Analyzing Learning in Professional Learning Communities: A Conceptual Framework

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Van Lare, Michelle D.; Brazer, S. David

2013-01-01

The purpose of this article is to build a conceptual framework that informs current understanding of how professional learning communities (PLCs) function in conjunction with organizational learning. The combination of sociocultural learning theories and organizational learning theories presents a more complete picture of PLC processes that has…

Computer-Assisted Language Learning (CALL) in Support of (Re)-Learning Native Languages: The Case of Runyakitara

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Katushemererwe, Fridah; Nerbonne, John

2015-01-01

This study presents the results from a computer-assisted language learning (CALL) system of Runyakitara (RU_CALL). The major objective was to provide an electronic language learning environment that can enable learners with mother tongue deficiencies to enhance their knowledge of grammar and acquire writing skills in Runyakitara. The system…

Constructivism, the so-called semantic learning theories, and situated cognition versus the psychological learning theories.

Science.gov (United States)

Aparicio, Juan José; Rodríguez Moneo, María

2005-11-01

In this paper, the perspective of situated cognition, which gave rise both to the pragmatic theories and the so-called semantic theories of learning and has probably become the most representative standpoint of constructivism, is examined. We consider the claim of situated cognition to provide alternative explanations of the learning phenomenon to those of psychology and, especially, to those of the symbolic perspective, currently predominant in cognitive psychology. The level of analysis of situated cognition (i.e., global interactive systems) is considered an inappropriate approach to the problem of learning. From our analysis, it is concluded that the pragmatic theories and the so-called semantic theories of learning which originated in situated cognition can hardly be considered alternatives to the psychological learning theories, and they are unlikely to add anything of interest to the learning theory or to contribute to the improvement of our knowledge about the learning phenomenon.

A framework of call admission control procedures for integrated services mobile wireless networks

International Nuclear Information System (INIS)

Mahmoud, Ashraf S. Hasan; Al-Qahtani, Salman A.

2007-01-01

This paper presents a general framework for a wide range of call admission control (CAC) algorithms. For several CAC schemes, which are a subset of this general framework, an analytical performance evaluation is presented for a multi-traffic mobile wireless network. These CAC algorithms consider a variety of mechanisms to prioritize traffic in an attempt to support different levels of quality of service (QoS) for different types of calls. These mechanisms include dividing the handoff traffic into more than one class and using guard channels or allowing channel splitting to admit more handoff calls. Other mechanisms aimed at adding priority for handoff calls consider employing queuing of handoff calls or dynamically reducing the number lower priority calls. Furthermore our analysis relaxes the typically used assumptions of equal channel holding time and equal resource usage for voice and data calls. The main contribution of this paper is the development of an analytical model for each of the three CAC algorithms specified in this study. In addition to the call blocking and termination probabilities which are usually cited as the performance metrics, in this work we derive and evaluate other metrics that not have be considered by the previous work such as the average queue length, the average queue residency, and the time-out probability for handoff calls. We also develop a simulation tool to test and verify our results. Finally, we present numerical examples to demonstrate the performance of the proposed CAG algorithms and we show that analytical and simulation results are in total agreement. (author)

Complexity Theory and CALL Curriculum in Foreign Language Learning

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Hassan Soleimani

2014-05-01

Full Text Available Complexity theory literally indicates the complexity of a system, behavior, or a process. Its connotative meaning, while, implies dynamism, openness, sensitivity to initial conditions and feedback, and adaptation properties of a system. Regarding English as a Foreign/ Second Language (EFL/ESL this theory emphasizes on the complexity of the process of teaching and learning, including all the properties of a complex system. The purpose of the current study is to discuss the role of CALL as a modern technology in simplifying the process of teaching and learning a new language while integrating into the complexity theory. Nonetheless, the findings obtained from reviewing previously conducted studies in this field confirmed the usefulness of CALL curriculum in EFL/ESL contexts. These findings can also provide pedagogical implications for employing computer as an effective teaching and learning tool.

Reinforcement Learning Based Novel Adaptive Learning Framework for Smart Grid Prediction

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Tian Li

2017-01-01

Full Text Available Smart grid is a potential infrastructure to supply electricity demand for end users in a safe and reliable manner. With the rapid increase of the share of renewable energy and controllable loads in smart grid, the operation uncertainty of smart grid has increased briskly during recent years. The forecast is responsible for the safety and economic operation of the smart grid. However, most existing forecast methods cannot account for the smart grid due to the disabilities to adapt to the varying operational conditions. In this paper, reinforcement learning is firstly exploited to develop an online learning framework for the smart grid. With the capability of multitime scale resolution, wavelet neural network has been adopted in the online learning framework to yield reinforcement learning and wavelet neural network (RLWNN based adaptive learning scheme. The simulations on two typical prediction problems in smart grid, including wind power prediction and load forecast, validate the effectiveness and the scalability of the proposed RLWNN based learning framework and algorithm.

Investigating Language Learning Activity Using a CALL Task in the Self-access Centre

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Carlos Montoro

2011-09-01

Full Text Available This article describes a small study of the language learning activity of individual learners using a CALL task in a self-access environment. The research focuses on the nature of the language learning activity, the most salient elements that make up its structure and major disturbances observed between and within some of those elements. It is set in the context of computer-assisted language learning (CALL and activity theory. A CALL task designed by the authors was made available online to be used as a research and learning tool. Empirical data was collected from two participants using ethnographic tools, such as participant observation and stimulated recall sessions. The analysis focuses on disturbances mainly involving the subject (i.e., the learner, mediating artefacts (e.g., the CALL task, the community (e.g., management and other self-access centre users and the object of the activity (i.e., learning English. It is recommended that future studies should look deeper into contradictions in the learning activity from a cultural-historical perspective.

Psychological theory and pedagogical effectiveness: the learning promotion potential framework.

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Tomlinson, Peter

2008-12-01

After a century of educational psychology, eminent commentators are still lamenting problems besetting the appropriate relating of psychological insights to teaching design, a situation not helped by the persistence of crude assumptions concerning the nature of pedagogical effectiveness. To propose an analytical or meta-theoretical framework based on the concept of learning promotion potential (LPP) as a basis for understanding the basic relationship between psychological insights and teaching strategies, and to draw out implications for psychology-based pedagogical design, development and research. This is a theoretical and meta-theoretical paper relying mainly on conceptual analysis, though also calling on psychological theory and research. Since teaching consists essentially in activity designed to promote learning, it follows that a teaching strategy has the potential in principle to achieve particular kinds of learning gains (LPP) to the extent that it embodies or stimulates the relevant learning processes on the part of learners and enables the teacher's functions of on-line monitoring and assistance for such learning processes. Whether a teaching strategy actually does realize its LPP by way of achieving its intended learning goals depends also on the quality of its implementation, in conjunction with other factors in the situated interaction that teaching always involves. The core role of psychology is to provide well-grounded indication of the nature of such learning processes and the teaching functions that support them, rather than to directly generate particular ways of teaching. A critically eclectic stance towards potential sources of psychological insight is argued for. Applying this framework, the paper proposes five kinds of issue to be attended to in the design and evaluation of psychology-based pedagogy. Other work proposing comparable ideas is briefly reviewed, with particular attention to similarities and a key difference with the ideas of Oser

Conceptual Framework: Development of Interactive Reading Malay Language Learning System (I-ReaMaLLS

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Ismail Nurulisma

2018-01-01

Full Text Available Reading is very important to access knowledge. Reading skills starts during preschool level no matter of the types of languages. At present, there are many preschool children who are still unable to recognize letters or even words. This leads to the difficulties in reading. Therefore, there is a need of intervention in reading to overcome such problems. Thus, technologies were adapted in enhancing learning skills, especially in learning to read among the preschool children. Phonological is one of the factors to be considered to ensure a smooth of transition into reading. Phonological concept enables the first learner to easily learn reading such to learn reading Malay language. The medium of learning to read Malay language can be assisted via the supportive of multimedia technology to enhance the preschool children learning. Thus, an interactive system is proposed via a development of interactive reading Malay language learning system, which is called as I-ReaMaLLS. As a part of the development of I-ReaMaLLS, this paper focus on the development of conceptual framework in developing interactive reading Malay language learning system (I-ReaMaLLS. I-ReaMaLLS is voice based system that facilitates the preschool learner in learning reading Malay language. The conceptual framework of developing I-ReaMaLLS is conceptualized based on the initial study conducted via methods of literature review and observation with the preschool children, aged 5 – 6 years. As the result of the initial study, research objectives have been affirmed that finally contributes to the design of conceptual framework for the development of I-ReaMaLLS.

Supporting Collective Inquiry: A Technology Framework for Distributed Learning

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Tissenbaum, Michael

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

Research on machine learning framework based on random forest algorithm

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Ren, Qiong; Cheng, Hui; Han, Hai

2017-03-01

With the continuous development of machine learning, industry and academia have released a lot of machine learning frameworks based on distributed computing platform, and have been widely used. However, the existing framework of machine learning is limited by the limitations of machine learning algorithm itself, such as the choice of parameters and the interference of noises, the high using threshold and so on. This paper introduces the research background of machine learning framework, and combined with the commonly used random forest algorithm in machine learning classification algorithm, puts forward the research objectives and content, proposes an improved adaptive random forest algorithm (referred to as ARF), and on the basis of ARF, designs and implements the machine learning framework.

Evaluation of Learning Materials: A Holistic Framework

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Bundsgaard, Jeppe; Hansen, Thomas Illum

2011-01-01

This paper presents a holistic framework for evaluating learning materials and designs for learning. A holistic evaluation comprises investigations of the potential learning potential, the actualised learning potential, and the actual learning. Each aspect is explained and exemplified through theoretical models and definitions. (Contains 3 figures…

Sustainability in CALL Learning Environments: A Systemic Functional Grammar Approach

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McDonald, Peter

2014-01-01

This research aims to define a sustainable resource in Computer-Assisted Language Learning (CALL). In order for a CALL resource to be sustainable it must work within existing educational curricula. This feature is a necessary prerequisite of sustainability because, despite the potential for educational change that digitalization has offered since…

Attitudes of Jordanian Undergraduate Students towards Using Computer Assisted Language Learning (CALL

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Farah Jamal Abed Alrazeq Saeed

2018-01-01

Full Text Available The study aimed at investigating the attitudes of Jordanian undergraduate students towards using computer assisted -language learning (CALL and its effectiveness in the process of learning the English language.  In order to fulfill the study’s objective, the researchers used a questionnaire to collect data, followed-up with semi-structured interviews to investigate the students’ beliefs towards CALL. Twenty- one of Jordanian BA students majoring in English language and literature were selected according to simple random sampling. The results revealed positive attitudes towards CALL in facilitating the process of writing assignments, gaining information; making learning enjoyable; improving their creativity, productivity, academic achievement, critical thinking skills, and enhancing their knowledge about vocabulary grammar, and culture. Furthermore, they believed that computers can motivate them to learn English language and help them to communicate and interact with their teachers and colleagues. The researchers recommended conducting a research on the same topic, taking into consideration the variables of age, gender, experience in using computers, and computer skills.

Studying Language Learning Opportunities Afforded by a Collaborative CALL Task

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Leahy, Christine

2016-01-01

This research study explores the learning potential of a computer-assisted language learning (CALL) activity. Research suggests that the dual emphasis on content development and language accuracy, as well as the complexity of L2 production in natural settings, can potentially create cognitive overload. This study poses the question whether, and…

The ICCE Framework: Framing Learning Experiences Afforded by Games

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Foster, Aroutis; Shah, Mamta

2015-01-01

There is a need for game-based learning frameworks that provide a lens for understanding learning experiences afforded in digital games. These frameworks should aim to facilitate game analyses, identification of learning opportunities, and support for learner experiences. This article uses the inquiry, communication, construction, and expression…

Is CALL Obsolete? Language Acquisition and Language Learning Revisited in a Digital Age

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Jarvis, Huw; Krashen, Stephen

2014-01-01

In this article, Huw Jarvis and Stephen Krashen ask "Is CALL Obsolete?" When the term CALL (Computer-Assisted Language Learning) was introduced in the 1960s, the language education profession knew only about language learning, not language acquisition, and assumed the computer's primary contribution to second language acquisition…

One lens missing? Clarifying the clinical microsystem framework with learning theories.

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Norman, Ann-Charlott; Fritzen, Lena; Fridh, Marianne Lindblad

2013-01-01

The clinical microsystem (CMS) approach is widely used and is perceived as helpful in practice but, we ask the question: "Is its learning potential sufficiently utilized?" To scrutinize aspects of learning within the CMS framework and to clarify the learning aspects the framework includes and thereby support the framework with the enhanced learning perspective that becomes visible. Literature on the CMS framework was systematically searched and selected using inclusion criteria. An analytical tool was constructed in the form of a theoretical lens that was used to clarify learning aspects that are associated with the framework. The analysis revealed 3 learning aspects: (1) The CMS framework describes individual and social learning but not how to adapt learning strategies for purposes of change. (2) The metaphorical language of how to reach a holistic health care system for each patient has developed over time but can still be improved by naming social interactions to transcend organizational boundaries. (3) Power structures are recognized but not as a characteristic that restricts learning due to asymmetric communication. The "lens" perspective reveals new meanings to learning that enhance our understanding of health care as a social system and provides new practical learning strategies.

Facilitation of social learning in teacher education: the ‘Dimensions of Social Learning Framework’

NARCIS (Netherlands)

de Laat, M.M.; Vrieling, E.; van den Beemt, A.A.J.; McDonald, J.; Cater-Steel, A.

2017-01-01

To understand the organization of social learning by groups in practice, this chapter elaborates on the use of a framework of dimensions and indicators to explore social learning within (prospective) teacher groups. The applied framework that we call the ‘Dimensions of Social Learning (DSL)

Intercultural Historical Learning: A Conceptual Framework

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Nordgren, Kenneth; Johansson, Maria

2015-01-01

This paper outlines a conceptual framework in order to systematically discuss the meaning of intercultural learning in history education and how it could be advanced. We do so by bringing together theories of historical consciousness, intercultural competence and postcolonial thinking. By combining these theories into one framework, we identify…

Pre-Service Teachers' Uses of and Barriers from Adopting Computer-Assisted Language Learning (CALL) Programs

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Samani, Ebrahim; Baki, Roselan; Razali, Abu Bakar

2014-01-01

Success in implementation of computer-assisted language learning (CALL) programs depends on the teachers' understanding of the roles of CALL programs in education. Consequently, it is also important to understand the barriers teachers face in the use of computer-assisted language learning (CALL) programs. The current study was conducted on 14…

ELPSA as A Lesson Design Framework

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Tom Lowrie

2015-07-01

Full Text Available This paper offers a framework for mathematics lesson design that is consistent with the way we learn about, and discover, most things in life. In addition, the framework provides a structure for identifying how mathematical concepts and understanding are acquired and developed. This framework is called ELPSA and represents five learning components, namely: Experience, Language, Pictorial, Symbolic and Applications. This framework has been used in developing lessons and teacher professional programs in Indonesia since 2012 in cooperation with the World Bank. This paper describes the theory that underlines the framework in general and in relation to each inter-connected component. Two explicit learning sequences for classroom practice are described, associated with Pythagoras theorem and probability. This paper then concludes with recommendations for using ELPSA in various institutional contexts.

Active Learning Using Hint Information.

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Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien

2015-08-01

The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

The Adaptation Study of the Questionnaires of the Attitude towards CALL (A-CALL), the Attitude towards CAL (A-CAL), the Attitude towards Foreign Language Learning (A-FLL) to Turkish Language

Science.gov (United States)

Erdem, Cahit; Saykili, Abdullah; Kocyigit, Mehmet

2018-01-01

This study primarily aims to adapt the Foreign Language Learning (FLL), Computer assisted Learning (CAL) and Computer assisted Language Learning (CALL) scales developed by Vandewaetere and Desmet into Turkish context. The instrument consists of three scales which are "the attitude towards CALL questionnaire" ("A-CALL")…

Learning Based Approach for Optimal Clustering of Distributed Program's Call Flow Graph

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Abofathi, Yousef; Zarei, Bager; Parsa, Saeed

Optimal clustering of call flow graph for reaching maximum concurrency in execution of distributable components is one of the NP-Complete problems. Learning automatas (LAs) are search tools which are used for solving many NP-Complete problems. In this paper a learning based algorithm is proposed to optimal clustering of call flow graph and appropriate distributing of programs in network level. The algorithm uses learning feature of LAs to search in state space. It has been shown that the speed of reaching to solution increases remarkably using LA in search process, and it also prevents algorithm from being trapped in local minimums. Experimental results show the superiority of proposed algorithm over others.

Framework for robot skill learning using reinforcement learning

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Wei, Yingzi; Zhao, Mingyang

2003-09-01

Robot acquiring skill is a process similar to human skill learning. Reinforcement learning (RL) is an on-line actor critic method for a robot to develop its skill. The reinforcement function has become the critical component for its effect of evaluating the action and guiding the learning process. We present an augmented reward function that provides a new way for RL controller to incorporate prior knowledge and experience into the RL controller. Also, the difference form of augmented reward function is considered carefully. The additional reward beyond conventional reward will provide more heuristic information for RL. In this paper, we present a strategy for the task of complex skill learning. Automatic robot shaping policy is to dissolve the complex skill into a hierarchical learning process. The new form of value function is introduced to attain smooth motion switching swiftly. We present a formal, but practical, framework for robot skill learning and also illustrate with an example the utility of method for learning skilled robot control on line.

A Framework for Mobile Learning for the enhancement of Learning in Higher Education

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Kadar Abdillahi Barreh

2015-07-01

Full Text Available As mobile learning becomes increasingly pervasive, many higher education institutions have embarked on a number of mobile learning initiatives to support their traditional learning modes. This study proposes a framework for mobile learning for the enhancement of learning in higher education. This framework for mobile learning is based on the research conducted on the second year course entitled “Internet Technology,” taught to second year students in the Department of Mathematics and Computer Science at the University of Djibouti. While the entire gamut of mobile technologies and academic applications needs to be considered, special emphasis and focus is provided to Short Message Services (SMS and popular social network sites such as Facebook, which is widely used for recreation. This paper highlights how mobile learning using SMS and Facebook can be designed to enhance student learning in order to help achieve learning outcomes.

CALL AND COOPERATIVE LEARNING: A SOLUTION TO DEVELOP STUDENTS‟ LISTENING ABILITY

OpenAIRE

Delsa Miranty

2017-01-01

This paper aims to provide some ideas both for English teachers and target learners about how to apply CALL and Cooperative Learning as the solution to develop students‘ listening activities in the classroom. Since teachers need to understand about students‘ needs, background, age and expectations when they learn English as the foreign language in the classroom. Therefore, the English teacher should provide environment which facilitates the children to have fun di the teaching learning proces...

Sustainability in CALL Learning Environments: A Systemic Functional Grammar Approach

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Peter McDonald

2014-09-01

Full Text Available This research aims to define a sustainable resource in Computer-Assisted Language Learning (CALL. In order for a CALL resource to be sustainable it must work within existing educational curricula. This feature is a necessary prerequisite of sustainability because, despite the potential for educational change that digitalization has offered since the nineteen nineties, curricula in traditional educational institutions have not fundamentally changed, even as we move from a pre-digital society towards a digital society. Curricula have failed to incorporate CALL resources because no agreed-upon pedagogical language enables teachers to discuss CALL classroom practices. Systemic Functional Grammar (SFG can help to provide this language and bridge the gap between the needs of the curriculum and the potentiality of CALL-based resources. This paper will outline how SFG principles can be used to create a pedagogical language for CALL and it will give practical examples of how this language can be used to create sustainable resources in classroom contexts.

ELPSA AS A LESSON DESIGN FRAMEWORK

Directory of Open Access Journals (Sweden)

Tom Lowrie

2015-07-01

Full Text Available This paper offers a framework for mathematics lesson design that is consistent with the way we learn about, and discover, most things in life. In addition, the framework provides a structure for identifying how mathematical concepts and understanding are acquired and developed. This framework is called ELPSA and represents five learning components, namely: Experience, Language, Pictorial, Symbolic and Applications. This framework has been used in developing lessons and teacher professional programs in Indonesia since 2012 in cooperation with the World Bank. This paper describes the theory that underlines the framework in general and in relation to each inter-connected component. Two explicit learning sequences for classroom practice are described, associated with Pythagoras theorem and probability. This paper then concludes with recommendations for using ELPSA in various institutional contexts.Keywords: ELPSA, lesson design framework, Pythagoras theorem, probability DOI: dx.doi.org/10.22342/jme.62.77

Driver. D530.2 – Tools for the Lessons Learned Framework

NARCIS (Netherlands)

Schaik, M.G. van; et al

2016-01-01

In this deliverable D530.2 “Tools for the Lessons Learned Framework” the overall lessons learned framework will be clarified based on the delivery D53.1 “Lessons Learned Framework Concept” and aligned with the deliverable D52.1 “Harmonized competence framework”. The Tools for the Lessons Learned

A Design Framework for Personal Learning Environments

NARCIS (Netherlands)

Rahimi, E.

2015-01-01

The purpose of our research was to develop a PLE (personal learning environment) design framework for workplace settings. By doing such, the research has answered this research question, how should a technology-based personal learning environment be designed, aiming at supporting learners to gain

Early Learning Foundations. Indiana's Early Learning Development Framework Aligned to the Indiana Academic Standards, 2014

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Indiana Department of Education, 2015

2015-01-01

The "Foundations" (English/language arts, mathematics, social emotional skills, approaches to play and learning, science, social studies, creative arts, and physical health and growth) are Indiana's early learning development framework and are aligned to the 2014 Indiana Academic Standards. This framework provides core elements that…

A Framework for the Flexible Content Packaging of Learning Objects and Learning Designs

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Lukasiak, Jason; Agostinho, Shirley; Burnett, Ian; Drury, Gerrard; Goodes, Jason; Bennett, Sue; Lockyer, Lori; Harper, Barry

2004-01-01

This paper presents a platform-independent method for packaging learning objects and learning designs. The method, entitled a Smart Learning Design Framework, is based on the MPEG-21 standard, and uses IEEE Learning Object Metadata (LOM) to provide bibliographic, technical, and pedagogical descriptors for the retrieval and description of learning…

Attitudes of Jordanian Undergraduate Students towards Using Computer Assisted Language Learning (CALL)

Science.gov (United States)

Saeed, Farah Jamal Abed Alrazeq; Al-Zayed, Norma Nawaf

2018-01-01

The study aimed at investigating the attitudes of Jordanian undergraduate students towards using computer assisted-language learning (CALL) and its effectiveness in the process of learning the English language. In order to fulfill the study's objective, the researchers used a questionnaire to collect data, followed-up with semi-structured…

A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks

NARCIS (Netherlands)

De Jong, Tim; Fuertes, Alba; Schmeits, Tally; Specht, Marcus; Koper, Rob

2008-01-01

De Jong, T., Fuertes, A., Schmeits, T., Specht, M., & Koper, R. (2009). A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks. In D. Goh (Ed.), Multiplatform E-Learning Systems and Technologies: Mobile Devices for Ubiquitous ICT-Based Education (pp.

Proposing a Framework for Mobile Applications in Disaster Health Learning.

Science.gov (United States)

Liu, Alexander G; Altman, Brian A; Schor, Kenneth; Strauss-Riggs, Kandra; Thomas, Tracy N; Sager, Catherine; Leander-Griffith, Michelle; Harp, Victoria

2017-08-01

Mobile applications, or apps, have gained widespread use with the advent of modern smartphone technologies. Previous research has been conducted in the use of mobile devices for learning. However, there is decidedly less research into the use of mobile apps for health learning (eg, patient self-monitoring, medical student learning). This deficiency in research on using apps in a learning context is especially severe in the disaster health field. The objectives of this article were to provide an overview of the current state of disaster health apps being used for learning, to situate the use of apps in a health learning context, and to adapt a learning framework for the use of mobile apps in the disaster health field. A systematic literature review was conducted by using the PRISMA checklist, and peer-reviewed articles found through the PubMed and CINAHL databases were examined. This resulted in 107 nonduplicative articles, which underwent a 3-phase review, culminating in a final selection of 17 articles. While several learning models were identified, none were sufficient as an app learning framework for the field. Therefore, we propose a learning framework to inform the use of mobile apps in disaster health learning. (Disaster Med Public Health Preparedness. 2017;11:487-495).

Design Framework for an Adaptive MOOC Enhanced by Blended Learning

DEFF Research Database (Denmark)

Gynther, Karsten

2016-01-01

The research project has developed a design framework for an adaptive MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of learning design principles which can be used to design in-service courses for teacher professional...

A Framework for Creating Semantically Adaptive Collaborative E-learning Environments

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Marija Cubric

2009-09-01

Full Text Available In this paper we present a framework that can be used to generate web-based, semantically adaptive, e-learning and computer-assisted assessment (CAA tools for any given knowledge domain, based upon dynamic ontological modeling. We accomplish this by generating “learning ontologies” for a given knowledge domain. The generated learning ontologies are built upon our previous work on a domain “Glossary” ontology and augmented with additional conceptual relations from the WordNet 3.0 lexical database, using Text2Onto, an open source ontology extraction tool. The main novelty of this work is in “on the fly” generation of computer assisted assessments based on the underlying ontology and pre-defined question templates that are founded on the Bloom’s taxonomy of educational objectives. The main deployment scenario for the framework is a web-service providing collaborative e- learning and knowledge management capabilities to various learning communities. The framework can be extended to provide collection and exploitation of the users’ learning behaviour metrics, in order to further adapt the generated e-learning environment to the learners’ needs.

Collaborative Learning Framework in Business Management Systems

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Vladimir GRIGORE

2008-01-01

Full Text Available This paper presents a solution based on collaboration with experts and practitioner from university and ERP companies involved in process learning by training and learning by working. The solution uses CPI test to establish proper team for framework modules: Real-Time Chat Room, Discussion Forum, E-mail Support and Learning through Training. We define novice, practitioner and expert competence level based on CORONET train methodology. ERP companies have own roles for mentoring services to knowledge workers and evaluate the performance of learning process with teachers’ cooperation in learning by teaching and learning by working module.

Simulation-Based E-Learning Framework for Entrepreneurship Education and Training

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Constanţa-Nicoleta Bodea

2015-02-01

Full Text Available The paper proposes an e-Learning framework in entrepreneurship. The framework has three main components, for identification the business opportunities, for developing business scenarios and for risk analysis. A common database assures the components integration. The main components of this framework are already available; the main challenging for those interested in using them is to design an integrated flow of activities, adapted with their curricula and other educational settings. The originality of the approach is that the framework is domain independent and uses advanced IT technologies, such as recommendation algorithms, agent-based simulations and extended graphical support. Using this e-learning framework, the students can learn how to choose relevant characteristics/aspects for a type of business and how important is each of them according specific criteria; how to set realistic values for different characteristics/aspects of the business, how a business scenario can be changed in order to fit better to the business context and how to assess/evaluate business scenarios.

Modeling Geomagnetic Variations using a Machine Learning Framework

Science.gov (United States)

Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.

2017-12-01

We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.

ENGAGE: A Game Based Learning and Problem Solving Framework

Science.gov (United States)

2012-07-13

Gamification Summit 2012  Mensa Colloquium 2012.2: Social and Video Games  Seattle Science Festival  TED Salon Vancouver : http...From - To) 6/1/2012 – 6/30/2012 4. TITLE AND SUBTITLE ENGAGE: A Game Based Learning and Problem Solving Framework 5a. CONTRACT NUMBER N/A 5b...Popović ENGAGE: A Game Based Learning and Problem Solving Framework (Task 1 Month 4) Progress, Status and Management Report Monthly Progress

An Integrated Framework Of Web 2.0 Technology And A Collaborative Learning

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Mohamed Madar

2015-05-01

Full Text Available Abstract This paper contributes to the suitability of web 2.0 technology in implementing collaborative learning and proposes an integrated framework of Web 2.0 tools and collaborative learning activities. This paper is also identifying the mismatch between adopting web 2.0 technologies and the delivery of the curriculum on the cloud or via the Internet. It is found that Web 2.0 and a collaborative learning are two platforms to be easily synchronized due to their common attributes that enable their complementariness. This paper argues that integrated framework of Web 2.0 and CL allow users exploit teachinglearning materials maximally and at the same upsurges learners understanding in the subject knowledge. Suitable of Web 2.0 in implementing curriculum was also encouraged since the proposed framework consists of both components of Web 2.0 functions and activities of collaborative learning environment. Pedagogically there has been a mismatch between E-learning technologies and mode of delivery for instance E-learning platforms are widely used to increase content accessibility only while now this framework introduces that Web 2.0 technology of E-learning can also be used to create share knowledge among users. The proposed framework if efficiently exploited will also allow users at all levels create personalized learning environment which suits perspective teachinglearning styles of the users. Apart from academic achievement or enhancements of the teaching and learning processes the proposed framework also would help learners develop generic skills which are very important in the workplaces. As a result of this fast and independent learning technically depend on technology based pedagogy and in this case this proposed model has two dimensions which are very crucial to the enrichment of students learning activities.

Conceptual Elements: A Detailed Framework to Support and Assess Student Learning of Biology Core Concepts

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Cary, Tawnya; Branchaw, Janet

2017-01-01

The Vision and Change in Undergraduate Biology Education: Call to Action report has inspired and supported a nationwide movement to restructure undergraduate biology curricula to address overarching disciplinary concepts and competencies. The report outlines the concepts and competencies generally but does not provide a detailed framework to guide the development of the learning outcomes, instructional materials, and assessment instruments needed to create a reformed biology curriculum. In this essay, we present a detailed Vision and Change core concept framework that articulates key components that transcend subdisciplines and scales for each overarching biological concept, the Conceptual Elements (CE) Framework. The CE Framework was developed using a grassroots approach of iterative revision and incorporates feedback from more than 60 biologists and undergraduate biology educators from across the United States. The final validation step resulted in strong national consensus, with greater than 92% of responders agreeing that each core concept list was ready for use by the biological sciences community, as determined by scientific accuracy and completeness. In addition, we describe in detail how educators and departments can use the CE Framework to guide and document reformation of individual courses as well as entire curricula. PMID:28450444

A framework for studying teacher learning by design

NARCIS (Netherlands)

Voogt, Joke; McKenney, Susan; Janssen, Fred; Berry, Amanda; Kicken, Wendy; Coenders, Fer

2012-01-01

Voogt, J., McKenney, S., Janssen, F., Berry, A., Kicken, W., & Coenders, F. (2012, 2-6 July). A framework for studying teacher learning by design. Paper presentation at the Teachers as Designers of Technology Enhanced Learning pre-conference workshop in conjunction with the ISLS annual meeting,

Framework of Strategic Learning: The PDCA Cycle

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Michał Pietrzak

2015-06-01

Full Text Available Nowadays, strategic planning has to be permanent process and organizational learning should support it. Researchers in theories of organizational learning attempt to understand processes, which lead to changes in organizational knowledge, as well as the effects of learning on organizational performance. In traditional approach, the strategy is viewed as one shot event. However, in contemporary turbulent environment this could not be still valid. There is a need of elastic strategic management, which employs organizational learning process. The crucial element of such process is information acquisition, which allows refining the initial version of strategic plan. In this article authors discuss the PDCA cycle as a framework of strategic learning process, including both single-loop and double loop learning. Authors proposed the ideas for further research in area of organizational learning and strategic management.

The 4C framework for making reasonable adjustments for people with learning disabilities.

Science.gov (United States)

Marsden, Daniel; Giles, Rachel

2017-01-18

Background People with learning disabilities experience significant inequalities in accessing healthcare. Legal frameworks, such as the Equality Act 2010, are intended to reduce such disparities in care, and require organisations to make 'reasonable adjustments' for people with disabilities, including learning disabilities. However, reasonable adjustments are often not clearly defined or adequately implemented in clinical practice. Aim To examine and synthesise the challenges in caring for people with learning disabilities to develop a framework for making reasonable adjustments for people with learning disabilities in hospital. This framework would assist ward staff in identifying and managing the challenges of delivering person-centred, safe and effective healthcare to people with learning disabilities in this setting. Method Fourth-generation evaluation, collaborative thematic analysis, reflection and a secondary analysis were used to develop a framework for making reasonable adjustments in the hospital setting. The authors attended ward manager and matron group meetings to collect their claims, concerns and issues, then conducted a collaborative thematic analysis with the group members to identify the main themes. Findings Four main themes were identified from the ward manager and matron group meetings: communication, choice-making, collaboration and coordination. These were used to develop the 4C framework for making reasonable adjustments for people with learning disabilities in hospital. Discussion The 4C framework has provided a basis for delivering person-centred care for people with learning disabilities. It has been used to inform training needs analyses, develop audit tools to review delivery of care that is adjusted appropriately to the individual patient; and to develop competencies for learning disability champions. The most significant benefit of the 4C framework has been in helping to evaluate and resolve practice-based scenarios. Conclusion Use of

An Analytic Framework to Support E.Learning Strategy Development

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Marshall, Stephen J.

2012-01-01

Purpose: The purpose of this paper is to discuss and demonstrate the relevance of a new conceptual framework for leading and managing the development of learning and teaching to e.learning strategy development. Design/methodology/approach: After reviewing and discussing the research literature on e.learning in higher education institutions from…

Pedagogy framework design in social networked-based learning: Focus on children with learning difficulties

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Samira Sadat Sajadi

2014-09-01

Full Text Available This paper presents an investigation on the theory of constructivism applicable for learners with learning difficulties, specifically learners with Attention Deficit Hyperactivity Disorder (ADHD. The primary objective of this paper is to determine whether a constructivist technology enhanced learning pedagogy could be used to help ADHD learners cope with their educational needs within a social-media learning environment. Preliminary work is stated here, in which we are seeking evidence to determine the viability of a constructivist approach for learners with ADHD. The novelty of this research lies in the proposals to support ADHD learners to overcome their weaknesses with appropriate pedagogically sound interventions. As a result, a framework has been designed to illuminate areas in which constructivist pedagogies require to address the limitations of ADHD learners. An analytical framework addressing the suitability of a constructivist learning for ADHD is developed from a combination of literature and expert advice from those involved in the education of learners with ADHD. This analytical framework is married to a new model of pedagogy, which the authors have derived from literature analysis. Future work will expand this model to develop a constructivist social network-based learning and eventually test it in specialist schools with ADHD learners.

Merging Problem-Based Learning with Simulation-Based Learning in the Medical Undergraduate Curriculum: The PAIRED Framework for Enhancing Lifelong Learning

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Koh, Jansen

2016-01-01

Lifelong learning is an essential trait that is expected of every physician. The CanMeds 2005 Physician Competency Framework emphasizes lifelong learning as a key competency that physicians must achieve in becoming better physicians. However, many physicians are not competent at engaging in lifelong learning. The current medical education system is deficient in preparing medical students to develop and carry out their own lifelong learning curriculum upon graduation. Despite understanding how physicians learn at work, medical students are not trained to learn while working. Similarly, although barriers to lifelong learning are known, medical students are not adequately skilled in overcoming these barriers. Learning to learn is just as important, if not more, as acquiring the skills and knowledge required of a physician. The medical undergraduate curriculum lacks a specific learning strategy to prepare medical students in becoming an adept lifelong learner. In this article, we propose a learning strategy for lifelong learning at the undergraduate level. In developing this novel strategy, we paid particular attention to two parameters. First, this strategy should be grounded on literature describing a physician’s lifelong learning process. Second, the framework for implementing this strategy must be based on existing undergraduate learning strategies to obviate the need for additional resources, learner burden, and faculty time. In this paper, we propose a Problem, Analysis, Independent Research Reporting, Experimentation Debriefing (PAIRED) framework that follows the learning process of a physician and serves to synergize the components of problem-based learning and simulation-based learning in specifically targeting the barriers to lifelong learning. PMID:27446767

The application of language-game theory to the analysis of science learning: Developing an interpretive classroom-level learning framework

Science.gov (United States)

Ahmadibasir, Mohammad

In this study an interpretive learning framework that aims to measure learning on the classroom level is introduced. In order to develop and evaluate the value of the framework, a theoretical/empirical study is designed. The researcher attempted to illustrate how the proposed framework provides insights on the problem of classroom-level learning. The framework is developed by construction of connections between the current literature on science learning and Wittgenstein's language-game theory. In this framework learning is defined as change of classroom language-game or discourse. In the proposed framework, learning is measured by analysis of classroom discourse. The empirical explanation power of the framework is evaluated by applying the framework in the analysis of learning in a fifth-grade science classroom. The researcher attempted to analyze how students' colloquial discourse changed to a discourse that bears more resemblance to science discourse. The results of the empirical part of the investigation are presented in three parts: first, the gap between what students did and what they were supposed to do was reported. The gap showed that students during the classroom inquiry wanted to do simple comparisons by direct observation, while they were supposed to do tool-assisted observation and procedural manipulation for a complete comparison. Second, it was illustrated that the first attempt to connect the colloquial to science discourse was done by what was immediately intelligible for students and then the teacher negotiated with students in order to help them to connect the old to the new language-game more purposefully. The researcher suggested that these two events in the science classroom are critical in discourse change. Third, it was illustrated that through the academic year, the way that students did the act of comparison was improved and by the end of the year more accurate causal inferences were observable in classroom communication. At the end of the

Adjusted Framework of M-Learning in Blended Learning System for Mathematics Study Field of Junior High School Level VII

Science.gov (United States)

Sugiyanta, Lipur; Sukardjo, Moch.

