A variational approach to learning curves

We combine the replica approach from statistical physics with a variational approach to analyze learning curves analytically. We apply the method to Gaussian process regression. As a main result we derive approximative relations between empirical error measures, the generalization error and the posterior variance.

Inquiring how a lecturer keeps learning about their teaching:a personal case history on reflective imagination

In order to reverse the use of lecture-based teaching, it is argued that personal reflection can be used as part of the quality assurance process. This paper proposes one response to personal reflection - reflective imagination, which is summarised as an action plan with six activities. It combines two conceptual issues raised in the US, the need to think creatively about learning and the reflective mindset, and one issue raised in the UK, cultivating the entrepreneurial imagination. Reflective imagination is linked to wider social science research, the place of self and reflexivity in scholarship. Finally, a personal history case study is presented which records a visit to Harvard Business School. The visit implements the six activities associated with reflective imagination. This is a method paper exploring reflective imagination.

Evaluation of the quality and promotion of open learning materials

In the UK, Open Learning has been used in industrial training for at least the last decade. Trainers and Open Learning practitioners have been concerned about the quality of the products and services being delivered. The argument put forward in this thesis is that there is ambiguity amongst industrialists over the meanings of `Open Learning' and `Quality in Open Learning'. For clarity, a new definition of Open Learning is proposed which challenges the traditional learner-centred approach favoured by educationalists. It introduces the concept that there are benefits afforded to the trainer/employer/teacher as well as to the learner. This enables a focussed view of what quality in Open Learning really means. Having discussed these issues, a new quantitative method of evaluating Open Learning is proposed. This is based upon an assessment of the degree of compliance with which products meet Parts 1 & 2 of the Open Learning Code of Practice. The vehicle for these research studies has been a commercial contract commissioned by the Training Agency for the Engineering Industry Training Board (EITB) to examine the quality of Open Learning products supplied to the engineering industry. A major part of this research has been the application of the evaluation technique to a range of 67 Open Learning products (in eight subject areas). The findings were that good quality products can be found right across the price range - so can average and poor quality ones. The study also shows quite convincingly that there are good quality products to be found at less than 50. Finally the majority (24 out of 34) of the good quality products were text based.

Parallel strategy for optimal learning in perceptrons

We developed a parallel strategy for learning optimally specific realizable rules by perceptrons, in an online learning scenario. Our result is a generalization of the Caticha–Kinouchi (CK) algorithm developed for learning a perceptron with a synaptic vector drawn from a uniform distribution over the N-dimensional sphere, so called the typical case. Our method outperforms the CK algorithm in almost all possible situations, failing only in a denumerable set of cases. The algorithm is optimal in the sense that it saturates Bayesian bounds when it succeeds.

Post-registration learning trends of community pharmacists

Background: Some Australian pharmacists use continuing education to maintain knowledge and acquire new information. There has been a progression from continuing education to continuing professional development (CPD) - a mandatory requirement for pharmacists in all jurisdictions of Australia. Aim: To identify post-registration learning trends of community pharmacists in Western Australia. Method: A questionnaire was developed and administered by face-to-face interviews with community pharmacists in metropolitan Perth. Pharmacists registered for less than 12 months and pharmacists working in hospitals were excluded. Results: 103 pharmacists were approached with a response rate of 95%. Journals (41%), reference books (23%) and the Internet (18%) were the most commonly used educational resources cited by pharmacists. Keeping scientific information up-to-date (39%) and gathering practical knowledge (22%) were the leading motivators for pharmacists to participate in continuing education. Factors that hindered participation in continuing education included lack of time (34%), family commitments (21%) and business commitments (21%). 79% of pharmacists agreed with the concept of mandatory CPD. 47% of pharmacists suggested that the primary sanction for not complying with mandatory CPD should be counselling to determine reasons for non-compliance. Conclusion: Community pharmacists preferred educational resources that were easily accessible at convenient times. Most pharmacists were able to fulfil the requirements of CPD, however, further educational support and promotion would ensure the successful uptake of CPD by community pharmacists in Western Australia.

