The hardest part is knowing I will survive: The use of music and creative mediums to enhance empathy and facilitate life-long distance learning in professionally qualified clinicians

© Redfame Publishing Inc.Music is an experience that can cross personal and professional domains alongside cultural, gender, age and generational boundaries; it can also enhance the learning process through emotional processing and connection. This paper focuses on the learning experience of qualified clinical psychologists (CPs) working in the United Kingdom. This group of CPs had experience of undertaking experiential learning and reflective writing during their professional training. It considers the potential to continue a learning process, 3 years post qualification, through long distance methods using vignette-based material. Empathising with, and understanding, the position of others from differing backgrounds is an important competency within the therapeutic work of CPs and this comes alongside acknowledging and understanding ones‟ own experiences, both past and present. CPs work with difficult life experiences and complex issues; connecting constantly can be exhausting and, perhaps, unrealistic. Yet, to truly empathise one must connect with, and understand, the lived experiences of others. We will consider what helps and hinders this process, and how music and other creative mediums can be effectively used in learning even via long distance methods. We will further consider how CPs may be well placed to enhance the learning about, and processing of, difficult emotional experiences for themselves, other clinicians and the people they might work with.Peer reviewe

Security in online learning assessment towards an effective trustworthiness approach to support e-learning teams

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.This paper proposes a trustworthiness model for the design of secure learning assessment in on-line collaborative learning groups. Although computer supported collaborative learning has been widely adopted in many educational institutions over the last decade, there exist still drawbacks which limit their potential in collaborative learning activities. Among these limitations, we investigate information security requirements in on-line assessment, (e-assessment), which can be developed in collaborative learning contexts. Despite information security enhancements have been developed in recent years, to the best of our knowledge, integrated and holistic security models have not been completely carried out yet. Even when security advanced methodologies and technologies are deployed in Learning Management Systems, too many types of vulnerabilities still remain opened and unsolved. Therefore, new models such as trustworthiness approaches can overcome these lacks and support e-assessment requirements for e-Learning. To this end, a trustworthiness model is designed in order to conduct the guidelines of a holistic security model for on-line collaborative learning through effective trustworthiness approaches. In addition, since users' trustworthiness analysis involves large amounts of ill-structured data, a parallel processing paradigm is proposed to build relevant information modeling trustworthiness levels for e-Learning.Peer ReviewedPostprint (author's final draft

Mobility, physical space and learning

Our biological inheritance is to sense the world through many channels including the non verbal. Learning theory, in both organizational and pedagogic contexts, has come to recognise as much, yet the dominant physical expressions given to learning space in both contexts remain rooted in linear arrangements. The advent of contemporary human processing tools and artefacts have the potential to liberate the learner yet space designs, driven by dictates of notional efficiency and a view of work and learning as separate, stationary processes, constrain through a reduction in the natural reliance on sensorial, embodied human capacities. With an example of case material, we suggest an asynchronous co-evolutionary process, a syncretisation of learning theories and space design. Granting physical expression to modern views of the learning process as mobile and corporeal can, accelerate learning. Key words Workspace, workplace, learning, complexity, organizational ecology, mobilit

Media Interaktif Pembelajaran Kandungan Gizi Dalam Sayuran Serta Manfaat Dalam Tubuh Manusia

The vegetable is an excellent food for the human body, many various of vegetables that sold at market make vegetable contain many different contents and benefits, many societies understand about vegetable but many less understood what the side effects of certain vegetables. Nowadays, there are many applications spread out there, but they could not get society\u27s concern because lack of image dan voice for naration.This application will give you knowledge about the content and the benefits, side effects, and processing interactively and it has images, sound, music, and interesting simulation, so that users could directly involved in the learning process. The material in this interactive media taken from 13 kinds of vegetables which are described the content and benefits, side effects, and processing. For content and material benefits, and side effects are provided animationfor material processing in the form of simulation. There is also a test to measure the users understanding towards material that already studied. This application was created using Adobe Flash CS6.With the simulation and animation that is contained in this application can really help users to understand the material being studied. Based on survey\u27s result from 30 respondents, 70% respondents agreed the explication from the material, 72.5% agreed that images support in learning process and 80% agreed that animation support in learning process. Thus will increase interest in learning from user applications

Life is… great! : emotional attention during instructed and uninstructed ambiguity resolution in relation to depressive symptoms

