TQM in e-Learning: a Self-assessment Model and Questionnaire

Organizations are seeking new, integrated systems that enable rapid changes through early identification of opportunities and problems, tracking of progress against plans, flexible allocation of resources to achieve goals, and consistent operations. Total Quality Management (TQM) is an overall business strategy. It means that all activities of the company will be focused on satisfying all stakeholders of the company. TQM can be realised by using the EFQM model. The EFQM model is a tool that organizations may use as a framework for self-evaluation that enables an organization to identify its strengths and areas for improvement and the extent to which its operations and results are in line with the characteristics of an excellent organization. We focus on a training organisation or to the learning department of an organization. So we are limiting the EFQM model to the training /learning activities. We can apply EFQM perfect on the level of an activity (business line) of a company. We selected the main criteria for which the learner can play the role of assessor. So only three main criteria left: the enabling resources, the enabling processes and the (learning) results for the learner. We limited the last one to “learning results” based on the Kirkpatrick model.

Self-Learning Fuzzy Spiking Neural Network as a Nonlinear Pulse-Position Threshold Detection Dynamic System Based on Second-Order Critically Damped Response Units

Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.

Use of Start Pages for Building a Mashup Personal Learning Environment to Support Self-Organized Learners

The paper explores the functionalities of eight start pages and considers their usefulness when used as a mashable platform for deployment of personal learning environments (PLE) for self-organized learners. The Web 2.0 effects and eLearning 2.0 strategies are examined from the point of view of how they influence the methods of gathering and capturing data, information and knowledge, and the learning process. Mashup technology is studied in order to see what kind of components can be used in PLE realization. A model of a PLE for self-organized learners is developed and it is used to prototype a personal learning and research environment in the start pages Netvibes, Pageflakes and iGoogle.

Parental confidence in managing food allergy:development of the Food Allergy Self-Efficacy Scale for parents (FASE-P)

Background: Food allergy is often a life-long condition that requires constant vigilance in order to prevent accidental exposure and avoid potentially life-threatening symptoms. Parents’ confidence in managing their child’s food allergy may relate to the poor quality of life anxiety and worry reported by parents of food allergic children. Objective: The aim of the current study was to develop and validate the first scale to measure parental confidence (self-efficacy) in managing food allergy in their child. Methods: The Food Allergy Self-Efficacy Scale for Parents (FASE-P) was developed through interviews with 53 parents, consultation of the literature and experts in the area. The FASE-P was then completed by 434 parents of food allergic children from a general population sample in addition to the General Self-Efficacy Scale (GSES), the Food Allergy Quality of Life Parental Burden Scale (FAQL-PB), the General Health Questionnaire (GHQ12) and the Food Allergy Impact Measure (FAIM). A total of 250 parents completed the re-test of the FASE-P. Results: Factor and reliability analysis resulted in a 21 item scale with 5 sub-scales. The overall scale and sub-scales has good to excellent internal consistency (α’s of 0.63-0.89) and the scale is stable over time. There were low to moderate significant correlations with the GSES, FAIM and GHQ12 and strong correlations with the FAQL-PB, with better parental confidence relating to better general self-efficacy, better quality of life and better mental health in the parent. Poorer self-efficacy was related to egg and milk allergy; self-efficacy was not related to severity of allergy. Conclusions and clinical relevance: The FASE-P is a reliable and valid scale for use with parents from a general population. Its application within clinical settings could aid provision of advice and improve targeted interventions by identifying areas where parents have less confidence in managing their child’s food allergy.

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Living well to the end:a phenomenological analysis of life in extra care housing

OBJECTIVES: To understand older adults' experiences of moving into extra care housing which offers enrichment activities alongside social and healthcare support. DESIGN: A longitudinal study was conducted which adopted a phenomenological approach to data generation and analysis. METHODS: Semi-structured interviews were conducted in the first 18 months of living in extra care housing. Interpretative phenomenological analysis was used because its commitment to idiography enabled an in-depth analysis of the subjective lived experience of moving into extra care housing. Themes generated inductively were examined against an existential-phenomenological theory of well-being. RESULTS: Learning to live in an extra care community showed negotiating new relationships was not straightforward; maintaining friendships outside the community became more difficult as capacity declined. In springboard for opportunity/confinement, living in extra care provided new opportunities for social engagement and a restored sense of self. Over time horizons began to shrink as incapacities grew. Seeking care illustrated reticence to seek care, due to embarrassment and a sense of duty to one's partner. Becoming aged presented an ontological challenge. Nevertheless, some showed a readiness for death, a sense of homecoming. CONCLUSIONS: An authentic later life was possible but residents required emotional and social support to live through the transition and challenges of becoming aged. Enhancement activities boosted residents' quality of life but the range of activities could be extended to cater better for quieter, smaller scale events within the community; volunteer activity facilitators could be used here. Peer mentoring may help build new relationships and opportunities for interactive stimulation. Acknowledging the importance of feeling-empathic imagination-in caregiving may help staff and residents relate better to each other, thus helping individuals to become ontologically secure and live well to the end.

