"Based on five months anthropological field study in a British affiliate of an American charity in London, Revsbech asks what does learning look like in a social voluntary organization for youth. Her chapter argues that volunteers develop entrepreneurial abilities by shifting flexibly between...

The Effect of Cooperative Learning Model and Kolb Learning Styles on Learning Result of the Basics of Politics

Science.gov (United States)

Sugiharto

2015-01-01

The aims of this research were to determine the effect of cooperative learning model and learning styles on learning result. This quasi-experimental study employed a 2x2 treatment by level, involved independent variables, i.e. cooperative learning model and learning styles, and learning result as the dependent variable. Findings signify that: (1)…

Facilitating Learning Organizations. Making Learning Count.

Science.gov (United States)

Marsick, Victoria J.; Watkins, Karen E.

This book offers advice to facilitators and change agents who wish to build systems-level learning to create knowledge that can be used to gain a competitive advantage. Chapter 1 describes forces driving companies to build, sustain, and effectively use systems-level learning and presents and links a working definition of the learning organization…

Provider-agency fit in substance abuse treatment organizations: implications for learning climate, morale, and evidence-based practice implementation.

Science.gov (United States)

Ramsey, Alex T; van den Berk-Clark, Carissa

2015-05-12

Substance abuse agencies have been slow to adopt and implement evidence-based practices (EBPs), due in part to poor provider morale and organizational climates that are not conducive to successful learning and integration of these practices. Person-organization fit theory suggests that alignment, or fit, between provider- and agency-level characteristics regarding the implementation of EBPs may influence provider morale and organizational learning climate and, thus, implementation success. The current study hypothesized that discrepancies, or lack of fit, between provider- and agency-level contextual factors would negatively predict provider morale and organizational learning climate, outcomes shown to be associated with successful EBP implementation. Direct service providers (n = 120) from four substance abuse treatment agencies responded to a survey involving provider morale, organizational learning climate, agency expectations for EBP use, agency resources for EBP use, and provider attitudes towards EBP use. Difference scores between combinations of provider- and agency-level factors were computed to model provider-agency fit. Quadratic regression analyses were conducted to more adequately and comprehensively model the level of the dependent variables across the entire "fit continuum". Discrepancies, or misfit, between agency expectations and provider attitudes and between agency resources and provider attitudes were associated with poorer provider morale and weaker organizational learning climate. For all hypotheses, the curvilinear model of provider-agency discrepancies significantly predicted provider morale and organizational learning climate, indicating that both directions of misfit (provider factors more favorable than agency factors, and vice-versa) were detrimental to morale and climate. However, outcomes were most negative when providers viewed EBPs favorably, but perceived that agency expectations and resources were less supportive of EBP use. The

The Impact of a Learning Organization on Performance: Focusing on Knowledge Performance and Financial Performance

Science.gov (United States)

Kim, Kyoungshin; Watkins, Karen E.; Lu, Zhenqiu

2017-01-01

Purpose: The purpose of this study is to examine the relationships among a learning organization, knowledge and financial performance using the Dimensions of the Learning Organization Questionnaire and its abbreviated version. Design/methodology/approach: This study used a secondary data set and performed second-order factor analysis and…

Beyond Rote Learning in Organic Chemistry: The Infusion and Impact of Argumentation in Tertiary Education

Science.gov (United States)

Pabuccu, Aybuke; Erduran, Sibel

2017-01-01

There exists bias among students that learning organic chemistry topics requires rote learning. In this paper, we address such bias through an organic chemistry activity designed to promote argumentation. We investigated how pre-service science teachers engage in an argumentation about conformational analysis. Analysis of the outcomes concentrated…

MACHINE LEARNING FOR THE SELF-ORGANIZATION OF DISTRIBUTED SYSTEMS IN ECONOMIC APPLICATIONS

OpenAIRE

Jerzy Balicki; Waldemar Korłub

2017-01-01

In this paper, an application of machine learning to the problem of self-organization of distributed systems has been discussed with regard to economic applications, with particular emphasis on supervised neural network learning to predict stock investments and some ratings of companies. In addition, genetic programming can play an important role in the preparation and testing of several financial information systems. For this reason, machine learning applications have been discussed because ...

Learning Markov models for stationary system behaviors

DEFF Research Database (Denmark)

Chen, Yingke; Mao, Hua; Jaeger, Manfred

2012-01-01

to a single long observation sequence, and in these situations existing automatic learning methods cannot be applied. In this paper, we adapt algorithms for learning variable order Markov chains from a single observation sequence of a target system, so that stationary system properties can be verified using......Establishing an accurate model for formal verification of an existing hardware or software system is often a manual process that is both time consuming and resource demanding. In order to ease the model construction phase, methods have recently been proposed for automatically learning accurate...... the learned model. Experiments demonstrate that system properties (formulated as stationary probabilities of LTL formulas) can be reliably identified using the learned model....

Model of e-learning with electronic educational resources of new generation

Directory of Open Access Journals (Sweden)

A. V. Loban

2017-01-01

Full Text Available Purpose of the article: improving of scientific and methodical base of the theory of the е-learning of variability. Methods used: conceptual and logical modeling of the е-learning of variability process with electronic educational resource of new generation and system analysis of the interconnection of the studied subject area, methods, didactics approaches and information and communication technologies means. Results: the formalization complex model of the е-learning of variability with electronic educational resource of new generation is developed, conditionally decomposed into three basic components: the formalization model of the course in the form of the thesaurusclassifier (“Author of e-resource”, the model of learning as management (“Coordination. Consultation. Control”, the learning model with the thesaurus-classifier (“Student”. Model “Author of e-resource” allows the student to achieve completeness, high degree of didactic elaboration and structuring of the studied material in triples of variants: modules of education information, practical task and control tasks; the result of the student’s (author’s of e-resource activity is the thesaurus-classifier. Model of learning as management is based on the principle of personal orientation of learning in computer environment and determines the logic of interaction between the lecturer and the student when determining the triple of variants individually for each student; organization of a dialogue between the lecturer and the student for consulting purposes; personal control of the student’s success (report generation and iterative search for the concept of the class assignment in the thesaurus-classifier before acquiring the required level of training. Model “Student” makes it possible to concretize the learning tasks in relation to the personality of the student and to the training level achieved; the assumption of the lecturer about the level of training of a

[Mathematical models of decision making and learning].

Science.gov (United States)

Ito, Makoto; Doya, Kenji

2008-07-01

Computational models of reinforcement learning have recently been applied to analysis of brain imaging and neural recording data to identity neural correlates of specific processes of decision making, such as valuation of action candidates and parameters of value learning. However, for such model-based analysis paradigms, selecting an appropriate model is crucial. In this study we analyze the process of choice learning in rats using stochastic rewards. We show that "Q-learning," which is a standard reinforcement learning algorithm, does not adequately reflect the features of choice behaviors. Thus, we propose a generalized reinforcement learning (GRL) algorithm that incorporates the negative reward effect of reward loss and forgetting of values of actions not chosen. Using the Bayesian estimation method for time-varying parameters, we demonstrated that the GRL algorithm can predict an animal's choice behaviors as efficiently as the best Markov model. The results suggest the usefulness of the GRL for the model-based analysis of neural processes involved in decision making.

A workflow learning model to improve geovisual analytics utility.

Science.gov (United States)

Roth, Robert E; Maceachren, Alan M; McCabe, Craig A

2009-01-01

INTRODUCTION: This paper describes the design and implementation of the G-EX Portal Learn Module, a web-based, geocollaborative application for organizing and distributing digital learning artifacts. G-EX falls into the broader context of geovisual analytics, a new research area with the goal of supporting visually-mediated reasoning about large, multivariate, spatiotemporal information. Because this information is unprecedented in amount and complexity, GIScientists are tasked with the development of new tools and techniques to make sense of it. Our research addresses the challenge of implementing these geovisual analytics tools and techniques in a useful manner. OBJECTIVES: The objective of this paper is to develop and implement a method for improving the utility of geovisual analytics software. The success of software is measured by its usability (i.e., how easy the software is to use?) and utility (i.e., how useful the software is). The usability and utility of software can be improved by refining the software, increasing user knowledge about the software, or both. It is difficult to achieve transparent usability (i.e., software that is immediately usable without training) of geovisual analytics software because of the inherent complexity of the included tools and techniques. In these situations, improving user knowledge about the software through the provision of learning artifacts is as important, if not more so, than iterative refinement of the software itself. Therefore, our approach to improving utility is focused on educating the user. METHODOLOGY: The research reported here was completed in two steps. First, we developed a model for learning about geovisual analytics software. Many existing digital learning models assist only with use of the software to complete a specific task and provide limited assistance with its actual application. To move beyond task-oriented learning about software use, we propose a process-oriented approach to learning based on

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches.