Attention and interpretation biases are closely involved in depression-related processing of emotional material. However, it is unclear whether attention and interpretation biases reflect a processing tendency (i.e., driven by schemas or prior learning) or an ability-related process (i.e., dependent on attentional control). This study tested how depressive symptom severity, attention bias, and interpretation bias are related under tendency versus ability processing conditions. Fifty-two participants completed two versions of the scrambled sentences test (to measure interpretation bias) while eye movements were recorded (to measure attention bias) in separate experimental sessions. To assess tendency and ability processes, participants were instructed to unscramble the sentences by reporting the first sentence that comes to mind (tendency version; session 1) and to unscramble the sentences in a fixed, positive manner (ability version; session 2). Results showed that depressive symptom severity was correlated with attention bias under both tendency and ability conditions. Analyses showed that attention bias (i.e., the fixation time spent on positive versus negative words) acted as an intervening variable in the relation between depressive symptoms and interpretation bias only during ability processes. These findings suggest that depression-linked biases in attention reflect both processing tendencies and ability-related processes in attentional control, with attentional control as a relevant mechanism in the subsequent interpretation of emotional material. Implications for cognitive theories and cognitive training methods are discussed.Depto. de Personalidad, Evaluación y Psicología ClínicaFac. de PsicologíaTRUEpu

PERSEPSI GURU PEMBIMBING TERHADAP PROSES PEMBELAJARAN MAHASISWA PRAKTIK PPL UNIVERSITAS NEGERI YOGYAKARTA DI SMK PIRI 1 YOGYAKARTA TAHUN AJARAN 2012/2013

This study aims to describe perception of tutor to student skills practice in the implementation of the learning process PPL SMK Piri 1 Yogyakarta in the academic year 2012/2013. Students in an effort to prepare myself as a professional teacher candidates must master a variety of skills to carry out the process of learning the skills of open learning, skills to master the material, skills of presenting the material, classroom management skills, closing skills lessons. This study uses a descriptive research with quantitative approach. The data collection technique using a questionnaire filled out by the respondents covered the entire guidance counselor at SMK Piri 1 Yogyakarta academic year 2012/2013 were 26 teacher mentors. To test the validity of the instrument using the product moment correlation, and for testing the reliability of the instrument using Cronbach alpha. The data analysis technique used is descriptive and statistical techniques for tendency classification is divided into three categories: high, medium, and low. Processing data using SPSS 17 for windows. The results of this study tutor perceptions on the implementation of learning practices of students PPL Yogyakarta State University academic year 2012/2013 are included in the category with the total percentage in the high category and the category was 73.08% which includes skills lesson opens with a total percentage in the high category and category at 76.92%, the skill to master the material with a total percentage in the high category and the category was 61.54%, the skill deliver material with a total percentage in the high category and the category was 69.23%, classroom management skills with the total percentage of the category high and medium category, 73.08%, and closing skills with a total percentage of subjects in the high category and the category was 73.08%, while 26.92% as included in the category of low-this is because the students do not have experience teaching practices and lack of control of components -components in the implementation of learning, especially in the ability to master and deliver the material so that the interaction with the students is not maximized

Structural Material Property Tailoring Using Deep Neural Networks

Advances in robotics, artificial intelligence, and machine learning are ushering in a new age of automation, as machines match or outperform human performance. Machine intelligence can enable businesses to improve performance by reducing errors, improving sensitivity, quality and speed, and in some cases achieving outcomes that go beyond current resource capabilities. Relevant applications include new product architecture design, rapid material characterization, and life-cycle management tied with a digital strategy that will enable efficient development of products from cradle to grave. In addition, there are also challenges to overcome that must be addressed through a major, sustained research effort that is based solidly on both inferential and computational principles applied to design tailoring of functionally optimized structures. Current applications of structural materials in the aerospace industry demand the highest quality control of material microstructure, especially for advanced rotational turbomachinery in aircraft engines in order to have the best tailored material property. In this paper, deep convolutional neural networks were developed to accurately predict processing-structure-property relations from materials microstructures images, surpassing current best practices and modeling efforts. The models automatically learn critical features, without the need for manual specification and/or subjective and expensive image analysis. Further, in combination with generative deep learning models, a framework is proposed to enable rapid material design space exploration and property identification and optimization. The implementation must take account of real-time decision cycles and the trade-offs between speed and accuracy

Statistical Shape Analysis using Kernel PCA

©2006 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The electronic version of this article is the complete one and can be found online at: http://dx.doi.org/10.1117/12.641417DOI:10.1117/12.641417Presented at Image Processing Algorithms and Systems, Neural Networks, and Machine Learning, 16-18 January 2006, San Jose, California, USA.Mercer kernels are used for a wide range of image and signal processing tasks like de-noising, clustering, discriminant analysis etc. These algorithms construct their solutions in terms of the expansions in a high-dimensional feature space F. However, many applications like kernel PCA (principal component analysis) can be used more effectively if a pre-image of the projection in the feature space is available. In this paper, we propose a novel method to reconstruct a unique approximate pre-image of a feature vector and apply it for statistical shape analysis. We provide some experimental results to demonstrate the advantages of kernel PCA over linear PCA for shape learning, which include, but are not limited to, ability to learn and distinguish multiple geometries of shapes and robustness to occlusions