Developing a robust self evaluation framework for active learning:the first stage of an ERASMUS+ project (QAEMarketPlace4HEI)

In ensuring the quality of learning and teaching in Higher Education, self-evaluation is an important component of the process. An example would be the approach taken within the CDIO community whereby self-evaluation against the CDIO standards is part of the quality assurance process. Eight European universities (Reykjavik University, Iceland; Turku University of Applied Sciences, Finland; Aarhus University, Denmark; Helsinki Metropolia University of Applied Sciences, Finland; Ume? University, Sweden; Telecom Bretagne, France; Aston University, United Kingdom; Queens University Belfast, United Kingdom) are engaged in an EU funded Erasmus + project that is exploring the quality assurance process associated with active learning. The development of a new self-evaluation framework that feeds into a ?Marketplace? where participating institutions can be paired up and then engage in peer evaluations and sharing around each institutions approach to and implementation of active learning. All of the partner institutions are engaged in the application of CDIO within their engineering programmes and this has provided a common starting point for the partnership to form and the project to be developed. Although the initial focus will be CDIO, the longer term aim is that the approach could be of value beyond CDIO and within other disciplines. The focus of this paper is the process by which the self-evaluation framework is being developed and the form of the draft framework. In today?s Higher Education environment, the need to comply with Quality Assurance standards is an ever present feature of programme development and review. When engaging in a project that spans several countries, the wealth of applicable standards and guidelines is significant. In working towards the development of a robust Self Evaluation Framework for this project, the project team decided to take a wide view of the available resources to ensure a full consideration of different requirements and practices. The approach to developing the framework considered: a) institutional standards and processes b) national standards and processes e.g. QAA in the UK c) documents relating to regional / global accreditation schemes e.g. ABET d) requirements / guidelines relating to particular learning and teaching frameworks e.g. CDIO. The resulting draft self-evaluation framework is to be implemented within the project team to start with to support the initial ?Marketplace? pairing process. Following this initial work, changes will be considered before a final version is made available as part of the project outputs. Particular consideration has been paid to the extent of the framework, as a key objective of the project is to ensure that the approach to quality assurance has impact but is not overly demanding in terms of time or paperwork. In other words that it is focused on action and value added to staff, students and the programmes being considered.

The impact of a family home-learning program on levels of parental/caregiver efficacy

This study sought to determine if participation in a home education learning program would impact the perceived levels of parental self-efficacy of parents/caregivers who participate in the completion of home-learning assignments and increase their levels of home-learning involvement practices. Also, the study examined the relationship between the parental involvement practice of completing interactive home-learning assignments and the reading comprehension achievement of first grade students. A total of 146 students and their parents/caregivers representing a convenience sample of eight first grade classes participated in the study. Four classes (n=74) were selected as the experimental group and four classes (n=72) served as the control group. There were 72 girls in the sample and 74 boys and the median age was 6 years 6 months. The study employed a quasi-experimental research design utilizing eight existing first grade classes. It examined the effects of a home-learning support intervention program on the perceived efficacy levels of the participating parents/caregivers, as measured by the Parent Perceptions of Parent Efficacy Scale (Hoover-Dempsey, Bassler, & Brissie, 1992) administered on a pre/post basis. The amount and type of parent involvement in the completion of home assignments was determined by means of a locally developed instrument, the H.E.L.P. Parent Involvement Home-learning Scale, administered on a pre/post basis. Student achievement in reading comprehension was measured via the reading subtest of the Brigance, CIB-S pre and post. The elementary students and their parents/caregivers participated in an interactive home-learning intervention program for 12 weeks that required parent/caregiver assistance. Results revealed the experimental group of parents/caregivers had a significant increase in their levels of perceived self-efficacy, p<.001, from the pre to post, and also had significantly increased levels of parental involvement in seven home-learning activities, p<.001, than the control group parents/caregivers. The experimental group students demonstrated significantly higher reading levels than the control group students, p<.001. This study provided evidence that interactive home-learning activities improved the levels of parental self-efficacy and parental involvement in home-learning activities, and improved the reading comprehension of the experimental group in comparison to the control.