Science.gov (United States)

Ließ, Mareike; Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils' carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms-including the model tuning and predictor selection-were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models' predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.

The Reflection of the Learning Organization Concept to School of Education

Directory of Open Access Journals (Sweden)

Esmahan AGAOGLU

2006-01-01

Full Text Available The change and development that has been observed everywhere, it is the result of the knowledge accumulated along the human history. The knowledge was increasing since the primitive era and is now becoming the unique factor of production fast sidelining both capital and power. As a result of this situation, it is treated of the knowledge society. In the knowledge society, it necessitates the learning organisations, which know to profit by knowledge as a basic power. In our time, the organization should adopt the education as a life style and transform them to learning organisation. This situation is current for educational organisations. The societies of today need the individuals who know how to reach knowledge, how to convert the gained knowledge to the behaviours, how to produce new knowledge using them. For growing up the individuals who have these characteristics, educational organisations have to transform to learning organisations. In this process, the teachers also have important role. For this reason, it was realised a descriptive study, which aimed to determine whether the schools of education have the learning organisation features. The sample group of study is the academic staff of the school of education at Anadolu University. The data was gathered with the questionnaire of learning organisation features. At the end of study, it was found that the academic staff believed the faculty had many features of learning organization, but some deficiencies about strategies.

Active Learning with Statistical Models.

Science.gov (United States)

1995-01-01

Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with

Personalised learning object based on multi-agent model and learners’ learning styles

Directory of Open Access Journals (Sweden)

Noppamas Pukkhem

2011-09-01

Full Text Available A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i non-personalised, ii preferred feature-based, and iii neighbour-based collaborative filtering. The analysis of preference error (PE was performed by comparing the actual preferred learning object with the predicted one. In our experiments, the feature-based recommendation algorithm has the fewest PE.

Political learning in territories of exclusion, conflict and popular organization (research notes)

OpenAIRE

Paulo J. Krischke

2006-01-01

This paper discusses some interfaces between the approaches to political learning, and their reference to situations of social exclusion, conflict and popular organization. The first part of the paper discusses the approach to the study of political learning among the elites; the second part examines approaches to research of political culture among the masses; and the third part outlines an alternative approach to political learning derived from Jürgen Habermass theory of comm...

Modellus: Learning Physics with Mathematical Modelling

Science.gov (United States)

Teodoro, Vitor

Computers are now a major tool in research and development in almost all scientific and technological fields. Despite recent developments, this is far from true for learning environments in schools and most undergraduate studies. This thesis proposes a framework for designing curricula where computers, and computer modelling in particular, are a major tool for learning. The framework, based on research on learning science and mathematics and on computer user interface, assumes that: 1) learning is an active process of creating meaning from representations; 2) learning takes place in a community of practice where students learn both from their own effort and from external guidance; 3) learning is a process of becoming familiar with concepts, with links between concepts, and with representations; 4) direct manipulation user interfaces allow students to explore concrete-abstract objects such as those of physics and can be used by students with minimal computer knowledge. Physics is the science of constructing models and explanations about the physical world. And mathematical models are an important type of models that are difficult for many students. These difficulties can be rooted in the fact that most students do not have an environment where they can explore functions, differential equations and iterations as primary objects that model physical phenomena--as objects-to-think-with, reifying the formal objects of physics. The framework proposes that students should be introduced to modelling in a very early stage of learning physics and mathematics, two scientific areas that must be taught in very closely related way, as they were developed since Galileo and Newton until the beginning of our century, before the rise of overspecialisation in science. At an early stage, functions are the main type of objects used to model real phenomena, such as motions. At a later stage, rates of change and equations with rates of change play an important role. This type of equations

Computational modeling of epiphany learning.

Science.gov (United States)

Chen, Wei James; Krajbich, Ian

2017-05-02

Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not all behavior seems to conform to the gradual convergence that is a central feature of RL. In some cases learning seems to happen all at once. Limited prior research on these "epiphanies" has shown evidence of sudden changes in behavior, but it remains unclear how such epiphanies occur. We propose a sequential-sampling model of epiphany learning (EL) and test it using an eye-tracking experiment. In the experiment, subjects repeatedly play a strategic game that has an optimal strategy. Subjects can learn over time from feedback but are also allowed to commit to a strategy at any time, eliminating all other options and opportunities to learn. We find that the EL model is consistent with the choices, eye movements, and pupillary responses of subjects who commit to the optimal strategy (correct epiphany) but not always of those who commit to a suboptimal strategy or who do not commit at all. Our findings suggest that EL is driven by a latent evidence accumulation process that can be revealed with eye-tracking data.

Organization and Integration of Learning Experiences in a Curriculum: A Case Study.

Science.gov (United States)

Everwijn, S. E. M.

1983-01-01

The literature on "organizers" by Ausubel, Earl, and Tyler provides clues to help teachers and students relate what has been learned in one subject to what is being learned in another. Problems of integration in a curriculum for student nurses are examined, and a solution to these problems is described. (RM)

Evaluation Models for E-Learning Platform in Riyadh City Universities (RCU with Applied of Geographical Information System (GIS

Directory of Open Access Journals (Sweden)

Abdulaziz I. Alharrah

2014-12-01

Full Text Available E-learning that integrates digital knowledge content, network and information technology has become an emerging learning method. As the e-learning platform approach is becoming an important tool to allow the flexibility and quality requested by such a kind of learning process. There is a new kind of problem faced by organizations consisting in the selection of the most suitable e-learning platform. This paper proposes evaluation model for E-Learning platform in Riyadh City universities (RCU with Applied Geographic Information System (GIS. The E-Learning platform solution selection is a multiple criteria decision-making problem that needs to be addressed objectively taking into consideration the relative weights of the criteria for any organization. We formulate the quoted multi criteria problem as a decision hierarchy to be solved using GIS. AGIS-based evaluation index system and web-based evaluating platform were established. In this paper we will show the general evaluation strategy and some obtained results using our model to evaluate some existing commercial platforms.The results of evaluation model are outlined as follows: Total weights of the proposed framework in management feature is 20.25/25, in collaborative feature is 9.2/10, in adaption learning path is 6.8/10 and in interactive learning object is 5/5. The total weights of all features are 41.25/50. In this study an evaluation model was applied on Riyadh City universities like KSU, IMAMU, NAUSS, YU and FU. Then, the results were compared with each other. The total weighs of KSU was 41. While the total weights of FU, IMAMU, YU and NAUSS was 40, 37, 36 and 32, respectively. Evaluation process shows that the proposed framework satisfied the objectives with applied GIS.

Tree-Structured Digital Organisms Model

Science.gov (United States)

Suzuki, Teruhiko; Nobesawa, Shiho; Tahara, Ikuo

Tierra and Avida are well-known models of digital organisms. They describe a life process as a sequence of computation codes. A linear sequence model may not be the only way to describe a digital organism, though it is very simple for a computer-based model. Thus we propose a new digital organism model based on a tree structure, which is rather similar to the generic programming. With our model, a life process is a combination of various functions, as if life in the real world is. This implies that our model can easily describe the hierarchical structure of life, and it can simulate evolutionary computation through mutual interaction of functions. We verified our model by simulations that our model can be regarded as a digital organism model according to its definitions. Our model even succeeded in creating species such as viruses and parasites.

Student nurses' experiences of the clinical learning environment in relation to the organization of supervision: a questionnaire survey.