2018-04-01

The 2013 curriculum requires teachers to be more productive, creative, and innovative in encouraging students to be more independent by strengthening attitudes, skills and knowledge. Teachers are given the options to create lesson plan according to the environment and conditions of their students. At the junior level, Core Competence (KI) and Basic Competence (KD) have been completely designed. In addition, there had already guidebooks, both for teacher manuals (Master’s Books) and for learners (Student Books). The lesson plan and guidebooks which already exist are intended only for learning in the classroom/in-school. Many alternative classrooms and alternatives learning models opened up using educational technology. The advance of educational technology opened opportunity for combination of class interaction using mobile learning applications. Mobile learning has rapidly evolved in education for the last ten years and many initiatives have been conducted worldwide. However, few of these efforts have produced any lasting outcomes. It is evident that mobile education applications are complex and hence, will not become sustainable. Long-term sustainability remains a risk. Long-term sustainability usually was resulted from continuous adaptation to changing conditions [4]. Frameworks are therefore required to avoid sustainability pitfalls. The implementation should start from simple environment then gradually become complex through adaptation steps. Therefore, our paper developed the framework of mobile learning (m-learning) adaptation for grade 7th (junior high school). The environment setup was blended mobile learning (not full mobile learning) and emphasize on Algebra. The research is done by R&D method (research and development). Results of the framework includes requirements and adaptation steps. The adjusted m-learning framework is designed to be a guidance for teachers to adopt m-learning to support blended learning environments. During mock-up prototype, the

Is "Learning without Limits" a Framework of Values?

Science.gov (United States)

Booth, Tony

2015-01-01

In this article the author connects his own work with Brian Simon's writing on IQ (intelligence quotient) testing and selection and with the Learning without Limits project. He discusses the significance he gives to a values framework in the development of education and asks whether "Learning without Limits," in part, stands for a…

Expanding the frontiers of national qualifications frameworks through lifelong learning

Science.gov (United States)

Owusu-Agyeman, Yaw

2017-10-01

The adoption of a national qualifications framework (NQF) by some governments in all world regions has shown some success in the area of formal learning. However, while NQFs continue to enhance formal learning in many countries, the same cannot be said for the recognition, validation and accreditation (RVA) of non-formal and informal learning. Focusing on competency-based technical and vocational education and training (TVET) within its NQF, Ghana introduced the National Technical and Vocational Education and Training Qualifications Framework (NTVETQF) as a sub-framework in 2012. In the wake of the NTVETQF's limited success, the author of this article reasons that a lifelong learning approach could enhance its effectiveness considerably. Comparing national and international policies, he argues that the NTVETQF should be able to properly address the issues of progression from informal and non-formal to formal modes of lifelong learning within the country's broad context of education. In addition, the study conceptualises the integration of lifelong learning within a broad NQF in four key domains: (1) individual; (2) institutional; (3) industry; and (4) state. The author concludes that, for the NTVETQF to achieve its goal of facilitating access to further education and training while also promoting lifelong learning for all (including workers in the informal economy), effective integration of all modes of lifelong learning is required. Although this entails some challenges, such as recognition of prior learning and validation of all modes of learning, it will help to widen access to education as well as providing individuals with a pathway for achieving their educational aspirations.

Honoring Family and Culture: Learning from New Zealand

Science.gov (United States)

Nagel, Nancy G.

2009-01-01

The New Zealand Ministry of Education's early childhood curriculum policy is built on a framework called "Te Whariki." This framework provides a sociocultural context for children's early learning and emphasizes a learning partnership between teachers, parents, families, and community. Besides interpersonal relationships, Te Whariki…

Visual Hybrid Development Learning System (VHDLS) framework for children with autism.

Science.gov (United States)

Banire, Bilikis; Jomhari, Nazean; Ahmad, Rodina

2015-10-01

The effect of education on children with autism serves as a relative cure for their deficits. As a result of this, they require special techniques to gain their attention and interest in learning as compared to typical children. Several studies have shown that these children are visual learners. In this study, we proposed a Visual Hybrid Development Learning System (VHDLS) framework that is based on an instructional design model, multimedia cognitive learning theory, and learning style in order to guide software developers in developing learning systems for children with autism. The results from this study showed that the attention of children with autism increased more with the proposed VHDLS framework.

A Teaching - Learning Framework for MEMS Education

International Nuclear Information System (INIS)

Sheeparamatti, B G; Angadi, S A; Sheeparamatti, R B; Kadadevaramath, J S

2006-01-01

Micro-Electro-Mechanical Systems (MEMS) technology has been identified as one of the most promising technologies in the 21st century. MEMS technology has opened up a wide array of unforeseen applications. Hence it is necessary to train the technocrats of tomorrow in this emerging field to meet the industrial/societal demands. The drive behind fostering of MEMS technology is the reduction in the cost, size, weight, and power consumption of the sensors, actuators, and associated electronics. MEMS is a multidisciplinary engineering and basic science area which includes electrical engineering, mechanical engineering, material science and biomedical engineering. Hence MEMS education needs a special approach to prepare the technocrats for a career in MEMS. The modern education methodology using computer based training systems (CBTS) with embedded modeling and simulation tools will help in this direction. The availability of computer based learning resources such as MATLAB, ANSYS/Multiphysics and rapid prototyping tools have contributed to proposition of an efficient teaching-learning framework for MEMS education presented in this paper. This paper proposes a conceptual framework for teaching/learning MEMS in the current technical education scenario

A Framework for Building an Interactive Satellite TV Based M-Learning Environment

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Ghassan Issa

2010-07-01

Full Text Available This paper presents a description of an interactive satellite TV based mobile learning (STV-ML framework, in which a satellite TV station is used as an integral part of a comprehensive interactive mobile learning (M-Learning environment. The proposed framework assists in building a reliable, efficient, and cost-effective environment to meet the growing demands of M-Learning all over the world, especially in developing countries. It utilizes recent advances in satellite reception, broadcasting technologies, and interactive TV to facilitate the delivery of gigantic learning materials. This paper also proposed a simple and flexible three-phase implementation methodology which includes construction of earth station, expansion of broadcasting channels, and developing true user interactivity. The proposed framework and implementation methodology ensure the construction of a true, reliable, and cost effective M-Learning system that can be used efficiently and effectively by a wide range of users and educational institutions to deliver ubiquitous learning.

The extraction and integration framework: a two-process account of statistical learning.

Science.gov (United States)

Thiessen, Erik D; Kronstein, Alexandra T; Hufnagle, Daniel G

2013-07-01

The term statistical learning in infancy research originally referred to sensitivity to transitional probabilities. Subsequent research has demonstrated that statistical learning contributes to infant development in a wide array of domains. The range of statistical learning phenomena necessitates a broader view of the processes underlying statistical learning. Learners are sensitive to a much wider range of statistical information than the conditional relations indexed by transitional probabilities, including distributional and cue-based statistics. We propose a novel framework that unifies learning about all of these kinds of statistical structure. From our perspective, learning about conditional relations outputs discrete representations (such as words). Integration across these discrete representations yields sensitivity to cues and distributional information. To achieve sensitivity to all of these kinds of statistical structure, our framework combines processes that extract segments of the input with processes that compare across these extracted items. In this framework, the items extracted from the input serve as exemplars in long-term memory. The similarity structure of those exemplars in long-term memory leads to the discovery of cues and categorical structure, which guides subsequent extraction. The extraction and integration framework provides a way to explain sensitivity to both conditional statistical structure (such as transitional probabilities) and distributional statistical structure (such as item frequency and variability), and also a framework for thinking about how these different aspects of statistical learning influence each other. 2013 APA, all rights reserved

A Framework for Collaborative Networked Learning in Higher Education: Design & Analysis

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Ghassan F. Issa

2014-06-01

Full Text Available This paper presents a comprehensive framework for building collaborative learning networks within higher educational institutions. This framework focuses on systems design and implementation issues in addition to a complete set of evaluation, and analysis tools. The objective of this project is to improve the standards of higher education in Jordan through the implementation of transparent, collaborative, innovative, and modern quality educational programs. The framework highlights the major steps required to plan, design, and implement collaborative learning systems. Several issues are discussed such as unification of courses and program of studies, using appropriate learning management system, software design development using Agile methodology, infrastructure design, access issues, proprietary data storage, and social network analysis (SNA techniques.

A Conceptual Framework for Evolving, Recommender Online Learning Systems

Science.gov (United States)

Peiris, K. Dharini Amitha; Gallupe, R. Brent

2012-01-01

A comprehensive conceptual framework is developed and described for evolving recommender-driven online learning systems (ROLS). This framework describes how such systems can support students, course authors, course instructors, systems administrators, and policy makers in developing and using these ROLS. The design science information systems…

CALL AND COOPERATIVE LEARNING: A SOLUTION TO DEVELOP STUDENTS‟ LISTENING ABILITY

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Delsa Miranty

2017-04-01

Full Text Available This paper aims to provide some ideas both for English teachers and target learners about how to apply CALL and Cooperative Learning as the solution to develop students‘ listening activities in the classroom. Since teachers need to understand about students‘ needs, background, age and expectations when they learn English as the foreign language in the classroom. Therefore, the English teacher should provide environment which facilitates the children to have fun di the teaching learning process, nice atmosphere, comfort and enjoyable to learn English and practice it both in the classroom and in the laboratory. Furthermore, this paper will provide what the teachers should do related activities such as: listening to the songs, movies, cartoon by applying STAD (Students Teams – Achievement Divisions in the classroom in order to develop students‘ listening ability both in the classroom and laboratory.

What is This Thing Called Sensemaking?: A Theoretical Framework for How Physics Students Resolve Inconsistencies in Understanding

Science.gov (United States)

Odden, Tor Ole B.

Students often emerge from introductory physics courses with a feeling that the concepts they have learned do not make sense. In recent years, science education researchers have begun to attend to this type of problem by studying the ways in which students make sense of science concepts. However, although many researchers agree intuitively on what sensemaking looks like, the literature on sensemaking is both theoretically fragmented and provides few guidelines for how to encourage and support the process. In this dissertation, I address this challenge by proposing a theoretical framework to describe students' sensemaking processes. I base this framework both on the science education research literature on sensemaking and on a series of video-recorded cognitive, clinical interviews conducted with introductory physics students enrolled in a course on electricity and magnetism. Using the science education research literature on sensemaking as well as a cognitivist, dynamic network model of mind as a theoretical lens, I first propose a coherent definition of sensemaking. Then, using this definition I analyze the sensemaking processes of these introductory physics students during episodes when they work to articulate and resolve gaps or inconsistencies in their understanding. Based on the students' framing, gestures, and dialogue I argue that the process of sensemaking unfolds in a distinct way, which we can describe as an epistemic game in which students first build a framework of knowledge, then identify a gap or inconsistency in that framework, iteratively build an explanation to resolve the gap or inconsistency, and (sometimes) successfully resolve it. I further argue that their entry into the sensemaking frame is facilitated by a specific question, which is in turn motivated by a gap or inconsistency in knowledge that I call the vexation point. I also investigate the results of sensemaking, arguing that students may use the technique of conceptual blending to both

A Call to Action for Research in Digital Learning: Learning without Limits of Time, Place, Path, Pace…or Evidence

Science.gov (United States)

Cavanaugh, Cathy; Sessums, Christopher; Drexler, Wendy

2015-01-01

This essay is a call for rethinking our approach to research in digital learning. It plots a path founded in social trends and advances in education. A brief review of these trends and advances is followed by discussion of what flattened research might look like at scale. Scaling research in digital learning is crucial to advancing understanding…

Active-constructive-interactive: a conceptual framework for differentiating learning activities.

Science.gov (United States)

Chi, Michelene T H

2009-01-01

Active, constructive, and interactive are terms that are commonly used in the cognitive and learning sciences. They describe activities that can be undertaken by learners. However, the literature is actually not explicit about how these terms can be defined; whether they are distinct; and whether they refer to overt manifestations, learning processes, or learning outcomes. Thus, a framework is provided here that offers a way to differentiate active, constructive, and interactive in terms of observable overt activities and underlying learning processes. The framework generates a testable hypothesis for learning: that interactive activities are most likely to be better than constructive activities, which in turn might be better than active activities, which are better than being passive. Studies from the literature are cited to provide evidence in support of this hypothesis. Moreover, postulating underlying learning processes allows us to interpret evidence in the literature more accurately. Specifying distinct overt activities for active, constructive, and interactive also offers suggestions for how learning activities can be coded and how each kind of activity might be elicited. Copyright © 2009 Cognitive Science Society, Inc.

Grounding theories of W(e)Learn: a framework for online interprofessional education.

Science.gov (United States)

Casimiro, Lynn; MacDonald, Colla J; Thompson, Terrie Lynn; Stodel, Emma J

2009-07-01

Interprofessional care (IPC) is a prerequisite for enhanced communication between healthcare team members, improved quality of care, and better outcomes for patients. A move to an IPC model requires changing the learning experiences of healthcare providers during and after their qualification program. With the rapid growth of online and blended approaches to learning, an educational framework that explains how to construct quality learning events to provide IPC is pressing. Such a framework would offer a quality standard to help educators design, develop, deliver, and evaluate online interprofessional education (IPE) programs. IPE is an extremely delicate process due to issues related to knowledge, status, power, accountability, personality traits, and culture that surround IPC. In this paper, a review of the pertinent literature that would inform the development of such a framework is presented. The review covers IPC, IPE, learning theories, and eLearning in healthcare.

Overcoming complexities: Damage detection using dictionary learning framework

Science.gov (United States)

Alguri, K. Supreet; Melville, Joseph; Deemer, Chris; Harley, Joel B.

2018-04-01

For in situ damage detection, guided wave structural health monitoring systems have been widely researched due to their ability to evaluate large areas and their ability detect many types of damage. These systems often evaluate structural health by recording initial baseline measurements from a pristine (i.e., undamaged) test structure and then comparing later measurements with that baseline. Yet, it is not always feasible to have a pristine baseline. As an alternative, substituting the baseline with data from a surrogate (nearly identical and pristine) structure is a logical option. While effective in some circumstance, surrogate data is often still a poor substitute for pristine baseline measurements due to minor differences between the structures. To overcome this challenge, we present a dictionary learning framework to adapt surrogate baseline data to better represent an undamaged test structure. We compare the performance of our framework with two other surrogate-based damage detection strategies: (1) using raw surrogate data for comparison and (2) using sparse wavenumber analysis, a precursor to our framework for improving the surrogate data. We apply our framework to guided wave data from two 108 mm by 108 mm aluminum plates. With 20 measurements, we show that our dictionary learning framework achieves a 98% accuracy, raw surrogate data achieves a 92% accuracy, and sparse wavenumber analysis achieves a 57% accuracy.

A Conceptual Framework for Educational Design at Modular Level to Promote Transfer of Learning

Science.gov (United States)

Botma, Yvonne; Van Rensburg, G. H.; Coetzee, I. M.; Heyns, T.

2015-01-01

Students bridge the theory-practice gap when they apply in practice what they have learned in class. A conceptual framework was developed that can serve as foundation to design for learning transfer at modular level. The framework is based on an adopted and adapted systemic model of transfer of learning, existing learning theories, constructive…

The CABES (Clare Adult Basic Education Service) Framework as a Tool for Teaching and Learning

Science.gov (United States)

Greene, Moira

2015-01-01

This article describes a Framework that can be used to help bridge the gap between theory and practice in adult learning. The Framework promotes practice informed by three strands important to adult literacy work: social theories of literacy, social-constructivist learning theory and principles of adult learning. The Framework shows how five key…

The allocation of attention to learning of goal-directed actions: A cognitive neuroscience framework focusing on the basal ganglia

Directory of Open Access Journals (Sweden)

Liz eFranz

2012-12-01

Full Text Available The present paper builds on the idea that attention is largely in service of our actions. A framework and model which captures the allocation of attention for learning of goal-directed actions is proposed and developed. This framework highlights an evolutionary model based on the notion that rudimentary brain functions have become embedded into increasingly higher levels of networks which all contribute to adaptive learning. Background literature is presented alongside key evidence based on experimental studies in the so-called ‘split-brain’ (surgically divided cerebral hemispheres with a key focus on bimanual actions. The proposed multilevel cognitive-neural system of attention is built upon key processes of a highly-adaptive basal-ganglia-thalamic-cortical system. Although overlap with other existing findings and models is acknowledged where appropriate, the proposed framework is an original synthesis of cognitive experimental findings with supporting evidence of a neural system and a carefully formulated model of attention. It is the hope that this new synthesis will be informative in fields of cognition and other fields of brain sciences and will lead to new avenues for experimentation across domains.

The ICAP Active Learning Framework Predicts the Learning Gains Observed in Intensely Active Classroom Experiences

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Benjamin L. Wiggins

2017-05-01

Full Text Available STEM classrooms (science, technology, engineering, and mathematics in postsecondary education are rapidly improved by the proper use of active learning techniques. These techniques occupy a descriptive spectrum that transcends passive teaching toward active, constructive, and, finally, interactive methods. While aspects of this framework have been examined, no large-scale or actual classroom-based data exist to inform postsecondary education STEM instructors about possible learning gains. We describe the results of a quasi-experimental study to test the apex of the ICAP framework (interactive, constructive, active, and passive in this ecological classroom environment. Students in interactive classrooms demonstrate significantly improved learning outcomes relative to students in constructive classrooms. This improvement in learning is relatively subtle; similar experimental designs without repeated measures would be unlikely to have the power to observe this significance. We discuss the importance of seemingly small learning gains that might propagate throughout a course or departmental curriculum, as well as improvements with the necessity for faculty to develop and implement similar activities.

The knowledge-learning-instruction framework: bridging the science-practice chasm to enhance robust student learning.

Science.gov (United States)

Koedinger, Kenneth R; Corbett, Albert T; Perfetti, Charles

2012-07-01

Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense-making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices. Copyright © 2012 Cognitive Science Society, Inc.

Orchestration Framework for Learning Activities in Augmented Reality Environments

OpenAIRE

Ibáñez, María Blanca; Delgado Kloos, Carlos; Di Serio, Angela

2011-01-01

Proceedings of: Across Spaces11 Workshop in conjunction with the EC-TEL2011, Palermo, Italy, September 21, 2011 In this paper we show how Augmented Reality (AR) technology restricted to the use of mobiles or PCs, can be used to develop learning activities with the minimun level of orchestation required by meaningful learning sequences. We use Popcode as programming language to deploy orchestrated learning activities specified with an AR framework. Publicado

A Conceptual Framework for Ambient Learning Displays

NARCIS (Netherlands)

Börner, Dirk; Kalz, Marco; Specht, Marcus

2011-01-01

Börner, D., Kalz, M., & Specht, M. (2010, 29 November-3 December). A Conceptual Framework for Ambient Learning Displays. Poster presented at the Work-in-Progress Poster and Invited Young Researcher Symposium of the 18th International Conference on Computers in Education, Putrajaya, Malaysia:

Teaching and Learning Numerical Analysis and Optimization: A Didactic Framework and Applications of Inquiry-Based Learning

Science.gov (United States)

Lappas, Pantelis Z.; Kritikos, Manolis N.

2018-01-01

The main objective of this paper is to propose a didactic framework for teaching Applied Mathematics in higher education. After describing the structure of the framework, several applications of inquiry-based learning in teaching numerical analysis and optimization are provided to illustrate the potential of the proposed framework. The framework…

Games and Simulations in Online Learning: Research and Development Frameworks

Science.gov (United States)

Gibson, David; Aldrich, Clark; Prensky, Marc

2007-01-01

Games and Simulations in Online Learning: Research and Development Frameworks examines the potential of games and simulations in online learning, and how the future could look as developers learn to use the emerging capabilities of the Semantic Web. It presents a general understanding of how the Semantic Web will impact education and how games and…

A Machine Learning Framework for Plan Payment Risk Adjustment.

Science.gov (United States)

Rose, Sherri

2016-12-01

To introduce cross-validation and a nonparametric machine learning framework for plan payment risk adjustment and then assess whether they have the potential to improve risk adjustment. 2011-2012 Truven MarketScan database. We compare the performance of multiple statistical approaches within a broad machine learning framework for estimation of risk adjustment formulas. Total annual expenditure was predicted using age, sex, geography, inpatient diagnoses, and hierarchical condition category variables. The methods included regression, penalized regression, decision trees, neural networks, and an ensemble super learner, all in concert with screening algorithms that reduce the set of variables considered. The performance of these methods was compared based on cross-validated R 2 . Our results indicate that a simplified risk adjustment formula selected via this nonparametric framework maintains much of the efficiency of a traditional larger formula. The ensemble approach also outperformed classical regression and all other algorithms studied. The implementation of cross-validated machine learning techniques provides novel insight into risk adjustment estimation, possibly allowing for a simplified formula, thereby reducing incentives for increased coding intensity as well as the ability of insurers to "game" the system with aggressive diagnostic upcoding. © Health Research and Educational Trust.

An Organizational Learning Framework for Patient Safety.

Science.gov (United States)

Edwards, Marc T

Despite concerted effort to improve quality and safety, high reliability remains a distant goal. Although this likely reflects the challenge of organizational change, persistent controversy over basic issues suggests that weaknesses in conceptual models may contribute. The essence of operational improvement is organizational learning. This article presents a framework for identifying leverage points for improvement based on organizational learning theory and applies it to an analysis of current practice and controversy. Organizations learn from others, from defects, from measurement, and from mindfulness. These learning modes correspond with contemporary themes of collaboration, no blame for human error, accountability for performance, and managing the unexpected. The collaborative model has dominated improvement efforts. Greater attention to the underdeveloped modes of organizational learning may foster more rapid progress in patient safety by increasing organizational capabilities, strengthening a culture of safety, and fixing more of the process problems that contribute to patient harm.

A Conceptual Framework over Contextual Analysis of Concept Learning within Human-Machine Interplays

DEFF Research Database (Denmark)

Badie, Farshad

2016-01-01

This research provides a contextual description concerning existential and structural analysis of ‘Relations’ between human beings and machines. Subsequently, it will focus on conceptual and epistemological analysis of (i) my own semantics-based framework [for human meaning construction] and of (ii......) a well-structured machine concept learning framework. Accordingly, I will, semantically and epistemologically, focus on linking those two frameworks for logical analysis of concept learning in the context of human-machine interrelationships. It will be demonstrated that the proposed framework provides...

A Framework for Narration and Learning in Educational Multimedia

DEFF Research Database (Denmark)

Mosegaard, Jesper; Bennedsen, Jens

2006-01-01

In this article we describe a multimedia adventure game framework for a learningenvironment to support the teaching and learning of introductory programming. In theframework we have conceptualized two important aspects of such an environment: narrationand learning topics. We describe the interplay...... between these aspects and how the frameworkutilizes this to adapt the learning process to the individual student. The motivation for theseparation is to help the teacher balance the two main driving forces of an edutainmentproduct: entertainment and learning. It is the responsibility of the teacher...

A Conceptual Framework for Ambient Learning Displays

NARCIS (Netherlands)

Börner, Dirk; Kalz, Marco; Specht, Marcus

2010-01-01

Börner, D., Kalz, M., & Specht, M. (2010). A Conceptual Framework for Ambient Learning Displays. In B. Chang, T. Hirashima, & H. Ogata (Eds.), Joint Proceedings of the Work-in-Progress Poster and Invited Young Researcher Symposium for the 18th International Conference on Computers in Education (pp.

A framework for designing and improving learning environments fostering creativity

Directory of Open Access Journals (Sweden)

Norio Ishii

Full Text Available This paper proposes a framework for designing and improving learning environment for creativity in engineering. The framework consists of the following three components: instructional design based on knowledge from psychology, development of systems for supporting creative activities, and objective evaluation of learning results related to creativity. Based on that framework, we design and practice course based in the programation of a robot at a Japan University in the 2004 academic year. As a result, we confirm the following two advantages of our framework: learners' idea generation skills were improved and their meta-cognitive activities were also activated. In the 2005 academic year, we improve the course based on 2004 results. As a result, we confirm that the number of uploads of activity data from students have increased in the 2005 course, students' reflection sheets have become more detailed, and their volume of information have also increased.

Social innovation education: towards a framework for learning design

OpenAIRE

Alden Rivers, Bethany; Armellini, Alejandro; Maxwell, Rachel; Allen, Sue; Durkin, Chris

2015-01-01

Purpose—This paper proposes a theoretical framework to support the embedding of social innovation education in existing academic programmes.\\ud Design/methodology/approach—By adopting Conole et al.’s (2004) methodological approach to reviewing, mapping and modelling learning theory, this study addresses four research questions: 1) How can social innovation education be defined? 2) Which learning theories best support social innovation education? 3) How do such learning theories relate to exis...

An analytical quality framework for learning cities and regions

Science.gov (United States)

Preisinger-Kleine, Randolph

2013-09-01

There is broad agreement that innovation, knowledge and learning have become the main source of wealth, employment and economic development of cities, regions and nations. Over the past two decades, the number of European cities and regions which label themselves as "learning city" or "learning region" has constantly grown. However, there are also pitfalls and constraints which not only hinder them in unlocking their full potential, but also significantly narrow their effects and their wider impact on society. Most prominently, learning cities and regions manifest serious difficulties in rendering transparent the surplus value they generate, which is vital for attracting investment into lifelong learning. While evaluation and quality management are still perceived as being a bureaucratic necessity rather than a lesson one could learn from or an investment in the future, it is also true that without evaluation and quality assurance local networks do not have the means to examine their strengths and weaknesses. In order to design strategies to maximise the strengths and effectively address the weaknesses it is necessary to understand the factors that contribute to success and those that pose challenges. This article proposes an analytical quality framework which is generic and can be used to promote a culture of quality in learning cities and regions. The proposed framework builds on the findings and results of the R3L+ project, part-funded by the European Commission under the Grundtvig (adult education) strand of the Lifelong Learning programme 2007-2013.

Using the 7Cs Framework for Designing MOOCs in Blended Contexts

DEFF Research Database (Denmark)

Buch, Bettina; Christiansen, René Boyer; Hansen, Dorrit

2018-01-01

the 7Cs framework put forward by Conole and colleagues and discuss it in relation to the concept of personalized learning paths and 'schooling' as a discourse. The article is mainly theoretical, but as empirical support for our theoretical arguments, we discuss examples from a MOOC developed......Designing teaching in an era of educational technology calls for new models for designing learning opportunities. The 7Cs framework developed by Professor Gráinne Conole and her colleagues provides a tool for discussing learning designs for online learning environments. In this paper, we introduce...... for the teacher education program at University College Absalon, Denmark. On this background, we propose a number of revisions for the 7Cs framework in order to adapt it for designing MOOCs that are used in blended contexts....

Beyond Effectiveness: A Pragmatic Evaluation Framework for Learning and Continuous Quality Improvement of e-Learning Interventions in Healthcare.

Science.gov (United States)

Dafalla, Tarig Dafalla Mohamed; Kushniruk, Andre W; Borycki, Elizabeth M

2015-01-01

A pragmatic evaluation framework for evaluating the usability and usefulness of an e-learning intervention for a patient clinical information scheduling system is presented in this paper. The framework was conceptualized based on two different but related concepts (usability and usefulness) and selection of appropriate and valid methods of data collection and analysis that included: (1) Low-Cost Rapid Usability Engineering (LCRUE), (2) Cognitive Task Analysis (CTA), (3) Heuristic Evaluation (HE) criteria for web-based learning, and (4) Software Usability Measurement Inventory (SUMI). The results of the analysis showed some areas where usability that were related to General Interface Usability (GIU), instructional design and content was problematic; some of which might account for the poorly rated aspects of usability when subjectively measured. This paper shows that using a pragmatic framework can be a useful way, not only for measuring the usability and usefulness, but also for providing a practical objective evidences for learning and continuous quality improvement of e-learning systems. The findings should be of interest to educators, developers, designers, researchers, and usability practitioners involved in the development of e-learning systems in healthcare. This framework could be an appropriate method for assessing the usability, usefulness and safety of health information systems both in the laboratory and in the clinical context.

Emergent frameworks of research teaching and learning in a cohort ...

African Journals Online (AJOL)

... frameworks for doctoral pedagogies –“democratic teaching/learning participation”, “structured scaffolding”, “Ubuntu” and “serendipity”– as useful explanatory shaping influences which underpin and frame the model promoting a contextually relevant and appropriate doctoral research teaching and learning pedagogy.

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…

A Reinforcement Learning Approach to Call Admission Control in HAPS Communication System

Directory of Open Access Journals (Sweden)

Ni Shu Yan

2017-01-01

Full Text Available The large changing of link capacity and number of users caused by the movement of both platform and users in communication system based on high altitude platform station (HAPS will resulting in high dropping rate of handover and reduce resource utilization. In order to solve these problems, this paper proposes an adaptive call admission control strategy based on reinforcement learning approach. The goal of this strategy is to maximize long-term gains of system, with the introduction of cross-layer interaction and the service downgraded. In order to access different traffics adaptively, the access utility of handover traffics and new call traffics is designed in different state of communication system. Numerical simulation result shows that the proposed call admission control strategy can enhance bandwidth resource utilization and the performances of handover traffics.

An Evaluation Quality Framework for Analysing School-Based Learning (SBL) to Work-Based Learning (WBL) Transition Module

International Nuclear Information System (INIS)

Alseddiqi, M; Mishra, R; Pislaru, C

2012-01-01

The paper presents the results from a quality framework to measure the effectiveness of a new engineering course entitled 'school-based learning (SBL) to work-based learning (WBL) transition module' in the Technical and Vocational Education (TVE) system in Bahrain. The framework is an extended version of existing information quality frameworks with respect to pedagogical and technological contexts. It incorporates specific pedagogical and technological dimensions as per the Bahrain modern industry requirements. Users' views questionnaire on the effectiveness of the new transition module was distributed to various stakeholders including TVE teachers and students. The aim was to receive critical information in diagnosing, monitoring and evaluating different views and perceptions about the effectiveness of the new module. The analysis categorised the quality dimensions by their relative importance. This was carried out using the principal component analysis available in SPSS. The analysis clearly identified the most important quality dimensions integrated in the new module for SBL-to-WBL transition. It was also apparent that the new module contains workplace proficiencies, prepares TVE students for work placement, provides effective teaching and learning methodologies, integrates innovative technology in the process of learning, meets modern industrial needs, and presents a cooperative learning environment for TVE students. From the principal component analysis finding, to calculate the percentage of relative importance of each factor and its quality dimensions, was significant. The percentage comparison would justify the most important factor as well as the most important quality dimensions. Also, the new, re-arranged quality dimensions from the finding with an extended number of factors tended to improve the extended version of the quality information framework to a revised quality framework.

Theoretical frameworks for the learning of geometrical reasoning

OpenAIRE

Jones, Keith

1998-01-01

With the growth in interest in geometrical ideas it is important to be clear about the nature of geometrical reasoning and how it develops. This paper provides an overview of three theoretical frameworks for the learning of geometrical reasoning: the van Hiele model of thinking in geometry, Fischbein’s theory of figural concepts, and Duval’s cognitive model of geometrical reasoning. Each of these frameworks provides theoretical resources to support research into the development of geometrical...

A Data Protection Framework for Learning Analytics

Science.gov (United States)

Cormack, Andrew

2016-01-01

Most studies on the use of digital student data adopt an ethical framework derived from human-subject research, based on the informed consent of the experimental subject. However, consent gives universities little guidance on using learning analytics as a routine part of educational provision: which purposes are legitimate and which analyses…

Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

Directory of Open Access Journals (Sweden)

Paula Miranda

2017-09-01

Full Text Available Aim/Purpose: As e-Learning 3.0 evolves from a theoretical construct into an actual solution for online learning, it becomes crucial to accompany this progress by scrutinising the elements that are at the origin of its success. Background: This paper outlines a framework of e-Learning 3.0’s critical success factors and its empirical validation. Methodology: The framework is the result of an extensive literature review and its empirical substantiation derives from semi-structured interviews with e-Learning experts. Contribution: The viewpoints of the experts enable the confirmation and the refinement of the original framework and serve as a foundation for the prospective implementation of e-Learning 3.0. Findings: The analysis of the interviews demonstrates that e-Learning 3.0 remains in its early stages with a reticent dissemination. Nonetheless, the interviewees invoked factors related to technology, content and stakeholders as being critical for the success of this new phase of e-Learning. Recommendations for Practitioners: Practitioners can use the framework as a guide for promoting and implementing effective e-Learning 3.0 initiatives. Recommendation for Researchers: As a new phenomenon with uncharted potential, e-Learning 3.0 should be placed at the centre of educational research. Impact on Society: The understanding of what drives the success of e-Learning 3.0 is fundamental for its implementation and for the progress of online education in this new stage of its evolution. Future Research: Future research ventures can include the design of quantitative and self-administered data collection instruments that can provide further insight into the elements of the framework.

A DBR Framework for Designing Mobile Virtual Reality Learning Environments

Science.gov (United States)

Cochrane, Thomas Donald; Cook, Stuart; Aiello, Stephen; Christie, Duncan; Sinfield, David; Steagall, Marcus; Aguayo, Claudio

2017-01-01

This paper proposes a design based research (DBR) framework for designing mobile virtual reality learning environments. The application of the framework is illustrated by two design-based research projects that aim to develop more authentic educational experiences and learner-centred pedagogies in higher education. The projects highlight the first…

Neural correlates of threat perception: neural equivalence of conspecific and heterospecific mobbing calls is learned.

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Marc T Avey

Full Text Available Songbird auditory areas (i.e., CMM and NCM are preferentially activated to playback of conspecific vocalizations relative to heterospecific and arbitrary noise. Here, we asked if the neural response to auditory stimulation is not simply preferential for conspecific vocalizations but also for the information conveyed by the vocalization. Black-capped chickadees use their chick-a-dee mobbing call to recruit conspecifics and other avian species to mob perched predators. Mobbing calls produced in response to smaller, higher-threat predators contain more "D" notes compared to those produced in response to larger, lower-threat predators and thus convey the degree of threat of predators. We specifically asked whether the neural response varies with the degree of threat conveyed by the mobbing calls of chickadees and whether the neural response is the same for actual predator calls that correspond to the degree of threat of the chickadee mobbing calls. Our results demonstrate that, as degree of threat increases in conspecific chickadee mobbing calls, there is a corresponding increase in immediate early gene (IEG expression in telencephalic auditory areas. We also demonstrate that as the degree of threat increases for the heterospecific predator, there is a corresponding increase in IEG expression in the auditory areas. Furthermore, there was no significant difference in the amount IEG expression between conspecific mobbing calls or heterospecific predator calls that were the same degree of threat. In a second experiment, using hand-reared chickadees without predator experience, we found more IEG expression in response to mobbing calls than corresponding predator calls, indicating that degree of threat is learned. Our results demonstrate that degree of threat corresponds to neural activity in the auditory areas and that threat can be conveyed by different species signals and that these signals must be learned.

Neural Correlates of Threat Perception: Neural Equivalence of Conspecific and Heterospecific Mobbing Calls Is Learned

Science.gov (United States)

Avey, Marc T.; Hoeschele, Marisa; Moscicki, Michele K.; Bloomfield, Laurie L.; Sturdy, Christopher B.

2011-01-01

Songbird auditory areas (i.e., CMM and NCM) are preferentially activated to playback of conspecific vocalizations relative to heterospecific and arbitrary noise [1]–[2]. Here, we asked if the neural response to auditory stimulation is not simply preferential for conspecific vocalizations but also for the information conveyed by the vocalization. Black-capped chickadees use their chick-a-dee mobbing call to recruit conspecifics and other avian species to mob perched predators [3]. Mobbing calls produced in response to smaller, higher-threat predators contain more “D” notes compared to those produced in response to larger, lower-threat predators and thus convey the degree of threat of predators [4]. We specifically asked whether the neural response varies with the degree of threat conveyed by the mobbing calls of chickadees and whether the neural response is the same for actual predator calls that correspond to the degree of threat of the chickadee mobbing calls. Our results demonstrate that, as degree of threat increases in conspecific chickadee mobbing calls, there is a corresponding increase in immediate early gene (IEG) expression in telencephalic auditory areas. We also demonstrate that as the degree of threat increases for the heterospecific predator, there is a corresponding increase in IEG expression in the auditory areas. Furthermore, there was no significant difference in the amount IEG expression between conspecific mobbing calls or heterospecific predator calls that were the same degree of threat. In a second experiment, using hand-reared chickadees without predator experience, we found more IEG expression in response to mobbing calls than corresponding predator calls, indicating that degree of threat is learned. Our results demonstrate that degree of threat corresponds to neural activity in the auditory areas and that threat can be conveyed by different species signals and that these signals must be learned. PMID:21909363

Neural correlates of threat perception: neural equivalence of conspecific and heterospecific mobbing calls is learned.

