A sphere of resonance for networked learning in the ‘non-places’ of our universities

The logic of ‘time’ in modern capitalist society appears to be a fixed concept. Time dictates human activity with a regularity, which as long ago as 1944, George Woodcock referred to as The Tyranny of the Clock. Seventy years on, Hartmut Rosa suggests humans no longer maintain speed to achieve something new, but simply to preserve the status quo, in a ‘social acceleration’ that is lethal to democracy. Political engagement takes time we no longer have, as we rush between our virtual spaces and ‘non-places’ of higher education. I suggest it’s time to confront the conspirators that, in partnership with the clock, accelerate our social engagements with technology in the context of learning. Through Critical Discourse Analysis (CDA) I reveal an alarming situation if we don’t. With reference to Bauman’s Liquid Modernity, I observe a ‘lightness’ in policy texts where humans have been ‘liquified’ Separating people from their own labour with technology in policy maintains the flow of speed a neoliberal economy demands. I suggest a new ‘solidity’ of human presence is required as we write about networked learning. ‘Writing ourselves back in’ requires a commitment to ‘be there’ in policy and provide arguments that decelerate the tyranny of time. I am though ever-mindful that social acceleration is also of our own making, and there is every possibility that we actually enjoy it.

Technology enhanced learning in Higher Education

Technology-Enhanced Learning in Higher Education is an anthology produced by the international association, Learning in Higher Education (LiHE). LiHE, whose scope includes the activities of colleges, universities and other institutions of higher education, has been one of the leading organisations supporting a shift in the education process from a transmission-based philosophy to a student-centred, learning-based approach. Traditionally education has been envisaged as a process in which the teacher disseminates knowledge and information to the student, and directs them to perform – instructing, cajoling, encouraging them as appropriate – despite different students’ abilities. Yet higher education is currently experiencing rapid transformation, with the introduction of a broad range of technologies which have the potential to enhance student learning. This anthology draws upon the experiences of those practitioners who have been pioneering new applications of technology in higher education, highlighting not only the technologies themselves but also the impact which they have had on student learning. The anthology illustrates how new technologies – which are increasingly well-known and accepted by today’s ‘digital natives’ undertaking higher education – can be adopted and incorporated. One key conclusion is that learning remains a social process even in technology-enhanced learning contexts. So the technology-based proxies we construct need to retain and reflect the agency of the teacher. Technology-Enhanced Learning in Higher Education showcases some of the latest pedagogical technologies and their most creative, state-of-the-art applications to learning in higher education from around the world. Each of the chapters explores technology-enhanced learning in higher education in terms of either policy or practice. They contain detailed descriptions of approaches taken in very different curriculum areas, and demonstrate clearly that technology may and can enhance learning only if it is designed with the learning process of students at its core. So the use of technology in education is more linked to pedagogy than it is to bits and bytes.

Using observation ageing to improve Markovian model learning in QoS engineering

Markovian models are widely used to analyse quality-of-service properties of both system designs and deployed systems. Thanks to the emergence of probabilistic model checkers, this analysis can be performed with high accuracy. However, its usefulness is heavily dependent on how well the model captures the actual behaviour of the analysed system. Our work addresses this problem for a class of Markovian models termed discrete-time Markov chains (DTMCs). We propose a new Bayesian technique for learning the state transition probabilities of DTMCs based on observations of the modelled system. Unlike existing approaches, our technique weighs observations based on their age, to account for the fact that older observations are less relevant than more recent ones. A case study from the area of bioinformatics workflows demonstrates the effectiveness of the technique in scenarios where the model parameters change over time.