Science.gov (United States)

Sundler, Annelie J; Björk, Maria; Bisholt, Birgitta; Ohlsson, Ulla; Engström, Agneta Kullén; Gustafsson, Margareta

2014-04-01

The aim was to investigate student nurses' experiences of the clinical learning environment in relation to how the supervision was organized. The clinical environment plays an essential part in student nurses' learning. Even though different models for supervision have been previously set forth, it has been stressed that there is a need both of further empirical studies on the role of preceptorship in undergraduate nursing education and of studies comparing different models. A cross-sectional study with comparative design was carried out with a mixed method approach. Data were collected from student nurses in the final term of the nursing programme at three universities in Sweden by means of a questionnaire. In general the students had positive experiences of the clinical learning environment with respect to pedagogical atmosphere, leadership style of the ward manager, premises of nursing, supervisory relationship, and role of the nurse preceptor and nurse teacher. However, there were significant differences in their ratings of the supervisory relationship (ppedagogical atmosphere (p 0.025) depending on how the supervision was organized. Students who had the same preceptor all the time were more satisfied with the supervisory relationship than were those who had different preceptors each day. Students' comments on the supervision confirmed the significance of the preceptor and the supervisory relationship. The organization of the supervision was of significance with regard to the pedagogical atmosphere and the students' relation to preceptors. Students with the same preceptor throughout were more positive concerning the supervisory relationship and the pedagogical atmosphere. © 2013.

Kolb's Experiential Learning Model: Critique from a Modeling Perspective

Science.gov (United States)

Bergsteiner, Harald; Avery, Gayle C.; Neumann, Ruth

2010-01-01

Kolb's experiential learning theory has been widely influential in adult learning. The theory and associated instruments continue to be criticized, but rarely is the graphical model itself examined. This is significant because models can aid scientific understanding and progress, as well as theory development and research. Applying accepted…

Model United Nations and Deep Learning: Theoretical and Professional Learning

Science.gov (United States)

Engel, Susan; Pallas, Josh; Lambert, Sarah

2017-01-01

This article demonstrates that the purposeful subject design, incorporating a Model United Nations (MUN), facilitated deep learning and professional skills attainment in the field of International Relations. Deep learning was promoted in subject design by linking learning objectives to Anderson and Krathwohl's (2001) four levels of knowledge or…

Cognitive components underpinning the development of model-based learning.

Science.gov (United States)

Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

2017-06-01

Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Learning strategies: a synthesis and conceptual model

Science.gov (United States)

Hattie, John A. C.; Donoghue, Gregory M.

2016-08-01

The purpose of this article is to explore a model of learning that proposes that various learning strategies are powerful at certain stages in the learning cycle. The model describes three inputs and outcomes (skill, will and thrill), success criteria, three phases of learning (surface, deep and transfer) and an acquiring and consolidation phase within each of the surface and deep phases. A synthesis of 228 meta-analyses led to the identification of the most effective strategies. The results indicate that there is a subset of strategies that are effective, but this effectiveness depends on the phase of the model in which they are implemented. Further, it is best not to run separate sessions on learning strategies but to embed the various strategies within the content of the subject, to be clearer about developing both surface and deep learning, and promoting their associated optimal strategies and to teach the skills of transfer of learning. The article concludes with a discussion of questions raised by the model that need further research.

Learning Probabilistic Logic Models from Probabilistic Examples.

Science.gov (United States)

Chen, Jianzhong; Muggleton, Stephen; Santos, José

2008-10-01

We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples.

Self-enhancement learning: target-creating learning and its application to self-organizing maps.

Science.gov (United States)

Kamimura, Ryotaro

2011-05-01

In this article, we propose a new learning method called "self-enhancement learning." In this method, targets for learning are not given from the outside, but they can be spontaneously created within a neural network. To realize the method, we consider a neural network with two different states, namely, an enhanced and a relaxed state. The enhanced state is one in which the network responds very selectively to input patterns, while in the relaxed state, the network responds almost equally to input patterns. The gap between the two states can be reduced by minimizing the Kullback-Leibler divergence between the two states with free energy. To demonstrate the effectiveness of this method, we applied self-enhancement learning to the self-organizing maps, or SOM, in which lateral interactions were added to an enhanced state. We applied the method to the well-known Iris, wine, housing and cancer machine learning database problems. In addition, we applied the method to real-life data, a student survey. Experimental results showed that the U-matrices obtained were similar to those produced by the conventional SOM. Class boundaries were made clearer in the housing and cancer data. For all the data, except for the cancer data, better performance could be obtained in terms of quantitative and topological errors. In addition, we could see that the trustworthiness and continuity, referring to the quality of neighborhood preservation, could be improved by the self-enhancement learning. Finally, we used modern dimensionality reduction methods and compared their results with those obtained by the self-enhancement learning. The results obtained by the self-enhancement were not superior to but comparable with those obtained by the modern dimensionality reduction methods.

Active Learning for Player Modeling

DEFF Research Database (Denmark)

Shaker, Noor; Abou-Zleikha, Mohamed; Shaker, Mohammad

2015-01-01

Learning models of player behavior has been the focus of several studies. This work is motivated by better understanding of player behavior, a knowledge that can ultimately be employed to provide player-adapted or personalized content. In this paper, we propose the use of active learning for player...... experience modeling. We use a dataset from hundreds of players playing Infinite Mario Bros. as a case study and we employ the random forest method to learn mod- els of player experience through the active learning approach. The results obtained suggest that only part of the dataset (up to half the size...... that the method can be used online during the content generation process where the mod- els can improve and better content can be presented as the game is being played....

Multidimensional Learner Model In Intelligent Learning System

Science.gov (United States)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

A novel self-organizing E-Learner community model with award and exchange mechanisms.

Science.gov (United States)

Yang, Fan; Shen, Rui-min; Han, Peng

2004-11-01

How to share experience and resources among learners is becoming one of the hottest topics in the field of E-Learning collaborative techniques. An intuitive way to achieve this objective is to group learners which can help each other into the same community and help them learn collaboratively. In this paper, we proposed a novel community self-organization model based on multi-agent mechanism, which can automatically group learners with similar preferences and capabilities. In particular, we proposed award and exchange schemas with evaluation and preference track records to raise the performance of this algorithm. The description of learner capability, the matchmaking process, the definition of evaluation and preference track records, the rules of award and exchange schemas and the self-organization algorithm are all discussed in this paper. Meanwhile, a prototype has been built to verify the validity and efficiency of the algorithm. Experiments based on real learner data showed that this mechanism can organize learner communities properly and efficiently; and that it has sustainable improved efficiency and scalability.

Efficient model learning methods for actor-critic control.

Science.gov (United States)

Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik

2012-06-01

We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.

Student Perceptions of Online Homework Use for Formative Assessment of Learning in Organic Chemistry.

Science.gov (United States)

Richards-Babb, Michelle; Curtis, Reagan; Georgieva, Zomitsa; Penn, John H

2015-11-10

Use of online homework as a formative assessment tool for organic chemistry coursework was examined. Student perceptions of online homework in terms of (i) its ranking relative to other course aspects, (ii) their learning of organic chemistry, and (iii) whether it improved their study habits and how students used it as a learning tool were investigated. Our students perceived the online homework as one of the more useful course aspects for learning organic chemistry content. We found a moderate and statistically significant correlation between online homework performance and final grade. Gender as a variable was ruled out since significant gender differences in overall attitude toward online homework use and course success rates were not found. Our students expressed relatively positive attitudes toward use of online homework with a majority indicating improved study habits (e.g., study in a more consistent manner). Our students used a variety of resources to remediate incorrect responses (e.g., class materials, general online materials, and help from others). However, 39% of our students admitted to guessing at times, instead of working to remediate incorrect responses. In large enrollment organic chemistry courses, online homework may act to bridge the student-instructor gap by providing students with a supportive mechanism for regulated learning of content.

Team learning: building shared mental models

NARCIS (Netherlands)

Bossche, van den P.; Gijselaers, W.; Segers, M.; Woltjer, G.B.; Kirschner, P.

2011-01-01

To gain insight in the social processes that underlie knowledge sharing in teams, this article questions which team learning behaviors lead to the construction of a shared mental model. Additionally, it explores how the development of shared mental models mediates the relation between team learning

Modeling the behavioral substrates of associate learning and memory - Adaptive neural models

Science.gov (United States)

Lee, Chuen-Chien

1991-01-01

Three adaptive single-neuron models based on neural analogies of behavior modification episodes are proposed, which attempt to bridge the gap between psychology and neurophysiology. The proposed models capture the predictive nature of Pavlovian conditioning, which is essential to the theory of adaptive/learning systems. The models learn to anticipate the occurrence of a conditioned response before the presence of a reinforcing stimulus when training is complete. Furthermore, each model can find the most nonredundant and earliest predictor of reinforcement. The behavior of the models accounts for several aspects of basic animal learning phenomena in Pavlovian conditioning beyond previous related models. Computer simulations show how well the models fit empirical data from various animal learning paradigms.