Science.gov (United States)

Avey, Marc T; Hoeschele, Marisa; Moscicki, Michele K; Bloomfield, Laurie L; Sturdy, Christopher B

2011-01-01

Songbird auditory areas (i.e., CMM and NCM) are preferentially activated to playback of conspecific vocalizations relative to heterospecific and arbitrary noise. Here, we asked if the neural response to auditory stimulation is not simply preferential for conspecific vocalizations but also for the information conveyed by the vocalization. Black-capped chickadees use their chick-a-dee mobbing call to recruit conspecifics and other avian species to mob perched predators. Mobbing calls produced in response to smaller, higher-threat predators contain more "D" notes compared to those produced in response to larger, lower-threat predators and thus convey the degree of threat of predators. We specifically asked whether the neural response varies with the degree of threat conveyed by the mobbing calls of chickadees and whether the neural response is the same for actual predator calls that correspond to the degree of threat of the chickadee mobbing calls. Our results demonstrate that, as degree of threat increases in conspecific chickadee mobbing calls, there is a corresponding increase in immediate early gene (IEG) expression in telencephalic auditory areas. We also demonstrate that as the degree of threat increases for the heterospecific predator, there is a corresponding increase in IEG expression in the auditory areas. Furthermore, there was no significant difference in the amount IEG expression between conspecific mobbing calls or heterospecific predator calls that were the same degree of threat. In a second experiment, using hand-reared chickadees without predator experience, we found more IEG expression in response to mobbing calls than corresponding predator calls, indicating that degree of threat is learned. Our results demonstrate that degree of threat corresponds to neural activity in the auditory areas and that threat can be conveyed by different species signals and that these signals must be learned.

Orchestration in Learning Technology Research: Evaluation of a Conceptual Framework

Science.gov (United States)

Prieto, Luis P.; Dimitriadis, Yannis; Asensio-Pérez, Juan I.; Looi, Chee-Kit

2015-01-01

The term "orchestrating learning" is being used increasingly often, referring to the coordination activities performed while applying learning technologies to authentic settings. However, there is little consensus about how this notion should be conceptualised, and what aspects it entails. In this paper, a conceptual framework for…

Determinants of E-learning Acceptance among Agricultural Extension Agents in Malaysia: A Conceptual Framework

OpenAIRE

Mangir, Safaie; Othman, Zakirah; Udin, Zulkifli Mohamed

2016-01-01

The objective of this paper is to develop a framework on e-learning acceptance among agricultural extension agents in Malaysian agricultural sector. E-learning is viewed as a solution in response to the increasing need for learning and training. This paper will review past literatures for the relevant factors that influence behavioral intention for e-learning acceptance as well as the relevant behavioral theories that provide the foundation for developing research framework to illustrate the ...

A Framework of Metacognitive Scaffolding in Learning Authoring System through Facebook

Science.gov (United States)

Jumaat, Nurul Farhana; Tasir, Zaidatun

2016-01-01

Scaffolding refers to a guidance that helps students during their learning sessions whereby it makes learning easier for them. This study aims to develop a framework of metacognitive scaffolding (MS) to guide students in learning Authoring System through Facebook. Thirty-seven master degree students who were enrolled in Authoring System course…

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

Science.gov (United States)

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Wearable Learning for Healthy Ageing through Creative Learning: A Conceptual Framework in the project “Fitness MOOC” (fMOOC

Directory of Open Access Journals (Sweden)

Ilona Buchem

2015-05-01

Full Text Available Physical activity is one of the key factors of ageing healthy and at the same time one of the key motivational challenges for the elderly. Supporting healthy ageing through physical fitness requires interventions that promote healthy levels of physical activity as part of the daily routine. Although wearable devices, such as activity trackers or smart wristbands, have been used by younger adopters to optimize physical fitness, little is known so far about how such emerging technologies may be used to improve well-being and overall health of senior users. In this paper we present the conceptual framework and the architecture of wearable-technology enhanced learning for healthy ageing as part of an R&D project called “Fitness MOOC - interaction of seniors with wearable fitness trackers in the fitness MOOC (fMOOC”, founded by the German Federal Ministry of Education and Research (BMBF. The fMOOC project is a cooperation between Beuth University of Applied Sciences Berlin and the Geriatrics Research Group, Charité - one of the largest medical universities in Europe. The project aims at developing a wearable-technology enhanced learning solution combining the MOOC (Massive Open Online Course approach with embodied and creative learning experience with support of activity trackers. fMOOC integrates an LMS backend with wearable fitness trackers, mobile user interface, gamification and analytics to promote healthy ageing through learning and interacting with senior users.

An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation

Science.gov (United States)

Zhang, Zhou; Pasolli, Edoardo; Crawford, Melba M.; Tilton, James C.

2015-01-01

Augmenting spectral data with spatial information for image classification has recently gained significant attention, as classification accuracy can often be improved by extracting spatial information from neighboring pixels. In this paper, we propose a new framework in which active learning (AL) and hierarchical segmentation (HSeg) are combined for spectral-spatial classification of hyperspectral images. The spatial information is extracted from a best segmentation obtained by pruning the HSeg tree using a new supervised strategy. The best segmentation is updated at each iteration of the AL process, thus taking advantage of informative labeled samples provided by the user. The proposed strategy incorporates spatial information in two ways: 1) concatenating the extracted spatial features and the original spectral features into a stacked vector and 2) extending the training set using a self-learning-based semi-supervised learning (SSL) approach. Finally, the two strategies are combined within an AL framework. The proposed framework is validated with two benchmark hyperspectral datasets. Higher classification accuracies are obtained by the proposed framework with respect to five other state-of-the-art spectral-spatial classification approaches. Moreover, the effectiveness of the proposed pruning strategy is also demonstrated relative to the approaches based on a fixed segmentation.

Continuing professional development for teachers in South Africa and social learning systems: conflicting conceptual frameworks of learning

Directory of Open Access Journals (Sweden)

G.M. Steyn

2008-07-01

Full Text Available To transform education in this country, South African teachers need to be appropriately equipped to meet the evolving challenges and needs of the country. The national policy framework for teacher education and development is an attempt to address the need for suitably qualified teachers in South Africa. Its aim is to improve the quality of education by focusing on the professional development of teachers. This article attempts to address the following research problem: Does continuing professional development for teachers (CPDT, as stipulated by the national policy framework, have the potential to contribute to the development of teachers as proposed by social learning systems? The answer to this question has the potential to inform and influence the policy and its implementation. The answer also describes how conceptual frameworks for learning in Wenger’s social learning systems conflict with effective professional development (PD programmes and CPDT.

Quality in e-learning:A framework for promoting and assuring quality in virtual institutions

OpenAIRE

Masoumi, Davoud; Lindstrom, Berner

2012-01-01

With the growing demand for e-learning along with striving for excellence associated with globalization, there are worldwide calls for enhancing and assuring quality in e-learning, specifically in the context of the developing countries. Such calls for quality enhancement, accountability, added value, value for money, self-evaluation, and role players’ satisfaction in higher education settings cannot go unheeded. Addressing the concerns regarding enhancing and assuring quality in e-learning, ...

A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

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Karim El-Laithy

2011-01-01

Full Text Available An integration of both the Hebbian-based and reinforcement learning (RL rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.

A framework for technological learning in the supply chain: A case study on CdTe photovoltaics

International Nuclear Information System (INIS)

Bergesen, Joseph D.; Suh, Sangwon

2016-01-01

Highlights: • A framework for technological learning in the supply chain is proposed. • This framework separates learning effects on value added and intermediate inputs. • Supply-chain learning can project both changing environmental impacts and costs. • Learning upstream in the supply chain can influence observed learning rates. • An example for CdTe photovoltaics illustrates how this framework can be implemented. - Abstract: Accounting for technological changes and innovation is important when assessing the implications of rapidly-developing greenhouse gas (GHG) mitigation technologies. Technological learning curves have been commonly used as a tool to understand technological change as a function of cumulative production. Traditional learning curve approaches, however, do not distinguish the direct and upstream, supply chain technological changes by which cost reductions are achieved. While recent advances in learning curves have focused on distinguishing the different physical and economic drivers of learning, forecasted technological changes have not been applied to estimate the potential changes in the environmental performance of a technology. This article illustrates how distinguishing the different effects of technological learning throughout the supply chain can help assess the changing costs, environmental impacts and natural resource implications of technologies as they develop. We propose a mathematical framework to distinguish the effects of learning on the direct inputs to a technology from the effects of learning on value added, and we incorporate those effects throughout the supply chain of a technology using a life cycle assessment (LCA) framework. An example for cadmium telluride (CdTe) photovoltaics (PV) illustrates how the proposed framework can be implemented. Results show that that life cycle GHG emissions can decrease at least 40% and costs can decrease at least 50% as cumulative production of CdTe reaches 100 GW. Technological

Conceptualizing Debates in Learning and Educational Research: Toward a Complex Systems Conceptual Framework of Learning

Science.gov (United States)

Jacobson, Michael J.; Kapur, Manu; Reimann, Peter

2016-01-01

This article proposes a conceptual framework of learning based on perspectives and methodologies being employed in the study of complex physical and social systems to inform educational research. We argue that the contexts in which learning occurs are complex systems with elements or agents at different levels--including neuronal, cognitive,…

A Multimodal Interaction Framework for Blended Learning

DEFF Research Database (Denmark)

Vidakis, Nikolaos; Kalafatis, Konstantinos; Triantafyllidis, Georgios

2016-01-01

Humans interact with each other by utilizing the five basic senses as input modalities, whereas sounds, gestures, facial expressions etc. are utilized as output modalities. Multimodal interaction is also used between humans and their surrounding environment, although enhanced with further senses ...... framework enabling deployment of a vast variety of modalities, tailored appropriately for use in blended learning environment....

Quality in E-Learning: A Framework for Promoting and Assuring Quality in Virtual Institutions

Science.gov (United States)

Masoumi, D.; Lindstrom, B.

2012-01-01

With the growing demand for e-learning along with striving for excellence associated with globalization, there are worldwide calls for enhancing and assuring quality in e-learning, specifically in the context of the developing countries. Such calls for quality enhancement, accountability, added value, value for money, self-evaluation, and role…

Designing for Learning and Play - The Smiley Model as Framework

DEFF Research Database (Denmark)

Weitze, Charlotte Lærke

2016-01-01

digital games. The Smiley Model inspired and provided a scaffold or a heuristic for the overall gamified learning design –- as well as for the students’ learning game design processes when creating small games turning the learning situation into an engaging experience. The audience for the experiments......This paper presents a framework for designing engaging learning experiences in games – the Smiley Model. In this Design-Based Research project, student-game-designers were learning inside a gamified learning design - while designing and implementing learning goals from curriculum into the small...... was adult upper secondary general students as well as 7th grade primary school students. The intention with this article is to inspire future learning designers that would like to experiment with integrating learning and play....

A systemic framework for managing e-learning adoption in campus universities: individual strategies in context

Directory of Open Access Journals (Sweden)

Carol Russell

2009-12-01

Full Text Available There are hopes that new learning technologies will help to transform university learning and teaching into a more engaging experience for twenty-first-century students. But since 2000 the changes in campus university teaching have been more limited than expected. I have drawn on ideas from organisational change management research to investigate why this is happening in one particular campus university context. My study examines the strategies of individual lecturers for adopting e-learning within their disciplinary, departmental and university work environments to develop a conceptual framework for analysing university learning and teaching as a complex adaptive system. This conceptual framework links the processes through which university teaching changes, the resulting forms of learning activity and the learning technologies used – all within the organisational context of the university. The framework suggests that systemic transformation of a university's learning and teaching requires coordinated change across activities that have traditionally been managed separately in campus universities. Without such coordination, established ways of organising learning and teaching will reassert themselves, as support staff and lecturers seek to optimise their own work locally. The conceptual framework could inform strategies for realising the full benefits of new learning technologies in other campus universities.

Expanding the Frontiers of National Qualifications Frameworks through Lifelong Learning

Science.gov (United States)

Owusu-Agyeman, Yaw

2017-01-01

The adoption of a national qualifications framework (NQF) by some governments in all world regions has shown some success in the area of formal learning. However, while NQFs continue to enhance "formal" learning in many countries, the same cannot be said for the recognition, validation and accreditation (RVA) of "non-formal"…

SQL Collaborative Learning Framework Based on SOA

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Armiati, S.; Awangga, RM

2018-04-01

The research is focused on designing collaborative learning-oriented framework fulfilment service in teaching SQL Oracle 10g. Framework built a foundation of academic fulfilment service performed by a layer of the working unit in collaboration with Program Studi Manajemen Informatika. In the design phase defined what form of collaboration models and information technology proposed for Program Studi Manajemen Informatika by using a framework of collaboration inspired by the stages of modelling a Service Oriented Architecture (SOA). Stages begin with analyzing subsystems, this activity is used to determine subsystem involved and reliance as well as workflow between the subsystems. After the service can be identified, the second phase is designing the component specifications, which details the components that are implemented in the service to include the data, rules, services, profiles can be configured, and variations. The third stage is to allocate service, set the service to the subsystems that have been identified, and its components. Implementation framework contributes to the teaching guides and application architecture that can be used as a landing realize an increase in service by applying information technology.

Decision support frameworks and tools for conservation

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Schwartz, Mark W.; Cook, Carly N.; Pressey, Robert L.; Pullin, Andrew S.; Runge, Michael C.; Salafsky, Nick; Sutherland, William J.; Williamson, Matthew A.

2018-01-01

The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.

From Computer Assisted Language Learning (CALL) to Mobile Assisted Language Use (MALU)

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Jarvis, Huw; Achilleos, Marianna

2013-01-01

This article begins by critiquing the long-established acronym CALL (Computer Assisted Language Learning). We then go on to report on a small-scale study which examines how student non-native speakers of English use a range of digital devices beyond the classroom in both their first (L1) and second (L2) languages. We look also at the extent to…

A leadership framework to support the use of e-learning resources.

Science.gov (United States)

McCutcheon, Karen

2014-06-01

Recognition needs to be given to emerging postgraduate nursing students' status of 'consumer', and the challenge for nurse education is to remain relevant and competitive in a consumer-led market. An e-learning model has been suggested as a competitive and contemporary way forward for student consumers, but successful introduction of this requires leadership and strong organisational management systems. This article applies the NHS leadership framework to nurse education in relation to implementation of e-learning and describes and interprets each element for application in higher education settings. By applying a leadership framework that acknowledges the skills and abilities of staff and encourages the formation of collaborative partnerships in the wider university community, educators can begin to develop skills and confidence in teaching using e-learning resources.

Call cultures in orang-utans?

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Serge A Wich

Full Text Available BACKGROUND: Several studies suggested great ape cultures, arguing that human cumulative culture presumably evolved from such a foundation. These focused on conspicuous behaviours, and showed rich geographic variation, which could not be attributed to known ecological or genetic differences. Although geographic variation within call types (accents has previously been reported for orang-utans and other primate species, we examine geographic variation in the presence/absence of discrete call types (dialects. Because orang-utans have been shown to have geographic variation that is not completely explicable by genetic or ecological factors we hypothesized that this will be similar in the call domain and predict that discrete call type variation between populations will be found. METHODOLOGY/PRINCIPAL FINDINGS: We examined long-term behavioural data from five orang-utan populations and collected fecal samples for genetic analyses. We show that there is geographic variation in the presence of discrete types of calls. In exactly the same behavioural context (nest building and infant retrieval, individuals in different wild populations customarily emit either qualitatively different calls or calls in some but not in others. By comparing patterns in call-type and genetic similarity, we suggest that the observed variation is not likely to be explained by genetic or ecological differences. CONCLUSION/SIGNIFICANCE: These results are consistent with the potential presence of 'call cultures' and suggest that wild orang-utans possess the ability to invent arbitrary calls, which spread through social learning. These findings differ substantially from those that have been reported for primates before. First, the results reported here are on dialect and not on accent. Second, this study presents cases of production learning whereas most primate studies on vocal learning were cases of contextual learning. We conclude with speculating on how these findings might

Pembuatan Kakas Pendeteksi Unused Method pada Kode Program PHP dengan Framework CodeIgniter Menggunakan Call Graph

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Divi Galih Prasetyo Putri

2014-03-01

Full Text Available Proses evolusi dan perawatan dari sebuah sistem merupakan proses yang sangat penting dalam rekayasa perangkat lunak tidak terkecuali pada aplikasi web. Pada proses ini kebanyakan pengembang tidak lagi berpatokan pada rancangan sistem. Hal ini menyebabkan munculnya unused method. Bagian-bagian program ini tidak lagi terpakai namun masih berada dalam sistem. Keadaan ini meningkatkan kompleksitas dan mengurangi tingkat understandability sistem. Guna mendeteksi adanya unused method pada progam diperlukan teknik untuk melakukan code analysis. Teknik static analysis yang digunakan memanfaatkan call graph yang dibangun dari kode program untuk mengetahui adanya unused method. Call graph dibangun berdasarkan pemanggilan antar method. Aplikasi ini mendeteksi unused method pada kode program PHP yang dibangun menggunakan framework CodeIgniter. Kode program sebagai inputan diurai kedalam bentuk Abstract Syntax Tree (AST yang kemudian dimanfaatkan untuk melakukan analisis terhadap kode program. Proses analisis tersebut kemudian menghasilkan sebuah call graph. Dari call graph yang dihasilkan dapat dideteksi method-method mana saja yang tidak berhasil ditelusuri dan tergolong kedalam unused method. Kakas telah diuji coba pada 5 aplikasi PHP dengan hasil  rata-rata nilai presisi sistem sebesar 0.749 dan recall sebesar 1.

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

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Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

Evaluating QR Code Case Studies Using a Mobile Learning Framework

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Rikala, Jenni

2014-01-01

The aim of this study was to evaluate the feasibility of Quick Response (QR) codes and mobile devices in the context of Finnish basic education. The feasibility was analyzed through a mobile learning framework, which includes the core characteristics of mobile learning. The study is part of a larger research where the aim is to develop a…

Teachers' Knowing How to Use Technology: Exploring a Conceptual Framework for Purposeful Learning Activity

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Fisher, Tony; Denning, Tim; Higgins, Chris; Loveless, Avril

2012-01-01

This article describes a project to apply and validate a conceptual framework of clusters of purposeful learning activity involving ICT tools. The framework, which is based in a socio-cultural perspective, is described as "DECK", and comprises the following major categories of the use of digital technologies to support learning:…

A Conceptual Framework for Web-Based Learning Design

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Alomyan, Hesham

2017-01-01

The purpose of this paper is to provide a coherent framework to present the relationship between individual differences and web-based learning. Two individual difference factors have been identified for investigation within the present paper: Cognitive style and prior knowledge. The importance of individual differences is reviewed and previous…

Towards a pedagogical model for science education: bridging educational contexts through a blended learning approach

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Bidarra, José; Rusman, Ellen

2017-01-01

This paper proposes a design framework to support science education through blended learning, based on a participatory and interactive approach supported by ICT-based tools, called Science Learning Activities Model (SLAM). The development of this design framework started as a response to complex

Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

OpenAIRE

Paula Miranda; Pedro Isaias; Carlos J Costa; Sara Pifano

2017-01-01

Aim/Purpose: As e-Learning 3.0 evolves from a theoretical construct into an actual solution for online learning, it becomes crucial to accompany this progress by scrutinising the elements that are at the origin of its success. Background: This paper outlines a framework of e-Learning 3.0’s critical success factors and its empirical validation. Methodology: The framework is the result of an extensive literature review and its empirical substantiation derives from semi-structured inte...

A Framework for Developing Self-Directed Technology Use for Language Learning

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Lai, Chun

2013-01-01

Critical to maximizing the potential of technology for learning is enhancing language learners' self-directed use of technology for learning purposes. This study aimed to enhance our understanding of the determinants of self-directed technology use through the construction of a structural equation modelling (SEM) framework of factors and…

Social Support System in Learning Network for lifelong learners: A Conceptual framework

NARCIS (Netherlands)

Nadeem, Danish; Stoyanov, Slavi; Koper, Rob

2009-01-01

Nadeem, D., Stoyanov, S., & Koper, R. (2009). Social support system in learning network for lifelong learners: A Conceptual framework [Special issue]. International Journal of Continuing Engineering Education and Life-Long Learning, 19(4/5/6), 337-351.

‘Living' theory: a pedagogical framework for process support in networked learning

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Philipa Levy

2006-12-01

Full Text Available This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the action research methodology. It then identifies key dimensions of four interconnected developmental processes–orientation, communication, socialisation and organisation–that were associated with ‘learning to learn' in the course's networked environment, and offers a flavour of participants' experiences in relation to these processes. A number of key evaluation issues that arose are highlighted. Finally, the paper presents the broad conceptual framework for the design and facilitation of process support in networked learning that was derived from this research. The framework proposes a strong, explicit focus on support for process as well as domain learning, and progression from tighter to looser design and facilitation structures for process-focused (as well as domain-focused learning tasks.

A conceptual framework for international service-learning course planning: promoting a foundation for ethical practice in the physical therapy and occupational therapy professions.

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Lattanzi, Jill Black; Pechak, Celia

2011-01-01

As physical therapy (PT) and occupational therapy (OT) educational programs endeavor to foster core values of social responsibility, justice, and altruism in an increasingly global community, the incorporation of local and international service-learning (ISL) into the curriculum is growing. Much of the research has focused on the measurement of student learning, with little written about the impact on the host community. Proponents of global health initiatives are calling for consideration of all stakeholders to ensure ethical practice. This paper explores the current literature related to PT and OT ISL and builds a conceptual framework for ISL course planning. The essential phases in the framework include: 1) pre-experience planning/preparation stage, 2) field immersion experience stage, and 3) postexperience stage. The essential elements are: 1) cultural competency training, 2) communication and coordination with community, 3) comprehensive assessment, and 4) strategic planning. The authors suggest this framework as a practical tool to structure ISL courses with an explicit emphasis on ethical concerns. Additionally, they seek to foster more dialogue and action related to the promotion of ethical practices in ISL in PT and OT education programs.

Children Learning to Use Technologies through Play: A Digital Play Framework

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Bird, Jo; Edwards, Susan

2015-01-01

Digital technologies are increasingly acknowledged as an important aspect of early childhood education. A significant problem for early childhood education has been how to understand the pedagogical use of technologies in a sector that values play-based learning. This paper presents a new framework to understand how children learn to use…

Evaluation Framework EFI for Measuring the Impact of Learning, Education and Training

NARCIS (Netherlands)

Stracke, Christian M.

2016-01-01

This article introduces the Evaluation Framework EFI for the Impact Measurement of learning, education and training: The Evaluation Framework for Impact Measurement was developed for specifying the evaluation phase and its objectives and tasks within the IDEAL Reference Model for the introduction

A Framework for Hierarchical Perception-Action Learning Utilizing Fuzzy Reasoning.

Science.gov (United States)

Windridge, David; Felsberg, Michael; Shaukat, Affan

2013-02-01

Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.

An Analysis of Learning Activities in a Technology Education Textbook for Teachers : Learning Process Based on Contents Framework and Learning Scene to Develop Technological Literacy

OpenAIRE

Yata, Chikahiko; Hamamoto, Kengo; Oguri, Takenori

2014-01-01

This study analyzed the learning activities in a textbook on technology education for teachers, in order to examine the learning processes and learning scenes detailed therein. Results of analyzing learning process, primary learning activity found each contents framework. Other learning activities designated to be related to complementary in learning process. Results of analyzing learning scene, 14 learning scenes, among them "Scene to recognize the impact on social life and progress of techn...

A framework for exploring integrated learning systems for the governance and management of public protected areas.

Science.gov (United States)

Nkhata, Bimo Abraham; Breen, Charles

2010-02-01

This article discusses how the concept of integrated learning systems provides a useful means of exploring the functional linkages between the governance and management of public protected areas. It presents a conceptual framework of an integrated learning system that explicitly incorporates learning processes in governance and management subsystems. The framework is premised on the assumption that an understanding of an integrated learning system is essential if we are to successfully promote learning across multiple scales as a fundamental component of adaptability in the governance and management of protected areas. The framework is used to illustrate real-world situations that reflect the nature and substance of the linkages between governance and management. Drawing on lessons from North America and Africa, the article demonstrates that the establishment and maintenance of an integrated learning system take place in a complex context which links elements of governance learning and management learning subsystems. The degree to which the two subsystems are coupled influences the performance of an integrated learning system and ultimately adaptability. Such performance is largely determined by how integrated learning processes allow for the systematic testing of societal assumptions (beliefs, values, and public interest) to enable society and protected area agencies to adapt and learn in the face of social and ecological change. It is argued that an integrated perspective provides a potentially useful framework for explaining and improving shared understanding around which the concept of adaptability is structured and implemented.

A Framework for Re-thinking Learning in Science from Recent Cognitive Science Perspectives

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Tytler, Russell; Prain, Vaughan

2010-10-01

Recent accounts by cognitive scientists of factors affecting cognition imply the need to reconsider current dominant conceptual theories about science learning. These new accounts emphasize the role of context, embodied practices, and narrative-based representation rather than learners' cognitive constructs. In this paper we analyse data from a longitudinal study of primary school children's learning to outline a framework based on these contemporary accounts and to delineate key points of difference from conceptual change perspectives. The findings suggest this framework provides strong theoretical and practical insights into how children learn and the key role of representational negotiation in this learning. We argue that the nature and process of conceptual change can be re-interpreted in terms of the development of students' representational resources.

Collaborative learning framework for online stakeholder engagement.

Science.gov (United States)

Khodyakov, Dmitry; Savitsky, Terrance D; Dalal, Siddhartha

2016-08-01

Public and stakeholder engagement can improve the quality of both research and policy decision making. However, such engagement poses significant methodological challenges in terms of collecting and analysing input from large, diverse groups. To explain how online approaches can facilitate iterative stakeholder engagement, to describe how input from large and diverse stakeholder groups can be analysed and to propose a collaborative learning framework (CLF) to interpret stakeholder engagement results. We use 'A National Conversation on Reducing the Burden of Suicide in the United States' as a case study of online stakeholder engagement and employ a Bayesian data modelling approach to develop a CLF. Our data modelling results identified six distinct stakeholder clusters that varied in the degree of individual articulation and group agreement and exhibited one of the three learning styles: learning towards consensus, learning by contrast and groupthink. Learning by contrast was the most common, or dominant, learning style in this study. Study results were used to develop a CLF, which helps explore multitude of stakeholder perspectives; identifies clusters of participants with similar shifts in beliefs; offers an empirically derived indicator of engagement quality; and helps determine the dominant learning style. The ability to detect learning by contrast helps illustrate differences in stakeholder perspectives, which may help policymakers, including Patient-Centered Outcomes Research Institute, make better decisions by soliciting and incorporating input from patients, caregivers, health-care providers and researchers. Study results have important implications for soliciting and incorporating input from stakeholders with different interests and perspectives. © 2015 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

A pedagogical design pattern framework for sharing experiences and enhancing communities of practice within online and blended learning

DEFF Research Database (Denmark)

May, Michael; Neutszky-Wulff, Chresteria; Rosthøj, Susanne

2016-01-01

for teachers at the University of Copenhagen a new and simpler pedagogical design pattern framework was developed for interfaculty sharing of experiences and enhancing communities of practice in relation to online and blended learning across the university. The framework of pedagogical design patterns were...... applied to describe the learning design in four online and blended learning courses within different academic disciplines: Classical Greek, Biostatistics, Environmental Management in Europe, and Climate Change Impacts, Adaptation and Mitigation. Future perspectives for using the framework for developing...... new E-learning patterns for online and blended learning courses are discussed....

A Learning and Interaction design framework, from a study on formulating principles for the design of engaging music learning games

DEFF Research Database (Denmark)

Weitze, Charlotte Lærke; Ørngreen, Rikke

2012-01-01

Based on a preliminary action research study investigating the design of digital music games and years of experiences from interaction design processes of learning resources, this extended abstract presents a framework that mixes designs for learning principles and game design with a process view...... using a simple interaction design lifecycle. Though the first outset was to design engaging music games, the resulting framework has a more generic character....

Formal Learning Sequences and Progression in the Studio: A Framework for Digital Design Education

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Pontus Wärnestål

2016-02-01

Full Text Available This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the digital space. We present a framework derived from literature on design, creativity, and theories on learning that: (a implements a theory of formal learning sequences as a user-centered design process in the studio; and (b describes design challenge progressions in the design studio environment modeled in seven dimensions. The framework can be used as a tool for designing, evaluating, and communicating course progressions within – and between series of – design studio courses. This approach is evaluated by implementing a formal learning sequence framework in a series of design studio courses that progress in an undergraduate design-oriented Informatics program. Reflections from students, teachers, and external clients indicate high student motivation and learning goal achievement, high teacher satisfaction and skill development, and high satisfaction among external clients.

PENGARUH PERMAINAN CALL CARDS TERHADAP HASIL BELAJAR DAN AKTIVITAS PEMBELAJARAN BIOLOGI

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A. Machin

2012-10-01

Full Text Available Tujuan penelitian untuk mengetahui pengaruh permainan call cards terhadap hasil belajar dan aktivitas pembelajaran. Aktivitas pembelajaran yang diukur meliputi aktivitas individual siswa dan kinerja guru. Penelitian ini merupakan penelitian eksperimental. Hasil penelitian menunjukkan bahwa media permainan call cards berkontribusi sebesar 46% terhadap hasil belajar siswa. Hasil belajar siswa yang diberi media permainan call cards lebih baik daripada hasil belajar siswa yang tidak diberi mediapermainan call cards. Dengan demikian, media permainan call cards dapat menjadi alternatif dalam pencapaian hasil belajar biologi yang lebih baik.   Research purposes to determine the effect of call cards game against learning outcomes and learning activities. Learning activities that were measured included the activity of individual student and teacher performance. This research was experimental. The results showed that the media play call cards account for 46% of the student learning outcomes. Learning outcomes of students who were given media cards call the game better than the learning outcomes of students who were not given mediapermainan call cards. Thus, the media play call cards can be an alternative in achieving the learning outcomes of biology better.

A Design Framework for Enhancing Engagement in Student-Centered Learning: Own It, Learn It, and Share It

Science.gov (United States)

Lee, Eunbae; Hannafin, Michael J.

2016-01-01

Student-centered learning (SCL) identifies students as the owners of their learning. While SCL is increasingly discussed in K-12 and higher education, researchers and practitioners lack current and comprehensive framework to design, develop, and implement SCL. We examine the implications of theory and research-based evidence to inform those who…

A blended learning framework for curriculum design and professional development

Directory of Open Access Journals (Sweden)

Negin Mirriahi

2015-10-01

Full Text Available The need for flexibility in learning and the affordances of technology provided the impetus for the rise of blended learning (BL globally across higher education institutions. However, the adoption of BL practices continues at a low pace due to academics’ low digital fluency, various views and BL definitions, and limited standards-based tools to guide academic practice. To address these issues, this paper introduces a BL framework, based on one definition and with criteria and standards of practice to support the evaluation and advancement of BL in higher education. The framework is theoretically underpinned by the extant literature and supported by focus group discussions. The evidence supporting the criteria and standards are discussed with suggestions for how they can be used to guide course design, academic practice, and professional development.

Latin American Investigative Journalism Education: Learning Practices, Learning Gaps

Science.gov (United States)

Schmitz Weiss, Amy; de Macedo Higgins Joyce, Vanessa; Saldaña, Magdalena; Alves, Rosental Calmon

2017-01-01

This study seeks to examine the state of investigative journalism practices used in higher education in Latin America. Using a meta-theoretical framework called the Community of Practice (CoP), this study seeks to identify whether a particular learning practice exists in this region. Based on an online survey conducted on Latin American educators…

CULTURE, CULTURE LEARNING AND NEW TECHNOLOGIES: TOWARDS A PEDAGOGICAL FRAMEWORK

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Mike Levy

2007-02-01

Full Text Available This paper seeks to improve approaches to the learning and teaching of culture using new technologies by relating the key qualities and dimensions of the culture concept to elements within a pedagogical framework. In Part One, five facets of the culture concept are developed: culture as elemental; culture as relative; culture as group membership; culture as contested; and culture as individual (variable and multiple. Each perspective aims to provide a focus for thinking about culture, and thereby to provide a valid and useful point of departure for thinking about the practice of culture learning and teaching with new technologies. The referenced literature draws from a broad range of disciplines and definitions of culture. In Part Two, five projects are chosen to represent relevant technologies currently in use for culture learning: e-mail, chat, a discussion forum and a Web-based project. Each project is used to illustrate facets of the culture concept discussed in Part One with a view to identifying key elements within a pedagogical framework that can help us respond effectively to the challenge of culture learning and teaching utilising new technologies. Thus the goal is to align fundamental qualities of the culture concept with specific pedagogical designs, tasks and technologies.

A Pedagogical Model for Science Education through Blended Learning

NARCIS (Netherlands)

Bidarra, José; Rusman, Ellen

2015-01-01

This paper proposes a framework to support science education through blended learning, based on a participatory and interactive approach supported by ICT-based tools, called Science Learning Activities Model (SLAM). The study constitutes a work in progress and started as a response to complex

Video copy protection and detection framework (VPD) for e-learning systems

Science.gov (United States)

ZandI, Babak; Doustarmoghaddam, Danial; Pour, Mahsa R.

2013-03-01

This Article reviews and compares the copyright issues related to the digital video files, which can be categorized as contended based and Digital watermarking copy Detection. Then we describe how to protect a digital video by using a special Video data hiding method and algorithm. We also discuss how to detect the copy right of the file, Based on expounding Direction of the technology of the video copy detection, and Combining with the own research results, brings forward a new video protection and copy detection approach in terms of plagiarism and e-learning systems using the video data hiding technology. Finally we introduce a framework for Video protection and detection in e-learning systems (VPD Framework).

A reference model and technical framework for mobile social software for learning

NARCIS (Netherlands)

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

2008-01-01

De Jong,T., Specht, M., & Koper, R. (2008). A reference model and technical framework for mobile social software for learning. In I. A. Sánchez & P. Isaías (Eds.), Proceedings of the IADIS Mobile Learning Conference 2008 (pp. 206-210). April, 11-13, 2008, Carvoeiro, Portugal.

A Pedagogical Framework for Mobile Learning: Categorizing Educational Applications of Mobile Technologies into Four Types

Directory of Open Access Journals (Sweden)

Yeonjeong Park

2011-02-01

Full Text Available Instructional designers and educators recognize the potential of mobile technologies as a learning tool for students and have incorporated them into the distance learning environment. However, little research has been done to categorize the numerous examples of mobile learning in the context of distance education, and few instructional design guidelines based on a solid theoretical framework for mobile learning exist. In this paper I compare mobile learning (m-learning with electronic learning (e-learning and ubiquitous learning (u-learning and describe the technological attributes and pedagogical affordances of mobile learning presented in previous studies. I modify transactional distance (TD theory and adopt it as a relevant theoretical framework for mobile learning in distance education. Furthermore, I attempt to position previous studies into four types of mobile learning: 1 high transactional distance socialized m-learning, 2 high transactional distance individualized m-learning, 3 low transactional distance socialized m-learning, and 4 low transactional distance individualized m-learning. As a result, this paper can be used by instructional designers of open and distance learning to learn about the concepts of mobile learning and how mobile technologies can be incorporated into their teaching and learning more effectively.

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 ...