Something to talk about: Content and Language Integrated Learning in Modern Languages in British Higher Education. A case study of German at Aston University

This thesis investigates Content and Language Integrated Learning (CLIL) in German undergraduate programmes in the UK. At its core is a study of how one German department integrates the teaching of language and content in its undergraduate programmes and how instructors and students experience this approach. This micro-context is embedded in the wider macro-context of UK Higher Education and subject to outside forces - be they political, economic, socio-cultural - whose effects will manifest in more or less obvious ways. Data was collected via an online survey of Heads of German at British universities to determine the status quo of CLIL in UK Higher Education and to investigate how certain institutional parameters determine the introduction of CLIL in Higher Education. This project employs a mixed-method case study approach and is based on student questionnaires and semi-structured interview with German teaching staff. The study brings to light a number of significant aspects. For example, contrary to popular belief, content provision in the L2 is rather common at British universities, which is currently not reflected in the research. Student data indicates that German students perceive clear advantages in the university’s approach to CLIL. They consider German-taught content classes challenging yet beneficial for their language development. Staff interviews have yielded intriguing information about perceived advantages and disadvantages of CLIL, about its implications for classroom practice, and about instructors’ attitude towards teacher training, which echo findings from similar investigations in European contexts. Finally, the results of the macro-analysis and the case study are compared and contrasted with findings from European research on ICLHE/CLIL to determine differences and similarities with the British context, a set of recommendations is made regarding CLIL practice at the case study institution, and some implications these indings may have for the future of CLIL in British higher education are discussed.

Assessing learning in Higher Education

Assessing Learning in Higher Education addresses what is probably the most time-consuming part of the work of staff in higher education, and something to the complexity of which many of the recent developments in higher education have added. Getting assessment ‘right’– that is, designing and implementing appropriate models and methods, can determine the future lives and careers of students. But, as Professor Phil Race comments in his excellent and thought-provoking foreword, students entering higher education often have little idea about how exactly assessment will work, and often find that the process is very different from anything they have previously encountered. Assessing Learning in Higher Education contains innovative approaches to assessment drawn from many different cultures and disciplines. The chapter authors argue the need for changing assessment and feedback processes so that they embrace online collaboration and discussion between students as well as between ‘students’ and ‘faculty’. The chapters demonstrate that at some points there is a need to be able to measure individual achievement, and to do this in ways that are valid, transparent, authentic – and above all fair. Assessment and feedback processes need to ensure that students are well prepared for this individual assessment, but also to take account of collaboration and interaction. The respective chapters of Assessing Learning in Higher Education all of which are complete in themselves, but with very useful links to ideas in other chapters, provide numerous illustrations of how this can be achieved.

Adaptive back-propagation in on-line learning of multilayer networks

An adaptive back-propagation algorithm is studied and compared with gradient descent (standard back-propagation) for on-line learning in two-layer neural networks with an arbitrary number of hidden units. Within a statistical mechanics framework, both numerical studies and a rigorous analysis show that the adaptive back-propagation method results in faster training by breaking the symmetry between hidden units more efficiently and by providing faster convergence to optimal generalization than gradient descent.

Noisy fitness evaluation in genetic algorithms and the dynamics of learning

A theoretical model is presented which describes selection in a genetic algorithm (GA) under a stochastic fitness measure and correctly accounts for finite population effects. Although this model describes a number of selection schemes, we only consider Boltzmann selection in detail here as results for this form of selection are particularly transparent when fitness is corrupted by additive Gaussian noise. Finite population effects are shown to be of fundamental importance in this case, as the noise has no effect in the infinite population limit. In the limit of weak selection we show how the effects of any Gaussian noise can be removed by increasing the population size appropriately. The theory is tested on two closely related problems: the one-max problem corrupted by Gaussian noise and generalization in a perceptron with binary weights. The averaged dynamics can be accurately modelled for both problems using a formalism which describes the dynamics of the GA using methods from statistical mechanics. The second problem is a simple example of a learning problem and by considering this problem we show how the accurate characterization of noise in the fitness evaluation may be relevant in machine learning. The training error (negative fitness) is the number of misclassified training examples in a batch and can be considered as a noisy version of the generalization error if an independent batch is used for each evaluation. The noise is due to the finite batch size and in the limit of large problem size and weak selection we show how the effect of this noise can be removed by increasing the population size. This allows the optimal batch size to be determined, which minimizes computation time as well as the total number of training examples required.