A reinforcement learning model of joy, distress, hope and fear

Science.gov (United States)

Broekens, Joost; Jacobs, Elmer; Jonker, Catholijn M.

2015-07-01

In this paper we computationally study the relation between adaptive behaviour and emotion. Using the reinforcement learning framework, we propose that learned state utility, ?, models fear (negative) and hope (positive) based on the fact that both signals are about anticipation of loss or gain. Further, we propose that joy/distress is a signal similar to the error signal. We present agent-based simulation experiments that show that this model replicates psychological and behavioural dynamics of emotion. This work distinguishes itself by assessing the dynamics of emotion in an adaptive agent framework - coupling it to the literature on habituation, development, extinction and hope theory. Our results support the idea that the function of emotion is to provide a complex feedback signal for an organism to adapt its behaviour. Our work is relevant for understanding the relation between emotion and adaptation in animals, as well as for human-robot interaction, in particular how emotional signals can be used to communicate between adaptive agents and humans.

A Hybrid Teaching and Learning Model

Science.gov (United States)

Juhary, Jowati Binti

This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches.

Directory of Open Access Journals (Sweden)

Mareike Ließ

Full Text Available Tropical forests are significant carbon sinks and their soils' carbon storage potential is immense. However, little is known about the soil organic carbon (SOC stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms-including the model tuning and predictor selection-were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models' predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.

Learning teams and networks: using information technology as a means of managing work process development in healthcare organizations.

Science.gov (United States)

Korhonen, Vesa; Paavilainen, Eija

2002-01-01

This article focuses on the introduction of team learning and shared knowledge creation using computer-based learning environments and teams as networks in the development of healthcare organizations. Using computer technology, care units can be considered learning teams and the hospital a network of those learning teams. Team learning requires that the healthcare workers' intellectual capital and personal competence be viewed as an important resource in developing the quality of action of the entire healthcare organization.

THE IMPACT OF VISIONARY LEADERSHIP, LEARNING ORGANIZATION AND INNOVATIVE BEHAVIOR TO PERFORMANCE OF CUSTOMS AND EXCISE FUNCTIONAL

Directory of Open Access Journals (Sweden)

Muhammad Anshar

2017-12-01

Full Text Available This research aims to determine the impact of visionary leadership, learning organization, and innovative behavior on the performance of Functional Officers of Customs and Excise Inspectors at Tanjung Priok Customs and Excise Main Service Office. The research was conducted at Tanjung Priok Customs and Excise Service Office using the number of samples of 78 Functional Officers of Customs and Excise Inspectors. The sample was selected using simple random sampling technique. Data collection was done by using questionnaire and data analysis using path analysis. The results showed that 1 visionary leadership, learning organization and innovative behavior have a direct and positive impact on performance, 2 visionary leadership, and learning organization have a direct and positive impact on innovative behavior and 3 visionary leadership have a direct and positive impact on learning organization. The conclusion of this research is to improve the performance of Functional Officer of Customs and Excise Inspectors at TanjungPriok Customs and Excise Main Service Office, it is necessary to increase the aspect of visionary leadership from Head of Main Service Office, learning organization at Main Service Office and innovative behavior at Functional Officers of Customs and Excise Inspectors.

Enhanced democratic learning within the Aalborg Model

DEFF Research Database (Denmark)

Qvist, Palle

2010-01-01

The Aalborg PBL Model [Kjersdam & Enemark, 1997; Kolmos et al., 2004] is an example of a democratic learning system [Qvist, 2008]. Writing one project each semester in teams is an important element in the model. Medicine with Industrial Specialisation - a study at the Faculties of Engineering......, Science and Medicine at Aalborg University - has combined the Aalborg Model with solving cases as used by other models. A questionnaire survey related to democratic learning indicates that the democratic learning has been enhanced. This paper presents the results....

Universities as Inclusive Learning Organizations for Women?: Considering the Role of Women in Faculty and Leadership Roles in Academe

Science.gov (United States)

Gouthro, Patricia; Taber, Nancy; Brazil, Amanda

2018-01-01

Purpose: The purpose of this paper is to explore the concept of the learning organization, first discussed by Senge (1990), to determine if it can work as a model in the higher education sector. Design/methodology/approach: Using a critical feminist framework, this paper assesses the possibilities and challenges of viewing universities as…

Dopamine selectively remediates 'model-based' reward learning: a computational approach.

Science.gov (United States)

Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna

2016-02-01

Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Variability in Dopamine Genes Dissociates Model-Based and Model-Free Reinforcement Learning.

Science.gov (United States)

Doll, Bradley B; Bath, Kevin G; Daw, Nathaniel D; Frank, Michael J

2016-01-27

Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by "model-free" learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by "model-based" learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative consideration of potential choice outcomes

Learning to classify organic and conventional wheat - a machine-learning driven approach using the MeltDB 2.0 metabolomics analysis platform

Directory of Open Access Journals (Sweden)

Nikolas eKessler

2015-03-01

Full Text Available We present results of our machine learning approach to the problem of classifying GC-MS data originating from wheat grains of different farming systems. The aim is to investigate the potential of learning algorithms to classify GC-MS data to be either from conventionally grown or from organically grown samples and considering different cultivars. The motivation of our work is rather obvious on the background of nowadays increased demand for organic food in post-industrialized societies and the necessity to prove organic food authenticity. The background of our data set is given by up to eleven wheat cultivars that have been cultivated in both farming systems, organic and conventional, throughout three years. More than 300 GC-MS measurements were recorded and subsequently processed and analyzed in the MeltDB 2.0 metabolomics analysis platform, being briefly outlined in this paper. We further describe how unsupervised (t-SNE, PCA and supervised (RF, SVM methods can be applied for sample visualization and classification. Our results clearly show that years have most and wheat cultivars have second-most influence on the metabolic composition of a sample. We can also show, that for a given year and cultivar, organic and conventional cultivation can be distinguished by machine-learning algorithms.

Mosaic model for sensorimotor learning and control.

Science.gov (United States)

Haruno, M; Wolpert, D M; Kawato, M

2001-10-01

Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.

A Judgement-Based Model of Workplace Learning

Science.gov (United States)

Athanasou, James A.

2004-01-01

The purpose of this paper is to outline a judgement-based model of adult learning. This approach is set out as a Perceptual-Judgemental-Reinforcement approach to social learning under conditions of complexity and where there is no single, clearly identified correct response. The model builds upon the Hager-Halliday thesis of workplace learning and…

Technology Learning Ratios in Global Energy Models

International Nuclear Information System (INIS)

Varela, M.

2001-01-01

The process of introduction of a new technology supposes that while its production and utilisation increases, also its operation improves and its investment costs and production decreases. The accumulation of experience and learning of a new technology increase in parallel with the increase of its market share. This process is represented by the technological learning curves and the energy sector is not detached from this process of substitution of old technologies by new ones. The present paper carries out a brief revision of the main energy models that include the technology dynamics (learning). The energy scenarios, developed by global energy models, assume that the characteristics of the technologies are variables with time. But this trend is incorporated in a exogenous way in these energy models, that is to say, it is only a time function. This practice is applied to the cost indicators of the technology such as the specific investment costs or to the efficiency of the energy technologies. In the last years, the new concept of endogenous technological learning has been integrated within these global energy models. This paper examines the concept of technological learning in global energy models. It also analyses the technological dynamics of the energy system including the endogenous modelling of the process of technological progress. Finally, it makes a comparison of several of the most used global energy models (MARKAL, MESSAGE and ERIS) and, more concretely, about the use these models make of the concept of technological learning. (Author) 17 refs

Learning and Model-checking Networks of I/O Automata

DEFF Research Database (Denmark)

Mao, Hua; Jaeger, Manfred

2012-01-01

We introduce a new statistical relational learning (SRL) approach in which models for structured data, especially network data, are constructed as networks of communicating nite probabilistic automata. Leveraging existing automata learning methods from the area of grammatical inference, we can...... learn generic models for network entities in the form of automata templates. As is characteristic for SRL techniques, the abstraction level aorded by learning generic templates enables one to apply the learned model to new domains. A main benet of learning models based on nite automata lies in the fact...

