Person-oriented and process-oriented teachers : an investigation of the links between ESOL teachers' personal belief systems and approaches to teaching

This thesis looks to two traditions in research into language teaching, teacher beliefs and classroom interaction, in order to investigate the question: Do teachers of ESOL have an identifiable and coherent system of beliefs about teaching and learning that may account for different approaches to teaching? A qualitative approach to research is taken, following a case study tradition, in order to carry out an in-depth study into the beliefs of six ESOL teachers. Five teachers participated in an initial pilot study and two subsequently became the main case studies for the research. The beliefs of a sixth teacher were then investigated to verify the findings. Semi-structured interviews and classroom observations were carried out with all the teachers. The teachers in the study were found to have personal belief systems that cohere around two orientations to teaching and learning - a person orientation and a process orientation. Moreover, the findings suggest that underlying the orientations is the perception that teachers have of their teacher identity, in terms of whether this is seen as a separate identity or as part of their personality. It is suggested that the two orientations may offer a powerful tool for teacher education as it is increasingly recognised that, in order to be effective, teacher educators must take into account the beliefs that teachers bring with them to training and development programmes. An initial investigations into the teachers’ classroom behaviour suggests that while their methodologies approach may be very similar there are fundamental differences in their interactions patterns and these differences may be a result of their own orientation. However, while teachers’ personal belief systems undoubtedly underlie their approach to teaching, further research is needed to establish the extent and the nature of the relationship between orientation and classroom interaction.

A systems approach to strategic manpower planning for technological development under conditions of manpower scarcity and centralised control

This thesis deals with the integration of the manpower criterion with the strategic decision making processes of technological projects in developing countries. This integration is to be achieved by ensuring the involvement of the actors, who have relevant roles and responsibilities along the whole life cycle of the project, in the strategic decision making phases of the project. The relevance of the actors is ascertained by the use of a responsibility index which relates their responsibility to the project's constituent stages. In the context of a technological project in a typical centrally-planned developing environment, the actors are identified as Arbiters, Planners, Implementors and Operators and their roles, concerns and objectives are derived. In this context, the actors are usually government and non-government organisations. Hence, decision making will involve multiple agencies as well as multiple criteria. A methodology covering the whole decision-making process, from options generation to options selection, and adopting Saaty's Analytical Hierarchy Process as an operational tool is proposed to deal with such multiple-criteria, multipleagency decision situations. The methodology is intended to integrate the consideration of the relevant criteria, the prevailing environmental and policy factors, and the concerns and objectives of the relevant actors into a unifying decision-making process which strives to facilitate enlightened decision making and to enhance learning and interaction. An extensive assessment of the methodology's feasibility, based on a specific technological project within the Iraqi oil industry is included, and indicates that the methodology should be both useful and implementable.

Adaptive electrical signal post-processing in optical communications systems

Improving bit error rates in optical communication systems is a difficult and important problem. The error correction must take place at high speed and be extremely accurate. We show the feasibility of using hardware implementable machine learning techniques. This may enable some error correction at the speed required.

Human resource development for inclusive procurement by intermediation:a situated learning theory application

This paper fills an important gap in the human resource development (HRD) literature by considering the role that NGO intermediation initiatives can play in bringing together and developing corporate procurement officials (CPOs) and ethnic minority business owner-managers (EMBOs) supplying goods and services. It has been suggested that such initiatives hold great promise in helping ethnic minority businesses escape from their disadvantageous sectoral concentration in the UK. Using situated learning theory as an application lens, the main aim of this paper is to demonstrate how nurturing communities of practice of CPOs and EMBOs and facilitating their interaction can help their professional development and their approaches to procuring and supplying, respectively. The paper reports on the authors' experience with an action research programme encompassing two intermediation initiatives of this kind. The lessons drawn from this study are useful for all those concerned with HRD for inclusive procurement; intermediaries promoting inclusive procurement, large procurers who are willing to engage with supplier diversity and ethnic minority suppliers who wish to access corporate procurement systems and 'break-out'. © 2013 Taylor & Francis.

Content-based VLE designs improve learning efficiency in constructivist statistics education

Background: We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific-purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. Objectives: The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Methods: Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. Results: The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. The findings demonstrate that a content-based design outperforms the traditional VLE-based design. © 2011 Wessa et al.