Labeling large scale social media data using budget-driven One-class SVM classification

The social media classification problems draw more and more attention in the past few years. With the rapid development of Internet and the popularity of computers, there is astronomical amount of information in the social network (social media platforms). The datasets are generally large scale and are often corrupted by noise. The presence of noise in training set has strong impact on the performance of supervised learning (classification) techniques. A budget-driven One-class SVM approach is presented in this thesis that is suitable for large scale social media data classification. Our approach is based on an existing online One-class SVM learning algorithm, referred as STOCS (Self-Tuning One-Class SVM) algorithm. To justify our choice, we first analyze the noise-resilient ability of STOCS using synthetic data. The experiments suggest that STOCS is more robust against label noise than several other existing approaches. Next, to handle big data classification problem for social media data, we introduce several budget driven features, which allow the algorithm to be trained within limited time and under limited memory requirement. Besides, the resulting algorithm can be easily adapted to changes in dynamic data with minimal computational cost. Compared with two state-of-the-art approaches, Lib-Linear and kNN, our approach is shown to be competitive with lower requirements of memory and time.

Validation of the English version of the Scale for Psychosocial Factors in Food Allergy and the relationship with mental health, quality of life, and self-efficacy

Background. The Scale for Psychosocial Factors in Food Allergy (SPS-FA) is based on the biopsychosocial model of health and was developed and validated in Chile to measure the interaction between psychological variables and allergy symptoms in the child. We sought to validate this scale in an English speaking population and explore its relationship with parental quality of life, self-efficacy, and mental health. Methods. Parents (n = 434) from the general population in the UK, who had a child with a clinical diagnosis of food allergy, completed the SPS-FA and validated scales on food allergy specific parental quality of life (QoL), parental self-efficacy, and general mental health. Findings. The SPS-FA had good internal consistency (alphas = .61-.86). Higher scores on the SPS-FA significantly correlated with poorer parental QoL, self-efficacy, and mental health. All predictors explained 57% of the variance in SPS-FA scores with QoL as the biggest predictor (β = .52). Discussion. The SPS-FA is a valid scale for use in the UK and provides a holistic view of the impact of food allergy on the family. In conjunction with health-related QoL measures, it can be used by health care practitioners to target care for patients and evaluate psychological interventions for improvement of food allergy management.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

The Impact of a Family Home-learning Program on levels of Parental/Caregiver Efficacy

This study sought to determine if participation in a home education learning program would impact the perceived levels of parental self-efficacy of parents/caregivers who participate in the completion of home-learning assignments and increase their levels of home-learning involvement practices. Also, the study examined the relationship between the parental involvement practice of completing interactive home-learning assignments and the reading comprehension achievement of first grade students. A total of 146 students and their parents/caregivers representing a convenience sample of eight first grade classes participated in the study. Four classes (n=74) were selected as the experimental group and four classes (n=72) served as the control group. . There were 72 girls in the sample and 74 boys and the median age was 6 years 6 months. The study employed a quasi-experimental research design utilizing eight existing first grade classes. It examined the effects of a home-learning support intervention program on the perceived efficacy levels of the participating parents/care¬givers, as measured by the Parent Perceptions of Parent Efficacy Scale (Hoover-Dempsey, Bassler, & Brissie, 1992) administered on a pre/post basis. The amount and type of parent involvement in the completion of home assignments was determined by means of a locally developed instrument, the H.E.L.P. Parent Involvement Home-learning Scale, administered on a pre/post basis. Student achievement in reading comprehension was measured via the reading subtest of the Brigance, CIB-S pre and post. The elementary students and their parents/caregivers participated in an interactive home-learning intervention program for 12 weeks that required parent/caregiver assistance. Results revealed the experimental group of parents/caregivers had a significant increase in their levels of perceived self-efficacy, p<.001, from the pre to post, and also had significantly increased levels of parental involvement in seven home-learning activities, p<.001, than the control group parents/caregivers. The experimental group students demonstrated significantly higher reading levels than the control group students, p<.001. This study provided evidence that interactive home-learning activities improved the levels of parental self-efficacy and parental involvement in home-learning activities, and improved the reading comprehension of the experimental group in comparison to the control.