(S)excerpts from a Life Told:sex, gender and learning lisability

This is an article about Sarah’s sexual teenage journey, seen through the lens of her mother, the author. It tackles learning disability, sexual experimentation, education, governance and responsibility. By using an autoethnographical method the article speaks personally to these intimate lived experiences and yet broadly and contextually these issues can give further insight into the difficult social processes that permeate surveillance and control, of sexual activity amongst a particular group of adults (young, learning disabled), by way of legal practice and sex education; family practices and the negotiation of power and control over sexual activity; and sexual citizenship and rights to a sexual identity.

Increased salience of gains versus decreased associative learning differentiate bipolar disorder from schizophrenia during incentive decision making

Background Abnormalities in incentive decision making, typically assessed using the Iowa Gambling Task (IGT), have been reported in both schizophrenia (SZ) and bipolar disorder (BD). We applied the Expectancy-Valence (E-V) model to determine whether motivational, cognitive and response selection component processes of IGT performance are differentially affected in SZ and BD. Method Performance on the IGT was assessed in 280 individuals comprising 70 remitted patients with SZ, 70 remitted patients with BD and 140 age-, sex-and IQ-matched healthy individuals. Based on the E-V model, we extracted three parameters, 'attention to gains or loses', 'expectancy learning' and 'response consistency', that respectively reflect motivational, cognitive and response selection influences on IGT performance. Results Both patient groups underperformed in the IGT compared to healthy individuals. However, the source of these deficits was diagnosis specific. Associative learning underlying the representation of expectancies was disrupted in SZ whereas BD was associated with increased incentive salience of gains. These findings were not attributable to non-specific effects of sex, IQ, psychopathology or medication. Conclusions Our results point to dissociable processes underlying abnormal incentive decision making in BD and SZ that could potentially be mapped to different neural circuits. © 2012 Cambridge University Press.

Issues in learning an ontology from text

Ontology construction for any domain is a labour intensive and complex process. Any methodology that can reduce the cost and increase efficiency has the potential to make a major impact in the life sciences. This paper describes an experiment in ontology construction from text for the animal behaviour domain. Our objective was to see how much could be done in a simple and relatively rapid manner using a corpus of journal papers. We used a sequence of pre-existing text processing steps, and here describe the different choices made to clean the input, to derive a set of terms and to structure those terms in a number of hierarchies. We describe some of the challenges, especially that of focusing the ontology appropriately given a starting point of a heterogeneous corpus. Results - Using mainly automated techniques, we were able to construct an 18055 term ontology-like structure with 73% recall of animal behaviour terms, but a precision of only 26%. We were able to clean unwanted terms from the nascent ontology using lexico-syntactic patterns that tested the validity of term inclusion within the ontology. We used the same technique to test for subsumption relationships between the remaining terms to add structure to the initially broad and shallow structure we generated. All outputs are available at http://thirlmere.aston.ac.uk/~kiffer/animalbehaviour/ webcite. Conclusion - We present a systematic method for the initial steps of ontology or structured vocabulary construction for scientific domains that requires limited human effort and can make a contribution both to ontology learning and maintenance. The method is useful both for the exploration of a scientific domain and as a stepping stone towards formally rigourous ontologies. The filtering of recognised terms from a heterogeneous corpus to focus upon those that are the topic of the ontology is identified to be one of the main challenges for research in ontology learning.

Network learning:an empirically-derived conceptual model of learning by groups of organizations

Building on a previous conceptual article, we present an empirically derived model of network learning - learning by a group of organizations as a group. Based on a qualitative, longitudinal, multiple-method empirical investigation, five episodes of network learning were identified. Treating each episode as a discrete analytic case, through cross-case comparison, a model of network learning is developed which reflects the common, critical features of the episodes. The model comprises three conceptual themes relating to learning outcomes, and three conceptual themes of learning process. Although closely related to conceptualizations that emphasize the social and political character of organizational learning, the model of network learning is derived from, and specifically for, more extensive networks in which relations among numerous actors may be arms-length or collaborative, and may be expected to change over time.