An investigation into inductive parameter learning in complex hierarchical knowledge structures representing clinical expertise

This dissertation investigates the very important and current problem of modelling human expertise. This is an apparent issue in any computer system emulating human decision making. It is prominent in Clinical Decision Support Systems (CDSS) due to the complexity of the induction process and the vast number of parameters in most cases. Other issues such as human error and missing or incomplete data present further challenges. In this thesis, the Galatean Risk Screening Tool (GRiST) is used as an example of modelling clinical expertise and parameter elicitation. The tool is a mental health clinical record management system with a top layer of decision support capabilities. It is currently being deployed by several NHS mental health trusts across the UK. The aim of the research is to investigate the problem of parameter elicitation by inducing them from real clinical data rather than from the human experts who provided the decision model. The induced parameters provide an insight into both the data relationships and how experts make decisions themselves. The outcomes help further understand human decision making and, in particular, help GRiST provide more accurate emulations of risk judgements. Although the algorithms and methods presented in this dissertation are applied to GRiST, they can be adopted for other human knowledge engineering domains.

Protein-protein interactions classification from text via local learning with class priors

Text classification is essential for narrowing down the number of documents relevant to a particular topic for further pursual, especially when searching through large biomedical databases. Protein-protein interactions are an example of such a topic with databases being devoted specifically to them. This paper proposed a semi-supervised learning algorithm via local learning with class priors (LL-CP) for biomedical text classification where unlabeled data points are classified in a vector space based on their proximity to labeled nodes. The algorithm has been evaluated on a corpus of biomedical documents to identify abstracts containing information about protein-protein interactions with promising results. Experimental results show that LL-CP outperforms the traditional semisupervised learning algorithms such as SVMand it also performs better than local learning without incorporating class priors.

Learning sentiment classification model from labeled features

We propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon. Preferences on expectations of sentiment labels of those lexicon words are expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than exiting weakly-supervised sentiment classification methods despite using no labeled documents.

National system of innovation and technological learning:an integrated framework for understanding technological capability development in the Russian forestry sector

One of the issues in the innovation system literature is examination of technological learning strategies of laggard nations. Two distinct bodies of literature have contributed to our insight into forces driving learning and innovation, National Systems of Innovation (NSI) and technological learning literature. Although both literatures yield insights on catch-up strategies of 'latecomer' nations, the explanatory powers of each literature by itself is limited. In this paper, a possible way of linking the macro- and the micro-level approaches by incorporating enterprises as active learning entities into the learning and innovation system is proposed. The proposed model has been used to develop research hypotheses and indicate research directions and is relevant for investigating the learning strategies of firms in less technologically intensive industries outside East Asia.

"Ignorance was bliss, now I'm ignorant and that is far more difficult":transdisciplinary learning and reflexivity in responsible management education

Purpose – The collapse of world economic systems brought the interconnectedness between business and global events sharply into focus. As Starkey points out: “leading business schools need to overcome their fascination with a particular form of finance and economics […] to broaden their intellectual horizons […] (and to) look at the lessons of history and other disciplines”. The purpose of this paper is to provide evidence from three years of research on the Aston MBA suggesting that an emphasis on developing capabilities within a far broader, connected and reflexive business curriculum is what business students and practitioners now recognise as an essential way forward for responsible management education. Design/methodology/approach – This research paper examines the reflective accounts of 300 MBA students undertaking a transdisciplinary Business Ethics, Responsibility and Sustainability core module. Findings – As Klein argues, transdisciplinarity is simultaneously an attitude and a form of action. The student reflections provide powerful discourses of individual learning and report a range of outcomes from finding “the vocabulary or the confidence” to raise issues to acting as “change agents” in the workplace. Originality/value – As responsibility and sustainability requires learners, researchers and educators to engage with real world complexity, uncertainty and risk, conventional disciplinary study, especially within business, often proves inadequate and partial. This paper demonstrates that creative and exploratory frames need to be developed to facilitate the development of more connected knowledge – informed by multiple stakeholders, able to contribute heterogeneous skills, perspectives and expertise.

Using process-oriented holonic (PrOH) modelling to increase understanding of information systems

Methodologies for understanding business processes and their information systems (IS) are often criticized, either for being too imprecise and philosophical (a criticism often levied at softer methodologies) or too hierarchical and mechanistic (levied at harder methodologies). The process-oriented holonic modelling methodology combines aspects of softer and harder approaches to aid modellers in designing business processes and associated IS. The methodology uses holistic thinking and a construct known as the holon to build process descriptions into a set of models known as a holarchy. This paper describes the methodology through an action research case study based in a large design and manufacturing organization. The scientific contribution is a methodology for analysing business processes in environments that are characterized by high complexity, low volume and high variety where there are minimal repeated learning opportunities, such as large IS development projects. The practical deliverables from the project gave IS and business process improvements for the case study company.