Evolutionarily stable learning schedules and cumulative culture in discrete generation models.

Science.gov (United States)

Aoki, Kenichi; Wakano, Joe Yuichiro; Lehmann, Laurent

2012-06-01

Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium. Copyright © 2012 Elsevier Inc. All rights reserved.

A Self-Organizing Incremental Neural Network based on local distribution learning.

Science.gov (United States)

Xing, Youlu; Shi, Xiaofeng; Shen, Furao; Zhou, Ke; Zhao, Jinxi

2016-12-01

In this paper, we propose an unsupervised incremental learning neural network based on local distribution learning, which is called Local Distribution Self-Organizing Incremental Neural Network (LD-SOINN). The LD-SOINN combines the advantages of incremental learning and matrix learning. It can automatically discover suitable nodes to fit the learning data in an incremental way without a priori knowledge such as the structure of the network. The nodes of the network store rich local information regarding the learning data. The adaptive vigilance parameter guarantees that LD-SOINN is able to add new nodes for new knowledge automatically and the number of nodes will not grow unlimitedly. While the learning process continues, nodes that are close to each other and have similar principal components are merged to obtain a concise local representation, which we call a relaxation data representation. A denoising process based on density is designed to reduce the influence of noise. Experiments show that the LD-SOINN performs well on both artificial and real-word data. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Comparative Study of Collaborative Learning and SDLC Model to develop IT Group Projects

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Sorapak Pukdesree

2017-11-01

Full Text Available The main objectives of this research were to compare the attitudes of learners between applying SDLC model with collaborative learning and typical SDLC model and to develop electronic courseware as group projects. The research was a quasi-experimental research. The populations of the research were students who took Computer Organization and Architecture course in the academic year 2015. There were 38 students who participated to the research. The participants were divided voluntary into two groups including an experimental group with 28 students using SDLC model with collaborative learning and a control group with 10 students using typical SDLC model. The research instruments were attitude questionnaire, semi-structured interview and self-assessment questionnaire. The collected data was analysed by arithmetic mean, standard deviation, and independent sample t-test. The results of the questionnaire revealed that the attitudes of the learners using collaborative learning and SDLC model were statistically significant difference between the mean score for experimental group and control group at a significance level of 0.05. The independent statistical analyses were significantly different between the two groups at a significance level of 0.05. The results of the interviewing revealed that most of the learners had the corresponding opinions that collaborative learning was very useful with highest level of their attitudes comparing with the previous methodology. Learners had left some feedbacks that collaborative learning should be applied to other courses.

A self-organized learning strategy for object recognition by an embedded line of attraction

Science.gov (United States)

Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

2012-04-01

For humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. In this paper we present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in an image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural network. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural network, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based

THE EFFECTS OF COOPERATIVE LEARNING MODEL GROUP INVESTIGATION AND MOTIVATION TOWARD PHYSICS LEARNING RESULTS MAN TANJUNGBALAI

Directory of Open Access Journals (Sweden)

Amalia Febri Aristi

2014-12-01

Full Text Available This study aimed to determine: (1 Is there a difference in student's learning outcomes with the application of learning models Investigation Group and Direct Instruction teaching model. (2 Is there a difference in students' motivation with the application of learning models Investigation Group and Direct Instruction teaching model, (3 Is there an interaction between learning models Investigation Group and Direct Instruction to improve students' motivation in learning outcomes Physics. This research is a quasi experimental. The study population was a student of class XII Tanjung Balai MAN. Random sample selection is done by randomizing the class. The instrument used consisted of: (1 achievement test (2 students' motivation questionnaire. The tests are used to obtain the data is shaped essay. The data in this study were analyzed using ANOVA analysis of two paths. The results showed that: (1 there were differences in learning outcomes between students who used the physics model of Group Investigation learning compared with students who used the Direct Instruction teaching model. (2 There was a difference in student's learning outcomes that had a low learning motivation and high motivation to learn both in the classroom and in the classroom Investigation Group Direct Instruction. (3 There was interaction between learning models Instruction Direct Group Investigation and motivation to learn in improving learning outcomes Physics.

Collective (Team) Learning Process Models: A Conceptual Review

Science.gov (United States)

Knapp, Randall

2010-01-01

Teams have become a key resource for learning and accomplishing work in organizations. The development of collective learning in specific contexts is not well understood, yet has become critical to organizational success. The purpose of this conceptual review is to inform human resource development (HRD) practice about specific team behaviors and…

Model-Agnostic Interpretability of Machine Learning

OpenAIRE

Ribeiro, Marco Tulio; Singh, Sameer; Guestrin, Carlos

2016-01-01

Understanding why machine learning models behave the way they do empowers both system designers and end-users in many ways: in model selection, feature engineering, in order to trust and act upon the predictions, and in more intuitive user interfaces. Thus, interpretability has become a vital concern in machine learning, and work in the area of interpretable models has found renewed interest. In some applications, such models are as accurate as non-interpretable ones, and thus are preferred f...

A model of positive and negative learning : Learning demands and resources, learning engagement, critical thinking, and fake news detection

NARCIS (Netherlands)

Dormann, Christian; Demerouti, Eva; Bakker, Arnold; Zlatkin-Troitschanskaia, O.; Wittum, G.; Dengel, A.

2018-01-01

This chapter proposes a model of positive and negative learning (PNL model). We use the term negative learning when stress among students occurs, and when knowledge and abilities are not properly developed. We use the term positive learning if motivation is high and active learning occurs. The PNL

Analisa Pengaruh Leadership Style terhadap Firm Performance melalui Learning Organization dan Employee Satisfaction pada Perusahaan Sektor Manufaktur di Surabaya

OpenAIRE

Yulia, Yemima

2015-01-01

This study aimed to examine the direct and significant affect of leadership style to learning organization, leadership style to employee's satisfaction, learning organization to firm's performance, employee's satisfaction to firm's performance, leadership style to firm's performance, and learning organization to employee's satisfaction on manufacturing companies in Surabaya. This study used quantitative approach and the data were obtained through the distribution of questionnaire to manufactu...

A Model for Electronic Good Governance in Electronic Learning Sector of Iran

Directory of Open Access Journals (Sweden)

Alireza Moghaddasi

2016-10-01

Full Text Available Despite the various models and frameworks on electronic good governance are introduced, the multiple dimensions model of electronic good governance in the field of e-Learning has not been reviewed this subject in a integrated, comprehensive, process-oriented and systematic model. In this article, in order to explain the process of electronic good governance, by a systematic review of the related literature and backgrounds, all factors were identified using meta-synthesis methodology. Then, based on grounded theory methodology and Strauss and Corbin paradigmatic approach, the open, axial and selective coding were conducted. In the following, by using survey method, we determined the importance and priority of all proposed factors. It was also indicated that this research was innovative in the fields of methodology, results and the proposed model which had not been considered in the previous researches. So that, the proposed model resolved the shortcomings of past researches and made it possible for the public sector, private and civil society organizations to consider the process of establishing electronic good governance in e-Learning sector in Iran as a dynamic process.

LEARNING ORGANISATION CHALLENGE FOR ROMANIAN PHARMACEUTICAL SMEs

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Otilia-Maria BORDEIANU

2014-04-01

Full Text Available The concept of the learning organization has gone through many changes both theoretically and also as practical implementation. Learning organizations do not appear automatically, they require a strong commitment for developing the skills needed in the workplace, and this commitment should start from the top of the organization. The learning process should be managed at different levels within the organization. Learning, therefore, is made up of several different components and requires a special management. Successful companies are the result of carefully cultivated attitudes, commitments and management processes. This paper investigates the learning organization dimensions analysed in case of pharmaceutical SMEs from Romania. The results obtained in this study allow us to draw relevant conclusions, constituting a practical starting point for businesses. The paper highlights the fact that SMEs pharmaceutical companies have taken important steps toward learning organization model, but reaching different levels from one key dimension to another.