Framework for the Development of OER-Based Learning Materials in ODL Environment

Science.gov (United States)

Teng, Khor Ean; Hung, Chung Sheng

2013-01-01

This paper describes the framework for the development of OER-based learning materials "TCC121/05 Programming Fundamentals with Java" for ODL learners in Wawasan Open University (WOU) using three main development phases mainly: creation, evaluation and production phases. The proposed framework has further been tested on ODL learners to…

A pedagogical design pattern framework for sharing experiences and enhancing communities of practice within online and blended learning

Directory of Open Access Journals (Sweden)

Chresteria Neutszky-Wulff

2016-12-01

Full Text Available ”Design patterns” were originally proposed in architecture and later in software engineering as a methodology to sketch and share solutions to recurring design problems. In recent years ”pedagogical design patterns” have been introduced as a way to sketch and share good practices in teaching and learning; specifically in the context of technology-enhanced learning (e-learning. Several attempts have been made to establish a framework for describing and sharing such e-learning patterns, but so far they have had limited success. At a series of workshops in a competence-development project for teachers at the University of Copenhagen a new and simpler pedagogical design pattern framework was developed for interfaculty sharing of experiences and enhancing communities of practice in relation to online and blended learning across the university. In this study, the new pedagogical design pattern framework is applied to describe the learning design in four online and blended learning courses within different academic disciplines: Classical Greek, Biostatistics, Environmental Management in Europe, and Climate Change Impacts, Adaptation and Mitigation. Future perspectives for using the framework for developing new E-learning patterns for online and blended learning courses are discussed.

Learning in Physics by Doing Laboratory Work: Towards a New Conceptual Framework

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Danielsson, Anna Teresia; Linder, Cedric

2009-01-01

Drawing on a study that explores university students' experiences of doing laboratory work in physics, this article outlines a proposed conceptual framework for extending the exploration of the gendered experience of learning. In this framework situated cognition and post-structural gender theory are merged together. By drawing on data that aim at…

Prototype-based models in machine learning.

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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.

Developing an effective corrective action process : lessons learned from operating a confidential close call reporting system

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2013-03-05

In 2007, the Federal Railroad Administration (FRA) launched : C3RS, the Confidential Close Call Reporting System, as a : demonstration project to learn how to facilitate the effective : reporting and implementation of corrective actions, and assess t...

The Belem Framework for Action: Harnessing the Power and Potential of Adult Learning and Education for a Viable Future

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Adult Learning, 2012

2012-01-01

This article presents the Belem Framework for Action. This framework focuses on harnessing the power and potential of adult learning and education for a viable future. This framework begins with a preamble on adult education and towards lifelong learning.

Developing an Evaluation Framework of Quality Indicators for Learning Analytics

NARCIS (Netherlands)

Scheffel, Maren; Drachsler, Hendrik; Specht, Marcus

2017-01-01

This paper presents results from the continuous process of developing an evaluation framework of quality indicators for learning analytics (LA). Building on a previous study, a group concept mapping approach that uses multidimensional scaling and hierarchical clustering, the study presented here

A New Framework for Massive Open Online Courses (MOOCs)

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Schoenack, Lindsie

2013-01-01

The challenges that massive open online courses (MOOCs) bring to the learning arena spur adult educators to improve delivery. A framework for a new type of MOOC is presented to address some of the challenges presented by earlier models. This new MOOC, called a mesoMOOC, can bridge several challenges that hinder current effective delivery of MOOCs…

Mapping of Supply Chain Learning: A Framework for SMEs

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Thakkar, Jitesh; Kanda, Arun; Deshmukh, S. G.

2011-01-01

Purpose: The aim of this paper is to propose a mapping framework for evaluating supply chain learning potential for the context of small- to medium-sized enterprises (SMEs). Design/methodology/approach: The extracts of recently completed case based research for ten manufacturing SME units and facts reported in the previous research are utilized…

An Experience-Based Learning Framework: Activities for the Initial Development of Sustainability Competencies

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Caniglia, Guido; John, Beatrice; Kohler, Martin; Bellina, Leonie; Wiek, Arnim; Rojas, Christopher; Laubichler, Manfred D.; Lang, Daniel

2016-01-01

Purpose: This paper aims to present an experience-based learning framework that provides a bottom-up, student-centered entrance point for the development of systems thinking, normative and collaborative competencies in sustainability. Design/methodology/approach: The framework combines mental mapping with exploratory walking. It interweaves…

Architectural Design and the Learning Environment: A Framework for School Design Research

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Gislason, Neil

2010-01-01

This article develops a theoretical framework for studying how instructional space, teaching and learning are related in practice. It is argued that a school's physical design can contribute to the quality of the learning environment, but several non-architectural factors also determine how well a given facility serves as a setting for teaching…

A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing.

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van den Akker, Jeroen; Mishne, Gilad; Zimmer, Anjali D; Zhou, Alicia Y

2018-04-17

Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. With recent advances in NGS technology and software tools, the majority of variants called using NGS alone are in fact accurate and reliable. However, a small subset of difficult-to-call variants that still do require orthogonal confirmation exist. For this reason, many clinical laboratories confirm NGS results using orthogonal technologies such as Sanger sequencing. Here, we report the development of a deterministic machine-learning-based model to differentiate between these two types of variant calls: those that do not require confirmation using an orthogonal technology (high confidence), and those that require additional quality testing (low confidence). This approach allows reliable NGS-based calling in a clinical setting by identifying the few important variant calls that require orthogonal confirmation. We developed and tested the model using a set of 7179 variants identified by a targeted NGS panel and re-tested by Sanger sequencing. The model incorporated several signals of sequence characteristics and call quality to determine if a variant was identified at high or low confidence. The model was tuned to eliminate false positives, defined as variants that were called by NGS but not confirmed by Sanger sequencing. The model achieved very high accuracy: 99.4% (95% confidence interval: +/- 0.03%). It categorized 92.2% (6622/7179) of the variants as high confidence, and 100% of these were confirmed to be present by Sanger sequencing. Among the variants that were categorized as low confidence, defined as NGS calls of low quality that are likely to be artifacts, 92.1% (513/557) were found to be not present by Sanger sequencing. This work shows that NGS data contains sufficient characteristics for a machine-learning-based model to

PEDLA: predicting enhancers with a deep learning-based algorithmic framework.

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Liu, Feng; Li, Hao; Ren, Chao; Bo, Xiaochen; Shu, Wenjie

2016-06-22

Transcriptional enhancers are non-coding segments of DNA that play a central role in the spatiotemporal regulation of gene expression programs. However, systematically and precisely predicting enhancers remain a major challenge. Although existing methods have achieved some success in enhancer prediction, they still suffer from many issues. We developed a deep learning-based algorithmic framework named PEDLA (https://github.com/wenjiegroup/PEDLA), which can directly learn an enhancer predictor from massively heterogeneous data and generalize in ways that are mostly consistent across various cell types/tissues. We first trained PEDLA with 1,114-dimensional heterogeneous features in H1 cells, and demonstrated that PEDLA framework integrates diverse heterogeneous features and gives state-of-the-art performance relative to five existing methods for enhancer prediction. We further extended PEDLA to iteratively learn from 22 training cell types/tissues. Our results showed that PEDLA manifested superior performance consistency in both training and independent test sets. On average, PEDLA achieved 95.0% accuracy and a 96.8% geometric mean (GM) of sensitivity and specificity across 22 training cell types/tissues, as well as 95.7% accuracy and a 96.8% GM across 20 independent test cell types/tissues. Together, our work illustrates the power of harnessing state-of-the-art deep learning techniques to consistently identify regulatory elements at a genome-wide scale from massively heterogeneous data across diverse cell types/tissues.

The Differences across Distributed Leadership Practices by School Position According to the Comprehensive Assessment of Leadership for Learning (CALL)

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Blitz, Mark H.; Modeste, Marsha

2015-01-01

The Comprehensive Assessment of Leadership for Learning (CALL) is a multi-source assessment of distributed instructional leadership. As part of the validation of CALL, researchers examined differences between teacher and leader ratings in assessing distributed leadership practices. The authors utilized a t-test for equality of means for the…

Selectivity in associative learning: A cognitive stage framework for blocking and cue competition phenomena

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Yannick eBoddez

2014-11-01

Full Text Available Blocking is the most important phenomenon in the history of associative learning theory: For over 40 years, blocking has inspired a whole generation of learning models. Blocking is part of a family of effects that are typically termed cue competition effects. Common amongst all cue competition effects is that a cue-outcome relation is poorly learned or poorly expressed because the cue is trained in the presence of an alternative predictor or cause of the outcome. We provide an overview of the cognitive processes involved in cue competition effects in humans and propose a stage framework that brings these processes together. The framework contends that the behavioral display of cue competition is cognitively construed following three stages that include (1 an encoding stage, (2 a retention stage, and (3 a performance stage. We argue that the stage framework supports a comprehensive understanding of cue competition effects.

Framework for e-learning assessment in dental education: a global model for the future.

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Arevalo, Carolina R; Bayne, Stephen C; Beeley, Josie A; Brayshaw, Christine J; Cox, Margaret J; Donaldson, Nora H; Elson, Bruce S; Grayden, Sharon K; Hatzipanagos, Stylianos; Johnson, Lynn A; Reynolds, Patricia A; Schönwetter, Dieter J

2013-05-01

The framework presented in this article demonstrates strategies for a global approach to e-curricula in dental education by considering a collection of outcome assessment tools. By combining the outcomes for overall assessment, a global model for a pilot project that applies e-assessment tools to virtual learning environments (VLE), including haptics, is presented. Assessment strategies from two projects, HapTEL (Haptics in Technology Enhanced Learning) and UDENTE (Universal Dental E-learning), act as case-user studies that have helped develop the proposed global framework. They incorporate additional assessment tools and include evaluations from questionnaires and stakeholders' focus groups. These measure each of the factors affecting the classical teaching/learning theory framework as defined by Entwistle in a standardized manner. A mathematical combinatorial approach is proposed to join these results together as a global assessment. With the use of haptic-based simulation learning, exercises for tooth preparation assessing enamel and dentine were compared to plastic teeth in manikins. Equivalence for student performance for haptic versus traditional preparation methods was established, thus establishing the validity of the haptic solution for performing these exercises. Further data collected from HapTEL are still being analyzed, and pilots are being conducted to validate the proposed test measures. Initial results have been encouraging, but clearly the need persists to develop additional e-assessment methods for new learning domains.

A machine learning-based framework to identify type 2 diabetes through electronic health records.

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Zheng, Tao; Xie, Wei; Xu, Liling; He, Xiaoying; Zhang, Ya; You, Mingrong; Yang, Gong; Chen, You

2017-01-01

To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. We propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014. We apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (∼0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC). Expert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our framework leverages machine learning and feature

Developing a Framework for Social Technologies in Learning via Design-Based Research

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Parmaxi, Antigoni; Zaphiris, Panayiotis

2015-01-01

This paper reports on the use of design-based research (DBR) for the development of a framework that grounds the use of social technologies in learning. The paper focuses on three studies which step on the learning theory of constructionism. Constructionism assumes that knowledge is better gained when students find this knowledge for themselves…

Towards a Framework for Learning in the OSMA Serious Game Engine

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Tanguy Coenen

2010-11-01

Full Text Available Online multiplayer serious games offer a way to support learning in a gaming paradigm that is familiar to many players and has proven its effectiveness in providing sustainably enjoyable gameplay. We aim to decrease development cost for these games by providing a modular game design framework and a component-based technical architecture. The technical architecture and the game design framework will be implemented and iteratively refined through two proofs of concept.

Using the Instructional Core to Implement a Professional Learning Programme for Primary Science Teachers in Australia: Teacher Learning and Student Skill Outcomes

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Loughland, Tony; Nguyen, Hoa Thi Mai

2016-01-01

There has been a call for effective professional learning to improve the quality of the science teaching of primary teachers in Australia. It seems from the literature that teaching science effectively is a challenging endeavour for primary teachers. Professional learning based on the instructional core framework is an emerging approach that has…

Students' "Uses and Gratification Expectancy" Conceptual Framework in Relation to E-Learning Resources

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Mondi, Makingu; Woods, Peter; Rafi, Ahmad

2007-01-01

This paper presents the systematic development of a "Uses and Gratification Expectancy" (UGE) conceptual framework which is able to predict students' "Perceived e-Learning Experience." It is argued that students' UGE as regards e-learning resources cannot be implicitly or explicitly explored without first examining underlying communication…

Refreshing Information Literacy: Learning from Recent British Information Literacy Models

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Martin, Justine

2013-01-01

Models play an important role in helping practitioners implement and promote information literacy. Over time models can lose relevance with the advances in technology, society, and learning theory. Practitioners and scholars often call for adaptations or transformations of these frameworks to articulate the learning needs in information literacy…

A web-based e-learning framework for public perception and acceptance on nuclear energy

International Nuclear Information System (INIS)

Zhou Yangping; Yoshikawa, Hidekazu; Liu Jingquan; Ouyang, Jun; Lu Daogang

2005-01-01

Now, public acceptance plays a central role in the nuclear energy. Public concerns on safety and sustainability of nuclear energy, ground nuclear power in many countries and territories to a stop or even a downfall. In this study, an e-learning framework by using Internet, is proposed for public education in order to boost public perception on nuclear energy, which will certainly affect public acceptance toward it. This study aims at investigating public perception and acceptance on nuclear energy in a continuous and accurate manner. In addition, this e-learning framework can promote public perception on nuclear energy by using teaching material with a graphical hierarchy about knowledge of nuclear energy. This web-based e-learning framework mainly consists of two components: (1) an e-learning support module which continuously investigates public perception and acceptance toward nuclear energy and teaches public knowledge about nuclear energy; (2) an updating module which may improve the education materials by analyzing the effect of education or proving the materials submitted by the visitors through Wiki pages. Advantages and future work of this study are also generally described. (author)

When Playing Meets Learning: Methodological Framework for Designing Educational Games

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Linek, Stephanie B.; Schwarz, Daniel; Bopp, Matthias; Albert, Dietrich

Game-based learning builds upon the idea of using the motivational potential of video games in the educational context. Thus, the design of educational games has to address optimizing enjoyment as well as optimizing learning. Within the EC-project ELEKTRA a methodological framework for the conceptual design of educational games was developed. Thereby state-of-the-art psycho-pedagogical approaches were combined with insights of media-psychology as well as with best-practice game design. This science-based interdisciplinary approach was enriched by enclosed empirical research to answer open questions on educational game-design. Additionally, several evaluation-cycles were implemented to achieve further improvements. The psycho-pedagogical core of the methodology can be summarized by the ELEKTRA's 4Ms: Macroadaptivity, Microadaptivity, Metacognition, and Motivation. The conceptual framework is structured in eight phases which have several interconnections and feedback-cycles that enable a close interdisciplinary collaboration between game design, pedagogy, cognitive science and media psychology.

A Novel Extreme Learning Control Framework of Unmanned Surface Vehicles.

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Wang, Ning; Sun, Jing-Chao; Er, Meng Joo; Liu, Yan-Cheng

2016-05-01

In this paper, an extreme learning control (ELC) framework using the single-hidden-layer feedforward network (SLFN) with random hidden nodes for tracking an unmanned surface vehicle suffering from unknown dynamics and external disturbances is proposed. By combining tracking errors with derivatives, an error surface and transformed states are defined to encapsulate unknown dynamics and disturbances into a lumped vector field of transformed states. The lumped nonlinearity is further identified accurately by an extreme-learning-machine-based SLFN approximator which does not require a priori system knowledge nor tuning input weights. Only output weights of the SLFN need to be updated by adaptive projection-based laws derived from the Lyapunov approach. Moreover, an error compensator is incorporated to suppress approximation residuals, and thereby contributing to the robustness and global asymptotic stability of the closed-loop ELC system. Simulation studies and comprehensive comparisons demonstrate that the ELC framework achieves high accuracy in both tracking and approximation.

AFFECT: Altered-Fidelity Framework for Enhancing Cognition and Training

Directory of Open Access Journals (Sweden)

Ryan Patrick McMahan

2016-11-01

Full Text Available In this paper, we present a new framework for analyzing and designing virtual reality (VR techniques. This framework is based on two concepts—system fidelity (i.e., the degree with which real-world experiences are reproduced by a system and memory (i.e., the formation and activation of perceptual, cognitive, and motor networks of neurons. The premise of the framework is to manipulate an aspect of system fidelity in order to assist a stage of memory. We call it the Altered-Fidelity Framework for Enhancing Cognition and Training (AFFECT. AFFECT provides nine categories of approaches to altering system fidelity to positively affect learning or training. These categories are based on the intersections of three aspects of system fidelity (interaction fidelity, scenario fidelity, and display fidelity and three stages of memory (encoding, implicit retrieval, and explicit retrieval. In addition to discussing the details of our new framework, we show how AFFECT can be used as a tool for analyzing and categorizing VR techniques designed to facilitate learning or training. We also demonstrate how AFFECT can be used as a design space for creating new VR techniques intended for educational and training systems.

Evidence-based Frameworks for Teaching and Learning in Classical Singing Training: A Systematic Review.

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Crocco, Laura; Madill, Catherine J; McCabe, Patricia

2017-01-01

The study systematically reviews evidence-based frameworks for teaching and learning of classical singing training. This is a systematic review. A systematic literature search of 15 electronic databases following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines was conducted. Eligibility criteria included type of publication, participant characteristics, intervention, and report of outcomes. Quality rating scales were applied to support assessment of the included literature. Data analysis was conducted using meta-aggregation. Nine papers met the inclusion criteria. No complete evidence-based teaching and learning framework was found. Thematic content analysis showed that studies either (1) identified teaching practices in one-to-one lessons, (2) identified student learning strategies in one-to-one lessons or personal practice sessions, and (3) implemented a tool to enhance one specific area of teaching and learning in lessons. The included studies showed that research in music education is not always specific to musical genre or instrumental group, with four of the nine studies including participant teachers and students of classical voice training only. The overall methodological quality ratings were low. Research in classical singing training has not yet developed an evidence-based framework for classical singing training. This review has found that introductory information on teaching and learning practices has been provided, and tools have been suggested for use in the evaluation of the teaching-learning process. High-quality methodological research designs are needed. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement

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Bodily, Robert; Nyland, Rob; Wiley, David

2017-01-01

The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. This is particularly useful in OER contexts where the…

Formal Framework to improve the reliability of concurrent and collaborative learning games

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Mounier

2014-05-01

Full Text Available Multi-player learning games are complex software applications resulting from a costly and complex engineering process, and involving multiple stakeholders (domain experts, teachers, game designers, programmers, testers, etc.. Moreover, they are dynamic systems that evolve over time and implement complex interactions between objects and players. Usually, once a learning game is developed, testing activities are conducted by humans who explore the possible executions of the game’s scenario to detect bugs. The complexity and the dynamic nature of multiplayer learning games enforces the complexity of testing activities. Indeed, it is impracticable to explore manually all possible executions due to their huge number. Moreover, the test cannot verify some properties on multi-player and collaborative scenarios, such as paths leading to deadlock between learners or prevent learners to meet all objectives and win the game. This type of properties should be verified at the design stage. We propose a framework enabling a formal modeling of game scenarios and an associated automatic verification of learning game’s scenario at the design stage of the development process.We use Symmetric Petri nets as a modeling language and choose to verify properties by means of model checkers. This paper discusses the possibilities offered by this framework to verify learning game’s properties before the programming stage.

Convergence of calls as animals form social bonds, active compensation for noisy communication channels, and the evolution of vocal learning in mammals.

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Tyack, Peter L

2008-08-01

The classic evidence for vocal production learning involves imitation of novel, often anthropogenic sounds. Among mammals, this has been reported for dolphins, elephants, harbor seals, and humans. A broader taxonomic distribution has been reported for vocal convergence, where the acoustic properties of calls from different individuals converge when they are housed together in captivity or form social bonds in the wild. Vocal convergence has been demonstrated for animals as diverse as songbirds, parakeets, hummingbirds, bats, elephants, cetaceans, and primates. For most species, call convergence is thought to reflect a group-distinctive identifier, with shared calls reflecting and strengthening social bonds. A ubiquitous function for vocal production learning that is starting to receive attention involves modifying signals to improve communication in a noisy channel. Pooling data on vocal imitation, vocal convergence, and compensation for noise suggests a wider taxonomic distribution of vocal production learning among mammals than has been generally appreciated. The wide taxonomic distribution of this evidence for vocal production learning suggests that perhaps more of the neural underpinnings for vocal production learning are in place in mammals than is usually recognized. (c) 2008 APA, all rights reserved

A Framework for Culturally Relevant Online Learning: Lessons from Alaska's Tribal Health Workers.

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Cueva, Katie; Cueva, Melany; Revels, Laura; Lanier, Anne P; Dignan, Mark; Viswanath, K; Fung, Teresa T; Geller, Alan C

2018-03-22

Culturally relevant health promotion is an opportunity to reduce health inequities in diseases with modifiable risks, such as cancer. Alaska Native people bear a disproportionate cancer burden, and Alaska's rural tribal health workers consequently requested cancer education accessible online. In response, the Alaska Native Tribal Health Consortium cancer education team sought to create a framework for culturally relevant online learning to inform the creation of distance-delivered cancer education. Guided by the principles of community-based participatory action research and grounded in empowerment theory, the project team conducted a focus group with 10 Alaska Native education experts, 12 culturally diverse key informant interviews, a key stakeholder survey of 62 Alaska Native tribal health workers and their instructors/supervisors, and a literature review on distance-delivered education with Alaska Native or American Indian people. Qualitative findings were analyzed in Atlas.ti, with common themes presented in this article as a framework for culturally relevant online education. This proposed framework includes four principles: collaborative development, interactive content delivery, contextualizing learning, and creating connection. As an Alaskan tribal health worker shared "we're all in this together. All about conversations, relationships. Always learn from you/with you, together what we know and understand from the center of our experience, our ways of knowing, being, caring." The proposed framework has been applied to support cancer education and promote cancer control with Alaska Native people and has motivated health behavior change to reduce cancer risk. This framework may be adaptable to other populations to guide effective and culturally relevant online interventions.

An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework

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Guanqiu Qi

2017-10-01

Full Text Available Image fusion is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Medical image fusion, as an important image fusion application, can extract the details of multiple images from different imaging modalities and combine them into an image that contains complete and non-redundant information for increasing the accuracy of medical diagnosis and assessment. The quality of the fused image directly affects medical diagnosis and assessment. However, existing solutions have some drawbacks in contrast, sharpness, brightness, blur and details. This paper proposes an integrated dictionary-learning and entropy-based medical image-fusion framework that consists of three steps. First, the input image information is decomposed into low-frequency and high-frequency components by using a Gaussian filter. Second, low-frequency components are fused by weighted average algorithm and high-frequency components are fused by the dictionary-learning based algorithm. In the dictionary-learning process of high-frequency components, an entropy-based algorithm is used for informative blocks selection. Third, the fused low-frequency and high-frequency components are combined to obtain the final fusion results. The results and analyses of comparative experiments demonstrate that the proposed medical image fusion framework has better performance than existing solutions.

Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

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Miranda, Paula; Isaias, Pedro; Costa, Carlos J.; Pifano, Sara

2017-01-01

Aim/Purpose: As e-Learning 3.0 evolves from a theoretical construct into an actual solution for online learning, it becomes crucial to accompany this progress by scrutinising the elements that are at the origin of its success. Background: This paper outlines a framework of e-Learning 3.0's critical success factors and its empirical validation.…

Praxis and reflexivity for interprofessional education: towards an inclusive theoretical framework for learning.

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Hutchings, Maggie; Scammell, Janet; Quinney, Anne

2013-09-01

While there is growing evidence of theoretical perspectives adopted in interprofessional education, learning theories tend to foreground the individual, focusing on psycho-social aspects of individual differences and professional identity to the detriment of considering social-structural factors at work in social practices. Conversely socially situated practice is criticised for being context-specific, making it difficult to draw generalisable conclusions for improving interprofessional education. This article builds on a theoretical framework derived from earlier research, drawing on the dynamics of Dewey's experiential learning theory and Archer's critical realist social theory, to make a case for a meta-theoretical framework enabling social-constructivist and situated learning theories to be interlinked and integrated through praxis and reflexivity. Our current analysis is grounded in an interprofessional curriculum initiative mediated by a virtual community peopled by health and social care users. Student perceptions, captured through quantitative and qualitative data, suggest three major disruptive themes, creating opportunities for congruence and disjuncture and generating a model of zones of interlinked praxis associated with professional differences and identity, pedagogic strategies and technology-mediated approaches. This model contributes to a framework for understanding the complexity of interprofessional learning and offers bridges between individual and structural factors for engaging with the enablements and constraints at work in communities of practice and networks for interprofessional education.

Toward a common theory for learning from reward, affect, and motivation: the SIMON framework.

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Madan, Christopher R

2013-10-07

While the effects of reward, affect, and motivation on learning have each developed into their own fields of research, they largely have been investigated in isolation. As all three of these constructs are highly related, and use similar experimental procedures, an important advance in research would be to consider the interplay between these constructs. Here we first define each of the three constructs, and then discuss how they may influence each other within a common framework. Finally, we delineate several sources of evidence supporting the framework. By considering the constructs of reward, affect, and motivation within a single framework, we can develop a better understanding of the processes involved in learning and how they interplay, and work toward a comprehensive theory that encompasses reward, affect, and motivation.

Sparse alignment for robust tensor learning.

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Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Zhao, Cairong; Sun, Mingming

2014-10-01

Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods, L1- and L2-norms are introduced to enhance the robustness in the alignment step of the STA. The advantage of the proposed technique is that the difficulty in selecting the size of the local neighborhood can be avoided in the manifold learning based tensor feature extraction algorithms. Although STA is an unsupervised learning method, the sparsity encodes the discriminative information in the alignment step and provides the robustness of STA. Extensive experiments on the well-known image databases as well as action and hand gesture databases by encoding object images as tensors demonstrate that the proposed STA algorithm gives the most competitive performance when compared with the tensor-based unsupervised learning methods.

Fundamentals of Learning. From the College and Career Ready Standards to Teaching and Learning in the Classroom: A Series of Resources for Teachers

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Heritage, Margaret; Jones, Barbara; Tobiason, Glory; Chang, Sandy; Herman, Joan

2015-01-01

This publication provides a framework, the Fundamentals of Learning (FOL), to assist teachers in transitioning to the classroom practices called for in the College- and Career-Ready Standards (CCRS). The content of this resource is drawn from leading theory and research about learning and assessment and from an examination of the Common Core State…

Clinical simulation practise framework.

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Khalili, Hossein

2015-02-01

Historically, simulation has mainly been used to teach students hands-on skills in a relatively safe environment. With changes in the patient population, professional regulations and clinical environments, clinical simulation practise (CSP) must assist students to integrate and apply their theoretical knowledge and skills with their critical thinking, clinical judgement, prioritisation, problem solving, decision making, and teamwork skills to provide holistic care and treatment to their patients. CSP holds great potential to derive a positive transformation in students' transition into the workplace, by associating and consolidating learning from classrooms to clinical settings, and creating bridges between theory and practice. For CSP to be successful in filling the gap, the design and management of the simulation is crucial. In this article a new framework called 'Clinical simulation practise framework: A knowledge to action strategy in health professional education' is being introduced that aims to assist educators and curriculum developers in designing and managing their simulations. This CSP framework theorises that simulation as an experiential educational tool could improve students' competence, confidence and collaboration in performing professional practice in real settings if the CSP provides the following three dimensions: (1) a safe, positive, reflective and fun simulated learning environment; (2) challenging, but realistic, and integrated simulated scenarios; and (3) interactive, inclusive, interprofessional patient-centred simulated practise. © 2015 John Wiley & Sons Ltd.

Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification.

Science.gov (United States)

Younghak Shin; Balasingham, Ilangko

2017-07-01

Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

A framework to develop a clinical learning culture in health facilities: ideas from the literature.

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Henderson, A; Briggs, J; Schoonbeek, S; Paterson, K

2011-06-01

Internationally, there is an increase in demand to educate nurses within the clinical practice environment. Clinical practice settings that encourage teaching and learning during episodes of care delivery can be powerful in educating both the existing nursing workforce and nursing students. This paper presents a framework, informed by the literature, that identifies the key factors that are needed to encourage the interactions fundamental to learning in clinical practice. Learning occurs when nurses demonstrate good practice, share their knowledge through conversations and discussions, and also provide feedback to learners, such as students and novices. These types of interactions occur when positive leadership practices encourage trust and openness between staff; when the management team provides sessions for staff to learn how to interact with learners, and also when partnerships provide support and guidance around learning in the workplace. APPLICATION OF CONCEPTS: This framework presents how the concepts of leadership, management and partnership interact to create and sustain learning environments. The feedback from proposed measurement tools can provide valuable information about the positive and negative aspects of these concepts in the clinical learning environment. Analysis of the subscales can assist in identifying appropriate recommended strategies outlined in the framework to guide nurses in improving the recognized deficits in the relationship between the concepts. Leadership, management and partnerships are pivotal for the creation and maintenance of positive learning environments. Diagnostic measurement tools can provide specific information about weaknesses across these areas. This knowledge can guide future initiatives. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

The Ghost in the Machine: Are "Teacherless" CALL Programs Really Possible?

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Davies, Ted; Williamson, Rodney

1998-01-01

Reflects critically on pedagogical issues in the production of computer-assisted language learning (CALL) courseware and ways CALL has affected the practice of language learning. Concludes that if CALL is to reach full potential, it must be more than a simple medium of information; it should provide a teaching/learning process, with the real…

Supporting Three-Dimensional Science Learning: The Role of Curiosity-Driven Classroom Discourse

Science.gov (United States)

Johnson, Wendy Renae

2017-01-01

The National Research Council's "Framework for K-12 Science Education" (2011) presents a new vision for science education that calls for the integration of the three dimensions of science learning: science and engineering practices, crosscutting concepts, and disciplinary core ideas. Unlike previous conceptions of science learning that…

A Framework for Research on E-Learning Assimilation in SMEs: A Strategic Perspective

Science.gov (United States)

Raymond, Louis; Uwizeyemungu, Sylvestre; Bergeron, Francois; Gauvin, Stephane

2012-01-01

Purpose: This study aims to propose an integrative conceptual framework of e-learning adoption and assimilation that is adapted to the specific context of small to medium-sized enterprises (SMEs). Design/methodology/approach: The literature on the state of e-learning usage in SMEs and on the IT adoption and assimilation factors that can be…

Towards a common theory for learning from reward, affect, and motivation: The SIMON framework

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Christopher R Madan

2013-10-01

Full Text Available While the effects of reward, affect, and motivation on learning have each developed into their own fields of research, they largely have been investigated in isolation. As all three of these constructs are highly related, and use similar experimental procedures, an important advance in research would be to consider the interplay between these constructs. Here we first define each of the three constructs, and then discuss how they may influence each other within a common framework. Finally, we delineate several sources of evidence supporting the framework. By considering the constructs of reward, affect, and motivation within a single framework, we can develop a better understanding of the processes involved in learning and how they interplay, and work towards a comprehensive theory that encompasses reward, affect, and motivation.

Incremental online object learning in a vehicular radar-vision fusion framework

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Ji, Zhengping [Los Alamos National Laboratory; Weng, Juyang [Los Alamos National Laboratory; Luciw, Matthew [IEEE; Zeng, Shuqing [IEEE

2010-10-19

In this paper, we propose an object learning system that incorporates sensory information from an automotive radar system and a video camera. The radar system provides a coarse attention for the focus of visual analysis on relatively small areas within the image plane. The attended visual areas are coded and learned by a 3-layer neural network utilizing what is called in-place learning, where every neuron is responsible for the learning of its own signal processing characteristics within its connected network environment, through inhibitory and excitatory connections with other neurons. The modeled bottom-up, lateral, and top-down connections in the network enable sensory sparse coding, unsupervised learning and supervised learning to occur concurrently. The presented work is applied to learn two types of encountered objects in multiple outdoor driving settings. Cross validation results show the overall recognition accuracy above 95% for the radar-attended window images. In comparison with the uncoded representation and purely unsupervised learning (without top-down connection), the proposed network improves the recognition rate by 15.93% and 6.35% respectively. The proposed system is also compared with other learning algorithms favorably. The result indicates that our learning system is the only one to fit all the challenging criteria for the development of an incremental and online object learning system.

The Social Outcomes of Older Adult Learning in Taiwan: Evaluation Framework and Indicators

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Lin, Li-Hui

2015-01-01

The purpose of this study is to explore the social outcomes of older adult learning in Taiwan. In light of our society's aging population structure, the task of establishing evaluation framework and indicators for the social outcomes of learning (SOL) as applied to older adults is urgent. In order to construct evaluation indicators for older adult…

Learning design: reflections upon the current landscape

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Brock Craft

2012-08-01

Full Text Available The mounting wealth of open and readily available information and the accelerated evolution of social, mobile and creative technologies call for a re-conceptualisation of the role of educators: from providers of knowledge to designers of learning. This call is reverberated by the rising trend of research in learning design (LD. Addressing this, the Art and Science of Learning Design workshop brought together leading voices in the field, and provided a forum for discussing its key issues. It focused on three major themes: (1 practices, methods and methodologies, (2 tools and resources and (3 theoretical frameworks. This paper proposes a definition of LD, reviews the main contributions from the workshop, and suggests some challenges for future research.

Quantitative Reasoning Learning Progressions for Environmental Science: Developing a Framework

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Robert L. Mayes

2013-01-01

Full Text Available Quantitative reasoning is a complex concept with many definitions and a diverse account in the literature. The purpose of this article is to establish a working definition of quantitative reasoning within the context of science, construct a quantitative reasoning framework, and summarize research on key components in that framework. Context underlies all quantitative reasoning; for this review, environmental science serves as the context.In the framework, we identify four components of quantitative reasoning: the quantification act, quantitative literacy, quantitative interpretation of a model, and quantitative modeling. Within each of these components, the framework provides elements that comprise the four components. The quantification act includes the elements of variable identification, communication, context, and variation. Quantitative literacy includes the elements of numeracy, measurement, proportional reasoning, and basic probability/statistics. Quantitative interpretation includes the elements of representations, science diagrams, statistics and probability, and logarithmic scales. Quantitative modeling includes the elements of logic, problem solving, modeling, and inference. A brief comparison of the quantitative reasoning framework with the AAC&U Quantitative Literacy VALUE rubric is presented, demonstrating a mapping of the components and illustrating differences in structure. The framework serves as a precursor for a quantitative reasoning learning progression which is currently under development.

Real World Learning: toward a differentiated framework for outdoor learning for sustainability

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Lewis Winks

2015-12-01

Full Text Available The Real World Learning network (RWLn set out in 2011 to explore elements which contribute to a ‘deep and meaningful’ outdoor education experience. Following three years of work, the RWLn developed the ‘Hand Model’, a learning model designed to support educators in the development of Outdoor Learning for Sustainability (OLfS. Since its launch in early 2014, the model has been used for planning, delivering and reflecting upon OLfS experiences. Making use of the comments made in Činčera’s (2015 Real World Learning: a critical analysis which highlights inconsistencies existent within the model’s internal logic, this paper considers the perceived contradiction between emancipatory and instrumental approaches to learning. Beginning with a comprehensive introduction to the Hand model, this paper goes on to discuss the theoretical divide which the model spans between a goal-led, knowledge based approach promoted by the model’s focus upon understanding and values, and a pluralistic and exploratory approach typified by aspects of educational empowerment and experience. In response to this and augmented by examples, a differentiated conceptual framework is presented to facilitate a pragmatic application of the model from a practice perspective, making use of what has been termed a ‘blended approach’, whilst acknowledging degrees of inconsistency and dissonance from a theoretical perspective. Additionally, the model is viewed from a context perspective where questions are asked regarding the appropriateness of particular approaches depending upon the setting in which learning takes place. It is hoped that by moving beyond theoretically entrenched positions a mediated middle ground for the model’s application may be established.

A Conceptual Framework for Error Remediation with Multiple External Representations Applied to Learning Objects

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Leite, Maici Duarte; Marczal, Diego; Pimentel, Andrey Ricardo; Direne, Alexandre Ibrahim

2014-01-01

This paper presents the application of some concepts of Intelligent Tutoring Systems (ITS) to elaborate a conceptual framework that uses the remediation of errors with Multiple External Representations (MERs) in Learning Objects (LO). To this is demonstrated a development of LO for teaching the Pythagorean Theorem through this framework. This…

A Fuzzy Logic Framework for Integrating Multiple Learned Models

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Hartog, Bobi Kai Den [Univ. of Nebraska, Lincoln, NE (United States)

1999-03-01

The Artificial Intelligence field of Integrating Multiple Learned Models (IMLM) explores ways to combine results from sets of trained programs. Aroclor Interpretation is an ill-conditioned problem in which trained programs must operate in scenarios outside their training ranges because it is intractable to train them completely. Consequently, they fail in ways related to the scenarios. We developed a general-purpose IMLM solution, the Combiner, and applied it to Aroclor Interpretation. The Combiner's first step, Scenario Identification (M), learns rules from very sparse, synthetic training data consisting of results from a suite of trained programs called Methods. S1 produces fuzzy belief weights for each scenario by approximately matching the rules. The Combiner's second step, Aroclor Presence Detection (AP), classifies each of three Aroclors as present or absent in a sample. The third step, Aroclor Quantification (AQ), produces quantitative values for the concentration of each Aroclor in a sample. AP and AQ use automatically learned empirical biases for each of the Methods in each scenario. Through fuzzy logic, AP and AQ combine scenario weights, automatically learned biases for each of the Methods in each scenario, and Methods' results to determine results for a sample.

