Bayesian invariant measurements of generalisation

The problem of evaluating different learning rules and other statistical estimators is analysed. A new general theory of statistical inference is developed by combining Bayesian decision theory with information geometry. It is coherent and invariant. For each sample a unique ideal estimate exists and is given by an average over the posterior. An optimal estimate within a model is given by a projection of the ideal estimate. The ideal estimate is a sufficient statistic of the posterior, so practical learning rules are functions of the ideal estimator. If the sole purpose of learning is to extract information from the data, the learning rule must also approximate the ideal estimator. This framework is applicable to both Bayesian and non-Bayesian methods, with arbitrary statistical models, and to supervised, unsupervised and reinforcement learning schemes.

Induction by a Hilbert hypercube representation

This thesis describes a novel connectionist machine utilizing induction by a Hilbert hypercube representation. This representation offers a number of distinct advantages which are described. We construct a theoretical and practical learning machine which lies in an area of overlap between three disciplines - neural nets, machine learning and knowledge acquisition - hence it is refered to as a "coalesced" machine. To this unifying aspect is added the various advantages of its orthogonal lattice structure as against less structured nets. We discuss the case for such a fundamental and low level empirical learning tool and the assumptions behind the machine are clearly outlined. Our theory of an orthogonal lattice structure the Hilbert hypercube of an n-dimensional space using a complemented distributed lattice as a basis for supervised learning is derived from first principles on clearly laid out scientific principles. The resulting "subhypercube theory" was implemented in a development machine which was then used to test the theoretical predictions again under strict scientific guidelines. The scope, advantages and limitations of this machine were tested in a series of experiments. Novel and seminal properties of the machine include: the "metrical", deterministic and global nature of its search; complete convergence invariably producing minimum polynomial solutions for both disjuncts and conjuncts even with moderate levels of noise present; a learning engine which is mathematically analysable in depth based upon the "complexity range" of the function concerned; a strong bias towards the simplest possible globally (rather than locally) derived "balanced" explanation of the data; the ability to cope with variables in the network; and new ways of reducing the exponential explosion. Performance issues were addressed and comparative studies with other learning machines indicates that our novel approach has definite value and should be further researched.

Good practice guide in learning and teaching

This is the second edition of our Aston Business School (ABS) Good Practice Guide and the enthusiasm of the contributors appears undiminished. I am again reminded that I work with a group of very committed, dedicated and professional colleagues. Once again this publication is produced to celebrate and promote good teaching across the School and to offer encouragement to those imaginative and innovative staff who continue to wish to challenge students to learn to maximum effect. It is hoped that others will pick up some good ideas from the articles contained in this volume. Contributors to this Guide were not chosen because they are the best teachers in the School, although they are undoubtedly all amongst my colleagues who are exponents of enthusiastic and inspiring approaches to learning. The Quality Unit approached these individuals because they declared on their Annual Module Reflection Forms that they were doing something interesting and worthwhile which they thought others might find useful. Amongst those reading the Guide I am sure that there are many other individuals who are trying to operate similar examples of good practice in their teaching, learning and assessment methods. I hope that this publication will provoke these people into providing comments and articles of their own and that these will form the basis of next year’s Guide. It may also provoke some people to try these methods in their own teaching. The themes of the articles this year can be divided into two groups. The first theme is the quest to help students to help themselves to learn via student-run tutorials, surprise tests and mock examinations linked with individual tutorials. The second theme is making learning come to life in exciting practical ways by, for example, hands-on workshops and simulations, story telling, rhetorical questioning and discussion groups. A common theme is one of enthusiasm, reflection and commitment on behalf of the lecturers concerned. None of the approaches discussed in this publication are low effort activities on the part of the facilitator, but this effort is regarded as worthwhile as a means of creating greater student engagement. As Biggs (2003)[1] says, in his similarly inspiring way, students learn more the less passive they are in their learning. (Ref). The articles in this publication bear witness of this and much more. Since last year Aston Business School has launched its Research Centre in Higher Education Learning and Management (HELM) which is another initiative to promote excellent learning and teaching. Even before this institution has become fully operational, at least one of the articles in this publication has seen the light of day in the research arena and at least two others are ripe for dissemination to a wider audience via journal publication. More news of our successes in this activity will appear in next year’s edition. May I thank the contributors for taking time out of their busy schedules to write the articles this summer, and to Julie Green who runs the ABS Quality Unit, for putting our diverse approaches into a coherent and publishable form and for chasing us when we have needed it! I would also like to thank Ann Morton and her colleagues in the Centre for Staff Development who have supported this publication. During the last year the Centre has further stimulated the learning and teaching life of the School (and the wider University) via their Learning and Teaching Week and sponsorship of Teaching Quality Enhancement Fund (TQEF) projects. Pedagogic excellence is in better health at Aston than ever before – long may this be because this is what life in HE should be about.