Color-Coded Graphic Organizers for Teaching Writing to Students with Learning Disabilities

Science.gov (United States)

Ewoldt, Kathy B.; Morgan, Joseph John

2017-01-01

A commonly used method for supporting the writing of students with learning disabilities (LD), graphic organizers have been shown to effectively support instruction for students with LD in a variety of content areas (Dexter & Hughes, 2011). Students with LD often struggle with the process of developing their ideas into organized sentences; the…

A Conceptual Model of eLearning Adoption

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Muneer Abbad

2011-05-01

Full Text Available Internet-based learning systems are being used in many universities and firms but their adoption requires a solid understanding of the user acceptance processes. The technology acceptance model (TAM has been used to test the acceptance of various technologies and software within an e-learning context. This research aims to discuss the main factors of a successful e-learning adoption by students. A conceptual research framework of e-learning adoption is proposed based on the TAM model.

A View of Professional Learning Communities through Three Frames: Leadership, Organization, and Culture

Science.gov (United States)

Mullen, Carol A.; Schunk, Dale H.

2010-01-01

In this discussion of professional learning communities (PLCs) in North American public schools, we examine three theoretical frames--leadership, organization, and culture. Issues related to learning are infused throughout our presentation of the frames. Based on our analysis of the current literature on this topic, PLCs offer a promising tool for…

Barriers to the Implementation of Electronic Learning in Governmental Organizations: Case of Iran

Science.gov (United States)

Jahromi, Gelayol Safavi; Nikabadi, Mohsen Shafiei; Maleki, Morteza

2017-01-01

New developments in technology, particularly the information technology, have changed the perception of learning. These changes have made distance learning an important part of education. However, it seems that this technology does not have a strong position in governmental organizations yet. Therefore, the main goal of this research is to present…

Modeling learning and memory using verbal learning tests: results from ACTIVE.

Science.gov (United States)

Gross, Alden L; Rebok, George W; Brandt, Jason; Tommet, Doug; Marsiske, Michael; Jones, Richard N

2013-03-01

To investigate the influence of memory training on initial recall and learning. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen's d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p learning, d = 3.10, p memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning.

SUSTAIN: a network model of category learning.

Science.gov (United States)

Love, Bradley C; Medin, Douglas L; Gureckis, Todd M

2004-04-01

SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.

A Coterminous Collaborative Learning Model: Interconnectivity of Leadership and Learning

Directory of Open Access Journals (Sweden)

Ilana Margolin

2012-05-01

Full Text Available This qualitative ethnographic study examines a collaborative leadership model focused on learning and socially just practices within a change context of a wide educational partnership. The study analyzes a range of perspectives of novice teachers, mentor teachers, teacher educators and district superintendents on leadership and learning. The findings reveal the emergence of a coalition of leaders crossing borders at all levels of the educational system: local school level, district level and teacher education level who were involved in coterminous collaborative learning. Four categories of learning were identified as critical to leading a change in the educational system: learning in professional communities, learning from practice, learning through theory and research and learning from and with leaders. The implications of the study for policy makers as well as for practitioners are to adopt a holistic approach to the educational environment and plan a collaborative learning continuum from initial pre-service programs through professional development learning at all levels.

Learning topic models by belief propagation.

Science.gov (United States)

Zeng, Jia; Cheung, William K; Liu, Jiming

2013-05-01

Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interest and touches on many important applications in text mining, computer vision and computational biology. This paper represents the collapsed LDA as a factor graph, which enables the classic loopy belief propagation (BP) algorithm for approximate inference and parameter estimation. Although two commonly used approximate inference methods, such as variational Bayes (VB) and collapsed Gibbs sampling (GS), have gained great success in learning LDA, the proposed BP is competitive in both speed and accuracy, as validated by encouraging experimental results on four large-scale document datasets. Furthermore, the BP algorithm has the potential to become a generic scheme for learning variants of LDA-based topic models in the collapsed space. To this end, we show how to learn two typical variants of LDA-based topic models, such as author-topic models (ATM) and relational topic models (RTM), using BP based on the factor graph representations.

A pedagogical model for simulation-based learning in healthcare

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Tuulikki Keskitalo

2015-11-01

Full Text Available The aim of this study was to design a pedagogical model for a simulation-based learning environment (SBLE in healthcare. Currently, simulation and virtual reality are a major focus in healthcare education. However, when and how these learning environments should be applied is not well-known. The present study tries to fill that gap. We pose the following research question: What kind of pedagogical model supports and facilitates students’ meaningful learning in SBLEs? The study used design-based research (DBR and case study approaches. We report the results from our second case study and how the pedagogical model was developed based on the lessons learned. The study involved nine facilitators and 25 students. Data were collected and analysed using mixed methods. The main result of this study is the refined pedagogical model. The model is based on the socio-cultural theory of learning and characteristics of meaningful learning as well as previous pedagogical models. The model will provide a more holistic and meaningful approach to teaching and learning in SBLEs. However, the model requires evidence and further development.

Benchmarking Deep Learning Models on Large Healthcare Datasets.

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Purushotham, Sanjay; Meng, Chuizheng; Che, Zhengping; Liu, Yan

2018-06-04

Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learning models with respect to the state-of-the-art machine learning models and prognostic scoring systems on publicly available healthcare datasets. In this paper, we present the benchmarking results for several clinical prediction tasks such as mortality prediction, length of stay prediction, and ICD-9 code group prediction using Deep Learning models, ensemble of machine learning models (Super Learner algorithm), SAPS II and SOFA scores. We used the Medical Information Mart for Intensive Care III (MIMIC-III) (v1.4) publicly available dataset, which includes all patients admitted to an ICU at the Beth Israel Deaconess Medical Center from 2001 to 2012, for the benchmarking tasks. Our results show that deep learning models consistently outperform all the other approaches especially when the 'raw' clinical time series data is used as input features to the models. Copyright © 2018 Elsevier Inc. All rights reserved.

A Meta-Analysis of Advance-Organizer Studies.

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Stone, Carol Leth

Long term studies of advance organizers (AO) were analyzed with Glass's meta-analysis technique. AO's were defined as bridges from reader's previous knowledge to what is to be learned. The results were compared with predictions from Ausubel's model of assimilative learning. The results of the study indicated that advance organizers were associated…

Organizational Learning Supported by Reference Architecture Models: Industry 4.0 Laboratory Study

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Marco Nardello

2017-10-01

Full Text Available The wave of the fourth industrial revolution (Industry 4.0 is bringing a new vision of the manufacturing industry. In manufacturing, one of the buzzwords of the moment is "Smart production". Smart production involves manufacturing equipment with many sensors that can generate and transmit large amounts of data. These data and information from manufacturing operations are however not shared in the organization. Therefore the organization is not using them to learn and improve their operations. To address this problem, the authors implemented in an Industry 4.0 laboratory an instance of an emerging technical standard specific for the manufacturing industry. Global manufacturing experts consider the Reference Architecture Model Industry 4.0 (RAMI4.0 as one of the corner stones for the implementation of Industry 4.0. The instantiation contributed to organizational learning in the laboratory by collecting and sharing up-to-date information concerning manufacturing equipment. This article discusses and generalizes the experience and outlines future research directions.

Student Modelling in Adaptive E-Learning Systems

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Clemens Bechter

2011-09-01

Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

E-Model for Online Learning Communities.

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Rogo, Ellen J; Portillo, Karen M

2015-10-01

The purpose of this study was to explore the students' perspectives on the phenomenon of online learning communities while enrolled in a graduate dental hygiene program. A qualitative case study method was designed to investigate the learners' experiences with communities in an online environment. A cross-sectional purposive sampling method was used. Interviews were the data collection method. As the original data were being analyzed, the researchers noted a pattern evolved indicating the phenomenon developed in stages. The data were re-analyzed and validated by 2 member checks. The participants' experiences revealed an e-model consisting of 3 stages of formal learning community development as core courses in the curriculum were completed and 1 stage related to transmuting the community to an informal entity as students experienced the independent coursework in the program. The development of the formal learning communities followed 3 stages: Building a Foundation for the Learning Community, Building a Supportive Network within the Learning Community and Investing in the Community to Enhance Learning. The last stage, Transforming the Learning Community, signaled a transition to an informal network of learners. The e-model was represented by 3 key elements: metamorphosis of relationships, metamorphosis through the affective domain and metamorphosis through the cognitive domain, with the most influential element being the affective development. The e-model describes a 4 stage process through which learners experience a metamorphosis in their affective, relationship and cognitive development. Synergistic learning was possible based on the interaction between synergistic relationships and affective actions. Copyright © 2015 The American Dental Hygienists’ Association.