The Inquiry, Communication, Construction and Expression (ICCE) Framework for Understanding Learning Experiences in Games

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Shah, Mamta; Foster, Aroutis

2014-01-01

There is a paucity of research frameworks that focus on aiding game selection and use, analyzing the game as a holistic system, and studying learner experiences in games. There is a need for frameworks that provide a lens for understanding learning experiences afforded in digital games and facilitating knowledge construction and motivation to…

Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework

OpenAIRE

Varun Mithal; Guruprasad Nayak; Ankush Khandelwal; Vipin Kumar; Ramakrishna Nemani; Nikunj C. Oza

2018-01-01

This paper presents an application of a novel machine-learning framework on MODIS (moderate-resolution imaging spectroradiometer) data to map burned areas over tropical forests of South America and South-east Asia. The RAPT (RAre Class Prediction in the absence of True labels) framework is able to build data adaptive classification models using noisy training labels. It is particularly suitable when expert annotated training samples are difficult to obtain as in the case of wild fires in the ...

A Proposed Framework Between Internal, External and Pedagogy Dimensions in Adoption of Interactive Multimedia e-Learning

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Fathia LAHWAL

2016-10-01

Full Text Available This study about interactive multimedia e-learning aims to improve our understanding about the dynamics of e-learning. The objective is to critical evaluate and better understand the interrelationships in the proposed framework between internal, external and the pedagogy dimensions in adoption of interactive multimedia and e-learning. It develops a tool to measure creative user adoption of interactive multimedia and e-learning services by using Partial Least Squares algorithm as the method of estimation and the major analytical tool in this study. Finding of a small scale data sampling of students in United Kingdom indicate that the proposed measurement framework is an acceptable fit with the data. Overall, the findings supply a precise tool for measuring creative user adoption of interactive multimedia and e-learning services, providing further insights for researchers and may provide to guide research and practice in interactive multimedia and e-learning by using communication media.

Some New Theoretical Issues in Systems Thinking Relevant for Modelling Corporate Learning

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Minati, Gianfranco

2007-01-01

Purpose: The purpose of this paper is to describe fundamental concepts and theoretical challenges with regard to systems, and to build on these in proposing new theoretical frameworks relevant to learning, for example in so-called learning organizations. Design/methodology/approach: The paper focuses on some crucial fundamental aspects introduced…

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

Science.gov (United States)

Kim, Dong Won; Yao, Jingtao

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

Optimizing microstimulation using a reinforcement learning framework.

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Brockmeier, Austin J; Choi, John S; Distasio, Marcello M; Francis, Joseph T; Príncipe, José C

2011-01-01

The ability to provide sensory feedback is desired to enhance the functionality of neuroprosthetics. Somatosensory feedback provides closed-loop control to the motor system, which is lacking in feedforward neuroprosthetics. In the case of existing somatosensory function, a template of the natural response can be used as a template of desired response elicited by electrical microstimulation. In the case of no initial training data, microstimulation parameters that produce responses close to the template must be selected in an online manner. We propose using reinforcement learning as a framework to balance the exploration of the parameter space and the continued selection of promising parameters for further stimulation. This approach avoids an explicit model of the neural response from stimulation. We explore a preliminary architecture--treating the task as a k-armed bandit--using offline data recorded for natural touch and thalamic microstimulation, and we examine the methods efficiency in exploring the parameter space while concentrating on promising parameter forms. The best matching stimulation parameters, from k = 68 different forms, are selected by the reinforcement learning algorithm consistently after 334 realizations.

Leveraging Competency Framework to Improve Teaching and Learning: A Methodological Approach

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Shankararaman, Venky; Ducrot, Joelle

2016-01-01

A number of engineering education programs have defined learning outcomes and course-level competencies, and conducted assessments at the program level to determine areas for continuous improvement. However, many of these programs have not implemented a comprehensive competency framework to support the actual delivery and assessment of an…

A framework for adaptive e-learning for continuum mechanics and structural analysis

OpenAIRE

Mosquera Feijoo, Juan Carlos; Plaza Beltrán, Luis Francisco; González Rodrigo, Beatriz

2015-01-01

This paper presents a project for providing the students of Structural Engineering with the flexibility to learn outside classroom schedules. The goal is a framework for adaptive E-learning based on a repository of open educational courseware with a set of basic Structural Engineering concepts and fundamentals. These are paramount for students to expand their technical knowledge and skills in structural analysis and design of tall buildings, arch-type structures as well as bridges. Thus, conc...

An Alienation-Based Framework for Student Experience in Higher Education: New Interpretations of Past Observations in Student Learning Theory

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Barnhardt, Bradford; Ginns, Paul

2014-01-01

This article orients a recently proposed alienation-based framework for student learning theory (SLT) to the empirical basis of the approaches to learning perspective. The proposed framework makes new macro-level interpretations of an established micro-level theory, across three levels of interpretation: (1) a context-free psychological state…

The Community of Inquiry Framework Meets the SOLO Taxonomy: A Process-Product Model of Online Learning

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Shea, Peter; Gozza-Cohen, Mary; Uzuner, Sedef; Mehta, Ruchi; Valtcheva, Anna Valentinova; Hayes, Suzanne; Vickers, Jason

2011-01-01

This paper presents both a conceptual and empirical investigation of teaching and learning in online courses. Employing both the Community of Inquiry framework (CoI) and the Structure of Observed Learning Outcomes (SOLO) taxonomy, two complete online courses were examined for the quality of both collaborative learning processes and learning…

A Proposed Framework between Internal, External and Pedagogy Dimensions in Adoption of Interactive Multimedia e-Learning

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Lahwal, Fathia; Al-Ajlan, Ajlan S.; Amain, Mohamad

2016-01-01

This study focuses on interactive multimedia e-learning aims to improve our understanding about the dynamics of e-learning. The objective is to critical evaluate and better understand the interrelationships in the proposed framework between internal, external and the pedagogy dimensions in adoption of interactive multimedia and e-learning. It…

Applying the Kirkpatrick Model: Evaluating an "Interaction for Learning Framework" Curriculum Intervention

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Paull, Megan; Whitsed, Craig; Girardi, Antonia

2016-01-01

Global perspectives and interpersonal and intercultural communication competencies are viewed as a priority within higher education. For management educators, globalisation, student mobility and widening pathways present numerous challenges, but afford opportunities for curriculum innovation. The "Interaction for Learning Framework"…

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

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Nicolas Frémaux

2013-04-01

Full Text Available Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD learning of Doya (2000 to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Learner Analysis Framework for Globalized E-Learning: A Case Study

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Mamta Saxena

2011-06-01

Full Text Available The shift to technology-mediated modes of instructional delivery and increased global connectivity has led to a rise in globalized e-learning programs. Educational institutions face multiple challenges as they seek to design effective, engaging, and culturally competent instruction for an increasingly diverse learner population. The purpose of this study was to explore strategies for expanding learner analysis within the instructional design process to better address cultural influences on learning. A case study approach leveraged the experience of practicing instructional designers to build a framework for culturally competent learner analysis.The study discussed the related challenges and recommended strategies to improve the effectiveness of cross-cultural learner analysis. Based on the findings, a framework for conducting cross-cultural learner analysis to guide the cultural analysis of diverse learners was proposed. The study identified the most critical factors in improving cross-cultural learner analysis as the judicious use of existing research on cross-cultural theories and joint deliberation on the part of all the participants from the management to the learners. Several strategies for guiding and improving the cultural inquiry process were summarized. Barriers and solutions for the requirements are also discussed.

How Multi-Levels of Individual and Team Learning Interact in a Public Healthcare Organisation: A Conceptual Framework

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Doyle, Louise; Kelliher, Felicity; Harrington, Denis

2016-01-01

The aim of this paper is to review the relevant literature on organisational learning and offer a preliminary conceptual framework as a basis to explore how the multi-levels of individual learning and team learning interact in a public healthcare organisation. The organisational learning literature highlights a need for further understanding of…

Threat driven modeling framework using petri nets for e-learning system.

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Khamparia, Aditya; Pandey, Babita

2016-01-01

Vulnerabilities at various levels are main cause of security risks in e-learning system. This paper presents a modified threat driven modeling framework, to identify the threats after risk assessment which requires mitigation and how to mitigate those threats. To model those threat mitigations aspects oriented stochastic petri nets are used. This paper included security metrics based on vulnerabilities present in e-learning system. The Common Vulnerability Scoring System designed to provide a normalized method for rating vulnerabilities which will be used as basis in metric definitions and calculations. A case study has been also proposed which shows the need and feasibility of using aspect oriented stochastic petri net models for threat modeling which improves reliability, consistency and robustness of the e-learning system.

Using apps for learning across the curriculum a literacy-based framework and guide

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Beach, Richard

2014-01-01

How can apps be used to foster learning with literacy across the curriculum? This book offers both a theoretical framework for considering app affordances and practical ways to use apps to build students' disciplinary literacies and to foster a wide range of literacy practices.Using Apps for Learning Across the Curriculumpresents a wide range of different apps and also assesses their value features methods for and apps related to planning instruction and assessing student learning identifies favorite apps whose affordances are most likely to foster certain disciplinary literacies includes reso

Proverbs as Theoretical Frameworks for Lifelong Learning in Indigenous African Education

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Avoseh, Mejai B. M.

2013-01-01

Every aspect of a community's life and values in indigenous Africa provide the theoretical framework for education. The holistic worldview of the traditional system places a strong emphasis on the centrality of the human element and orature in the symmetrical relationship between life and learning. This article focuses on proverbs and the words…

A basic framework for integrating social and collaborative applications into learning environments

NARCIS (Netherlands)

Moghnieh, Ayman; Blat, Josep

2009-01-01

Moghnieh, A., & Blat, J. (2009). A basic framework for integrating social and collaborative applications into learning environments. Proceedings of the first conference on Research, Reflection, and Innovations in Integrating ICT in Education: Vol. 2 (pp. 1057-1061). April, 22-24, 2009, Lisbon,

Learn, see, practice, prove, do, maintain: an evidence-based pedagogical framework for procedural skill training in medicine.

Science.gov (United States)

Sawyer, Taylor; White, Marjorie; Zaveri, Pavan; Chang, Todd; Ades, Anne; French, Heather; Anderson, JoDee; Auerbach, Marc; Johnston, Lindsay; Kessler, David

2015-08-01

Acquisition of competency in procedural skills is a fundamental goal of medical training. In this Perspective, the authors propose an evidence-based pedagogical framework for procedural skill training. The framework was developed based on a review of the literature using a critical synthesis approach and builds on earlier models of procedural skill training in medicine. The authors begin by describing the fundamentals of procedural skill development. Then, a six-step pedagogical framework for procedural skills training is presented: Learn, See, Practice, Prove, Do, and Maintain. In this framework, procedural skill training begins with the learner acquiring requisite cognitive knowledge through didactic education (Learn) and observation of the procedure (See). The learner then progresses to the stage of psychomotor skill acquisition and is allowed to deliberately practice the procedure on a simulator (Practice). Simulation-based mastery learning is employed to allow the trainee to prove competency prior to performing the procedure on a patient (Prove). Once competency is demonstrated on a simulator, the trainee is allowed to perform the procedure on patients with direct supervision, until he or she can be entrusted to perform the procedure independently (Do). Maintenance of the skill is ensured through continued clinical practice, supplemented by simulation-based training as needed (Maintain). Evidence in support of each component of the framework is presented. Implementation of the proposed framework presents a paradigm shift in procedural skill training. However, the authors believe that adoption of the framework will improve procedural skill training and patient safety.

Implementing Peer Learning in Clinical Education: A Framework to Address Challenges In the "Real World".

Science.gov (United States)

Tai, Joanna Hong Meng; Canny, Benedict J; Haines, Terry P; Molloy, Elizabeth K

2017-01-01

Phenomenon: Peer learning has many benefits and can assist students in gaining the educational skills required in future years when they become teachers themselves. Peer learning may be particularly useful in clinical learning environments, where students report feeling marginalized, overwhelmed, and unsupported. Educational interventions often fail in the workplace environment, as they are often conceived in the "ideal" rather than the complex, messy real world. This work sought to explore barriers and facilitators to implementing peer learning activities in a clinical curriculum. Previous peer learning research results and a matrix of empirically derived peer learning activities were presented to local clinical education experts to generate discussion around the realities of implementing such activities. Potential barriers and limitations of and strategies for implementing peer learning in clinical education were the focus of the individual interviews. Thematic analysis of the data identified three key considerations for real-world implementation of peer learning: culture, epistemic authority, and the primacy of patient-centered care. Strategies for peer learning implementation were also developed from themes within the data, focusing on developing a culture of safety in which peer learning could be undertaken, engaging both educators and students, and establishing expectations for the use of peer learning. Insights: This study identified considerations and strategies for the implementation of peer learning activities, which took into account both educator and student roles. Reported challenges were reflective of those identified within the literature. The resultant framework may aid others in anticipating implementation challenges. Further work is required to test the framework's application in other contexts and its effect on learner outcomes.

The Healthy ALLiances (HALL) framework: prerequisites for success.

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Koelen, Maria A; Vaandrager, Lenneke; Wagemakers, Annemarie

2012-04-01

Chronic conditions are on the rise worldwide, and there is increasingly a call for the primary care and public health sectors to join forces in alliances. GPs have an important role to play in such alliances. However, successful cooperation is not as obvious as it may seem, and the sectors are not used to working together. The objective is to identify conditions and prerequisites for successful alliances. Identification of conditions and prerequisites is mainly based on stepwise analysis and iterative developments in research on collaboration processes in the area of health promotion and public health. The process as a whole resulted in the framework presented in this paper. This so-called HALL framework identifies three clusters of factors that either hinder or facilitate the success of alliances: (i) institutional factors, (ii) personal factors of participants in the alliance and (iii) factors relating to the organization of the alliance. The institutional and personal factors 'stick' to the stakeholders and are brought into the alliance. The third group refers to the lessons learned from dealing with the first two characteristics to make the alliance successful. Partners in alliances bring in personal attributes and institutional characteristics that can form obstacles to successful alliances, but, when they are addressed in a flexible and positive way, obstacles can be turned in contributory factors, leading to many potential benefits, such as collaborative learning and innovation.

An Automatic Car Counting System Using OverFeat Framework

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Debojit Biswas

2017-06-01

Full Text Available Automatic car counting is an important component in the automated traffic system. Car counting is very important to understand the traffic load and optimize the traffic signals. In this paper, we implemented the Gaussian Background Subtraction Method and OverFeat Framework to count cars. OverFeat Framework is a combination of Convolution Neural Network (CNN and one machine learning classifier (like Support Vector Machines (SVM or Logistic Regression. With this study, we showed another possible application area for the OverFeat Framework. The advantages and shortcomings of the Background Subtraction Method and OverFeat Framework were analyzed using six individual traffic videos with different perspectives, such as camera angles, weather conditions and time of the day. In addition, we compared the two algorithms above with manual counting and a commercial software called Placemeter. The OverFeat Framework showed significant potential in the field of car counting with the average accuracy of 96.55% in our experiment.

An Automatic Car Counting System Using OverFeat Framework.

Science.gov (United States)

Biswas, Debojit; Su, Hongbo; Wang, Chengyi; Blankenship, Jason; Stevanovic, Aleksandar

2017-06-30

Automatic car counting is an important component in the automated traffic system. Car counting is very important to understand the traffic load and optimize the traffic signals. In this paper, we implemented the Gaussian Background Subtraction Method and OverFeat Framework to count cars. OverFeat Framework is a combination of Convolution Neural Network (CNN) and one machine learning classifier (like Support Vector Machines (SVM) or Logistic Regression). With this study, we showed another possible application area for the OverFeat Framework. The advantages and shortcomings of the Background Subtraction Method and OverFeat Framework were analyzed using six individual traffic videos with different perspectives, such as camera angles, weather conditions and time of the day. In addition, we compared the two algorithms above with manual counting and a commercial software called Placemeter. The OverFeat Framework showed significant potential in the field of car counting with the average accuracy of 96.55% in our experiment.

Skype™ Conference Calls: A Way to Promote Speaking Skills in the Teaching and Learning of English

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Yeferson Romaña Correa

2015-01-01

Full Text Available This article presents the results of a research project on the teaching and learning of English through the use of Skype™ conference calls. The research was carried out with a group of 12 English as a foreign language adult learners in the language institute of Universidad Distrital Francisco José de Caldas, Bogotá, Colombia. The findings of this study suggest that Skype™ conference calls might be considered as an influential computer-mediated communication tool in order to promote English as a foreign language adult A1 learners’ speaking skill, especially for social interaction purposes and oral reinforcement of both language fluency and course contents outside of classroom settings.

A decision analysis framework for stakeholder involvement and learning in groundwater management

Science.gov (United States)

Karjalainen, T. P.; Rossi, P. M.; Ala-aho, P.; Eskelinen, R.; Reinikainen, K.; Kløve, B.; Pulido-Velazquez, M.; Yang, H.

2013-12-01

Multi-criteria decision analysis (MCDA) methods are increasingly used to facilitate both rigorous analysis and stakeholder involvement in natural and water resource planning. Decision-making in that context is often complex and multi-faceted with numerous trade-offs between social, environmental and economic impacts. However, practical applications of decision-support methods are often too technically oriented and hard to use, understand or interpret for all participants. The learning of participants in these processes is seldom examined, even though successful deliberation depends on learning. This paper analyzes the potential of an interactive MCDA framework, the decision analysis interview (DAI) approach, for facilitating stakeholder involvement and learning in groundwater management. It evaluates the results of the MCDA process in assessing land-use management alternatives in a Finnish esker aquifer area where conflicting land uses affect the groundwater body and dependent ecosystems. In the assessment process, emphasis was placed on the interactive role of the MCDA tool in facilitating stakeholder participation and learning. The results confirmed that the structured decision analysis framework can foster learning and collaboration in a process where disputes and diverse interests are represented. Computer-aided interviews helped the participants to see how their preferences affected the desirability and ranking of alternatives. During the process, the participants' knowledge and preferences evolved as they assessed their initial knowledge with the help of fresh scientific information. The decision analysis process led to the opening of a dialogue, showing the overall picture of the problem context and the critical issues for the further process.

The POL Model: Using a Social Constructivist Framework to Develop Blended and Online Learning

DEFF Research Database (Denmark)

Dalsgaard, Christian; Godsk, Mikkel

2007-01-01

The paper presents a model for developing blended and online learning based on a given curriculum and typical learning objectives for university courses. The model consists of a three-step-process in which the instructor formulates product-oriented tasks, develops and structures the learning...... materials and tools, outlines a schedule, and supports the students' learning activity in developing a product. The model is based on our experiences with transforming traditional lecture-based lessons into problem-based blended and online learning using a social constructivist approach and a standard...... virtual learning environment (VLE). Our initial experiments indicate that our model is useful to develop blended and online modules and, furthermore, it seems fruitful to use a social constructivist framework and orienting learning activities towards the development of products....

Prototype-based Models for the Supervised Learning of Classification Schemes

Science.gov (United States)

Biehl, Michael; Hammer, Barbara; Villmann, Thomas

2017-06-01

An introduction is given to the use of prototype-based models in supervised machine learning. The main concept of the framework is to represent previously observed data in terms of so-called prototypes, which reflect typical properties of the data. Together with a suitable, discriminative distance or dissimilarity measure, prototypes can be used for the classification of complex, possibly high-dimensional data. We illustrate the framework in terms of the popular Learning Vector Quantization (LVQ). Most frequently, standard Euclidean distance is employed as a distance measure. We discuss how LVQ can be equipped with more general dissimilarites. Moreover, we introduce relevance learning as a tool for the data-driven optimization of parameterized distances.

A Symbiotic Framework for coupling Machine Learning and Geosciences in Prediction and Predictability

Science.gov (United States)

Ravela, S.

2017-12-01

In this presentation we review the two directions of a symbiotic relationship between machine learning and the geosciences in relation to prediction and predictability. In the first direction, we develop ensemble, information theoretic and manifold learning framework to adaptively improve state and parameter estimates in nonlinear high-dimensional non-Gaussian problems, showing in particular that tractable variational approaches can be produced. We demonstrate these applications in the context of autonomous mapping of environmental coherent structures and other idealized problems. In the reverse direction, we show that data assimilation, particularly probabilistic approaches for filtering and smoothing offer a novel and useful way to train neural networks, and serve as a better basis than gradient based approaches when we must quantify uncertainty in association with nonlinear, chaotic processes. In many inference problems in geosciences we seek to build reduced models to characterize local sensitivies, adjoints or other mechanisms that propagate innovations and errors. Here, the particular use of neural approaches for such propagation trained using ensemble data assimilation provides a novel framework. Through these two examples of inference problems in the earth sciences, we show that not only is learning useful to broaden existing methodology, but in reverse, geophysical methodology can be used to influence paradigms in learning.

Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept.

Science.gov (United States)

Cooper, Katelyn M; Ashley, Michael; Brownell, Sara E

2017-01-01

There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to student engagement in active learning. We propose using a theoretical lens of expectancy value theory to understand student resistance to active learning. In this study, we examined student perceptions of active learning after participating in 40 hours of active learning. We used the principal components of expectancy value theory to probe student experience in active learning: student perceived self-efficacy in active learning, value of active learning, and potential cost of participating in active learning. We found that students showed positive changes in the components of expectancy value theory and reported high levels of engagement in active learning, which provide proof of concept that expectancy value theory can be used to boost student perceptions of active learning and their engagement in active learning classrooms. From these findings, we have built a theoretical framework of expectancy value theory applied to active learning.

Indico CONFERENCE: Define the Call for Abstracts

CERN Multimedia

CERN. Geneva; Ferreira, Pedro

2017-01-01

In this tutorial, you will learn how to define and open a call for abstracts. When defining a call for abstracts, you will be able to define settings related to the type of questions asked during a review of an abstract, select the users who will review the abstracts, decide when to open the call for abstracts, and more.

Learning Performance Enhancement Using Computer-Assisted Language Learning by Collaborative Learning Groups

Directory of Open Access Journals (Sweden)

Ya-huei Wang

2017-08-01

Full Text Available This study attempted to test whether the use of computer-assisted language learning (CALL and innovative collaborative learning could be more effective than the use of traditional collaborative learning in improving students’ English proficiencies. A true experimental design was used in the study. Four randomly-assigned groups participated in the study: a traditional collaborative learning group (TCLG, 34 students, an innovative collaborative learning group (ICLG, 31 students, a CALL traditional collaborative learning group (CALLTCLG, 32 students, and a CALL innovative collaborative learning group (CALLICLG, 31 students. TOEIC (Test of English for International Communication listening, reading, speaking, and writing pre-test and post-test assessments were given to all students at an interval of sixteen weeks. Multivariate analysis of covariance (MANCOVA, multivariate analysis of variance (MANOVA, and analysis of variance (ANOVA were used to analyze the data. The results revealed that students who used CALL had significantly better learning performance than those who did not. Students in innovative collaborative learning had significantly better learning performances than those in traditional collaborative learning. Additionally, students using CALL innovative collaborative learning had better learning performances than those in CALL collaborative learning, those in innovative collaborative learning, and those in traditional collaborative learning.

Integrating Interview Methodology to Analyze Inter-Institutional Comparisons of Service-Learning within the Carnegie Community Engagement Classification Framework

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Plante, Jarrad D.; Cox, Thomas D.

2016-01-01

Service-learning has a longstanding history in higher education in and includes three main tenets: academic learning, meaningful community service, and civic learning. The Carnegie Foundation for the Advancement of Teaching created an elective classification system called the Carnegie Community Engagement Classification for higher education…

A framework for understanding outcomes of mutual learning situations in IT projects

DEFF Research Database (Denmark)

Hansen, Magnus Rotvit Perlt

2012-01-01

How do we analyse and understand design decisions derived from mutual learning (ML) situations and how may practitioners take advantage of these in IT projects? In the following we present a framework of design decisions inferred from ML situations that occurred between end-users and stakeholders...

Cognitive Presence in Virtual Collaborative Learning: Assessing and Improving Critical Thinking in Online Discussion Forums

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Beckmann, Jennifer; Weber, Peter

2015-01-01

The paper introduces a virtual collaborative learning setting called "Net Economy," which we established as part of an international learning network of currently seven universities. Using the Community of Inquiry framework as guidance and Canonical Action Research (CAR) as the chosen research design, the discussion forum of the online…

Enabling Problem Based Learning through Web 2.0 Technologies

DEFF Research Database (Denmark)

Tambouris, Efthimios; Panopoulou, Eleni; Tarabanis, Konstantinos

2012-01-01

of modern educational systems. Established pedagogical strategies, such as Problem Based Learning (PBL), are being adapted for online use in conjunction with modern Web 2.0 technologies and tools. However, even though Web 2.0 and progressive social-networking technologies are automatically associated......Advances in Information and Communications Technology (ICT), particularly the so-called Web 2.0, are affecting all aspects of our life: how we communicate, how we shop, how we socialise, and how we learn. Facilitating learning through the use of ICT, also known as eLearning, is a vital part...... with ideals such as collaboration, sharing, and active learning, it is also possible to use them in a very conservative, teacher-centred way limiting thus their impact. In this paper, we present a PBL 2.0 framework, i.e., a framework combining PBL practices with Web 2.0 technologies. More specifically, we (a...

Editorial (special issue on CALL, e-learning and m-learning

Directory of Open Access Journals (Sweden)

Jo Mynard

2011-09-01

Full Text Available Technology has, in one form of another, been a part of self-access learning since the very first self-access centres (SACs of the 1980s. Some of the better-funded centres featured elaborate listening and recording machinery and (occasionally early personal computers. Early software programmes and language-learning websites available for self-access use tended to be aimed at individual study, initially following the language lab model, and were often designed to teach or test discrete language points. Of course, in 2011 programmes aimed at individual study do still exist and certainly have a place in self-access learning, particularly if a learner has identified a target language area that the software or website covers. However, in this special issue we go beyond language learning software and look at tools and technologies currently available to the learner as self-access resources.

Significant Learning and Civic Education: Shifting Frameworks for Teaching in Light of Learning about the Financial Crisis

Directory of Open Access Journals (Sweden)

KimMarie McGoldrick

2011-10-01

Full Text Available The recent financial crisis has motivated economic educators to rethink what economics should be taught, acknowledging disconnects between classroom content and real world events. We introduce a learning theory approach that is broader, one that goes beyond such context specific discussions of foundational knowledge and application (i.e., teaching about this specific crisis and provide a framework to address the broader issue of how teaching practices can, by their very nature, minimize such disconnects and provide more effective processes for teaching about current economic conditions. The theory of significant learning (Fink 2003 is presented as a model of how experiences can be used to develop a deep approach to learning, learning that lasts. Experiential learning pedagogies are timeless in that they can be readily modified to promote deeper understanding over a wide range of economic environments. Focusing on one category of significant learning, the human dimension, and one component of the financial crisis, unemployment, examples which modify existing experiential learning practices are described to demonstrate how such pedagogic practices can be readily adapted to teaching and learning about current economic conditions. In short, we demonstrate that incorporating student experiences into pedagogic practice provides a natural alignment of teaching content and real world events, regardless of how those change over time.

A framework for learning and planning against switching strategies in repeated games

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Hernandez-Leal, Pablo; Munoz de Cote, Enrique; Sucar, L. Enrique

2014-04-01

Intelligent agents, human or artificial, often change their behaviour as they interact with other agents. For an agent to optimise its performance when interacting with such agents, it must be capable of detecting and adapting according to such changes. This work presents an approach on how to effectively deal with non-stationary switching opponents in a repeated game context. Our main contribution is a framework for online learning and planning against opponents that switch strategies. We present how two opponent modelling techniques work within the framework and prove the usefulness of the approach experimentally in the iterated prisoner's dilemma, when the opponent is modelled as an agent that switches between different strategies (e.g. TFT, Pavlov and Bully). The results of both models were compared against each other and against a state-of-the-art non-stationary reinforcement learning technique. Results reflect that our approach obtains competitive results without needing an offline training phase, as opposed to the state-of-the-art techniques.

A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

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Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-09-01

Exascale-level simulations require fault-resilient algorithms that are robust against repeated and expected software and/or hardware failures during computations, which may render the simulation results unsatisfactory. If each processor can share some global information about the simulation from a coarse, limited accuracy but relatively costless auxiliary simulator we can effectively fill-in the missing spatial data at the required times by a statistical learning technique - multi-level Gaussian process regression, on the fly; this has been demonstrated in previous work [1]. Based on the previous work, we also employ another (nonlinear) statistical learning technique, Diffusion Maps, that detects computational redundancy in time and hence accelerate the simulation by projective time integration, giving the overall computation a "patch dynamics" flavor. Furthermore, we are now able to perform information fusion with multi-fidelity and heterogeneous data (including stochastic data). Finally, we set the foundations of a new framework in CFD, called patch simulation, that combines information fusion techniques from, in principle, multiple fidelity and resolution simulations (and even experiments) with a new adaptive timestep refinement technique. We present two benchmark problems (the heat equation and the Navier-Stokes equations) to demonstrate the new capability that statistical learning tools can bring to traditional scientific computing algorithms. For each problem, we rely on heterogeneous and multi-fidelity data, either from a coarse simulation of the same equation or from a stochastic, particle-based, more "microscopic" simulation. We consider, as such "auxiliary" models, a Monte Carlo random walk for the heat equation and a dissipative particle dynamics (DPD) model for the Navier-Stokes equations. More broadly, in this paper we demonstrate the symbiotic and synergistic combination of statistical learning, domain decomposition, and scientific computing in

Exercise, character strengths, well-being, and learning climate in the prediction of performance over a 6-month period at a call center.

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Moradi, Saleh; Nima, Ali A; Rapp Ricciardi, Max; Archer, Trevor; Garcia, Danilo

2014-01-01

Performance monitoring might have an adverse influence on call center agents' well-being. We investigate how performance, over a 6-month period, is related to agents' perceptions of their learning climate, character strengths, well-being (subjective and psychological), and physical activity. Agents (N = 135) self-reported perception of the learning climate (Learning Climate Questionnaire), character strengths (Values In Action Inventory Short Version), well-being (Positive Affect, Negative Affect Schedule, Satisfaction With Life Scale, Psychological Well-Being Scales Short Version), and how often/intensively they engaged in physical activity. Performance, "time on the phone," was monitored for 6 consecutive months by the same system handling the calls. Performance was positively related to having opportunities to develop, the character strengths clusters of Wisdom and Knowledge (e.g., curiosity for learning, perspective) and Temperance (e.g., having self-control, being prudent, humble, and modest), and exercise frequency. Performance was negatively related to the sense of autonomy and responsibility, contentedness, the character strengths clusters of Humanity and Love (e.g., helping others, cooperation) and Justice (e.g., affiliation, fairness, leadership), positive affect, life satisfaction and exercise Intensity. Call centers may need to create opportunities to develop to increase agents' performance and focus on individual differences in the recruitment and selection of agents to prevent future shortcomings or worker dissatisfaction. Nevertheless, performance measurement in call centers may need to include other aspects that are more attuned with different character strengths. After all, allowing individuals to put their strengths at work should empower the individual and at the end the organization itself. Finally, physical activity enhancement programs might offer considerable positive work outcomes.

Exercise, Character Strengths, Well-Being and Learning Climate in the Prediction of Performance over a Six-Month Period at a Call Center

Directory of Open Access Journals (Sweden)

Saleh eMoradi

2014-06-01

Full Text Available Background: Performance monitoring might have an adverse influence on call center agents’ well-being. We investigate how performance, over a six-month period, is related to agents’ perceptions of their learning climate, character strengths, well-being (subjective and psychological, and physical activity.Method: Agents (N = 135 self-reported perception of the learning climate (Learning Climate Questionnaire, character strengths (Values In Action Inventory Short Version, well-being (Positive Affect, Negative Affect Schedule, Satisfaction With Life Scale, Psychological Well-Being Scales Short Version, and how often/intensively they engaged in physical activity. Performance, time on the phone, was monitored for six consecutive months by the same system handling the calls. Results: Performance was positively related to having opportunities to develop, the character strengths clusters of Wisdom and Knowledge (e.g., curiosity for learning, perspective and Temperance (e.g., having self-control, being prudent, humble, and modest, and exercise frequency. Performance was negatively related to the sense of autonomy and responsibility, contentedness, the character strengths clusters of Humanity and Love (e.g., helping others, cooperation and Justice (e.g., affiliation, fairness, leadership, positive affect, life satisfaction and exercise Intensity.Conclusion: Call centers may need to create opportunities to develop to increase agents’ performance and focus on individual differences in the recruitment and selection of agents to prevent future shortcomings or worker dissatisfaction. Nevertheless, performance measurement in call centers may need to include other aspects that are more attuned with different character strengths. After all, allowing individuals to put their strengths at work should empower the individual and at the end the organization itself. Finally, physical activity enhancement programs might offer considerable positive work outcomes.

Application of Resource Description Framework to Personalise Learning: Systematic Review and Methodology

Science.gov (United States)

Jevsikova, Tatjana; Berniukevicius, Andrius; Kurilovas, Eugenijus

2017-01-01

The paper is aimed to present a methodology of learning personalisation based on applying Resource Description Framework (RDF) standard model. Research results are two-fold: first, the results of systematic literature review on Linked Data, RDF "subject-predicate-object" triples, and Web Ontology Language (OWL) application in education…

The Learner, the Media and the Community: How Does Learning Take Place in the Other CALL Triangle?

Science.gov (United States)

Sockett, Geoffrey

2012-01-01

In this research project, students in applied linguistics were asked to keep blogs over a three-month period in which they reported on their online informal learning of English through activities such as social networking, downloading films and TV series and listening to music on demand. The study is situated within the framework of complexity…

Analytical framework and tool kit for SEA follow-up

International Nuclear Information System (INIS)

Nilsson, Mans; Wiklund, Hans; Finnveden, Goeran; Jonsson, Daniel K.; Lundberg, Kristina; Tyskeng, Sara; Wallgren, Oskar

2009-01-01

Most Strategic Environmental Assessment (SEA) research and applications have so far neglected the ex post stages of the process, also called SEA follow-up. Tool kits and methodological frameworks for engaging effectively with SEA follow-up have been conspicuously missing. In particular, little has so far been learned from the much more mature evaluation literature although many aspects are similar. This paper provides an analytical framework and tool kit for SEA follow-up. It is based on insights and tools developed within programme evaluation and environmental systems analysis. It is also grounded in empirical studies into real planning and programming practices at the regional level, but should have relevance for SEA processes at all levels. The purpose of the framework is to promote a learning-oriented and integrated use of SEA follow-up in strategic decision making. It helps to identify appropriate tools and their use in the process, and to systematise the use of available data and knowledge across the planning organization and process. It distinguishes three stages in follow-up: scoping, analysis and learning, identifies the key functions and demonstrates the informational linkages to the strategic decision-making process. The associated tool kit includes specific analytical and deliberative tools. Many of these are applicable also ex ante, but are then used in a predictive mode rather than on the basis of real data. The analytical element of the framework is organized on the basis of programme theory and 'DPSIR' tools. The paper discusses three issues in the application of the framework: understanding the integration of organizations and knowledge; understanding planners' questions and analytical requirements; and understanding interests, incentives and reluctance to evaluate

Impact of Using CALL on Iranian EFL Learners' Vocabulary Knowledge

Science.gov (United States)

Yunus, Melor Md; Salehi, Hadi; Amini, Mahdi

2016-01-01

Computer Assisted Language Learning (CALL) integration in EFL contexts has intensified noticeably in recent years. This integration might be in different ways and for different purposes such as vocabulary acquisition, grammar learning, phonology, writing skills, etc. More explicitly, this study is an attempt to explore the effect of using CALL on…

Defining a risk-informed framework for whole-of-government lessons learned: A Canadian perspective.

Science.gov (United States)

Friesen, Shaye K; Kelsey, Shelley; Legere, J A Jim

Lessons learned play an important role in emergency management (EM) and organizational agility. Virtually all aspects of EM can derive benefit from a lessons learned program. From major security events to exercises, exploiting and applying lessons learned and "best practices" is critical to organizational resilience and adaptiveness. A robust lessons learned process and methodology provides an evidence base with which to inform decisions, guide plans, strengthen mitigation strategies, and assist in developing tools for operations. The Canadian Safety and Security Program recently supported a project to define a comprehensive framework that would allow public safety and security partners to regularly share event response best practices, and prioritize recommendations originating from after action reviews. This framework consists of several inter-locking elements: a comprehensive literature review/environmental scan of international programs; a survey to collect data from end users and management; the development of a taxonomy for organizing and structuring information; a risk-informed methodology for selecting, prioritizing, and following through on recommendations; and standardized templates and tools for tracking recommendations and ensuring implementation. This article discusses the efforts of the project team, which provided "best practice" advice and analytical support to ensure that a systematic approach to lessons learned was taken by the federal community to improve prevention, preparedness, and response activities. It posits an approach by which one might design a systematic process for information sharing and event response coordination-an approach that will assist federal departments to institutionalize a cross-government lessons learned program.