On-line learning with adaptive back-propagation in two-layer networks

An adaptive back-propagation algorithm parameterized by an inverse temperature 1/T is studied and compared with gradient descent (standard back-propagation) for on-line learning in two-layer neural networks with an arbitrary number of hidden units. Within a statistical mechanics framework, we analyse these learning algorithms in both the symmetric and the convergence phase for finite learning rates in the case of uncorrelated teachers of similar but arbitrary length T. These analyses show that adaptive back-propagation results generally in faster training by breaking the symmetry between hidden units more efficiently and by providing faster convergence to optimal generalization than gradient descent.

Noise, regularizers, and unrealizable scenarios in online learning from restricted training sets

We study the dynamics of on-line learning in multilayer neural networks where training examples are sampled with repetition and where the number of examples scales with the number of network weights. The analysis is carried out using the dynamical replica method aimed at obtaining a closed set of coupled equations for a set of macroscopic variables from which both training and generalization errors can be calculated. We focus on scenarios whereby training examples are corrupted by additive Gaussian output noise and regularizers are introduced to improve the network performance. The dependence of the dynamics on the noise level, with and without regularizers, is examined, as well as that of the asymptotic values obtained for both training and generalization errors. We also demonstrate the ability of the method to approximate the learning dynamics in structurally unrealizable scenarios. The theoretical results show good agreement with those obtained by computer simulations.

The development and evaluation of distance learning materials for administrative personnel in a multi-national company

There has been substantial research into the role of distance learning in education. Despite the rise in the popularity and practice of this form of learning in business, there has not been a parallel increase in the amount of research carried out in this field. An extensive investigation was conducted into the entire distance learning system of a multi-national company with particular emphasis on the design, implementation and evaluation of the materials. In addition, the performance and attitudes of trainees were examined. The results of a comparative study indicated that trainees using distance learning had significantly higher test scores than trainees using conventional face-to-face training. The influence of the previous distance learning experience, educational background and selected study environment of trainees was investigated. Trainees with previous experience of distance learning were more likely to complete the course and with significantly higher test scores than trainees with no previous experience. The more advanced the educational background of trainees, the greater the likelihood of their completing the course, although there was no significant difference in the test scores achieved. Trainees preferred to use the materials at home and those opting to study in this environment scored significantly higher than those studying in the office, the study room at work or in a combination of environments. The influence of learning styles (Kolb, 1976) was tested. The results indicated that the convergers had the greatest completion rates and scored significantly higher than trainees with the assimilator, accommodator and diverger learning styles. The attitudes of the trainees, supervisors and trainers were examined using questionnaire, interview and discussion techniques. The findings highlighted the potential problems of lack of awareness and low motivation which could prove to be major obstacles to the success of distance learning in business.

A study in Britain and France of the development of cross-cultural in-house sales training using distance learning.

The thesis is concerned with cross-cultural distance learning in two countries: Great Britain and France. Taking the example of in-house sales training, it argues that it is possible to develop courses for use in two or more countries of differing culture and language. Two courses were developed by the researcher. Both were essentially print-based distance-learning courses designed to help salespeople achieve a better understanding of their customers. One used a quantitative, the other qualitative approach. One considered the concept of the return on investment and the other, for which a video support was also developed, considered the analysis of a customer's needs. Part 1 of the thesis considers differences in the training context between France and Britain followed by a review of the learning process with reference to distance learning. Part 2 looks at the choice of training medium course design and evaluation and sets out the methodology adopted, including problems encountered in this type of fieldwork. Part 3 analyses the data and draws conclusions from the findings, before offering a series of guidelines for those concerned with the development of cross-cultural in-house training courses. The results of the field tests on the two courses were analysed in relation to the socio-cultural, educational and experiential background of the learners as well as their preferred learning styles. The thesis argues that it is possible to develop effective in-house sales training courses to be used in two cultures and identifies key considerations which need to be taken into account when carrying out this type of work.