Social software in Higher Education:the diversity of applications and their contributions to students' learning experiences

Higher education institutions are increasingly using social software tools to support teaching and learning. Despite the fact that social software is often used in a social context, these applications can significantly contribute to the educational experience of a student. However, as the social software domain comprises a considerable diversity of tools, the respective tools can be expected to differ in the way they can contribute to teaching and learning. In this review on the educational use of social software, we systematically analyze and compare the diverse social software tools and identify their contributions to teaching and learning. By integrating established learning theory and the extant literature on the individual social software applications we seek to contribute to a theoretical foundation for social software use and the choice of tools. Case vignettes from several UK higher education institutions are used to illustrate the different applications of social software tools in teaching and learning.

IT and learning in Higher Education

Educational institutions are under pressure to provide high quality education to large numbers of students very efficiently. The efficiency target combined with the large numbers generally militates against providing students with a great deal of personal or small group tutorial contact with academic staff. As a result of this, students often develop their learning criteria as a group activity, being guided by comparisons one with another rather than the formal assessments made of their submitted work. IT systems and the World Wide Web are increasingly employed to amplify the resources of academic departments although their emphasis tends to be with course administration rather than learning support. The ready availability of information on the World Wide Web and the ease with which is may be incorporated into essays can lead students to develop a limited view of learning as the process of finding, editing and linking information. This paper examines a module design strategy for tackling these issues, based on developments in modules where practical knowledge is a significant element of the learning objectives. Attempts to make effective use of IT support in these modules will be reviewed as a contribution to the development of an IT for learning strategy currently being undertaken in the author’s Institution.

Adaptive electrical signal post-processing in optical communications systems

Improving bit error rates in optical communication systems is a difficult and important problem. The error correction must take place at high speed and be extremely accurate. We show the feasibility of using hardware implementable machine learning techniques. This may enable some error correction at the speed required.

Learning and change in interorganizational networks:the case for network learning and network change

The ALBA 2002 Call for Papers asks the question ‘How do organizational learning and knowledge management contribute to organizational innovation and change?’. Intuitively, we would argue, the answer should be relatively straightforward as links between learning and change, and knowledge management and innovation, have long been commonly assumed to exist. On the basis of this assumption, theories of learning tend to focus ‘within organizations’, and assume a transfer of learning from individual to organization which in turn leads to change. However, empirically, we find these links are more difficult to articulate. Organizations exist in complex embedded economic, political, social and institutional systems, hence organizational change (or innovation) may be influenced by learning in this wider context. Based on our research in this wider interorganizational setting, we first make the case for the notion of network learning that we then explore to develop our appreciation of change in interorganizational networks, and how it may be facilitated. The paper begins with a brief review of lite rature on learning in the organizational and interorganizational context which locates our stance on organizational learning versus the learning organization, and social, distributed versus technical, centred views of organizational learning and knowledge. Developing from the view that organizational learning is “a normal, if problematic, process in every organization” (Easterby-Smith, 1997: 1109), we introduce the notion of network learning: learning by a group of organizations as a group. We argue this is also a normal, if problematic, process in organizational relationships (as distinct from interorganizational learning), which has particular implications for network change. Part two of the paper develops our analysis, drawing on empirical data from two studies of learning. The first study addresses the issue of learning to collaborate between industrial customers and suppliers, leading to the case for network learning. The second, larger scale study goes on to develop this theme, examining learning around several major change issues in a healthcare service provider network. The learning processes and outcomes around the introduction of a particularly controversial and expensive technology are described, providing a rich and contrasting case with the first study. In part three, we then discuss the implications of this work for change, and for facilitating change. Conclusions from the first study identify potential interventions designed to facilitate individual and organizational learning within the customer organization to develop individual and organizational ‘capacity to collaborate’. Translated to the network example, we observe that network change entails learning at all levels – network, organization, group and individual. However, presenting findings in terms of interventions is less meaningful in an interorganizational network setting given: the differences in authority structures; the less formalised nature of the network setting; and the importance of evaluating performance at the network rather than organizational level. Academics challenge both the idea of managing change and of managing networks. Nevertheless practitioners are faced with the issue of understanding and in fluencing change in the network setting. Thus we conclude that a network learning perspective is an important development in our understanding of organizational learning, capability and change, locating this in the wider context in which organizations are embedded. This in turn helps to develop our appreciation of facilitating change in interorganizational networks, both in terms of change issues (such as introducing a new technology), and change orientation and capability.