Critical Thinking and Collaboration: A Strategy to Enhance Student Learning

Directory of Open Access Journals (Sweden)

Ronald A. Styron, Jr.

2014-12-01

Full Text Available In numerous studies relative to collaboration and critical thinking, an instructional strategy called Team- Based Learning has proven to be an effective approach to teaching and learning. Team-Based Learning utilizes a specific sequence of individual work, group work and immediate feedback to create a motivational framework in which students increasingly hold each other accountable for coming to class prepared and contributing to discussion. Using an action research conceptual model diffusion of innovation theory, the process of P-20 quality enhancement using Team-Based Learning is examined.

Conceptual Frameworks in Didactics--Learning and Teaching: Trends, Evolutions and Comparative Challenges

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Ligozat, Florence; Almqvist, Jonas

2018-01-01

This special issue of the "European Educational Research Journal" presents a series of research papers reflecting the trends and evolutions in conceptual frameworks that took place within the EERA 27 "Didactics--Learning and Teaching" network during its first ten years of existence. Most conceptual tools used in this field were…

A Framework for Evaluating and Enhancing Alignment in Self-Regulated Learning Research

Science.gov (United States)

Dent, Amy L.; Hoyle, Rick H.

2015-01-01

We discuss the articles of this special issue with reference to an important yet previously only implicit dimension of study quality: alignment across the theoretical and methodological decisions that collectively define an approach to self-regulated learning. Integrating and extending work by leaders in the field, we propose a framework for…

SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications.

Directory of Open Access Journals (Sweden)

Ahmad Karim

Full Text Available Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS, disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.

SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications.

Science.gov (United States)

Karim, Ahmad; Salleh, Rosli; Khan, Muhammad Khurram

2016-01-01

Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.

SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications

Science.gov (United States)

Karim, Ahmad; Salleh, Rosli; Khan, Muhammad Khurram

2016-01-01

Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks’ back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps’ detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies. PMID:26978523

Learning from instructional explanations: effects of prompts based on the active-constructive-interactive framework.

Science.gov (United States)

Roelle, Julian; Müller, Claudia; Roelle, Detlev; Berthold, Kirsten

2015-01-01

Although instructional explanations are commonly provided when learners are introduced to new content, they often fail because they are not integrated into effective learning activities. The recently introduced active-constructive-interactive framework posits an effectiveness hierarchy in which interactive learning activities are at the top; these are then followed by constructive and active learning activities, respectively. Against this background, we combined instructional explanations with different types of prompts that were designed to elicit these learning activities and tested the central predictions of the active-constructive-interactive framework. In Experiment 1, N = 83 students were randomly assigned to one of four combinations of instructional explanations and prompts. To test the active learning hypothesis, the learners received either (1) complete explanations and engaging prompts designed to elicit active activities or (2) explanations that were reduced by inferences and inference prompts designed to engage learners in constructing the withheld information. Furthermore, in order to explore how interactive learning activities can be elicited, we gave the learners who had difficulties in constructing the prompted inferences adapted remedial explanations with either (3) unspecific engaging prompts or (4) revision prompts. In support of the active learning hypothesis, we found that the learners who received reduced explanations and inference prompts outperformed the learners who received complete explanations and engaging prompts. Moreover, revision prompts were more effective in eliciting interactive learning activities than engaging prompts. In Experiment 2, N = 40 students were randomly assigned to either (1) a reduced explanations and inference prompts or (2) a reduced explanations and inference prompts plus adapted remedial explanations and revision prompts condition. In support of the constructive learning hypothesis, the learners who received

Active Learning Framework for Non-Intrusive Load Monitoring: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jin, Xin

2016-05-16

Non-Intrusive Load Monitoring (NILM) is a set of techniques that estimate the electricity usage of individual appliances from power measurements taken at a limited number of locations in a building. One of the key challenges in NILM is having too much data without class labels yet being unable to label the data manually for cost or time constraints. This paper presents an active learning framework that helps existing NILM techniques to overcome this challenge. Active learning is an advanced machine learning method that interactively queries a user for the class label information. Unlike most existing NILM systems that heuristically request user inputs, the proposed method only needs minimally sufficient information from a user to build a compact and yet highly representative load signature library. Initial results indicate the proposed method can reduce the user inputs by up to 90% while still achieving similar disaggregation performance compared to a heuristic method. Thus, the proposed method can substantially reduce the burden on the user, improve the performance of a NILM system with limited user inputs, and overcome the key market barriers to the wide adoption of NILM technologies.

Factors Influencing the Use of Learning Management System in Saudi Arabian Higher Education: A Theoretical Framework

Science.gov (United States)

Asiri, Mohammed J. Sherbib; Mahmud, Rosnaini bt; Bakar, Kamariah Abu; Ayub, Ahmad Fauzi bin Mohd

2012-01-01

The purpose of this paper is to present the theoretical framework underlying a research on factors that influence utilization of the Jusur Learning Management System (Jusur LMS) in Saudi Arabian public universities. Development of the theoretical framework was done based on library research approach. Initially, the existing literature relevant to…

A Machine LearningFramework to Forecast Wave Conditions

Science.gov (United States)

Zhang, Y.; James, S. C.; O'Donncha, F.

2017-12-01

Recently, significant effort has been undertaken to quantify and extract wave energy because it is renewable, environmental friendly, abundant, and often close to population centers. However, a major challenge is the ability to accurately and quickly predict energy production, especially across a 48-hour cycle. Accurate forecasting of wave conditions is a challenging undertaking that typically involves solving the spectral action-balance equation on a discretized grid with high spatial resolution. The nature of the computations typically demands high-performance computing infrastructure. Using a case-study site at Monterey Bay, California, a machine learning framework was trained to replicate numerically simulated wave conditions at a fraction of the typical computational cost. Specifically, the physics-based Simulating WAves Nearshore (SWAN) model, driven by measured wave conditions, nowcast ocean currents, and wind data, was used to generate training data for machine learning algorithms. The model was run between April 1st, 2013 and May 31st, 2017 generating forecasts at three-hour intervals yielding 11,078 distinct model outputs. SWAN-generated fields of 3,104 wave heights and a characteristic period could be replicated through simple matrix multiplications using the mapping matrices from machine learning algorithms. In fact, wave-height RMSEs from the machine learning algorithms (9 cm) were less than those for the SWAN model-verification exercise where those simulations were compared to buoy wave data within the model domain (>40 cm). The validated machine learning approach, which acts as an accurate surrogate for the SWAN model, can now be used to perform real-time forecasts of wave conditions for the next 48 hours using available forecasted boundary wave conditions, ocean currents, and winds. This solution has obvious applications to wave-energy generation as accurate wave conditions can be forecasted with over a three-order-of-magnitude reduction in

Statistical Learning Framework with Adaptive Retraining for Condition-Based Maintenance

International Nuclear Information System (INIS)

An, Sang Ha; Chang, Soon Heung; Heo, Gyun Young; Seo, Ho Joon; Kim, Su Young

2009-01-01

As systems become more complex and more critical in our daily lives, the need for the maintenance based on the reliable monitoring and diagnosis has become more apparent. However, in reality, the general opinion has been that 'maintenance is a necessary evil' or 'nothing can be done to improve maintenance costs'. Perhaps these were true statements twenty years ago when many of the diagnostic technologies were not fully developed. The developments of microprocessor or computer based instrumentation that can be used to monitor the operating condition of plant equipment, machinery and systems have provided the means to manage the maintenance operation. They have provided the means to reduce or eliminate unnecessary repairs, prevent catastrophic machine failures and reduce the negative impact of the maintenance operation on the profitability of manufacturing and production plants. Condition-based maintenance (CBM) techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. Most of the statistical learning techniques are only valid as long as the physics of a system does not change. If any significant change such as the replacement of a component or equipment occurs in the system, the statistical learning model should be re-trained or re-developed to adapt the new system. In this research, authors will propose a statistical learning framework which can be applicable for various CBMs, and the concept of the adaptive retraining technique will be described to support the execution of the framework so that the monitoring system does not need to be re-developed or re-trained even though there are any significant changes in the system or component

A pedagogical framework for facilitating parents' learning in nurse-parent partnership.

Science.gov (United States)

Hopwood, Nick; Clerke, Teena; Nguyen, Anne

2018-04-01

Nursing work increasingly demands forms of expertise that complement specialist knowledge. In child and family nursing, this need arises when nurses work in partnership with parents of young children at risk. Partnership means working with parents in respectful, negotiated and empowering ways. Existing partnership literature emphasises communicative and relational skills, but this paper focuses on nurses' capacities to facilitate parents' learning. Referring to data from home visiting, day-stay and specialist toddler clinic services in Sydney, a pedagogical framework is presented. Analysis shows how nurses notice aspects of children, parents and parent-child interactions as a catalyst for building on parents' strengths, enhancing guided chance or challenging unhelpful constructs. Prior research shows the latter can be a sticking point in partnership, but this paper reveals diverse ways in which challenges are folded into learning process that position parents as agents of positive change. Noticing is dependent on embodied and communicative expertise, conceptualised in terms of sensory and reported channels. The framework offers a new view of partnership as mind-expanding for the parent and specifies the nurse's role in facilitating this process. © 2017 John Wiley & Sons Ltd.

Designing Learning for Co-Creation

DEFF Research Database (Denmark)

Gnaur, Dorina; Larsen-Nielsen, Marie

2017-01-01

Designing learning for co-creation - conceptual and practical considerations, Dorina Gnaur and Inger Marie Larsen-Nielsen explore the practical educational point of view. The question they are posing themselves is: how can higher and further education (HE) educate for co-creation, that is, provide...... educational frameworks that respond to the societal demand for co-creation, particularly within the public welfare sector? First, they focus on which organisational and individual requirements an HE learning design should take into account in order to support the diffusion of co-creation competences....... Then they argue for the need to integrate these considerations in the learning design and demonstrate a practical application in the form of a didactical design. They call this a hybrid learning design, in that it takes advantage of technological developments to mediate co-creative learning in multiple learning...

A Conceptual Framework for the Cultural Integration of Cooperative Learning: A Thai Primary Mathematics Education Perspective

Science.gov (United States)

Park, Ji Yong; Nuntrakune, Tippawan

2013-01-01

The Thailand education reform adopted cooperative learning to improve the quality of education. However, it has been reported that the introduction and maintenance of cooperative learning has been difficult and uncertain because of the cultural differences. The study proposed a conceptual framework developed based on making a connection between…

Teacher Competencies for the Implementation of Collaborative Learning in the Classroom: A Framework and Research Review

Science.gov (United States)

Kaendler, Celia; Wiedmann, Michael; Rummel, Nikol; Spada, Hans

2015-01-01

This article describes teacher competencies for implementing collaborative learning in the classroom. Research has shown that the effectiveness of collaborative learning largely depends on the quality of student interaction. We therefore focus on what a "teacher" can do to foster student interaction. First, we present a framework that…

CALL in the Year 2000: A Look Back from 2016

Science.gov (United States)

Chapelle, Carol A.

2016-01-01

This commentary offers a brief reflection on the state of CALL in 1997, when "Language Learning & Technology" was launched with my paper entitled "CALL in the year 2000: Still in search of research paradigms?" The point of my 1997 paper was to suggest the potential value of research on second language learning for the study…

SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.

Science.gov (United States)

Liu, Jing; Zhao, Songzheng; Wang, Gang

2018-01-01

With the development of Web 2.0 technology, social media websites have become lucrative but under-explored data sources for extracting adverse drug events (ADEs), which is a serious health problem. Besides ADE, other semantic relation types (e.g., drug indication and beneficial effect) could hold between the drug and adverse event mentions, making ADE relation extraction - distinguishing ADE relationship from other relation types - necessary. However, conducting ADE relation extraction in social media environment is not a trivial task because of the expertise-dependent, time-consuming and costly annotation process, and the feature space's high-dimensionality attributed to intrinsic characteristics of social media data. This study aims to develop a framework for ADE relation extraction using patient-generated content in social media with better performance than that delivered by previous efforts. To achieve the objective, a general semi-supervised ensemble learning framework, SSEL-ADE, was developed. The framework exploited various lexical, semantic, and syntactic features, and integrated ensemble learning and semi-supervised learning. A series of experiments were conducted to verify the effectiveness of the proposed framework. Empirical results demonstrate the effectiveness of each component of SSEL-ADE and reveal that our proposed framework outperforms most of existing ADE relation extraction methods The SSEL-ADE can facilitate enhanced ADE relation extraction performance, thereby providing more reliable support for pharmacovigilance. Moreover, the proposed semi-supervised ensemble methods have the potential of being applied to effectively deal with other social media-based problems. Copyright © 2017 Elsevier B.V. All rights reserved.

Intergenerational Learning at a Nature Center: Families Using Prior Experiences and Participation Frameworks to Understand Raptors

Science.gov (United States)

Zimmerman, Heather Toomey; McClain, Lucy Richardson

2014-01-01

Using a sociocultural framework to approach intergenerational learning, this inquiry examines learning processes used by families during visits to one nature center. Data were collected from videotaped observations of families participating in an environmental education program and a follow-up task to draw the habitat of raptors. Based on a…

Lunar phases and crisis center telephone calls.

Science.gov (United States)

Wilson, J E; Tobacyk, J J

1990-02-01

The lunar hypothesis, that is, the notion that lunar phases can directly affect human behavior, was tested by time-series analysis of 4,575 crisis center telephone calls (all calls recorded for a 6-month interval). As expected, the lunar hypothesis was not supported. The 28-day lunar cycle accounted for less than 1% of the variance of the frequency of crisis center calls. Also, as hypothesized from an attribution theory framework, crisis center workers reported significantly greater belief in lunar effects than a non-crisis-center-worker comparison group.

Unpacking Virtual and Intercultural Spaces: A Presentation of a Conceptual Framework to Investigate the Connection between Technology and Intercultural Learning

DEFF Research Database (Denmark)

Pedersen, Rikke; Jørgensen, Mette; Harrison, Roger

This paper presents a framework for the development of research within the emerging areas of internationalisation and technology that connect to build potential learning spaces within intercultural and global settings.......This paper presents a framework for the development of research within the emerging areas of internationalisation and technology that connect to build potential learning spaces within intercultural and global settings....

A deep learning and novelty detection framework for rapid phenotyping in high-content screening

Science.gov (United States)

Sommer, Christoph; Hoefler, Rudolf; Samwer, Matthias; Gerlich, Daniel W.

2017-01-01

Supervised machine learning is a powerful and widely used method for analyzing high-content screening data. Despite its accuracy, efficiency, and versatility, supervised machine learning has drawbacks, most notably its dependence on a priori knowledge of expected phenotypes and time-consuming classifier training. We provide a solution to these limitations with CellCognition Explorer, a generic novelty detection and deep learning framework. Application to several large-scale screening data sets on nuclear and mitotic cell morphologies demonstrates that CellCognition Explorer enables discovery of rare phenotypes without user training, which has broad implications for improved assay development in high-content screening. PMID:28954863

Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept

OpenAIRE

Cooper, Katelyn M.; Ashley, Michael; Brownell, Sara E.

2017-01-01

There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to studen...

Help Options in CALL: A Systematic Review

Science.gov (United States)

Cardenas-Claros, Monica S.; Gruba, Paul A.

2009-01-01

This paper is a systematic review of research investigating help options in the different language skills in computer-assisted language learning (CALL). In this review, emerging themes along with is-sues affecting help option research are identified and discussed. We argue that help options in CALL are application resources that do not only seem…

Controlling misses and false alarms in a machine learning framework for predicting uniformity of printed pages

Science.gov (United States)

Nguyen, Minh Q.; Allebach, Jan P.

2015-01-01

In our previous work1 , we presented a block-based technique to analyze printed page uniformity both visually and metrically. The features learned from the models were then employed in a Support Vector Machine (SVM) framework to classify the pages into one of the two categories of acceptable and unacceptable quality. In this paper, we introduce a set of tools for machine learning in the assessment of printed page uniformity. This work is primarily targeted to the printing industry, specifically the ubiquitous laser, electrophotographic printer. We use features that are well-correlated with the rankings of expert observers to develop a novel machine learning framework that allows one to achieve the minimum "false alarm" rate, subject to a chosen "miss" rate. Surprisingly, most of the research that has been conducted on machine learning does not consider this framework. During the process of developing a new product, test engineers will print hundreds of test pages, which can be scanned and then analyzed by an autonomous algorithm. Among these pages, most may be of acceptable quality. The objective is to find the ones that are not. These will provide critically important information to systems designers, regarding issues that need to be addressed in improving the printer design. A "miss" is defined to be a page that is not of acceptable quality to an expert observer that the prediction algorithm declares to be a "pass". Misses are a serious problem, since they represent problems that will not be seen by the systems designers. On the other hand, "false alarms" correspond to pages that an expert observer would declare to be of acceptable quality, but which are flagged by the prediction algorithm as "fails". In a typical printer testing and development scenario, such pages would be examined by an expert, and found to be of acceptable quality after all. "False alarm" pages result in extra pages to be examined by expert observers, which increases labor cost. But "false

Factors Affecting the Normalization of CALL in Chinese Senior High Schools

Science.gov (United States)

He, Bi; Puakpong, Nattaya; Lian, Andrew

2015-01-01

With the development of Information Technology, increasing attention has been paid to Computer Assisted Language Learning (CALL). Meanwhile, increasing enthusiasm is seen for English learning and teaching in China. Yet, few research studies have focused on the normalization of CALL in ethnically diverse areas. In response to this research gap,…

HCI^2 Framework: A software framework for multimodal human-computer interaction systems

NARCIS (Netherlands)

Shen, Jie; Pantic, Maja

2013-01-01

This paper presents a novel software framework for the development and research in the area of multimodal human-computer interface (MHCI) systems. The proposed software framework, which is called the HCI∧2 Framework, is built upon publish/subscribe (P/S) architecture. It implements a

Factors Hindering the Integration of CALL in a Tertiary Institution

Directory of Open Access Journals (Sweden)

Izaham Shah Ismail

2008-12-01

Full Text Available The field of Computer Assisted Language Learning (CALL is a field that is constantly evolving as it is very much dependent on the advancement of computer technologies. With new technologies being invented almost every day, experts in the field are looking for ways to apply these new technologies in the language classroom. Despite that, teachers are said to be slow at adopting technology in their classrooms and language teachers, whether at schools or tertiary institutions, are no exception. This study attempts to investigate the factors that hinder ESL instructors at an institution of higher learning from integrating CALL in their lessons. Interviews were conducted with five ESL instructors and results revealed that factors which hinder them from integrating CALL in their teaching are universal factors such as knowledge in technology and pedagogy, computer facilities and resources, absence of exemplary integration of CALL, personal beliefs on language teaching, views on the role of a computers as teacher, and evaluation of learning outcomes.

The Predictive Relationship among the Community of Inquiry Framework, Perceived Learning and Online, and Graduate Students' Course Grades in Online Synchronous and Asynchronous Courses

Science.gov (United States)

Rockinson-Szapkiw, Amanda J.; Wendt, Jillian; Wighting, Mervyn; Nisbet, Deanna

2016-01-01

The Community of Inquiry framework has been widely supported by research to provide a model of online learning that informs the design and implementation of distance learning courses. However, the relationship between elements of the CoI framework and perceived learning warrants further examination as a predictive model for online graduate student…

Multimedia Based E-learning : Design and Integration of Multimedia Content in E-learning

Directory of Open Access Journals (Sweden)

Abdulaziz Omar Alsadhan

2014-05-01

Full Text Available The advancement in multimedia and information technologies also have impacted the way of imparting education. This advancement has led to rapid use of e learning systems and has enabled greater integration of multimedia content into e learning systems. This paper present a model for development of e learning systems based on multimedia content. The model is called “Multimedia based e learning” and is loosely based on waterfall software development model. This model consists of three distinct phases; Multimedia Content Modelling, Multimedia content Development, Multimedia content Integration. These three phases are further sub divided into 7 different activities which are analysis, design, technical requirements, content development, content production & integration, implementation and evaluation. This model defines a general framework that can be applied for the development of e learning systems across all disciplines and subjects.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

Science.gov (United States)

Bao, Wei; Yue, Jun; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

A Competence-Based Science Learning Framework Illustrated through the Study of Natural Hazards and Disaster Risk Reduction

Science.gov (United States)

Oyao, Sheila G.; Holbrook, Jack; Rannikmäe, Miia; Pagunsan, Marmon M.

2015-01-01

This article proposes a competence-based learning framework for science teaching, applied to the study of "big ideas", in this case to the study of natural hazards and disaster risk reduction (NH&DRR). The framework focuses on new visions of competence, placing emphasis on nurturing connectedness and behavioral actions toward…

Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

Science.gov (United States)

Kagawa, Rina; Kawazoe, Yoshimasa; Ida, Yusuke; Shinohara, Emiko; Tanaka, Katsuya; Imai, Takeshi; Ohe, Kazuhiko

2017-07-01

Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects. We propose a practical phenotyping framework using both expert knowledge and a machine learning approach to develop 2 phenotyping algorithms: one is for screening; the other is for identifying research subjects. We employ expert knowledge as rules to exclude obvious control patients and machine learning to increase accuracy for complicated patients. We developed phenotyping algorithms on the basis of our framework and performed binary classification to determine whether a patient has T2DM. To facilitate development of practical phenotyping algorithms, this study introduces new evaluation metrics: area under the precision-sensitivity curve (AUPS) with a high sensitivity and AUPS with a high positive predictive value. The proposed phenotyping algorithms based on our framework show higher performance than baseline algorithms. Our proposed framework can be used to develop 2 types of phenotyping algorithms depending on the tuning approach: one for screening, the other for identifying research subjects. We develop a novel phenotyping framework that can be easily implemented on the basis of proper evaluation metrics, which are in accordance with users' objectives. The phenotyping algorithms based on our framework are useful for extraction of T2DM patients in retrospective studies.

The Piagetian "Schème": A Framework to Study Professional Learning through Conceptualization

Science.gov (United States)

Tourmen, Claire; Holgado, Otilia; Métral, Jean-françois; Mayen, Patrick; Olry, Paul

2017-01-01

Different theories of learning have been used in vocational education studies and Piaget is a common source of reference. Our intent is to present a specific and original way in which the Piagetian theory of "schèmes" has been developed since the 1990s in studies called "vocational didactics." Developed in French-speaking…

RAPPORT-BUILDING THROUGH CALL IN TEACHING CHINESE AS A FOREIGN LANGUAGE: AN EXPLORATORY STUDY

Directory of Open Access Journals (Sweden)

Wenying Jiang

2005-05-01

Full Text Available Technological advances have brought about the ever-increasing utilisation of computer-assisted language learning (CALL media in the learning of a second language (L2. Computer-mediated communication, for example, provides a practical means for extending the learning of spoken language, a challenging process in tonal languages such as Chinese, beyond the realms of the classroom. In order to effectively improve spoken language competency, however, CALL applications must also reproduce the social interaction that lies at the heart of language learning and language use. This study draws on data obtained from the utilisation of CALL in the learning of L2 Chinese to explore whether this medium can be used to extend opportunities for rapport-building in language teaching beyond the face-to-face interaction of the classroom. Rapport's importance lies in its potential to enhance learning, motivate learners, and reduce learner anxiety. To date, CALL's potential in relation to this facet of social interaction remains a neglected area of research. The results of this exploratory study suggest that CALL may help foster learner-teacher rapport and that scaffolding, such as strategically composing rapport-fostering questions in sound-files, is conducive to this outcome. The study provides an instruction model for this application of CALL.

Zebra finch mates use their forebrain song system in unlearned call communication.

Science.gov (United States)

Ter Maat, Andries; Trost, Lisa; Sagunsky, Hannes; Seltmann, Susanne; Gahr, Manfred

2014-01-01

Unlearned calls are produced by all birds whereas learned songs are only found in three avian taxa, most notably in songbirds. The neural basis for song learning and production is formed by interconnected song nuclei: the song control system. In addition to song, zebra finches produce large numbers of soft, unlearned calls, among which "stack" calls are uttered frequently. To determine unequivocally the calls produced by each member of a group, we mounted miniature wireless microphones on each zebra finch. We find that group living paired males and females communicate using bilateral stack calling. To investigate the role of the song control system in call-based male female communication, we recorded the electrical activity in a premotor nucleus of the song control system in freely behaving male birds. The unique combination of acoustic monitoring together with wireless brain recording of individual zebra finches in groups shows that the neuronal activity of the song system correlates with the production of unlearned stack calls. The results suggest that the song system evolved from a brain circuit controlling simple unlearned calls to a system capable of producing acoustically rich, learned vocalizations.

Mature women and the New Zealand qualifications framework. realising the potential of recognising prior learning

OpenAIRE

Kamp, Annelies

2003-01-01

Against a backtground of 'second-wave' lifelong learning in Aotearoa New Zealand a new framework for post-compulsory national qualfications was introduced. The restulting competency-based system was argued to present a number of benefits for mature women including flexibility in curriculum and delivery and portability across educational sectors. Competency-based education was to include provision for recognition of prior skills and knowledge gained in formal learning environments and the work...

An Instructional Design Framework to Improve Student Learning in a First-Year Engineering Class

Science.gov (United States)

Yelamarthi, Kumar; Drake, Eron; Prewett, Matthew

2016-01-01

Increasingly, numerous universities have identified benefits of flipped learning environments and have been encouraging instructors to adapt such methodologies in their respective classrooms, at a time when departments are facing significant budget constraints. This article proposes an instructional design framework utilized to strategically…

A Draft Conceptual Framework of Relevant Theories to Inform Future Rigorous Research on Student Service-Learning Outcomes

Science.gov (United States)

Whitley, Meredith A.

2014-01-01

While the quality and quantity of research on service-learning has increased considerably over the past 20 years, researchers as well as governmental and funding agencies have called for more rigor in service-learning research. One key variable in improving rigor is using relevant existing theories to improve the research. The purpose of this…

An Instructional Design Framework to Improve Student Learning in a First-Year Engineering Class

Directory of Open Access Journals (Sweden)

Kumar Yelamarthi

2016-12-01

Full Text Available Increasingly, numerous universities have identified benefits of flipped learning environments and have been encouraging instructors to adapt such methodologies in their respective classrooms, at a time when departments are facing significant budget constraints. This article proposes an instructional design framework utilized to strategically enhance traditional flipped methodologies in a first-year engineering course, by using low-cost technology aids and proven pedagogical techniques to enhance student learning. Implemented in a first-year engineering course, this modified flipped model demonstrated an improved student awareness of essential engineering concepts and improved academic performance through collaborative and active learning activities, including flipped learning methodologies, without the need for expensive, formal active learning spaces. These findings have been validated through two studies and have shown similar results confirming that student learning is improved by the implementation of multi-pedagogical strategies in-formed by the use of an instructional design in a traditional classroom setting.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory

Science.gov (United States)

Bao, Wei; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day’s closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance. PMID:28708865

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

Directory of Open Access Journals (Sweden)

Wei Bao

Full Text Available The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT, stacked autoencoders (SAEs and long-short term memory (LSTM are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

Yield curve and Recession Forecasting in a Machine Learning Framework

OpenAIRE

Theophilos Papadimitriou; Periklis Gogas; Maria Matthaiou; Efthymia Chrysanthidou

2014-01-01

In this paper, we investigate the forecasting ability of the yield curve in terms of the U.S. real GDP cycle. More specifically, within a Machine Learning (ML) framework, we use data from a variety of short (treasury bills) and long term interest rates (bonds) for the period from 1976:Q3 to 2011:Q4 in conjunction with the real GDP for the same period, to create a model that can successfully forecast output fluctuations (inflation and output gaps) around its long-run trend. We focus our attent...

Criteria for Evaluating a Game-Based CALL Platform

Science.gov (United States)

Ní Chiaráin, Neasa; Ní Chasaide, Ailbhe

2017-01-01

Game-based Computer-Assisted Language Learning (CALL) is an area that currently warrants attention, as task-based, interactive, multimodal games increasingly show promise for language learning. This area is inherently multidisciplinary--theories from second language acquisition, games, and psychology must be explored and relevant concepts from…

Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.

Science.gov (United States)

El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher

2018-01-01

Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.

The ABLe change framework: a conceptual and methodological tool for promoting systems change.

Science.gov (United States)

Foster-Fishman, Pennie G; Watson, Erin R

2012-06-01

This paper presents a new approach to the design and implementation of community change efforts like a System of Care. Called the ABLe Change Framework, the model provides simultaneous attention to the content and process of the work, ensuring effective implementation and the pursuit of systems change. Three key strategies are employed in this model to ensure the integration of content and process efforts and effective mobilization of broad scale systems change: Systemic Action Learning Teams, Simple Rules, and Small Wins. In this paper we describe the ABLe Change Framework and present a case study in which we successfully applied this approach to one system of care effort in Michigan.

Systemic assessment framework of a learning organization's competitive positioning

Directory of Open Access Journals (Sweden)

Wissam EL Hachem

2014-09-01

Full Text Available Purpose: The purpose of this paper is to devise an innovative feasible, replicable and comprehensive assessment framework of a learning organization's competitive positioning. Design/methodology/approach: The three characteristics listed above are approached as follows. Feasible refers to being easy and not in need of much resources (time, personnel,.... This is done through early elimination of non-important variables. Replicable is having a well structured methodology based on scientific proven methods. Following this methodology would result in good results that can be explained if needed and replicated if deemed necessary. Comprehensive translates into a holistic set of indices that measure performance as well as organizational learning. Findings and Originality/value: The three attributes (feasible, replicable and comprehensive have become crucial for ensuring any kind of added value for such a methodology that hopes to tackle the modern dynamic business environment and gaining a sustainable competitive advantage. Research limitations/implications: Such a methodology would require several full contextual applications to be able to set its final design. It entails thorough internal revision of a company's structure. Therefore a great deal of transparency and self-transcendence from the individual involved is a pre-requisite for any chance of success. Originality/value: It offers a systematic way to assess a company's performance/competitive positioning while accounting for the crucial attribute of organizational learning in its makeup.

Interrogating "Belonging" in Belonging, Being and Becoming: The Early Years Learning Framework for Australia

Science.gov (United States)

Sumsion, Jennifer; Wong, Sandie

2011-01-01

In this article, the authors interrogate the use of "belonging" in "Belonging, Being and Becoming: the Early Years Learning Framework for Australia" (EYLF), Australia's first national curriculum for early childhood education and care settings and, from the authors' interrogation, possibilities are offered for thinking about and…

Applying the Quadratic Usage Framework to Research on K-12 STEM Digital Learning Resources

Science.gov (United States)

Luetkemeyer, Jennifer R.

2016-01-01

Numerous policymakers have called for K-12 educators to increase their effectiveness by transforming science, technology, engineering, and mathematics (STEM) learning and teaching with digital resources and tools. In this study we outline the significance of studying pressing issues related to use of digital resources in the K-12 environment and…

A framework for designing a research-based “maths counsellor” teacher programme

DEFF Research Database (Denmark)

Jankvist, Uffe Thomas; Niss, Mogens

2015-01-01

force” of so-called “maths counsellors”, i.e., mathematics teachers whose goal it is to help identify students with genuine learning difficulties in mathematics, investigate the nature of these difficulties, and carry out research-based interventions to assist the students in overcoming them. We present...... and discuss the various components of the programme, theoretical as well as practical, and account for how these make up a framework for designing a research-based “maths counsellor” teacher programme...

Picasso: A Modular Framework for Visualizing the Learning Process of Neural Network Image Classifiers

Directory of Open Access Journals (Sweden)

Ryan Henderson

2017-09-01

Full Text Available Picasso is a free open-source (Eclipse Public License web application written in Python for rendering standard visualizations useful for analyzing convolutional neural networks. Picasso ships with occlusion maps and saliency maps, two visualizations which help reveal issues that evaluation metrics like loss and accuracy might hide: for example, learning a proxy classification task. Picasso works with the Tensorflow deep learning framework, and Keras (when the model can be loaded into the Tensorflow backend. Picasso can be used with minimal configuration by deep learning researchers and engineers alike across various neural network architectures. Adding new visualizations is simple: the user can specify their visualization code and HTML template separately from the application code.

EVALUATION OF CONCEPTUAL FRAMEWORKS IN ASTRONOMY

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David Pundak

2016-02-01

Full Text Available Even though astronomy is the oldest science, it is still an open question how to evaluate students’ understanding in astronomy. In spite of the fact that some methods and evaluation tools have been developed for that purpose, the sources of students' difficulties in astronomy are still unclear. This paper presents an investigation of the changes in conceptual frameworks in astronomy among 50 engineering students as a result of learning a general course in astronomy. A special tool called Conceptual Frameworks in Astronomy (CFA, which was initially used in 1989, was adopted to gather data for the present research. In its new version, the tool includes 23 questions and five to six optional answers to each question. Each of the answers characterizes one of the four conceptual frameworks: pre-scientific, geocentric, heliocentric and sidereal. These four conceptual frameworks act as a taxonomical system that enables us to evaluate astronomical understanding. The paper describes the background of the CFA, its development, and discusses its validity and reliability. Using the CFA we were able to: (1 identify the students’ conceptual frameworks at the beginning of the course and at its end, (2 to evaluate the students’ paradigmatic change following the course. It was found that the measure of the students’ improvement (gain index was g = 0.37. Approximately 45% of the students in the course improved their conceptual frameworks in astronomy and 26% deepened their understanding of the heliocentric or sidereal conceptual frameworks. The CFA can also be applied as an evaluation tool in all schools and institutions that teach astronomy.

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

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Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming

What and how do students learn in an interprofessional student-run clinic? An educational framework for team-based care

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Lie, Désirée A.; Forest, Christopher P.; Walsh, Anne; Banzali, Yvonne; Lohenry, Kevin

2016-01-01

Background The student-run clinic (SRC) has the potential to address interprofessional learning among health professions students. Purpose To derive a framework for understanding student learning during team-based care provided in an interprofessional SRC serving underserved patients. Methods The authors recruited students for a focus group study by purposive sampling and snowballing. They constructed two sets of semi-structured questions for uniprofessional and multiprofessional groups. Sessions were audiotaped, and transcripts were independently coded and adjudicated. Major themes about learning content and processes were extracted. Grounded theory was followed after data synthesis and interpretation to establish a framework for interprofessional learning. Results Thirty-six students from four professions (medicine, physician assistant, occupational therapy, and pharmacy) participated in eight uniprofessional groups; 14 students participated in three multiprofessional groups (N = 50). Theme saturation was achieved. Six common themes about learning content from uniprofessional groups were role recognition, team-based care appreciation, patient experience, advocacy-/systems-based models, personal skills, and career choices. Occupational therapy students expressed self-advocacy, and medical students expressed humility and self-discovery. Synthesis of themes from all groups suggests a learning continuum that begins with the team huddle and continues with shared patient care and social interactions. Opportunity to observe and interact with other professions in action is key to the learning process. Discussion Interprofessional SRC participation promotes learning ‘with, from, and about’ each other. Participation challenges misconceptions and sensitizes students to patient experiences, health systems, advocacy, and social responsibility. Learning involves interprofessional interactions in the patient encounter, reinforced by formal and informal communications

A framework for detection of malicious software in Android handheld systems using machine learning techniques

OpenAIRE

Torregrosa García, Blas

2015-01-01

The present study aims at designing and developing new approaches to detect malicious applications in Android-based devices. More precisely, MaLDroide (Machine Learning-based Detector for Android malware), a framework for detection of Android malware based on machine learning techniques, is introduced here. It is devised to identify malicious applications. Este trabajo tiene como objetivo el diseño y el desarrollo de nuevas formas de detección de aplicaciones maliciosas en los dispositivos...

Developing an integrated framework of problem-based learning and coaching psychology for medical education: a participatory research.

