The importance of power dynamics in the development of asynchronous online learning communities

This research explored how a more student-directed learning design can support the creation of togetherness and belonging in a community of distance learners in formal higher education. Postgraduate students in a New Zealand School of Education experienced two different learning tasks as part of their online distance learning studies. The tasks centered around two online asynchronous discussions each for the same period of time and with the same group of students, but following two different learning design principles. All messages were analyzed using a twostep analysis process, content analysis and social network analysis. Although the findings showed a balance of power between the tutor and the students in the first high e-moderated activity, a better pattern of group interaction and community feeling was found in the low e-moderated activity. The paper will discuss the findings in terms of the implications for learning design and the role of the tutor.

Joint sentiment/topic model for sentiment analysis

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

Accounting students' perceptions of a Learning Management System:an international comparison

Purpose - The purpose of this study is to investigate student perceptions of the design features included in an off the shelf Learning Management System (LMS) in teaching undergraduate accounting students. Design/methodology/approach - Questionnaire responses from 846 accounting students studying in the UK, Australia and New Zealand provide international data to develop a model to explain student perception of the LMS. Findings - The final model shows student satisfaction with the use of a LMS is positively associated with three variables: usefulness of lecture notes, bulletin boards and discussion forums, and other LMS tools. Further, the comparison of cultural differences of the three countries shows all students treat the provision of notes as a desirable attribute on a LMS. Findings also suggest that although students find the provision of materials over the LMS does not enhance student engagement in class, overall a comparison of the three countries shows all students treat the provision of notes as a desirable attribute of a LMS. Research limitations/implications - Future research should collect ethnicity data to enable an analysis of cultural influence on student perceptions of the LMS. Practical implications - As increased motivation to learn is found to contribute to improved achievement of learning outcomes, the study's findings have implications for faculty contemplating the adoption of a LMS in their courses. The findings specifically confirm that usefulness of lecture notes, use of bulletin/discussion boards, and other LMS tools are positively endorsed by students and hence increase their motivation to learn. Originality/value - The current paper adds to the literature as the motivation to use and engage with LMSs by accounting students is not well understood. © Emerald Group Publishing Limited.

An analysis of users' reactions to an expert advisory system

Ignorance of user factors can be seen as one of the nontechnical issues contributing to expert system failure. An expert advisory system is built for nonexpert users; the users' acceptance is a very important factor for its successful implementation. If an expert advisory system satisfactorily represents the expertise in the domain, there still remains the question: "Will the end-users use the system?" This paper aims to address users' issues by analysing their reactions towards an expert advisory system called ADGAME, developed to help its users make better decisions in playing a competitive business game. Two experiments with ADGAME have been carried out. The research results show that, when the use of the expert advisory system is optional, there is considerable reluctance to use it, particularly amongst the "worst" potential users. Users also doubt the potential benefits in terms of improved learning and confidence in decisions made. Strangely, the one positive expectation that users had, that the system would save them time, proved not to be the case in practice; ADGAME appears to improve the users' effectiveness rather than their efficiency. © 1995.

Designing post-disaster supply chains:learning from housing reconstruction projects

Post-disaster housing reconstruction projects face several challenges. Resources and material supplies are often scarce; several and different types of organizations are involved, while projects must be completed as quickly as possible to foster recovery. Within this context, the chapter aims to increase the understanding of relief supply chain design in reconstruction. In addition, the chapter is introducing a community based and beneficiary perspective to relief supply chains by evaluating the implications of local components for supply chain design in reconstruction. This is achieved through the means of secondary data analysis based on the evaluation reports of two major housing reconstruction projects that took place in Europe the last decade. A comparative analysis of the organizational designs of these projects highlights the ways in which users can be involved. The performance of reconstruction supply chains seems to depend to a large extent on the way beneficiaries are integrated in supply chain design impacting positively on the effectiveness of reconstruction supply chains.

Professionalism and quality in European business courses:utilising research to enhance student learning and promote employability - a pan-European study

This..paper provides a comparative analysis of Quality Management and standards in four European countries, (the UK, Austria, Slovenia and Romania) and in doing so addresses the gap in academic knowledge about how the introduction and implementation of Quality Management Strategies can both facilitate and enhance student learning within Universities.

Network learning:Exploring learning by interorganizational networks

The importance of interorganizational networks in supporting or hindering the achievement of organizational objectives is now widely acknowledged. Network research is directed at understanding network processes and structures, and their impact upon performance. A key process is learning. The concepts of individual, group and organizational learning are long established. This article argues that learning might also usefully be regarded as occurring at a fourth system level, the interorganizational network. The concept of network learning - learning by a group of organizations as a group - is presented, and differentiated from other types of learning, notably interorganizational learning (learning in interorganizational contexts). Four cases of network learning are identified and analysed to provide insights into network learning processes and outcomes. It is proposed that 'network learning episode' offers a suitable unit of analysis for the empirical research needed to develop our understanding of this potentially important concept.

Evaluating the impact of a web-based resource on student learning

This paper reports on an experiment of using a publisher provided web-based resource to make available a series of optional practice quizzes and other supplementary material to all students taking a first year introductory microeconomics module. The empirical analysis evaluates the impact these supplementary resources had on student learning. First, we investigate which students decided to make use of the resources. Then, we analyse the impact this decision has on their subsequent performance in the examination at the end of the module. The results show that, even after taking into account the possibility of self-selection bias, using the web-based resource had a significant positive effect on student learning.