An Investigation of the Features and Effectiveness of the Full-Day Early Learning Kindergarten Program in Ontario

This dissertation includes two studies. Study 1 is a qualitative case study that describes enactment of the main components of a high fidelity Full-Day Early Learning Kindergarten (FDELK) classroom, specifically play-based learning and teacher-ECE collaboration. Study 2 is a quantitative analysis that investigates how effectively the FDELK program promotes school readiness skills, namely self-regulation, literacy, and numeracy, in Kindergarteners. To describe the main components of an FDELK classroom in Study 1, a sub-sample of four high fidelity case study schools were selected from a larger case study sample. Interview data from these schools’ administrators, educators, parents, and community stakeholders were used to describe how the main components of the FDELK program enabled educators to meet the individual needs of students and promote students’ SR development. In Study 2, hierarchical regression analyses of 32,207 students’ self-regulation, literacy, and numeracy outcomes using 2012 Ontario Early Development Instrument (EDI) data revealed essentially no benefit for students participating in the FDELK program when compared to peers in Half-Day or Alternate-Day Kindergarten programs. Being older and female predicted more positive SR and literacy outcomes. Age and gender accounted for limited variance in numeracy outcomes. Results from both studies suggest that the Ontario Ministry of Education should take steps to improve the quality of the FDELK program by incorporating evidence-based guidelines and goals for play, reducing Kindergarten class sizes to more effectively scaffold learning, and revising curriculum expectations to include a greater focus on SR, literacy, and numeracy skills.

Correlation between anxiety and academic self-concept in interpreter trainees

This paper focuses on two basic issues: the anxiety-generating nature of the interpreting task and the relevance of interpreter trainees’ academic self-concept. The first has already been acknowledged, although not extensively researched, in several papers, and the second has only been mentioned briefly in interpreting literature. This study seeks to examine the relationship between the anxiety and academic self-concept constructs among interpreter trainees. An adapted version of the Foreign Language Anxiety Scale (Horwitz et al., 1986), the Academic Autoconcept Scale (Schmidt, Messoulam & Molina, 2008) and a background information questionnaire were used to collect data. Students’ t-Test analysis results indicated that female students reported experiencing significantly higher levels of anxiety than male students. No significant gender difference in self-concept levels was found. Correlation analysis results suggested, on the one hand, that younger would-be interpreters suffered from higher anxiety levels and students with higher marks tended to have lower anxiety levels; and, on the other hand, that younger students had lower self-concept levels and higher-ability students held higher self-concept levels. In addition, the results revealed that students with higher anxiety levels tended to have lower self-concept levels. Based on these findings, recommendations for interpreting pedagogy are discussed.

Unraveling networked learning initiatives: an analytic framework

Networked learning happens naturally within the social systems of which we are all part. However, in certain circumstances individuals may want to actively take initiative to initiate interaction with others they are not yet regularly in exchange with. This may be the case when external influences and societal changes require innovation of existing practices. This paper proposes a framework with relevant dimensions providing insight into precipitated characteristics of designed as well as ‘fostered or grown’ networked learning initiatives. Networked learning initiatives are characterized as “goal-directed, interest-, or needs based activities of a group of (at least three) individuals that initiate interaction across the boundaries of their regular social systems”. The proposed framework is based on two existing research traditions, namely 'networked learning' and 'learning networks', comparing, integrating and building upon knowledge from both perspectives. We uncover some interesting differences between definitions, but also similarities in the way they describe what ‘networked’ means and how learning is conceptualized. We think it is productive to combine both research perspectives, since they both study the process of learning in networks extensively, albeit from different points of view, and their combination can provide valuable insights in networked learning initiatives. We uncover important features of networked learning initiatives, characterize actors and connections of which they are comprised and conditions which facilitate and support them. The resulting framework could be used both for analytic purposes and (partly) as a design framework. In this framework it is acknowledged that not all successful networks have the same characteristics: there is no standard ‘constellation’ of people, roles, rules, tools and artefacts, although there are indications that some network structures work better than others. Interactions of individuals can only be designed and fostered till a certain degree: the type of network and its ‘growth’ (e.g. in terms of the quantity of people involved, or the quality and relevance of co-created concepts, ideas, artefacts and solutions to its ‘inhabitants’) is in the hand of the people involved. Therefore, the framework consists of dimensions on a sliding scale. It introduces a structured and analytic way to look at the precipitation of networked learning initiatives: learning networks. Successive research on the application of this framework and feedback from the networked learning community is needed to further validate it’s usability and value to both research as well as practice.