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Wang, Qing; Li, Huiping; Pang, Weiguo; Liang, Shuo; Su, Yiliang

2016-01-05

Medical schools have been making efforts to develop their own problem-based learning (PBL) approaches based on their educational conditions, human resources and existing curriculum structures. This study aimed to explore a new framework by integrating the essential features of PBL and coaching psychology applicable to the undergraduate medical education context. A participatory research design was employed. Four educational psychology researchers, eight undergraduate medical school students and two accredited PBL tutors participated in a four-month research programme. Data were collected through participatory observation, focus groups, semi-structured interviews, workshop documents and feedback surveys and then subjected to thematic content analysis. The triangulation of sources and member checking were used to ensure the credibility and trustworthiness of the research process. Five themes emerged from the analysis: current experience of PBL curriculum; the roles of and relationships between tutors and students; student group dynamics; development of self-directed learning; and coaching in PBL facilitation. On the basis of this empirical data, a systematic model of PBL and coaching psychology was developed. The findings highlighted that coaching psychology could be incorporated into the facilitation system in PBL. The integrated framework of PBL and coaching psychology in undergraduate medical education has the potential to promote the development of the learning goals of cultivating clinical reasoning ability, lifelong learning capacities and medical humanity. Challenges, benefits and future directions for implementing the framework are discussed in this paper.

A Critical Review of the Use of Wenger's Community of Practice (CoP) Theoretical Framework in Online and Blended Learning Research, 2000-2014

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Smith, Sedef Uzuner; Hayes, Suzanne; Shea, Peter

2017-01-01

After presenting a brief overview of the key elements that underpin Etienne Wenger's communities of practice (CoP) theoretical framework, one of the most widely cited and influential conceptions of social learning, this paper reviews extant empirical work grounded in this framework to investigate online/blended learning in higher education and in…

DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters

OpenAIRE

Kim, Hanjoo; Park, Jaehong; Jang, Jaehee; Yoon, Sungroh

2016-01-01

The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters involved in DNN training. Distributed computing platforms and GPGPU-based acceleration provide a mainstream solution to this computational challenge. In this paper, we propose DeepSpark, a distributed and parallel deep learning framework that exploits Apache Spark on commodity clusters. To support parallel operation...

A Personalized e-Learning Framework

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Alhawiti, Mohammed M.; Abdelhamid, Yasser

2017-01-01

With the advent of web based learning and content management tools, e-learning has become a matured learning paradigm, and changed the trend of instructional design from instructor centric learning paradigm to learner centric approach, and evolved from "one instructional design for many learners" to "one design for one learner"…

Language teacher education in CALL: history and perspectives

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Ana Cristina Biondo Salomão

2013-01-01

Full Text Available Over the last years, the new technologies have changed the way we relate to information and communicate with other people, which has brought on impact to foreign language teaching and learning, and, consequently, to the area of foreign language teacher education. The abbreviation CALL (Computer Assisted Language Learning has been used to designate the processes of language teaching and learning with the use of computers, and language teacher education in CALL to name teacher education for and with the use of new technologies, since a number of authors point to the interdependence of both processes. We intend in this article to present an overview of the literature of the area of language teacher education in CALL nowadays and discuss issues related to the use of new technologies concerning its integration to teacher education and the functional and institutional roles to be taken. We also present two proposals of teacher education with the use of new technologies which are being implemented and at the same time studied in Brazil, which we believe have essential elements for the development of language teachers for and with the use of new technologies currently.

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

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Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

Wavefront cellular learning automata.

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Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Wavefront cellular learning automata

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Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

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Karpatne, A.; Kumar, V.

2017-12-01

Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

Architectural frameworks: defining the structures for implementing learning health systems.

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Lessard, Lysanne; Michalowski, Wojtek; Fung-Kee-Fung, Michael; Jones, Lori; Grudniewicz, Agnes

2017-06-23

The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort. Indeed, the structures necessary to effectively design and implement LHSs on a larger scale are lacking. In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution. Because these frameworks support the analysis of LHSs and allow their outcomes to be simulated, they act as pre-implementation decision-support tools that identify potential barriers and enablers of system development. They thus increase the chances of successful LHS deployment. We present an architectural framework for LHSs that incorporates five dimensions-goals, scientific, social, technical, and ethical-commonly found in the LHS literature. The proposed architectural framework is comprised of six decision layers that model these dimensions. The performance layer models goals, the scientific layer models the scientific dimension, the organizational layer models the social dimension, the data layer and information technology layer model the technical dimension, and the ethics and security layer models the ethical dimension. We describe the types of decisions that must be made within each layer and identify methods to support decision-making. In this paper, we outline

Don't Call It School

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Robb, Daniel

2006-01-01

"Homeschooling," "deschooling," and "unschooling" are commonly used terms in the alternative-education world, but each lacks specificity. In this article, the author describes what he discovered during several visits to North Star. Known officially as North Star: Self-Directed Learning for Teens, it is not as structured as a so-called "free"…

Evidence in the learning organization

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Umscheid Craig A

2009-03-01

Full Text Available Abstract Background Organizational leaders in business and medicine have been experiencing a similar dilemma: how to ensure that their organizational members are adopting work innovations in a timely fashion. Organizational leaders in healthcare have attempted to resolve this dilemma by offering specific solutions, such as evidence-based medicine (EBM, but organizations are still not systematically adopting evidence-based practice innovations as rapidly as expected by policy-makers (the knowing-doing gap problem. Some business leaders have adopted a systems-based perspective, called the learning organization (LO, to address a similar dilemma. Three years ago, the Society of General Internal Medicine's Evidence-based Medicine Task Force began an inquiry to integrate the EBM and LO concepts into one model to address the knowing-doing gap problem. Methods During the model development process, the authors searched several databases for relevant LO frameworks and their related concepts by using a broad search strategy. To identify the key LO frameworks and consolidate them into one model, the authors used consensus-based decision-making and a narrative thematic synthesis guided by several qualitative criteria. The authors subjected the model to external, independent review and improved upon its design with this feedback. Results The authors found seven LO frameworks particularly relevant to evidence-based practice innovations in organizations. The authors describe their interpretations of these frameworks for healthcare organizations, the process they used to integrate the LO frameworks with EBM principles, and the resulting Evidence in the Learning Organization (ELO model. They also provide a health organization scenario to illustrate ELO concepts in application. Conclusion The authors intend, by sharing the LO frameworks and the ELO model, to help organizations identify their capacities to learn and share knowledge about evidence-based practice

SemiBoost: boosting for semi-supervised learning.

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Mallapragada, Pavan Kumar; Jin, Rong; Jain, Anil K; Liu, Yi

2009-11-01

Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most previous studies have focused on designing special algorithms to effectively exploit the unlabeled data in conjunction with labeled data. Our goal is to improve the classification accuracy of any given supervised learning algorithm by using the available unlabeled examples. We call this as the Semi-supervised improvement problem, to distinguish the proposed approach from the existing approaches. We design a metasemi-supervised learning algorithm that wraps around the underlying supervised algorithm and improves its performance using unlabeled data. This problem is particularly important when we need to train a supervised learning algorithm with a limited number of labeled examples and a multitude of unlabeled examples. We present a boosting framework for semi-supervised learning, termed as SemiBoost. The key advantages of the proposed semi-supervised learning approach are: 1) performance improvement of any supervised learning algorithm with a multitude of unlabeled data, 2) efficient computation by the iterative boosting algorithm, and 3) exploiting both manifold and cluster assumption in training classification models. An empirical study on 16 different data sets and text categorization demonstrates that the proposed framework improves the performance of several commonly used supervised learning algorithms, given a large number of unlabeled examples. We also show that the performance of the proposed algorithm, SemiBoost, is comparable to the state-of-the-art semi-supervised learning algorithms.

Promoting Student Learning and Productive Persistence in Developmental Mathematics: Research Frameworks Informing the Carnegie Pathways

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Edwards, Ann R.; Beattie, Rachel L.

2016-01-01

This paper focuses on two research-based frameworks that inform the design of instruction and promote student success in accelerated, developmental mathematics pathways. These are Learning Opportunities--productive struggle on challenging and relevant tasks, deliberate practice, and explicit connections, and Productive Persistence--promoting…

Analytics4Action Evaluation Framework: A Review of Evidence-Based Learning Analytics Interventions at the Open University UK

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Rienties, Bart; Boroowa, Avinash; Cross, Simon; Kubiak, Chris; Mayles, Kevin; Murphy, Sam

2016-01-01

There is an urgent need to develop an evidence-based framework for learning analytics whereby stakeholders can manage, evaluate, and make decisions about which types of interventions work well and under which conditions. In this article, we will work towards developing a foundation of an Analytics4Action Evaluation Framework (A4AEF) that is…

Label-Driven Learning Framework: Towards More Accurate Bayesian Network Classifiers through Discrimination of High-Confidence Labels

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Yi Sun

2017-12-01

Full Text Available Bayesian network classifiers (BNCs have demonstrated competitive classification accuracy in a variety of real-world applications. However, it is error-prone for BNCs to discriminate among high-confidence labels. To address this issue, we propose the label-driven learning framework, which incorporates instance-based learning and ensemble learning. For each testing instance, high-confidence labels are first selected by a generalist classifier, e.g., the tree-augmented naive Bayes (TAN classifier. Then, by focusing on these labels, conditional mutual information is redefined to more precisely measure mutual dependence between attributes, thus leading to a refined generalist with a more reasonable network structure. To enable finer discrimination, an expert classifier is tailored for each high-confidence label. Finally, the predictions of the refined generalist and the experts are aggregated. We extend TAN to LTAN (Label-driven TAN by applying the proposed framework. Extensive experimental results demonstrate that LTAN delivers superior classification accuracy to not only several state-of-the-art single-structure BNCs but also some established ensemble BNCs at the expense of reasonable computation overhead.

Evaluating mobile learning practice. Towards a framework for analysis of user-generated contexts with reference to the socio-cultural ecology of mobile learning

Directory of Open Access Journals (Sweden)

Judith Seipold

2011-04-01

Full Text Available Against the conceptual and theoretical background of a socio-culturally orientated approach to mobile learning (Pachler, Bachmair and Cook, 2010, this paper examines the evaluation of user-generated contexts by referring to an example from the use of mobile phones in schools. We discuss how mobile device-related, user- generated contexts around structures, agency and cultural practices might be brought into a fruitful relationship with institution-based learning. And, we provide categories for evaluating the use of mobile devices to generate meaning from and with fragmented and discontinuous media and modes at the interface of learning in formal, institutionalised and informal, self-directed settings. The evaluation criteria build on the framework of a socio-cultural ecology of mobile learning developed by the London Mobile Learning Group.

Policy Learning and Organizational Capacities in Innovation Policies

DEFF Research Database (Denmark)

Borrás, Susana

2011-01-01

Bengt-Åke Lundvall’s work has underlined the importance of policy learning for inducing innovation systems’ adaptability. In spite of his efforts and of the general interest in this topic, studies of policy learning in innovation policy continue to be scarce. Elaborating from recent theoretical...... advances, the paper identifies three levels of policy learning and argues that their effects on innovation systems are related to specific capacities of the relevant organizations implementing change. This analytical framework is used in the study of trans-national policy learning in Europe in the area...... of science–industry relations, showing the importance of capacities (or lack thereof). This calls for the practical need of addressing organizational capacity-building, in particular of analytical capacity, for truly strategic innovation policy-making....

A semi-supervised learning framework for biomedical event extraction based on hidden topics.

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Zhou, Deyu; Zhong, Dayou

2015-05-01

Scientists have devoted decades of efforts to understanding the interaction between proteins or RNA production. The information might empower the current knowledge on drug reactions or the development of certain diseases. Nevertheless, due to the lack of explicit structure, literature in life science, one of the most important sources of this information, prevents computer-based systems from accessing. Therefore, biomedical event extraction, automatically acquiring knowledge of molecular events in research articles, has attracted community-wide efforts recently. Most approaches are based on statistical models, requiring large-scale annotated corpora to precisely estimate models' parameters. However, it is usually difficult to obtain in practice. Therefore, employing un-annotated data based on semi-supervised learning for biomedical event extraction is a feasible solution and attracts more interests. In this paper, a semi-supervised learning framework based on hidden topics for biomedical event extraction is presented. In this framework, sentences in the un-annotated corpus are elaborately and automatically assigned with event annotations based on their distances to these sentences in the annotated corpus. More specifically, not only the structures of the sentences, but also the hidden topics embedded in the sentences are used for describing the distance. The sentences and newly assigned event annotations, together with the annotated corpus, are employed for training. Experiments were conducted on the multi-level event extraction corpus, a golden standard corpus. Experimental results show that more than 2.2% improvement on F-score on biomedical event extraction is achieved by the proposed framework when compared to the state-of-the-art approach. The results suggest that by incorporating un-annotated data, the proposed framework indeed improves the performance of the state-of-the-art event extraction system and the similarity between sentences might be precisely

Research Notes ~ Second Language Acquisition Theories as a Framework for Creating Distance Learning Courses

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Eileen N. Ariza

2003-10-01

Full Text Available Moore and Kearsley (1996 maintain distance educators should provide for three types of interaction: a learner-content; b learner-instructor; and c learner-learner. According to interactionist second language acquisition (SLA theories that reflect Krashen’s theory (1994 that comprehensible input is critical for second language acquisition, interaction can enhance second language acquisition and fluency. Effective output is necessary as well. We reviewed the research on distance learning for second language learners and concluded that SLA theories can, and should, be the framework that drives the development of courses for students seeking to learn languages by distance technology. This article delineates issues to consider in support of combining SLA theories and research literature as a guide in creating distance language learning courses.

A Security Monitoring Framework For Virtualization Based HEP Infrastructures

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Gomez Ramirez, A.; Martinez Pedreira, M.; Grigoras, C.; Betev, L.; Lara, C.; Kebschull, U.; ALICE Collaboration

2017-10-01

High Energy Physics (HEP) distributed computing infrastructures require automatic tools to monitor, analyze and react to potential security incidents. These tools should collect and inspect data such as resource consumption, logs and sequence of system calls for detecting anomalies that indicate the presence of a malicious agent. They should also be able to perform automated reactions to attacks without administrator intervention. We describe a novel framework that accomplishes these requirements, with a proof of concept implementation for the ALICE experiment at CERN. We show how we achieve a fully virtualized environment that improves the security by isolating services and Jobs without a significant performance impact. We also describe a collected dataset for Machine Learning based Intrusion Prevention and Detection Systems on Grid computing. This dataset is composed of resource consumption measurements (such as CPU, RAM and network traffic), logfiles from operating system services, and system call data collected from production Jobs running in an ALICE Grid test site and a big set of malware samples. This malware set was collected from security research sites. Based on this dataset, we will proceed to develop Machine Learning algorithms able to detect malicious Jobs.

Student Teachers and CALL: Personal and Pedagogical Uses and Beliefs

Science.gov (United States)

Hlas, Anne Cummings; Conroy, Kelly; Hildebrandt, Susan A.

2017-01-01

The student teaching semester affords teacher candidates the chance to apply what they have learned during their teacher preparation coursework. Therefore, it can be a prime opportunity for student teachers to use technology for their own language learning and to implement computer assisted language learning (CALL) in their instruction. This study…

The Effect of Computer Assisted Language Learning (CALL) on Performance in the Test of English for International Communication (TOEIC) Listening Module

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van Han, Nguyen; van Rensburg, Henriette

2014-01-01

Many companies and organizations have been using the Test of English for International Communication (TOEIC) for business and commercial communication purpose in Vietnam and around the world. The present study investigated the effect of Computer Assisted Language Learning (CALL) on performance in the Test of English for International Communication…

A conceptual framework to identify spatial implications of new ways of learning in higher education

NARCIS (Netherlands)

Beckers, R; van der Voordt, Theo; Dewulf, G

2015-01-01

Purpose - The purpose of this paper is to explore the spatial implications of new learning theories and the use of Information and Communication Technologies (ICT) in higher education.
Design/methodology/approach - Based on a review of literature, a theoretical framework has been developed that

Erotic Education: Elaborating a Feminist and Faith-Based Pedagogy for Experiential Learning in Religious Studies

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Carbine, Rosemary P.

2010-01-01

This essay explores intersections among Jesuit, Quaker, and feminist theologies and pedagogies of social justice education in order to propose and elaborate an innovative theoretical and theological framework for experiential learning in religious studies that prioritizes relationality, called erotic education. This essay then applies the…

A Learning Framework for Control-Oriented Modeling of Buildings

Energy Technology Data Exchange (ETDEWEB)

Rubio-Herrero, Javier; Chandan, Vikas; Siegel, Charles M.; Vishnu, Abhinav; Vrabie, Draguna L.

2018-01-18

Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and big data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.

Disciplinary Literacies and Learning to Read for Understanding: A Conceptual Framework for Disciplinary Literacy

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Goldman, Susan R.; Britt, M. Anne; Brown, Willard; Cribb, Gayle; George, MariAnne; Greenleaf, Cynthia; Lee, Carol D.; Shanahan, Cynthia

2016-01-01

This article presents a framework and methodology for designing learning goals targeted at what students need to know and be able to do in order to attain high levels of literacy and achievement in three disciplinary areas--literature, science, and history. For each discipline, a team of researchers, teachers, and specialists in that discipline…

Editorial - Keeping the Learning in Computer-Based Learning

Directory of Open Access Journals (Sweden)

William Kilbride

2002-09-01

Full Text Available Political rhetoric about knowledge economies and learning societies really ought to be an educationalist's dream. Add to that the revolutionary power of electronic media, and an insatiable hunger for archaeology among the public, archaeology teaching should be well placed to flourish. In England, the Department for Culture Media and Sport has just closed its call for interest in the multi-million pound Culture Online programme. The New Opportunities Fund has already spent fifty million pounds on digitisation alone, while the Heritage Lottery Fund is encouraging heritage agencies to distribute their data sets online. The JISC continues to expand its information environment, investing most recently in virtual learning environments. In Europe, the 6th Framework promises a single European Research Area, and grid technologies allow high quantities of data to empower an information society - supported by the millions of euros already invested in 'e-content'. All of these programmes, and many many more, provide openings for archaeologists to invest in training, teaching and learning. How can archaeology, in particular staff and students in our educational establishments, take best advantage of this information-rich, digitally-empowered learning society?

A conceptual framework to identify spatial implications of new ways of learning in higher education

NARCIS (Netherlands)

Geert Dewulf; Theo van der Voordt; Ronald Beckers

2015-01-01

Purpose – The purpose of this paper is to explore the spatial implications of new learning theories and the use of information and communication technologies (ICT) in higher education. Design/methodology/approach – Based on a review of the literature, a theoretical framework has been developed

A conceptual framework to identify spatial implications of new ways of learning in higher education

NARCIS (Netherlands)

Beckers, Ronald; van der Voordt, Theo; Dewulf, Geert P.M.R.

2015-01-01

Purpose – The purpose of this paper is to explore the spatial implications of new learning theories and the use of information and communication technologies (ICT) in higher education. Design/methodology/approach – Based on a review of the literature, a theoretical framework has been developed that

A unified framework of image latent feature learning on Sina microblog

Science.gov (United States)

Wei, Jinjin; Jin, Zhigang; Zhou, Yuan; Zhang, Rui

2015-10-01

Large-scale user-contributed images with texts are rapidly increasing on the social media websites, such as Sina microblog. However, the noise and incomplete correspondence between the images and the texts give rise to the difficulty in precise image retrieval and ranking. In this paper, a hypergraph-based learning framework is proposed for image ranking, which simultaneously utilizes visual feature, textual content and social link information to estimate the relevance between images. Representing each image as a vertex in the hypergraph, complex relationship between images can be reflected exactly. Then updating the weight of hyperedges throughout the hypergraph learning process, the effect of different edges can be adaptively modulated in the constructed hypergraph. Furthermore, the popularity degree of the image is employed to re-rank the retrieval results. Comparative experiments on a large-scale Sina microblog data-set demonstrate the effectiveness of the proposed approach.

Hierarchical modeling of systems with similar components: A framework for adaptive monitoring and control

International Nuclear Information System (INIS)

Memarzadeh, Milad; Pozzi, Matteo; Kolter, J. Zico

2016-01-01

System management includes the selection of maintenance actions depending on the available observations: when a system is made up by components known to be similar, data collected on one is also relevant for the management of others. This is typically the case of wind farms, which are made up by similar turbines. Optimal management of wind farms is an important task due to high cost of turbines' operation and maintenance: in this context, we recently proposed a method for planning and learning at system-level, called PLUS, built upon the Partially Observable Markov Decision Process (POMDP) framework, which treats transition and emission probabilities as random variables, and is therefore suitable for including model uncertainty. PLUS models the components as independent or identical. In this paper, we extend that formulation, allowing for a weaker similarity among components. The proposed approach, called Multiple Uncertain POMDP (MU-POMDP), models the components as POMDPs, and assumes the corresponding parameters as dependent random variables. Through this framework, we can calibrate specific degradation and emission models for each component while, at the same time, process observations at system-level. We compare the performance of the proposed MU-POMDP with PLUS, and discuss its potential and computational complexity. - Highlights: • A computational framework is proposed for adaptive monitoring and control. • It adopts a scheme based on Markov Chain Monte Carlo for inference and learning. • Hierarchical Bayesian modeling is used to allow a system-level flow of information. • Results show potential of significant savings in management of wind farms.

Paying the Piper: Foundation Evaluation Capacity Calls the Tune

Science.gov (United States)

Behrens, Teresa R.; Kelly, Thomas

2008-01-01

An overview is presented of forces that have shaped how public and private funders approach evaluation, including the challenges that funders, and particularly foundations, face in effectively using evaluation within an organizational learning framework. Even with internal organizational challenges to learning, foundations are increasingly…

A multidimensional framework of conceptual change for developing chemical equilibrium learning

Science.gov (United States)

Chanyoo, Wassana; Suwannoi, Paisan; Treagust, David F.

2018-01-01

The purposes of this research is to investigate the existing chemical equilibrium lessons in Thailand based on the multidimensional framework of conceptual change, to determine how the existing lessons could enhance students' conceptual change. This research was conducted based on qualitative perspective. Document, observations and interviews were used to collect data. To comprehend all students conceptions, diagnostic tests were applied comprised of The Chemical Equilibrium Diagnostic Test (the CEDT) and The Chemical Equilibrium Test for Reveal Conceptual Change (the CETforRCC). In addition, to study students' motivations, the Motivated Strategies for Learning Questionnaire (the MSLQ) and students' task engagement were applied. Following each perspective of conceptual change - ontological, epistemological, and social/affective - the result showed that the existing chemical equilibrium unit did not enhance students' conceptual change, and some issues were found. The problems obstructed students conceptual change should be remedy under the multidimensional framework of conceptual change. Finally, some suggestions were provided to enhance students' conceptual change in chemical equilibrium effectively

Investigating the Effectiveness of Computer-Assisted Language Learning (CALL) Using Google Documents in Enhancing Writing--A Study on Senior 1 Students in a Chinese Independent High School

Science.gov (United States)

Ambrose, Regina Maria; Palpanathan, Shanthini

2017-01-01

Computer-assisted language learning (CALL) has evolved through various stages in both technology as well as the pedagogical use of technology (Warschauer & Healey, 1998). Studies show that the CALL trend has facilitated students in their English language writing with useful tools such as computer based activities and word processing. Students…

Integration of a framework with a learning management system for detection, assessment and assistance of university students with reading difficulties

Directory of Open Access Journals (Sweden)

Carolina Mejía Corredor

2015-12-01

Full Text Available Rev.esc.adm.neg Dyslexia is a common learning disability in Spanish-speaking university students, and requires special attention from higher educational institutions in order to support affected individuals during their learning process. In previous studies, a framework to detect, assess and assist university students with reading difficulties related to dyslexia was developed. In this paper, the integration of this framework with a Learning Management System (LMS is presented. Two case studies were performed to test the functionality and the usability of this integration. The first case study was carried out with 20 students, while the second one with four teachers. The results show that both students and teachers were satisfied with the integration performed in Moodle.ce, among others.

An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels

Directory of Open Access Journals (Sweden)

Gang Zhang

2015-01-01

Full Text Available Objective. This study aims to establish a model to analyze clinical experience of TCM veteran doctors. We propose an ensemble learning based framework to analyze clinical records with ICD-10 labels information for effective diagnosis and acupoints recommendation. Methods. We propose an ensemble learning framework for the analysis task. A set of base learners composed of decision tree (DT and support vector machine (SVM are trained by bootstrapping the training dataset. The base learners are sorted by accuracy and diversity through nondominated sort (NDS algorithm and combined through a deep ensemble learning strategy. Results. We evaluate the proposed method with comparison to two currently successful methods on a clinical diagnosis dataset with manually labeled ICD-10 information. ICD-10 label annotation and acupoints recommendation are evaluated for three methods. The proposed method achieves an accuracy rate of 88.2%  ±  2.8% measured by zero-one loss for the first evaluation session and 79.6%  ±  3.6% measured by Hamming loss, which are superior to the other two methods. Conclusion. The proposed ensemble model can effectively model the implied knowledge and experience in historic clinical data records. The computational cost of training a set of base learners is relatively low.

76 Computer Assisted Language Learning (CALL) Software ...

African Journals Online (AJOL)

Ike Odimegwu

combination with other factors which may enhance or ameliorate the ... form of computer-based learning which carries two important features: .... To take some commonplace examples, a ... photographs, and even full-motion video clips.

The National School Safety Framework: A framework for preventing ...

African Journals Online (AJOL)

The National School Safety Framework (NSSF) – approved by the Minister of Education in April 2015 - is located within a range of international and national laws and policies that recognise the safety of learners and educators as a prerequisite for quality learning and teaching at school. The framework affirms the ...

AUDIT SISTEM INFORMASI MENGGUNAKAN FRAMEWORK COBIT 4.1 PADA E-LEARNING UNISNU JEPARA

Directory of Open Access Journals (Sweden)

Noor Azizah

2017-04-01

Full Text Available Perkembangan teknologi saat ini tak bisa dibendung lagi. Kemajuan disetiap bidang tak lepas dari teknologi sebagai penunjangnya, terutama teknologi informasi. Akan tetapi hal tersebut harus dimbangi dengan adanya sebuah evaluasi atau audit terhadap sistem informasi sehingga ancaman atau kerugian dapat  dihindari  ataupun  dicegah.  Penelitian  ini  bertujuan  mengetahui  sejauh  mana  kinerja  sistem informasi pembelajaran yaitu e-learning sebagai layanan publik yang telah diterapkan pada UNISNU Jepara dan  memberikan   rekomendasi tata  kelola perbaikan setelah mengetahui kesenjangan antara tatakelola saat ini dengan tatakelola yang diharapkan sesuai dengan framework yang digunakan. Framework  yang digunakan dalam penelitian ini adalah COBIT versi 4.1 khusus pada domain Deliver and Support (DS. Teknik pengumpulan datanya dilakukan dengan wawancara dan kuisioner dengan narasumber yang telah ditentukan sesuai dengan domain dan Control Objective yang digunakan. Metode analisis data dilakukan beberapa tahap, yaitu penentuan domain, penentuan proses kontrol, penentuan indikator dan pemetaan tingkatkematangan. Hasil dari penelitian ini adalah untuk mengetahui tingkat kematangan (maturity level pada implementasi e-learning UNISNU Jepara khusus pada Domain DS, yaitu berada pada level 4 yang berarti sudah terukur dan terintegrasi antar proses yang berlangsung. Dan analisa GAP antara kondisi yang diharapkan dengan kondisi saat ini rata-rata sebesar 0,6.

A Driver Behavior Learning Framework for Enhancing Traffic Simulation

Directory of Open Access Journals (Sweden)

Ramona Maria Paven

2014-06-01

Full Text Available Traffic simulation provides an essential support for developing intelligent transportation systems. It allows affordable validation of such systems using a large variety of scenarios that involves massive data input. However, realistic traffic models are hard to be implemented especially for microscopic traffic simulation. One of the hardest problems in this context is to model the behavior of drivers, due the complexity of human nature. The work presented in this paper proposes a framework for learning driver behavior based on a Hidden Markov Model technique. Moreover, we propose also a practical method to inject this behavior in a traffic model used by the SUMO traffic simulator. To demonstrate the effectiveness of this method we present a case study involving real traffic collected from Timisoara city area.

Press Play for Learning: A Framework to Guide Serious Computer Game Use in the Classroom

Science.gov (United States)

Southgate, Erica; Budd, Janene; Smith, Shamus

2017-01-01

Computer gaming is a global phenomenon and there has been rapid growth in "serious" games for learning. An emergent body of evidence demonstrates how serious games can be used in primary and secondary school classrooms. Despite the popularity of serious games and their pedagogical potential, there are few specialised frameworks to guide…

Developing Policy Instruments for Education in the EU: The European Qualifications Framework for Lifelong Learning

Science.gov (United States)

Elken, Mari

2015-01-01

The European Qualifications Framework (EQF) for lifelong learning has been characterized as a policy instrument with a number of contested ideas, raising questions about the process through which such instruments are developed at European level. The introduction of the EQF is in this article examined through variations of neo-institutional theory:…

What and how do students learn in an interprofessional student-run clinic? An educational framework for teambased care

OpenAIRE

Lie, Désirée A.; Forest, Christopher P.; Walsh, Anne; Banzali, Yvonne; Lohenry, Kevin

2016-01-01

Background: The student-run clinic (SRC) has the potential to address interprofessional learning among health professions students.Purpose: To derive a framework for understanding student learning during team-based care provided in an interprofessional SRC serving underserved patients.Methods: The authors recruited students for a focus group study by purposive sampling and snowballing. They constructed two sets of semi-structured questions for uniprofessional and multiprofessional groups. Ses...

“Computer Assisted Language Learning” (CALL

Directory of Open Access Journals (Sweden)

Nazlı Gündüz

2005-10-01

Full Text Available This article will provide an overview of computers; an overview of the history of CALL, itspros and cons, the internet, World Wide Web, Multimedia, and research related to the uses of computers in the language classroom. Also, it also aims to provide some background for the beginnerson using the Internet in language classes today. It discusses some of the common types of Internetactivities that are being used today, what the minimum requirements are for using the Internet forlanguage learning, and some easy activities you can adapt for your classes. Some special terminology related to computers will also be used in this paper. For example, computer assisted language learning(CALL refers to the sets of instructions which need to be loaded into the computer for it to be able to work in the language classroom. It should be borne in mind that CALL does not refer to the use of acomputer by a teacher to type out a worksheet or a class list or preparing his/her own teaching alone.Hardware refers to any computer equipment used, including the computer itself, the keyboard, screen (or the monitor, the disc-drive, and the printer. Software (computer programs refers to the sets of instructions which need to be loaded into the computer for it to be able to work.

Programming Entity Framework

CERN Document Server

Lerman, Julia

2010-01-01

Get a thorough introduction to ADO.NET Entity Framework 4 -- Microsoft's core framework for modeling and interacting with data in .NET applications. The second edition of this acclaimed guide provides a hands-on tour of the framework latest version in Visual Studio 2010 and .NET Framework 4. Not only will you learn how to use EF4 in a variety of applications, you'll also gain a deep understanding of its architecture and APIs. Written by Julia Lerman, the leading independent authority on the framework, Programming Entity Framework covers it all -- from the Entity Data Model and Object Service

A Framework for Learning Analytics Using Commodity Wearable Devices.

Science.gov (United States)

Lu, Yu; Zhang, Sen; Zhang, Zhiqiang; Xiao, Wendong; Yu, Shengquan

2017-06-14

We advocate for and introduce LEARNSense, a framework for learning analytics using commodity wearable devices to capture learner's physical actions and accordingly infer learner context (e.g., student activities and engagement status in class). Our work is motivated by the observations that: (a) the fine-grained individual-specific learner actions are crucial to understand learners and their context information; (b) sensor data available on the latest wearable devices (e.g., wrist-worn and eye wear devices) can effectively recognize learner actions and help to infer learner context information; (c) the commodity wearable devices that are widely available on the market can provide a hassle-free and non-intrusive solution. Following the above observations and under the proposed framework, we design and implement a sensor-based learner context collector running on the wearable devices. The latest data mining and sensor data processing techniques are employed to detect different types of learner actions and context information. Furthermore, we detail all of the above efforts by offering a novel and exemplary use case: it successfully provides the accurate detection of student actions and infers the student engagement states in class. The specifically designed learner context collector has been implemented on the commodity wrist-worn device. Based on the collected and inferred learner information, the novel intervention and incentivizing feedback are introduced into the system service. Finally, a comprehensive evaluation with the real-world experiments, surveys and interviews demonstrates the effectiveness and impact of the proposed framework and this use case. The F1 score for the student action classification tasks achieve 0.9, and the system can effectively differentiate the defined three learner states. Finally, the survey results show that the learners are satisfied with the use of our system (mean score of 3.7 with a standard deviation of 0.55).

Responsibly managing students' learning experiences in student-run clinics: a virtues-based ethical framework.

Science.gov (United States)

Coverdale, John H; McCullough, Laurence B

2014-01-01

Many medical schools now offer students a distinctive clinical and learning opportunity, the student-run clinic (SRC), in which generalist physicians often play the major role. Although SRCs have become popular, they pose as-yet unexplored ethical challenges for the learning experiences of students. In SRCs students not only take on a significant administrative role especially in coordinating care, but also provide direct patient care for a clinically challenging, biopsychosocially vulnerable, medically indigent population of patients. SRCs provide an exemplar of the ethical challenges of care for such patients. The ethical framework proposed in this article emphasizes that these valued learning opportunities for students should occur in the context of professional formation, with explicit attention to developing the professional virtues, with faculty as role models for these virtues. The valued learning opportunities for students in SRCs should occur in the context of professional formation, with explicit attention to developing the professional virtues of integrity, compassion, self-effacement, self-sacrifice, and courage, which are required for the appropriate care of the vulnerable populations served by SRCs.

Integration of Culturally Relevant Pedagogy Into the Science Learning Progression Framework

Science.gov (United States)

Bernardo, Cyntra

This study integrated elements of culturally relevant pedagogy into a science learning progression framework, with the goal of enhancing teachers' cultural knowledge and thereby creating better teaching practices in an urban public high school science classroom. The study was conducted using teachers, an administrator, a science coach, and students involved in science courses in public high school. Through a qualitative intrinsic case study, data were collected and analyzed using traditional methods. Data from primary participants (educators) were analyzed through identification of big ideas, open coding, and themes. Through this process, patterns and emergent ideas were reported. Outcomes of this study demonstrated that educators lack knowledge about research-based academic frameworks and multicultural education strategies, but benefit through institutionally-based professional development. Students from diverse cultures responded positively to culturally-based instruction. Their progress was further manifested in better communication and discourse with their teacher and peers, and increased academic outcomes. This study has postulated and provided an exemplar for science teachers to expand and improve multicultural knowledge, ultimately transferring these skills to their pedagogical practice.

Framework for online teaching

DEFF Research Database (Denmark)

Strobel, Bjarne W.

2014-01-01

The following framework for online teaching is a guidance to inspire you on how to to use e-learning in your teaching. Maybe you want to make a whole online course (distance learning) or maybe you want to use e-learning as a part of a course (blended learning). If you want to go further or have...

Contextual Mobile Learning: A Step Further to Mastering Professional Appliances

Directory of Open Access Journals (Sweden)

René Chalon

2007-10-01

Full Text Available In this paper we describe our approach whose objective is to apply MOCOCO concepts to e-learning. After a short presentation of MOCOCO (Mobility, Cooperation, Contextualization and IMERA (Mobile Interaction in the Augmented Real Environment principles we will discuss their use in a project called HMTD (Help Me To Do whose aim is to use wearable computer for a framework of activities of better use, maintenance and repairing of professional appliances. We will successively describe m-learning scope, contextualization and cooperation advantages as well as learning methods. A case study of configuration of wearable computer and its peripherals, taking into account context, in-situ storage, traceability and regulation in these activities finishes this paper.

Virtual Learning Environments on the Go: CALL Meets MALL

Science.gov (United States)

Arús Hita, Jorge

2016-01-01

This paper presents "Eating out," a Moodle-based digital learning resource for English as a Foreign Language (EFL) teaching that can be run both on computers and mobile devices. It is argued that Mobile Assisted Language Learning (MALL) resources do not necessarily need to be specifically designed for such platforms. Rather, a carefully…

Integrating CALL into an Iranian EAP Course: Constraints and Affordances

Science.gov (United States)

Mehran, Parisa; Alizadeh, Mehrasa

2015-01-01

Iranian universities have recently displayed a growing interest in integrating Computer-Assisted Language Learning (CALL) into teaching/learning English. The English for Academic Purposes (EAP) context, however, is not keeping pace with the current changes since EAP courses are strictly text-based and exam-oriented, and little research has thus…

Repurposing learning object components

NARCIS (Netherlands)

Verbert, K.; Jovanovic, J.; Gasevic, D.; Duval, E.; Meersman, R.

2005-01-01

This paper presents an ontology-based framework for repurposing learning object components. Unlike the usual practice where learning object components are assembled manually, the proposed framework enables on-the-fly access and repurposing of learning object components. The framework supports two

Learning Inverse Rig Mappings by Nonlinear Regression.