The exact sample complexity of PAC-learning problems with unit VC dimension

The Vapnik-Chervonenkis (VC) dimension is a combinatorial measure of a certain class of machine learning problems, which may be used to obtain upper and lower bounds on the number of training examples needed to learn to prescribed levels of accuracy. Most of the known bounds apply to the Probably Approximately Correct (PAC) framework, which is the framework within which we work in this paper. For a learning problem with some known VC dimension, much is known about the order of growth of the sample-size requirement of the problem, as a function of the PAC parameters. The exact value of sample-size requirement is however less well-known, and depends heavily on the particular learning algorithm being used. This is a major obstacle to the practical application of the VC dimension. Hence it is important to know exactly how the sample-size requirement depends on VC dimension, and with that in mind, we describe a general algorithm for learning problems having VC dimension 1. Its sample-size requirement is minimal (as a function of the PAC parameters), and turns out to be the same for all non-trivial learning problems having VC dimension 1. While the method used cannot be naively generalised to higher VC dimension, it suggests that optimal algorithm-dependent bounds may improve substantially on current upper bounds.

Dynamics of on-line learning in radial basis function networks

On-line learning is examined for the radial basis function network, an important and practical type of neural network. The evolution of generalization error is calculated within a framework which allows the phenomena of the learning process, such as the specialization of the hidden units, to be analyzed. The distinct stages of training are elucidated, and the role of the learning rate described. The three most important stages of training, the symmetric phase, the symmetry-breaking phase, and the convergence phase, are analyzed in detail; the convergence phase analysis allows derivation of maximal and optimal learning rates. As well as finding the evolution of the mean system parameters, the variances of these parameters are derived and shown to be typically small. Finally, the analytic results are strongly confirmed by simulations.

Incorporating curvature information into on-line learning

We analyse the dynamics of a number of second order on-line learning algorithms training multi-layer neural networks, using the methods of statistical mechanics. We first consider on-line Newton's method, which is known to provide optimal asymptotic performance. We determine the asymptotic generalization error decay for a soft committee machine, which is shown to compare favourably with the result for standard gradient descent. Matrix momentum provides a practical approximation to this method by allowing an efficient inversion of the Hessian. We consider an idealized matrix momentum algorithm which requires access to the Hessian and find close correspondence with the dynamics of on-line Newton's method. In practice, the Hessian will not be known on-line and we therefore consider matrix momentum using a single example approximation to the Hessian. In this case good asymptotic performance may still be achieved, but the algorithm is now sensitive to parameter choice because of noise in the Hessian estimate. On-line Newton's method is not appropriate during the transient learning phase, since a suboptimal unstable fixed point of the gradient descent dynamics becomes stable for this algorithm. A principled alternative is to use Amari's natural gradient learning algorithm and we show how this method provides a significant reduction in learning time when compared to gradient descent, while retaining the asymptotic performance of on-line Newton's method.

Retail multinational learning:a case study of Tesco

Purpose - This article examines the internationalisation of Tesco and extracts the salient lessons learned from this process. Design/methodology/ approach - This research draws on a dataset of 62 in-depth interviews with key executives, sell- and buy-side analysts and corporate advisers at the leading investment banks in the City of London to detail the experiences of Tesco's European expansion. Findings - The case study of Tesco illuminates a number of different dimensions of the company's international experience. It offers some new insights into learning in international distribution environments such as the idea that learning is facilitated by uncertainty or "shocks" in the international retail marketplace; the size of the domestic market may inhibit change and so disable international learning; and learning is not necessarily facilitated by step-by-step incremental approaches to expansion. Research limitations/implications - The paper explores learning from a rather broad perspective, although it is hoped that these parameters can be used to raise a new set of more detailed priorities for future research on international retail learning. It is also recognised that the data gathered for this case study focus on Tesco's European operations. Practical implications - This paper raises a number of interesting issues such as whether the extremities of the business may be a more appropriate place for management to experiment and test new retail innovations, and the extent to which retailers take self-reflection seriously. Originality/value - The paper applies a new theoretical learning perspective to capture the variety of experiences during the internationalisation process, thus addressing a major gap in our understanding of the whole internationalisation process. © Emerald Group Publishing Limited.

Understanding learning strategies in the workplace:a factor analytic investigation

The aim of this study was to validate a scale of learning strategies, as derived from the educational literature, in an organizational context. Participants were 628 call centre employees. Both exploratory and confirmatory factor analyses suggested that a six-factor structure most accurately represented the learning strategies examined. Specifically, three cognitive (extrinsic work reflection, intrinsic work reflection, reproduction) and three behavioural strategies (interpersonal help seeking, help seeking from written material, practical application) were found.

Financial accounting:a practical introduction

Discussing the theory and the application of accounting methods in isolation does not enable the learner to fully understand the material and the key techniques, and get the practice required. This text is an effort to “put a face” on this problem. Learning financial accounting is like learning a different language and as such, lots of practice is required. Financial accounting is not particularly a popular subject among first year students. Students usually find the first year introductory financial accounting module quite challenging and demanding. Many lecturers are consistently asked to provide more questions and exercises. Attempting a large number of accounting questions provides students with the necessary self-assurance and familiarity required to deal with more difficult aspects of financial accounting.