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

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Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K

2014-09-04

In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.

Learning the Task Management Space of an Aircraft Approach Model

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Krall, Joseph; Menzies, Tim; Davies, Misty

2014-01-01

Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.

Hierarchical Bayesian Models of Subtask Learning

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Anglim, Jeromy; Wynton, Sarah K. A.

2015-01-01

The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

Car-following Behavior Model Learning Using Timed Automata

NARCIS (Netherlands)

Zhang, Yihuan; Lin, Q.; Wang, Jun; Verwer, S.E.; Dochain, D.; Henrion, D.; Peaucelle, D.

Learning driving behavior is fundamental for autonomous vehicles to “understand” traffic situations. This paper proposes a novel method for learning a behavioral model of car-following using automata learning algorithms. The model is interpretable for car-following behavior analysis. Frequent common

The visual simulators for architecture and computer organization learning

OpenAIRE

Nikolić Boško; Grbanović Nenad; Đorđević Jovan

2009-01-01

The paper proposes a method of an effective distance learning of architecture and computer organization. The proposed method is based on a software system that is possible to be applied in any course in this field. Within this system students are enabled to observe simulation of already created computer systems. The system provides creation and simulation of switch systems, too.

A phase model of intergenerational learning in organizations

NARCIS (Netherlands)

Gerpott, F.H.; Lehmann-Willenbrock, N.; Voelpel, S.C.

Demographic changes challenge organizations to qualify employees across all career stages and to ensure the transfer of company-specific knowledge between experienced and young workers. Human resource development programs for employees from different generations may help address these challenges.

Project-matrix models of marketing organization

Directory of Open Access Journals (Sweden)

Gutić Dragutin

2009-01-01

Full Text Available Unlike theory and practice of corporation organization, in marketing organization numerous forms and contents at its disposal are not reached until this day. It can be well estimated that marketing organization today in most of our companies and in almost all its parts, noticeably gets behind corporation organization. Marketing managers have always been occupied by basic, narrow marketing activities as: sales growth, market analysis, market growth and market share, marketing research, introduction of new products, modification of products, promotion, distribution etc. They rarely found it necessary to focus a bit more to different aspects of marketing management, for example: marketing planning and marketing control, marketing organization and leading. This paper deals with aspects of project - matrix marketing organization management. Two-dimensional and more-dimensional models are presented. Among two-dimensional, these models are analyzed: Market management/products management model; Products management/management of product lifecycle phases on market model; Customers management/marketing functions management model; Demand management/marketing functions management model; Market positions management/marketing functions management model. .

Bio-Inspired Neural Model for Learning Dynamic Models

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Duong, Tuan; Duong, Vu; Suri, Ronald

2009-01-01

A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

Learner Open Modeling in Adaptive Mobile Learning System for Supporting Student to Learn English

Directory of Open Access Journals (Sweden)

Van Cong Pham

2011-10-01

Full Text Available This paper represents a personalized context-aware mobile learning architecture for supporting student to learn English as foreign language in order to prepare for TOEFL test. We consider how to apply open learner modeling techniques to adapt contents for different learners based on context, which includes location, amount of time to learn, the manner as well as learner's knowledge in learning progress. Through negotiation with system, the editable learner model will be updated to support adaptive engine to select adaptive contents meeting learner's demands. Empirical testing results for students who used application prototype indicate that interaction user modeling is helpful in supporting learner to learn adaptive materials.

A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system

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Kaplan, Bernhard A.; Lansner, Anders

2014-01-01

Olfactory sensory information passes through several processing stages before an odor percept emerges. The question how the olfactory system learns to create odor representations linking those different levels and how it learns to connect and discriminate between them is largely unresolved. We present a large-scale network model with single and multi-compartmental Hodgkin–Huxley type model neurons representing olfactory receptor neurons (ORNs) in the epithelium, periglomerular cells, mitral/tufted cells and granule cells in the olfactory bulb (OB), and three types of cortical cells in the piriform cortex (PC). Odor patterns are calculated based on affinities between ORNs and odor stimuli derived from physico-chemical descriptors of behaviorally relevant real-world odorants. The properties of ORNs were tuned to show saturated response curves with increasing concentration as seen in experiments. On the level of the OB we explored the possibility of using a fuzzy concentration interval code, which was implemented through dendro-dendritic inhibition leading to winner-take-all like dynamics between mitral/tufted cells belonging to the same glomerulus. The connectivity from mitral/tufted cells to PC neurons was self-organized from a mutual information measure and by using a competitive Hebbian–Bayesian learning algorithm based on the response patterns of mitral/tufted cells to different odors yielding a distributed feed-forward projection to the PC. The PC was implemented as a modular attractor network with a recurrent connectivity that was likewise organized through Hebbian–Bayesian learning. We demonstrate the functionality of the model in a one-sniff-learning and recognition task on a set of 50 odorants. Furthermore, we study its robustness against noise on the receptor level and its ability to perform concentration invariant odor recognition. Moreover, we investigate the pattern completion capabilities of the system and rivalry dynamics for odor mixtures. PMID

The Effect of Learning Based on Technology Model and Assessment Technique toward Thermodynamic Learning Achievement

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Makahinda, T.

2018-02-01

The purpose of this research is to find out the effect of learning model based on technology and assessment technique toward thermodynamic achievement by controlling students intelligence. This research is an experimental research. The sample is taken through cluster random sampling with the total respondent of 80 students. The result of the research shows that the result of learning of thermodynamics of students who taught the learning model of environmental utilization is higher than the learning result of student thermodynamics taught by simulation animation, after controlling student intelligence. There is influence of student interaction, and the subject between models of technology-based learning with assessment technique to student learning result of Thermodynamics, after controlling student intelligence. Based on the finding in the lecture then should be used a thermodynamic model of the learning environment with the use of project assessment technique.

Leading and Managing Disparate Generations in Cross-Cultural Learning Organizations

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Mujtaba, Bahaudin; Thomas, Gimol

2005-01-01

The enclosed literature focuses on learning about the various generations of the workforce and techniques that employers can utilize to organize collaborative teams in today's multigenerational and multicultural workplaces. Trainers and teachers can use this material to provide effective skills for managers that deal with a multi-generation of…

LEARNING CREATIVE WRITING MODEL BASED ON NEUROLINGUISTIC PROGRAMMING

OpenAIRE

Rustan, Edhy

2017-01-01

The objectives of the study are to determine: (1) condition on learning creative writing at high school students in Makassar, (2) requirement of learning model in creative writing, (3) program planning and design model in ideal creative writing, (4) feasibility of model study based on creative writing in neurolinguistic programming, and (5) the effectiveness of the learning model based on creative writing in neurolinguisticprogramming.The method of this research uses research development of L...

Learning to Model in Engineering

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Gainsburg, Julie

2013-01-01

Policymakers and education scholars recommend incorporating mathematical modeling into mathematics education. Limited implementation of modeling instruction in schools, however, has constrained research on how students learn to model, leaving unresolved debates about whether modeling should be reified and explicitly taught as a competence, whether…

Professional Student Organizations and Experiential Learning Activities: What Drives Student Intentions to Participate?

Science.gov (United States)

Munoz, Laura; Miller, Richard; Poole, Sonja Martin

2016-01-01

Experiential learning theory has been referenced as a possible method for attracting and retaining members in student organizations. In a survey, undergraduate students evaluated a variety of organizational features pertaining to their intention to participate in professional student organizations. The study found that students value activities…

Kaiser Permanente's performance improvement system, Part 4: Creating a learning organization.