Semisupervised learning of hierarchical latent trait models for data visualization

Recently, we have developed the hierarchical Generative Topographic Mapping (HGTM), an interactive method for visualization of large high-dimensional real-valued data sets. In this paper, we propose a more general visualization system by extending HGTM in three ways, which allows the user to visualize a wider range of data sets and better support the model development process. 1) We integrate HGTM with noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM). This enables us to visualize data of inherently discrete nature, e.g., collections of documents, in a hierarchical manner. 2) We give the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode, the user selects "regions of interest," whereas in the automatic mode, an unsupervised minimum message length (MML)-inspired construction of a mixture of LTMs is employed. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. 3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualization plots, since they can highlight the boundaries between data clusters. We illustrate our approach on a toy example and evaluate it on three more complex real data sets. © 2005 IEEE.

Innovating engineering education: the RVS approach:an empirically grounded method to improved practice and enhanced student experience

This paper builds on previous work (Clark, 2009; Clark & Andrews 2011, 2014) to continue the debate around a seemingly universal question…“How can educational theory be applied to engineering education in such a way so as to make the subject more accessible and attractive to students? It argues that there are three key elements to student success; Relationships, Variety & Synergy (RVS). By further examining the purposefully developed bespoke learning and teaching approach constructed around these three elements (RVS) the discourse in this paper links educational theory to engineering education and in doing so further develops arguments for the introduction of a purposefully designed pedagogic approach for use in engineering education.

Incremental tensor biased discriminant analysis:a new color-based visual tracking method

Most existing color-based tracking algorithms utilize the statistical color information of the object as the tracking clues, without maintaining the spatial structure within a single chromatic image. Recently, the researches on the multilinear algebra provide the possibility to hold the spatial structural relationship in a representation of the image ensembles. In this paper, a third-order color tensor is constructed to represent the object to be tracked. Considering the influence of the environment changing on the tracking, the biased discriminant analysis (BDA) is extended to the tensor biased discriminant analysis (TBDA) for distinguishing the object from the background. At the same time, an incremental scheme for the TBDA is developed for the tensor biased discriminant subspace online learning, which can be used to adapt to the appearance variant of both the object and background. The experimental results show that the proposed method can track objects precisely undergoing large pose, scale and lighting changes, as well as partial occlusion. © 2009 Elsevier B.V.

Photo-sketch synthesis and recognition based on subspace learning

This paper aims to reducing difference between sketches and photos by synthesizing sketches from photos, and vice versa, and then performing sketch-sketch/photo-photo recognition with subspace learning based methods. Pseudo-sketch/pseudo-photo patches are synthesized with embedded hidden Markov model. Because these patches are assembled by averaging their overlapping area in most of the local strategy based methods, which leads to blurring effect to the resulted pseudo-sketch/pseudo-photo, we integrate the patches with image quilting. Experiments are carried out to demonstrate that the proposed method is effective to produce pseudo-sketch/pseudo-photo with high quality and achieve promising recognition results. © 2009.

Models, Techniques and Applications of e-Learning Personalization

In recent years Web has become mainstream medium for communication and information dissemination. This paper presents approaches and methods for adaptive learning implementation, which are used in some contemporary web-interfaced Learning Management Systems (LMSs). The problem is not how to create electronic learning materials, but how to locate and utilize the available information in personalized way. Different attitudes to personalization are briefly described in section 1. The real personalization requires a user profile containing information about preferences, aims, and educational history to be stored and used by the system. These issues are considered in section 2. A method for development and design of adaptive learning content in terms of learning strategy system support is represented in section 3. Section 4 includes a set of innovative personalization services that are suggested by several very important research projects (SeLeNe project, ELENA project, etc.) dated from the last few years. This section also describes a model for role- and competency-based learning customization that uses Web Services approach. The last part presents how personalization techniques are implemented in Learning Grid-driven applications.

Generalized Nets Model of an E-Learning System Software Architecture

The paper has been presented at the International Conference Pioneers of Bulgarian Mathematics, Dedicated to Nikola Obreshko ff and Lubomir Tschakaloff , Sofi a, July, 2006.