An investigation of the factor-analytic approach to the determination of abilities involved in psychomotor learning

This research began with an attempt to solve a practical problem, namely, the prediction of the rate at which an operator will learn a task. From a review of the literature, communications with researchers in this area and the study of psychomotor learning in factories it was concluded that a more fundamental approach was required which included the development of a task taxonomy. This latter objective had been researched for over twenty years by E. A. Fleishman and his approach was adopted. Three studies were carried out to develop and extend Fleishman's approach to the industrial area. However, the results of these studies were not in accord with FIeishman's conclusions and suggested that a critical re-assessment was required of the arguments, methods and procedures used by Fleishman and his co-workers. It was concluded that Fleishman's findings were to some extent an artifact of the approximate methods and procedures which he used in the original factor analyses and that using the more modern computerised factor analytic methods a reliable ability taxonomy could be developed to describe the abilities involved in the learning of psychomotor tasks. The implications for a changing-task or changing-subject model were drawn and it was concluded that a changing task and subject model needs to be developed.

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.

Evaluating and developing project-based learning:an empirical approach to evaluating CDIO

As a global profession, engineering is integral to the maintenance and further development of society. Indeed, contemporary social problems requiring engineering solutions are not only a consequence of natural and ‘manmade’ disasters (such as the Japanese earthquake or the oil leakage in the Gulf of Mexico) but also encapsulate 21st Century dilemmas around sustainability, poverty and pollution [2,6,7]. Given the complexity of such problems and the constant need for innovation, the demand for engineering education to provide a ready supply of suitably qualified engineering graduates, able to make innovative decisions has never been higher [3,5]. Bearing this in mind, and taking account problems of attrition in engineering education [1,6,4] innovation in the way in which the curriculum is developed and delivered is crucial. CDIO [Conceive, Design, Implement, Operate] provides a potentially ground-breaking solution to such dilemmas. Aimed at equipping students with practical engineering skills supported by the necessary theoretical background, CDIO could potentially change the way engineering is perceived and experienced within higher education. Aston University introduced CDIO into its Mechanical Engineering and Design programmes in October 2011. From its induction, engineering education researchers have ‘shadowed’ the staff responsible for developing and teaching the programme. Utilising an Action Research Design, and adopting a mixed methodological research design, the researchers have worked closely with the teaching team to critically reflect on the processes involved in introducing CDIO into the curriculum. Concurrently, research has been conducted to capture students’ perspectives of CDIO. In evaluating the introduction of CDIO at Aston, the researchers have developed a distinctive research strategy with which to evaluate CDIO. It is the emergent findings from this research that form the basis of this paper. Although early-on in its development CDIO is making a significant difference to engineering education at the University. The paper draws attention to pedagogical, practical and professional issues – discussing each one in turn and in doing so critically analysing the value of CDIO from academic, student and industrial perspectives. The paper concludes by noting that whilst CDIO represents a forwardthinking approach to engineering education, the need for constant innovation in learning and teaching should not be forgotten. Indeed, engineering education needs to put itself at the forefront of pedagogic practice. Providing all-rounded engineers, ready to take on the challenges of the 21st Century!

A bridge too far? Breaching the research/learning and teaching nexus in a previously research-led university

The relationship between research and learning and teaching represents what has been described as ‘amongst the most intellectually tangled, managerially complex and politically contentious issues in mass higher education’ (Scott, 2005, p 53). Despite this, arguments that in order to achieve high quality scholarly outcomes, university teachers need to adopt an approach to teaching similar to that of research (i.e. founded upon academic rigour and evidence), has long been discussed in the literature (see for example, Elton, 2005 & Healey, 2000). However, the practicalities of promoting an empirical and evidence-based approach to teaching within a research-led institution makes dealing with the research/learning and teaching nexus a somewhat challenging proposition. Drawing upon the findings of a mixed methodological study, this paper critically analyses the pedagogical, organisational and practical issues encountered by academics and support staff working within a newly established Centre for Learning Innovation and Professional Practice. Comprising an eclectic group of staff drawn from across the five Schools in the University, the Centre is dedicated to enhancing student learning through the development of evidence based teaching practice. Based upon the premise that the promotion of research-led teaching will act to bring teaching and research together, and in doing so enhance students learning experiences (Simmons & Elen 2007), the paper critically analyses the challenges encountered by staff responsible for developing and introducing a new learning & teaching focused organisational strategy (by reflecting on the previous 12 months work). In doing so it makes a significant contribution to current academic theory and debate in the areas of pedagogic practice and organisational management. Focusing specifically on the impact of the new policy on various aspects of university life including, pedagogic practice, student support, staff training, and organisational management, the paper critically addresses the cultural and attitudinal challenges of change management (Kotter, 1996) within a ‘grey-brick’ university. It concludes by arguing that the move towards becoming a more learning-focused university has started to develop an awareness of the positive impact the change initiative is having on the student experience and wider institution; whilst also drawing attention to the organisational challenges ahead.