Science.gov (United States)

Schilling, Lisa; Dearing, James W; Staley, Paul; Harvey, Patti; Fahey, Linda; Kuruppu, Francesca

2011-12-01

In 2006, recognizing variations in performance in quality, safety, service, and efficiency, Kaiser Permanente leaders initiated the development of a performance improvement (PI) system. Kaiser Permanente has implemented a strategy for creating the systemic capacity for continuous improvement that characterizes a learning organization. Six "building blocks" were identified to enable Kaiser Permanente to make the transition to becoming a learning organization: real-time sharing of meaningful performance data; formal training in problem-solving methodology; workforce engagement and informal knowledge sharing; leadership structures, beliefs, and behaviors; internal and external benchmarking; and technical knowledge sharing. Putting each building block into place required multiple complex strategies combining top-down and bottom-up approaches. Although the strategies have largely been successful, challenges remain. The demand for real-time meaningful performance data can conflict with prioritized changes to health information systems. It is an ongoing challenge to teach PI, change management, innovation, and project management to all managers and staff without consuming too much training time. Challenges with workforce engagement include low initial use of tools intended to disseminate information through virtual social networking. Uptake of knowledge-sharing technologies is still primarily by innovators and early adopters. Leaders adopt new behaviors at varying speeds and have a range of abilities to foster an environment that is psychologically safe and stimulates inquiry. A learning organization has the capability to improve, and it develops structures and processes that facilitate the acquisition and sharing of knowledge.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition.

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Johannes Bill

Full Text Available During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

Science.gov (United States)

Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

2015-01-01

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

The Influence Of Learning Model Guided Findings Of Student Learning Outcomes

Directory of Open Access Journals (Sweden)

A. SaefulBahri

2015-03-01

Full Text Available Abstract This study examines the influence of the learning model guided findings on student learning outcomes in subjects PAI eighth grade students of SMP Plus al Masoem. The research method used in this study is a quantitative method in the form of quasi-experiment Quasi-Experimental Design. The findings of the study are expected to demonstrate 1 the difference significant increase in learning outcomes between the experimental class using guided discovery method that uses the control class discussion of learning models 2 Constraints in the method of guided discovery activities and the limited ability of educators in the experimental class in implements the method of guided discovery and constraints faced by students while digging the information they need so we need special strategies to motivate students in the experimental class in order for them creatively find the right way to gather information that supports learning PAI.

Can model-free reinforcement learning explain deontological moral judgments?

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Ayars, Alisabeth

2016-05-01

Dual-systems frameworks propose that moral judgments are derived from both an immediate emotional response, and controlled/rational cognition. Recently Cushman (2013) proposed a new dual-system theory based on model-free and model-based reinforcement learning. Model-free learning attaches values to actions based on their history of reward and punishment, and explains some deontological, non-utilitarian judgments. Model-based learning involves the construction of a causal model of the world and allows for far-sighted planning; this form of learning fits well with utilitarian considerations that seek to maximize certain kinds of outcomes. I present three concerns regarding the use of model-free reinforcement learning to explain deontological moral judgment. First, many actions that humans find aversive from model-free learning are not judged to be morally wrong. Moral judgment must require something in addition to model-free learning. Second, there is a dearth of evidence for central predictions of the reinforcement account-e.g., that people with different reinforcement histories will, all else equal, make different moral judgments. Finally, to account for the effect of intention within the framework requires certain assumptions which lack support. These challenges are reasonable foci for future empirical/theoretical work on the model-free/model-based framework. Copyright © 2016 Elsevier B.V. All rights reserved.

The Comparative Study of Collaborative Learning and SDLC Model to develop IT Group Projects

OpenAIRE

Sorapak Pukdesree

2017-01-01

The main objectives of this research were to compare the attitudes of learners between applying SDLC model with collaborative learning and typical SDLC model and to develop electronic courseware as group projects. The research was a quasi-experimental research. The populations of the research were students who took Computer Organization and Architecture course in the academic year 2015. There were 38 students who participated to the research. The participants were divided voluntary into two g...

Ontology Learning for Chinese Information Organization and Knowledge Discovery in Ethnology and Anthropology

Directory of Open Access Journals (Sweden)

Jing Kong

2007-09-01

Full Text Available This paper presents an ontology learning architecture that reflects the interaction between ontology learning and other applications such as ontology-engineering tools and information systems. Based on this architecture, we have developed a prototype system CHOL: a Chinese ontology learning tool. CHOL learns domain ontology from Chinese domain specific texts. On the one hand, it supports a semi-automatic domain ontology acquisition and dynamic maintenance, and on the other hand, it supports an auto-indexing and auto-classification of Chinese scholarly literature. CHOL has been applied in ethnology and anthropology for Chinese information organization and knowledge discovery.

A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.

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Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi

2015-12-01

Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.

A connectionist model of category learning by individuals with high-functioning autism spectrum disorder.

Science.gov (United States)

Dovgopoly, Alexander; Mercado, Eduardo

2013-06-01

Individuals with autism spectrum disorder (ASD) show atypical patterns of learning and generalization. We explored the possible impacts of autism-related neural abnormalities on perceptual category learning using a neural network model of visual cortical processing. When applied to experiments in which children or adults were trained to classify complex two-dimensional images, the model can account for atypical patterns of perceptual generalization. This is only possible, however, when individual differences in learning are taken into account. In particular, analyses performed with a self-organizing map suggested that individuals with high-functioning ASD show two distinct generalization patterns: one that is comparable to typical patterns, and a second in which there is almost no generalization. The model leads to novel predictions about how individuals will generalize when trained with simplified input sets and can explain why some researchers have failed to detect learning or generalization deficits in prior studies of category learning by individuals with autism. On the basis of these simulations, we propose that deficits in basic neural plasticity mechanisms may be sufficient to account for the atypical patterns of perceptual category learning and generalization associated with autism, but they do not account for why only a subset of individuals with autism would show such deficits. If variations in performance across subgroups reflect heterogeneous neural abnormalities, then future behavioral and neuroimaging studies of individuals with ASD will need to account for such disparities.

Computer-Mediated Intersensory Learning Model for Students with Learning Disabilities

Science.gov (United States)

Seok, Soonhwa; DaCosta, Boaventura; Kinsell, Carolyn; Poggio, John C.; Meyen, Edward L.

2010-01-01

This article proposes a computer-mediated intersensory learning model as an alternative to traditional instructional approaches for students with learning disabilities (LDs) in the inclusive classroom. Predominant practices of classroom inclusion today reflect the six principles of zero reject, nondiscriminatory evaluation, appropriate education,…

Technology Integration and Technology Leadership in Schools as Learning Organizations

Science.gov (United States)

Cakir, Recep

2012-01-01

The purpose of this study was to investigate technology integration in primary schools from the perspective of leadership in learning organizations. To that end, the study examines two groups: school administrators who play effective roles in technology integration in schools and computer teachers who are mainly responsible for schools' technology…

A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity.

Directory of Open Access Journals (Sweden)

Quan Wang

2017-08-01

Full Text Available The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP and synaptic normalization (SN. When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network's changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network's sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that

Semantic modeling of portfolio assessment in e-learning environment

Directory of Open Access Journals (Sweden)

Lucila Romero

2017-01-01

Full Text Available In learning environment, portfolio is used as a tool to keep track of learner’s progress. Particularly, when it comes to e-learning, continuous assessment allows greater customization and efficiency in learning process and prevents students lost interest in their study. Also, each student has his own characteristics and learning skills that must be taken into account in order to keep learner`s interest. So, personalized monitoring is the key to guarantee the success of technology-based education. In this context, portfolio assessment emerge as the solution because is an easy way to allow teacher organize and personalize assessment according to students characteristic and need. A portfolio assessment can contain various types of assessment like formative assessment, summative assessment, hetero or self-assessment and use different instruments like multiple choice questions, conceptual maps, and essay among others. So, a portfolio assessment represents a compilation of all assessments must be solved by a student in a course, it documents progress and set targets. In previous work, it has been proposed a conceptual framework that consist of an ontology network named AOnet which is a semantic tool conceptualizing different types of assessments. Continuing that work, this paper presents a proposal to implement portfolios assessment in e-learning environments. The proposal consists of a semantic model that describes key components and relations of this domain to set the bases to develop a tool to generate, manage and perform portfolios assessment.

Learning from video modeling examples: Does gender matter?

NARCIS (Netherlands)

Hoogerheide, V.; Loyens, S.M.M.; van Gog, T.

2016-01-01

Online learning from video modeling examples, in which a human model demonstrates and explains how to perform a learning task, is an effective instructional method that is increasingly used nowadays. However, model characteristics such as gender tend to differ across videos, and the model-observer

Learning models of activities involving interacting objects

DEFF Research Database (Denmark)

Manfredotti, Cristina; Pedersen, Kim Steenstrup; Hamilton, Howard J.

2013-01-01

We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...