Science.gov (United States)

Holden, Daniel; Saito, Jun; Komura, Taku

2017-03-01

We present a framework to design inverse rig-functions-functions that map low level representations of a character's pose such as joint positions or surface geometry to the representation used by animators called the animation rig. Animators design scenes using an animation rig, a framework widely adopted in animation production which allows animators to design character poses and geometry via intuitive parameters and interfaces. Yet most state-of-the-art computer animation techniques control characters through raw, low level representations such as joint angles, joint positions, or vertex coordinates. This difference often stops the adoption of state-of-the-art techniques in animation production. Our framework solves this issue by learning a mapping between the low level representations of the pose and the animation rig. We use nonlinear regression techniques, learning from example animation sequences designed by the animators. When new motions are provided in the skeleton space, the learned mapping is used to estimate the rig controls that reproduce such a motion. We introduce two nonlinear functions for producing such a mapping: Gaussian process regression and feedforward neural networks. The appropriate solution depends on the nature of the rig and the amount of data available for training. We show our framework applied to various examples including articulated biped characters, quadruped characters, facial animation rigs, and deformable characters. With our system, animators have the freedom to apply any motion synthesis algorithm to arbitrary rigging and animation pipelines for immediate editing. This greatly improves the productivity of 3D animation, while retaining the flexibility and creativity of artistic input.

Conceptual Frameworks for the Workplace Change Adoption Process: Elements Integration from Decision Making and Learning Cycle Process.

Science.gov (United States)

Radin Umar, Radin Zaid; Sommerich, Carolyn M; Lavender, Steve A; Sanders, Elizabeth; Evans, Kevin D

2018-05-14

Sound workplace ergonomics and safety-related interventions may be resisted by employees, and this may be detrimental to multiple stakeholders. Understanding fundamental aspects of decision making, behavioral change, and learning cycles may provide insights into pathways influencing employees' acceptance of interventions. This manuscript reviews published literature on thinking processes and other topics relevant to decision making and incorporates the findings into two new conceptual frameworks of the workplace change adoption process. Such frameworks are useful for thinking about adoption in different ways and testing changes to traditional intervention implementation processes. Moving forward, it is recommended that future research focuses on systematic exploration of implementation process activities that integrate principles from the research literature on sensemaking, decision making, and learning processes. Such exploration may provide the groundwork for development of specific implementation strategies that are theoretically grounded and provide a revised understanding of how successful intervention adoption processes work.

Tecolote: An object-oriented framework for physics development

Energy Technology Data Exchange (ETDEWEB)

Marshall, J.; Ankeny, L.; Clancy, S. [and others

1998-12-31

The authors describe a C++ physics development environment, called the Tecolote Framework, which allows model developers to work more efficiently and accurately. This Framework contains a variety of meshes, operators, and parallel fields, as well as an input/output (I/O) subsystem and graphics capabilities. Model developers can inherit Tecolote`s generic model interface and use the Framework`s high-level field and operator components to write parallel physics equations. New Tecolote models are easily registered with the Framework, and they can be built and called directly from the input file, which greatly expedites model installation. In the process of developing an extensible and robust framework, they have found appealing solutions to some of the serious problems they encounter when parallelizing and extending the older codes. They also discuss memory and performance issues for a large hydrodynamics application built in this Framework.

Learning Theory Foundations of Simulation-Based Mastery Learning.

Science.gov (United States)

McGaghie, William C; Harris, Ilene B

2018-06-01

Simulation-based mastery learning (SBML), like all education interventions, has learning theory foundations. Recognition and comprehension of SBML learning theory foundations are essential for thoughtful education program development, research, and scholarship. We begin with a description of SBML followed by a section on the importance of learning theory foundations to shape and direct SBML education and research. We then discuss three principal learning theory conceptual frameworks that are associated with SBML-behavioral, constructivist, social cognitive-and their contributions to SBML thought and practice. We then discuss how the three learning theory frameworks converge in the course of planning, conducting, and evaluating SBML education programs in the health professions. Convergence of these learning theory frameworks is illustrated by a description of an SBML education and research program in advanced cardiac life support. We conclude with a brief coda.

Promoting Reflective Physics Teaching Through the Use of Collaborative Learning Annotation System

Science.gov (United States)

Milner-Bolotin, Marina

2018-05-01

Effective physics teaching requires extensive knowledge of physics, relevant pedagogies, and modern educational technologies that can support student learning. Acquiring this knowledge is a challenging task, considering how fast modern technologies and expectations of student learning outcomes and of teaching practices are changing Therefore 21st-century physics teachers should be supported in developing a different way of thinking about technology-enhanced physics teaching and learning. We call it Deliberate Pedagogical Thinking with Technology, and base it on the original Pedagogical Content Knowledge and Technological Pedagogical Content Knowledge frameworks. However, unlike the two aforementioned frameworks, the Deliberate Pedagogical Thinking with Technology emphasizes not only teachers' knowledge, but also their attitudes and dispositions about using digital tools in order to support student learning. This paper examines how an online system that allows an ongoing discussion of videos uploaded on it by the students can support reflection in physics teacher education. Examples of using such a system in physics teacher education and teacher-candidates' feedback on their experiences with it are also discussed.

Preparing Teacher-Students for Twenty-First-Century Learning Practices (PREP 21): A Framework for Enhancing Collaborative Problem-Solving and Strategic Learning Skills

Science.gov (United States)

Häkkinen, Päivi; Järvelä, Sanna; Mäkitalo-Siegl, Kati; Ahonen, Arto; Näykki, Piia; Valtonen, Teemu

2017-01-01

With regard to the growing interest in developing teacher education to match the twenty-first-century skills, while many assumptions have been made, there has been less theoretical elaboration and empirical research on this topic. The aim of this article is to present our pedagogical framework for the twenty-first-century learning practices in…

Assessment of Student Performance in a PSI College Physics Course Using Ausubel's Learning Theory as a Theoretical Framework for Content Organization.

Science.gov (United States)

Moriera, M. A.

1979-01-01

David Ausubel's learning theory was used as a framework for the content organization of an experimental Personalized System of Instruction (PSI) course in physics. Evaluation suggests that the combination of PSI as a method of instruction and Ausubel's theory for organization might result in better learning outcomes. (Author/JMD)

Exploring Middle School Students' Representational Competence in Science: Development and Verification of a Framework for Learning with Visual Representations

Science.gov (United States)

Tippett, Christine Diane

Scientific knowledge is constructed and communicated through a range of forms in addition to verbal language. Maps, graphs, charts, diagrams, formulae, models, and drawings are just some of the ways in which science concepts can be represented. Representational competence---an aspect of visual literacy that focuses on the ability to interpret, transform, and produce visual representations---is a key component of science literacy and an essential part of science reading and writing. To date, however, most research has examined learning from representations rather than learning with representations. This dissertation consisted of three distinct projects that were related by a common focus on learning from visual representations as an important aspect of scientific literacy. The first project was the development of an exploratory framework that is proposed for use in investigations of students constructing and interpreting multimedia texts. The exploratory framework, which integrates cognition, metacognition, semiotics, and systemic functional linguistics, could eventually result in a model that might be used to guide classroom practice, leading to improved visual literacy, better comprehension of science concepts, and enhanced science literacy because it emphasizes distinct aspects of learning with representations that can be addressed though explicit instruction. The second project was a metasynthesis of the research that was previously conducted as part of the Explicit Literacy Instruction Embedded in Middle School Science project (Pacific CRYSTAL, http://www.educ.uvic.ca/pacificcrystal). Five overarching themes emerged from this case-to-case synthesis: the engaging and effective nature of multimedia genres, opportunities for differentiated instruction using multimodal strategies, opportunities for assessment, an emphasis on visual representations, and the robustness of some multimodal literacy strategies across content areas. The third project was a mixed

Nonpasserine bird produces soft calls and pays retaliation cost

OpenAIRE

Paweł Ręk; Tomasz S. Osiejuk

2011-01-01

Low-amplitude vocalizations produced during aggressive encounters, courtship, or both (quiet/soft songs) have been described for many species of song-learning passerines; however, such signals have not been studied among nonlearning birds. During aggressive interactions, apart from using the broadcast call, male corncrakes (Crex crex) produce a low-amplitude, gurgling--mewing call, which appears to be equivalent to soft songs of songbirds. Previous studies have shown that low-amplitude vocali...

COMPUTER ASSISTED LANGUAGE LEARNING (CALL: ITS PROSPECTS AND CONSEQUENCES FOR NIGERIAN LANGUAGES / L'APPRENTISSAGE DE LA LANGUE À L'AIDE DES TICE: PERSPECTIVES ET CONSÉQUENCES POUR LES LANGUES NIGÉRIENNES / ÎNVĂŢAREA LIMBII CU TIC: PERSPECTIVE ŞI CONSECINŢE PENTRU LIMBILE NIGERIENE

Directory of Open Access Journals (Sweden)

Oyè Táíwò

2014-11-01

Full Text Available The shift in language learning today is from “classical teaching environment” to “self-learning environment”. In Nigeria today, although CALL efforts are made by schools and individuals, these effort are geared towards the English language learning other than Nigerian languages. This paper seeks to explore the development of CALL for Nigerian Languages and the challenges of running CALL in Nigeria. The results indicate that CALL for Nigerian languages is needed and should be promoted. CALL in Nigerian can only be successful if the shortcomings of CALL are recognized and the mitigating circumstances tackled. Adequate arrangements must be made to manage CALL and Teacher-Assisted language learning (TALL in consideration of the socioeconomic impact of CALL on the teachers Nigerian languages. The attitude of Nigerians towards Nigerian languages should be positive. The government, corporate bodies and individuals must intervene in CALL programs in schools so as to control the resulting high tuition fee.

An evaluation framework for participatory modelling

Science.gov (United States)

Krueger, T.; Inman, A.; Chilvers, J.

2012-04-01

Strong arguments for participatory modelling in hydrology can be made on substantive, instrumental and normative grounds. These arguments have led to increasingly diverse groups of stakeholders (here anyone affecting or affected by an issue) getting involved in hydrological research and the management of water resources. In fact, participation has become a requirement of many research grants, programs, plans and policies. However, evidence of beneficial outcomes of participation as suggested by the arguments is difficult to generate and therefore rare. This is because outcomes are diverse, distributed, often tacit, and take time to emerge. In this paper we develop an evaluation framework for participatory modelling focussed on learning outcomes. Learning encompasses many of the potential benefits of participation, such as better models through diversity of knowledge and scrutiny, stakeholder empowerment, greater trust in models and ownership of subsequent decisions, individual moral development, reflexivity, relationships, social capital, institutional change, resilience and sustainability. Based on the theories of experiential, transformative and social learning, complemented by practitioner experience our framework examines if, when and how learning has occurred. Special emphasis is placed on the role of models as learning catalysts. We map the distribution of learning between stakeholders, scientists (as a subgroup of stakeholders) and models. And we analyse what type of learning has occurred: instrumental learning (broadly cognitive enhancement) and/or communicative learning (change in interpreting meanings, intentions and values associated with actions and activities; group dynamics). We demonstrate how our framework can be translated into a questionnaire-based survey conducted with stakeholders and scientists at key stages of the participatory process, and show preliminary insights from applying the framework within a rural pollution management situation in

Call Forecasting for Inbound Call Center

Directory of Open Access Journals (Sweden)

Peter Vinje

2009-01-01

Full Text Available In a scenario of inbound call center customer service, the ability to forecast calls is a key element and advantage. By forecasting the correct number of calls a company can predict staffing needs, meet service level requirements, improve customer satisfaction, and benefit from many other optimizations. This project will show how elementary statistics can be used to predict calls for a specific company, forecast the rate at which calls are increasing/decreasing, and determine if the calls may stop at some point.

Algorithm Building and Learning Programming Languages Using a New Educational Paradigm

Science.gov (United States)

Jain, Anshul K.; Singhal, Manik; Gupta, Manu Sheel

2011-08-01

This research paper presents a new concept of using a single tool to associate syntax of various programming languages, algorithms and basic coding techniques. A simple framework has been programmed in Python that helps students learn skills to develop algorithms, and implement them in various programming languages. The tool provides an innovative and a unified graphical user interface for development of multimedia objects, educational games and applications. It also aids collaborative learning amongst students and teachers through an integrated mechanism based on Remote Procedure Calls. The paper also elucidates an innovative method for code generation to enable students to learn the basics of programming languages using drag-n-drop methods for image objects.

A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with contrast enhanced ultrasound images.

Science.gov (United States)

Guo, Le-Hang; Wang, Dan; Qian, Yi-Yi; Zheng, Xiao; Zhao, Chong-Ke; Li, Xiao-Long; Bo, Xiao-Wan; Yue, Wen-Wen; Zhang, Qi; Shi, Jun; Xu, Hui-Xiong

2018-04-04

With the fast development of artificial intelligence techniques, we proposed a novel two-stage multi-view learning framework for the contrast-enhanced ultrasound (CEUS) based computer-aided diagnosis for liver tumors, which adopted only three typical CEUS images selected from the arterial phase, portal venous phase and late phase. In the first stage, the deep canonical correlation analysis (DCCA) was performed on three image pairs between the arterial and portal venous phases, arterial and delayed phases, and portal venous and delayed phases respectively, which then generated total six-view features. While in the second stage, these multi-view features were then fed to a multiple kernel learning (MKL) based classifier to further promote the diagnosis result. Two MKL classification algorithms were evaluated in this MKL-based classification framework. We evaluated proposed DCCA-MKL framework on 93 lesions (47 malignant cancers vs. 46 benign tumors). The proposed DCCA-MKL framework achieved the mean classification accuracy, sensitivity, specificity, Youden index, false positive rate, and false negative rate of 90.41 ± 5.80%, 93.56 ± 5.90%, 86.89 ± 9.38%, 79.44 ± 11.83%, 13.11 ± 9.38% and 6.44 ± 5.90%, respectively, by soft margin MKL classifier. The experimental results indicate that the proposed DCCA-MKL framework achieves best performance for discriminating benign liver tumors from malignant liver cancers. Moreover, it is also proved that the three-phase CEUS image based CAD is feasible for liver tumors with the proposed DCCA-MKL framework.

Reinforcement learning for a biped robot based on a CPG-actor-critic method.

Science.gov (United States)

Nakamura, Yutaka; Mori, Takeshi; Sato, Masa-aki; Ishii, Shin

2007-08-01

Animals' rhythmic movements, such as locomotion, are considered to be controlled by neural circuits called central pattern generators (CPGs), which generate oscillatory signals. Motivated by this biological mechanism, studies have been conducted on the rhythmic movements controlled by CPG. As an autonomous learning framework for a CPG controller, we propose in this article a reinforcement learning method we call the "CPG-actor-critic" method. This method introduces a new architecture to the actor, and its training is roughly based on a stochastic policy gradient algorithm presented recently. We apply this method to an automatic acquisition problem of control for a biped robot. Computer simulations show that training of the CPG can be successfully performed by our method, thus allowing the biped robot to not only walk stably but also adapt to environmental changes.

Using Campinha-Bacote's Framework to Examine Cultural Competence from an Interdisciplinary International Service Learning Program

Science.gov (United States)

Wall-Bassett, Elizabeth DeVane; Hegde, Archana Vasudeva; Craft, Katelyn; Oberlin, Amber Louise

2018-01-01

The purpose of this study was to investigate an interdisciplinary international service learning program and its impact on student sense of cultural awareness and competence using the Campinha-Bacote's (2002) framework of cultural competency model. Seven undergraduate and one graduate student from Human Development and Nutrition Science…

Drawing-to-Learn: A Framework for Using Drawings to Promote Model-Based Reasoning in Biology

Science.gov (United States)

Quillin, Kim; Thomas, Stephen

2015-01-01

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094

Tecolote: An object-oriented framework for physics development

International Nuclear Information System (INIS)

Marshall, J.; Ankeny, L.; Clancy, S.

1998-01-01

The authors describe a C++ physics development environment, called the Tecolote Framework, which allows model developers to work more efficiently and accurately. This Framework contains a variety of meshes, operators, and parallel fields, as well as an input/output (I/O) subsystem and graphics capabilities. Model developers can inherit Tecolote's generic model interface and use the Framework's high-level field and operator components to write parallel physics equations. New Tecolote models are easily registered with the Framework, and they can be built and called directly from the input file, which greatly expedites model installation. In the process of developing an extensible and robust framework, they have found appealing solutions to some of the serious problems they encounter when parallelizing and extending the older codes. They also discuss memory and performance issues for a large hydrodynamics application built in this Framework

A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA

Science.gov (United States)

Nolan, Bernard T.; Fienen, Michael N.; Lorenz, David L.

2015-01-01

We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

A program wide framework for evaluating data driven teaching and learning - earth analytics approaches, results and lessons learned

Science.gov (United States)

Wasser, L. A.; Gold, A. U.

2017-12-01

There is a deluge of earth systems data available to address cutting edge science problems yet specific skills are required to work with these data. The Earth analytics education program, a core component of Earth Lab at the University of Colorado - Boulder - is building a data intensive program that provides training in realms including 1) interdisciplinary communication and collaboration 2) earth science domain knowledge including geospatial science and remote sensing and 3) reproducible, open science workflows ("earth analytics"). The earth analytics program includes an undergraduate internship, undergraduate and graduate level courses and a professional certificate / degree program. All programs share the goals of preparing a STEM workforce for successful earth analytics driven careers. We are developing an program-wide evaluation framework that assesses the effectiveness of data intensive instruction combined with domain science learning to better understand and improve data-intensive teaching approaches using blends of online, in situ, asynchronous and synchronous learning. We are using targeted online search engine optimization (SEO) to increase visibility and in turn program reach. Finally our design targets longitudinal program impacts on participant career tracts over time.. Here we present results from evaluation of both an interdisciplinary undergrad / graduate level earth analytics course and and undergraduate internship. Early results suggest that a blended approach to learning and teaching that includes both synchronous in-person teaching and active classroom hands-on learning combined with asynchronous learning in the form of online materials lead to student success. Further we will present our model for longitudinal tracking of participant's career focus overtime to better understand long-term program impacts. We also demonstrate the impact of SEO optimization on online content reach and program visibility.

Introducing a New Learning and Teaching Evaluation Planning Framework for Small Internally Funded Projects in Higher Education

Science.gov (United States)

Huber, Elaine

2017-01-01

Scholarly evaluation practices in learning and teaching projects are under-reported in the literature. In order for robust evaluative measures to be implemented, a project requires a well-designed evaluation plan. This research study describes the development of a practical evaluation planning framework through an action research approach, using…

Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework

Directory of Open Access Journals (Sweden)

Juan Carlos Davila

2017-06-01

Full Text Available The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, several factors related to sensor data alignment, data losses, and noise, among other experimental constraints, deteriorate data quality and model accuracy. To tackle these issues, this paper presents a data-driven iterative learning framework to classify human locomotion activities such as walk, stand, lie, and sit, extracted from the Opportunity dataset. Data acquired by twelve 3-axial acceleration sensors and seven inertial measurement units are initially de-noised using a two-stage consecutive filtering approach combining a band-pass Finite Impulse Response (FIR and a wavelet filter. A series of statistical parameters are extracted from the kinematical features, including the principal components and singular value decomposition of roll, pitch, yaw and the norm of the axial components. The novel interactive learning procedure is then applied in order to minimize the number of samples required to classify human locomotion activities. Only those samples that are most distant from the centroids of data clusters, according to a measure presented in the paper, are selected as candidates for the training dataset. The newly built dataset is then used to train an SVM multi-class classifier. The latter will produce the lowest prediction error. The proposed learning framework ensures a high level of robustness to variations in the quality of input data, while only using a much lower number of training samples and therefore a much shorter training time, which is an important consideration given the large size of the dataset.

Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework.

Science.gov (United States)

Davila, Juan Carlos; Cretu, Ana-Maria; Zaremba, Marek

2017-06-07

The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, several factors related to sensor data alignment, data losses, and noise, among other experimental constraints, deteriorate data quality and model accuracy. To tackle these issues, this paper presents a data-driven iterative learning framework to classify human locomotion activities such as walk, stand, lie, and sit, extracted from the Opportunity dataset. Data acquired by twelve 3-axial acceleration sensors and seven inertial measurement units are initially de-noised using a two-stage consecutive filtering approach combining a band-pass Finite Impulse Response (FIR) and a wavelet filter. A series of statistical parameters are extracted from the kinematical features, including the principal components and singular value decomposition of roll, pitch, yaw and the norm of the axial components. The novel interactive learning procedure is then applied in order to minimize the number of samples required to classify human locomotion activities. Only those samples that are most distant from the centroids of data clusters, according to a measure presented in the paper, are selected as candidates for the training dataset. The newly built dataset is then used to train an SVM multi-class classifier. The latter will produce the lowest prediction error. The proposed learning framework ensures a high level of robustness to variations in the quality of input data, while only using a much lower number of training samples and therefore a much shorter training time, which is an important consideration given the large size of the dataset.

Investigating CALL in the Classroom: Situational Variables to Consider

Directory of Open Access Journals (Sweden)

Darlene Liutkus

2012-01-01

Full Text Available A new paradigm in second language pedagogy has Computer Assisted Language Learning (CALL playing a significant role. Much of the literature to-date claims that CALL can have a positive impact on students’ second language acquisition (SLA. Mixed method of research produces data to investigate if CALL positively affects student language proficiency, motivation and autonomy. Classroom observation of participants in their natural environment is a qualitative technique used but has situational variables that could skew results if not structured. A questionnaire is a quantitative tool that can offer insight regarding participants’ perception of performance but can contradict what the researcher has observed. This paper will take an in-depth look at variables such as: instructor’s pedagogical application; blending CALL into the curriculum; types of CALL implemented; feedback received and their implications for design of the data collection tools

Utilization of information communication technology (ICT) - Based training / learning for capacity building in radiation protection framework

International Nuclear Information System (INIS)

Oluyemi, I.O.D.

2008-01-01

Full text: Radiation protection is the science of protecting people and the environment from the harmful effects of ionizing radiation, which includes both particle radiation and high energy electromagnetic radiation. It includes occupational radiation protection, which is the protection of workers; medical radiation protection, which is the protection of patients; and public radiation protection, which is about protection of individual members of the public, and of the population as a whole. ICT has made possible the development of e-learning and several Virtual Learning Environments (VLEs) which can support a wide range of capacity building requirements, ranging from under-graduate and post-graduate programmes, continuing professional development courses, right through to short subject specific and research courses, thereby eliminating the problems of conventional forms of training / learning, some of which are: limited access, cost effectiveness and language / cultural barriers. This paper focuses on the utilization of these ICT-based training / learning for capacity building in radiation protection framework and concludes with suggestions on implementation strategies. (author)

A self-organizing learning account of number-form synaesthesia.

Science.gov (United States)

Makioka, Shogo

2009-09-01

Some people automatically and involuntarily "see" mental images of numbers in spatial arrays when they think of numbers. This phenomenon, called number forms, shares three key characteristics with the other types of synaesthesia, within-individual consistency, between-individual variety, and mixture of regularity and randomness. A theoretical framework called SOLA (self-organizing learning account of number forms) is proposed, which explains the generation process of number forms and the origin of those three characteristics. The simulations replicated the qualitative properties of the shapes of number forms, the property that numbers are aligned in order of size, that discontinuity usually occurs at the point of carry, and that continuous lines tend to have many bends.

Toward a common theory for learning from reward, affect, and motivation: the SIMON framework

OpenAIRE

Madan, Christopher R.

2013-01-01

While the effects of reward, affect, and motivation on learning have each developed into their own fields of research, they largely have been investigated in isolation. As all three of these constructs are highly related, and use similar experimental procedures, an important advance in research would be to consider the interplay between these constructs. Here we first define each of the three constructs, and then discuss how they may influence each other within a common framework. Finally, we...

Tourism websites in English as a source for the autonomous learning of specialized terminology: A CALL application

Directory of Open Access Journals (Sweden)

Ángel Felices Lago

2016-04-01

Full Text Available For years now, it has been an unquestioned fact that a large majority of textbooks available in English for Tourism, either in book format, CD-Rom or web site access are based on situations and professional contexts connected with the Anglo-Saxon environment, even though the vast majority of graduates in Tourism in Spain (and other countries end up working in the region (autonomous community of origin or in the province of reference for studies. There is, therefore, a clear dysfunction between the textbooks available in the market and the materials and situations that the students will face in their professional future. However, the Internet now allows us to exploit the availability of vast quantities of local resources (websites, blogs, etc. with their corresponding versions in English, which include tourist information referring to, for example, hotels, restaurants, historical and artistic heritage sites, tour operators, travel agencies, trade fairs or specialized services at the national, regional or communal levels. All these sites offer a special showcase of all the linguistic resources available (be they lexical, syntactic or terminological that the learners must acquire for their professional development. Consequently, the purpose of this study is to offer the results of the computer-assisted language learning (CALL project entitled Autonomous Learning of Specialized Vocabulary in English for Tourism (http://wdb.ugr.es/~afelices/, which takes into consideration the previous premises in order to promote, as its title indicates, autonomous learning in a more realistic professional context and to serve as a model for the development of similar e-learning platforms in other regions or countries.

Readiness of Adults to Learn Using E-Learning, M-Learning and T-Learning Technologies

Science.gov (United States)

Vilkonis, Rytis; Bakanoviene, Tatjana; Turskiene, Sigita

2013-01-01

The article presents results of the empirical research revealing readiness of adults to participate in the lifelong learning process using e-learning, m-learning and t-learning technologies. The research has been carried out in the framework of the international project eBig3 aiming at development a new distance learning platform blending virtual…

Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations.

Science.gov (United States)

Cario, Clinton L; Witte, John S

2018-03-15

As whole-genome tumor sequence and biological annotation datasets grow in size, number and content, there is an increasing basic science and clinical need for efficient and accurate data management and analysis software. With the emergence of increasingly sophisticated data stores, execution environments and machine learning algorithms, there is also a need for the integration of functionality across frameworks. We present orchid, a python based software package for the management, annotation and machine learning of cancer mutations. Building on technologies of parallel workflow execution, in-memory database storage and machine learning analytics, orchid efficiently handles millions of mutations and hundreds of features in an easy-to-use manner. We describe the implementation of orchid and demonstrate its ability to distinguish tissue of origin in 12 tumor types based on 339 features using a random forest classifier. Orchid and our annotated tumor mutation database are freely available at https://github.com/wittelab/orchid. Software is implemented in python 2.7, and makes use of MySQL or MemSQL databases. Groovy 2.4.5 is optionally required for parallel workflow execution. JWitte@ucsf.edu. Supplementary data are available at Bioinformatics online.

Comprehensive Framework for Evaluating e-Learning Systems: Using BSC Framework

Science.gov (United States)

Momeni, Mansor; Jamporazmey, Mona; Mehrafrouz, Mohsen; Bahadori, Fatemeh

2013-01-01

The development of information and communication technology (ICT) is changing the way in which people work, communicate and learn. Recently developing and implementing e-learning solutions have increased dramatically. According to heavily investing in this area, it is essential to evaluate its different aspects and understand measures, which…

'Learning Organizations': a clinician's primer.

Science.gov (United States)

O'Connor, Nick; Kotze, Beth

2008-06-01

Most clinicians are poorly informed in relation to the key concepts of organizational learning. Yet the paradigm may offer clinicians a powerful method for using their knowledge and skills to respond to the demands of a changing environment through experimentation and learning. The concept is critically examined. Organizational learning principles are presented, including a conceptual framework for assessing health services as Learning Organizations. Barriers to organizational learning and strategies to overcome these are discussed. The seminal works of Argyris and Senge are reviewed and a framework for assessing organizational learning in health services is proposed. Current area health service actions are evaluated against the 'diagnostic' framework for a Learning Organization. Although critical examination reveals a poor empirical basis for the concept, the metaphor of the Learning Organization provides a useful conceptual framework and tools for individuals and organizations to apply in developing knowledge and effecting change. The Clinical Practice Improvement and Root Cause Analysis programs being conducted across NSW area health services meet the criteria for effective organizational learning. Key concepts from organizational learning theory provide a diagnostic framework for evaluating area health services as Learning Organizations and support two current strategies for overcoming barriers to organizational learning.

Sex differences in the representation of call stimuli in a songbird secondary auditory area.

Science.gov (United States)

Giret, Nicolas; Menardy, Fabien; Del Negro, Catherine

2015-01-01

Understanding how communication sounds are encoded in the central auditory system is critical to deciphering the neural bases of acoustic communication. Songbirds use learned or unlearned vocalizations in a variety of social interactions. They have telencephalic auditory areas specialized for processing natural sounds and considered as playing a critical role in the discrimination of behaviorally relevant vocal sounds. The zebra finch, a highly social songbird species, forms lifelong pair bonds. Only male zebra finches sing. However, both sexes produce the distance call when placed in visual isolation. This call is sexually dimorphic, is learned only in males and provides support for individual recognition in both sexes. Here, we assessed whether auditory processing of distance calls differs between paired males and females by recording spiking activity in a secondary auditory area, the caudolateral mesopallium (CLM), while presenting the distance calls of a variety of individuals, including the bird itself, the mate, familiar and unfamiliar males and females. In males, the CLM is potentially involved in auditory feedback processing important for vocal learning. Based on both the analyses of spike rates and temporal aspects of discharges, our results clearly indicate that call-evoked responses of CLM neurons are sexually dimorphic, being stronger, lasting longer, and conveying more information about calls in males than in females. In addition, how auditory responses vary among call types differ between sexes. In females, response strength differs between familiar male and female calls. In males, temporal features of responses reveal a sensitivity to the bird's own call. These findings provide evidence that sexual dimorphism occurs in higher-order processing areas within the auditory system. They suggest a sexual dimorphism in the function of the CLM, contributing to transmit information about the self-generated calls in males and to storage of information about the

Sex differences in the representation of call stimuli in a songbird secondary auditory area

Directory of Open Access Journals (Sweden)

Nicolas eGiret

2015-10-01

Full Text Available Understanding how communication sounds are encoded in the central auditory system is critical to deciphering the neural bases of acoustic communication. Songbirds use learned or unlearned vocalizations in a variety of social interactions. They have telencephalic auditory areas specialized for processing natural sounds and considered as playing a critical role in the discrimination of behaviorally relevant vocal sounds. The zebra finch, a highly social songbird species, forms lifelong pair bonds. Only male zebra finches sing. However, both sexes produce the distance call when placed in visual isolation. This call is sexually dimorphic, is learned only in males and provides support for individual recognition in both sexes. Here, we assessed whether auditory processing of distance calls differs between paired males and females by recording spiking activity in a secondary auditory area, the caudolateral mesopallium (CLM, while presenting the distance calls of a variety of individuals, including the bird itself, the mate, familiar and unfamiliar males and females. In males, the CLM is potentially involved in auditory feedback processing important for vocal learning. Based on both the analyses of spike rates and temporal aspects of discharges, our results clearly indicate that call-evoked responses of CLM neurons are sexually dimorphic, being stronger, lasting longer and conveying more information about calls in males than in females. In addition, how auditory responses vary among call types differ between sexes. In females, response strength differs between familiar male and female calls. In males, temporal features of responses reveal a sensitivity to the bird’s own call. These findings provide evidence that sexual dimorphism occurs in higher-order processing areas within the auditory system. They suggest a sexual dimorphism in the function of the CLM, contributing to transmit information about the self-generated calls in males and to storage of

A Development of Game-Based Learning Environment to Activate Interaction among Learners

Science.gov (United States)

Takaoka, Ryo; Shimokawa, Masayuki; Okamoto, Toshio

Many studies and systems that incorporate elements such as “pleasure” and “fun” in the game to improve a learner's motivation have been developed in the field of learning environments. However, few are the studies of situations where many learners gather at a single computer and participate in a game-based learning environment (GBLE), and where the GBLE designs the learning process by controlling the interactions between learners such as competition, collaboration, and learning by teaching. Therefore, the purpose of this study is to propose a framework of educational control that induces and activates interaction between learners intentionally to create a learning opportunity that is based on the knowledge understanding model of each learner. In this paper, we explain the design philosophy and the framework of our GBLE called “Who becomes the king in the country of mathematics?” from a game viewpoint and describe the method of learning support control in the learning environment. In addition, we report the results of the learning experiment with our GBLE, which we carried out in a junior high school, and include some comments by a principal and a teacher. From the results of the experiment and some comments, we noticed that a game may play a significant role in weakening the learning relationship among students and creating new relationships in the world of the game. Furthermore, we discovered that learning support control of the GBLE has led to activation of the interaction between learners to some extent.

The Effects of the CALL Model on College English Reading Teaching

Directory of Open Access Journals (Sweden)

Dan Zhang

2017-12-01

Full Text Available Computer Assisted Language Learning (CALL is an important concept in English teaching method reform. College students’ English reading ability is an important indicator in the evaluation on the college students’ English proficiency. Therefore, this paper applies the CALL model in English reading teaching. Firstly, it introduces the application and development prospect of the CALL model, and analyzes its advantages and disadvantages; secondly, it analyzes the present situation of college English teaching and its influencing factors and then designs an application example to integrate the CALL model with different aspect of English reading. Finally, it analyzes the teaching results of college English reading under the CALL model. Therefore, in both theory and practice, this paper proves the effectiveness and innovativeness of the CALL model.

Game-powered machine learning.

Science.gov (United States)

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-04-24

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the "wisdom of the crowds." Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., "funky jazz with saxophone," "spooky electronica," etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data.

Roles and Domains to Teach in Online Learning Environments: Educational ICT Competency Framework for University Teachers

Science.gov (United States)

Guasch, Teresa; Alvarez, Ibis; Espasa, Anna

This chapter is aimed at presenting an integrated framework of the educational information and communications technology (ICT) competencies that university teachers should have to teach in an online learning environment. Teaching through ICT in higher education involves performing three main roles - pedagogical, socialist, and design/planning - and also two cross-cutting domains that arise from the online environment: technological and managerial. This framework as well as the competencies for university teachers associated with it were validated at a European level by a dual process of net-based focus groups of teachers and teacher trainers in each of the participating countries in a European Project (Elene-TLC) and an online Delphi method involving 78 experts from 14 universities of ten European countries. The competency framework and the examples provided in the chapter are the basis for designing innovative professional development activities in online university environments.

A model-based risk management framework

Energy Technology Data Exchange (ETDEWEB)

Gran, Bjoern Axel; Fredriksen, Rune

2002-08-15

The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

Interdisciplinary Research at the Intersection of CALL, NLP, and SLA: Methodological Implications from an Input Enhancement Project

Science.gov (United States)

Ziegler, Nicole; Meurers, Detmar; Rebuschat, Patrick; Ruiz, Simón; Moreno-Vega, José L.; Chinkina, Maria; Li, Wenjing; Grey, Sarah

2017-01-01

Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The…

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…

Evaluating the Motivational Impact of CALL Systems: Current Practices and Future Directions

Science.gov (United States)

Bodnar, Stephen; Cucchiarini, Catia; Strik, Helmer; van Hout, Roeland

2016-01-01

A major aim of computer-assisted language learning (CALL) is to create computer environments that facilitate students' second language (L2) acquisition. To achieve this aim, CALL employs technological innovations to create novel types of language practice. Evaluations of the new practice types serve the important role of distinguishing effective…

Call mimicry by eastern towhees and its significance in relation to auditory learning

Science.gov (United States)

Jon S. Greenlaw; Clifford E. Shackelford; Raymond E. Brown

1998-01-01

The authors document cases of eastern towhees (Pipilo erythrophthalmus) using mimicked alarm calls from three presumptive models (blue jay (Cyanocitta cristata), brown thrasher (Toxostoma rufum), and American robin (Turdus migratorius)). In four instances, male towhees employed heterospecific calls without substitution in their own call repertoires. Three birds (New...

Code-first development with Entity Framework

CERN Document Server

Barskiy, Sergey

2015-01-01

This book is intended for software developers with some prior experience with the Microsoft .NET framework who want to learn how to use Entity Framework. This book will get you up and running quickly, providing many examples that illustrate all the key concepts of Entity Framework.

The Game Embedded CALL System to Facilitate English Vocabulary Acquisition and Pronunciation

Science.gov (United States)

Young, Shelley Shwu-Ching; Wang, Yi-Hsuan

2014-01-01

The aim of this study is to make a new attempt to explore the potential of integrating game strategies with automatic speech recognition technologies to provide learners with individual opportunities for English pronunciation learning. The study developed the Game Embedded CALL (GeCALL) system with two activities for on-line speaking practice. For…

Neutrality as Obstructionist in Academic Activism: Calling Bullshit

Science.gov (United States)

Rose, Barbara J.

2018-01-01

In this essay, the author uses experiences as a teacher educator and learning from a historically significant activism movement to (a) compare values in activism-centered and education-centered organizations, (b) posit ways that the concept of neutrality weakens academic activism, and (c) call for teacher education curricula and practices that…

Young doctors' problem solving strategies on call may be improved.