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.

Learning from a deceptively spacious policy discourse

Networked Learning, e-Learning and Technology Enhanced Learning have each been defined in different ways, as people's understanding about technology in education has developed. Yet each could also be considered as a terminology competing for a contested conceptual space. Theoretically this can be a ‘fertile trans-disciplinary ground for represented disciplines to affect and potentially be re-orientated by others’ (Parchoma and Keefer, 2012), as differing perspectives on terminology and subject disciplines yield new understandings. Yet when used in government policy texts to describe connections between humans, learning and technology, terms tend to become fixed in less fertile positions linguistically. A deceptively spacious policy discourse that suggests people are free to make choices conceals an economically-based assumption that implementing new technologies, in themselves, determines learning. Yet it actually narrows choices open to people as one route is repeatedly in the foreground and humans are not visibly involved in it. An impression that the effective use of technology for endless improvement is inevitable cuts off critical social interactions and new knowledge for multiple understandings of technology in people's lives. This paper explores some findings from a corpus-based Critical Discourse Analysis of UK policy for educational technology during the last 15 years, to help to illuminate the choices made. This is important when through political economy, hierarchical or dominant neoliberal logic promotes a single ‘universal model’ of technology in education, without reference to a wider social context (Rustin, 2013). Discourse matters, because it can ‘mould identities’ (Massey, 2013) in narrow, objective economically-based terms which 'colonise discourses of democracy and student-centredness' (Greener and Perriton, 2005:67). This undermines subjective social, political, material and relational (Jones, 2012: 3) contexts for those learning when humans are omitted. Critically confronting these structures is not considered a negative activity. Whilst deterministic discourse for educational technology may leave people unconsciously restricted, I argue that, through a close analysis, it offers a deceptively spacious theoretical tool for debate about the wider social and economic context of educational technology. Methodologically it provides insights about ways technology, language and learning intersect across disciplinary borders (Giroux, 1992), as powerful, mutually constitutive elements, ever-present in networked learning situations. In sharing a replicable approach for linguistic analysis of policy discourse I hope to contribute to visions others have for a broader theoretical underpinning for educational technology, as a developing field of networked knowledge and research (Conole and Oliver, 2002; Andrews, 2011).

A novel adaptive weight selection algorithm for multi-objective multi-agent reinforcement learning

To solve multi-objective problems, multiple reward signals are often scalarized into a single value and further processed using established single-objective problem solving techniques. While the field of multi-objective optimization has made many advances in applying scalarization techniques to obtain good solution trade-offs, the utility of applying these techniques in the multi-objective multi-agent learning domain has not yet been thoroughly investigated. Agents learn the value of their decisions by linearly scalarizing their reward signals at the local level, while acceptable system wide behaviour results. However, the non-linear relationship between weighting parameters of the scalarization function and the learned policy makes the discovery of system wide trade-offs time consuming. Our first contribution is a thorough analysis of well known scalarization schemes within the multi-objective multi-agent reinforcement learning setup. The analysed approaches intelligently explore the weight-space in order to find a wider range of system trade-offs. In our second contribution, we propose a novel adaptive weight algorithm which interacts with the underlying local multi-objective solvers and allows for a better coverage of the Pareto front. Our third contribution is the experimental validation of our approach by learning bi-objective policies in self-organising smart camera networks. We note that our algorithm (i) explores the objective space faster on many problem instances, (ii) obtained solutions that exhibit a larger hypervolume, while (iii) acquiring a greater spread in the objective space.

Learning in friendship groups:developing students’ conceptual understanding through social interaction

The role that student friendship groups play in learning was investigated here. Employing a critical realist design, two focus groups on undergraduates were conducted to explore their experience of studying. Data from the "case-by-case" analysis suggested student-to-student friendships produced social contexts which facilitated conceptual understanding through discussion, explanation, and application to "real life" contemporary issues. However, the students did not conceive this as a learning experience or suggest the function of their friendships involved learning. These data therefore challenge the perspective that student groups in higher education are formed and regulated for the primary function of learning. Given these findings, further research is needed to assess the role student friendships play in developing disciplinary conceptual understanding.

New lecturers' beliefs about learning, teaching and assessment in higher education:the role of the PGCLTHE programme

This study was carried out with new lecturers on a two year Post Graduate Certificate in Learning and Teaching in Higher Education programme in a UK university. The aim was to establish their beliefs about how studying on the programme aligned with their teaching and learning philosophy and what, if anything, had changed or constrained those beliefs. Ten lecturers took part in an in-depth semi-structured interview. Content analysis of the transcripts suggested positive reactions to the programme but lecturers’ new insights were sometimes constrained by departments and university bureaucracy, particularly in the area of assessment. The conflicting roles of research and teaching were also a major issue facing these new professionals.

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.

Complex skills and academic writing:a review of evidence about the types of learning required to meet core assessment criteria

Assessment criteria are increasingly incorporated into teaching, making it important to clarify the pedagogic status of the qualities to which they refer. We reviewed theory and evidence about the extent to which four core criteria for student writing-critical thinking, use of language, structuring, and argument-refer to the outcomes of three types of learning: generic skills learning, a deep approach to learning, and complex learning. The analysis showed that all four of the core criteria describe to some extent properties of text resulting from using skills, but none qualify fully as descriptions of the outcomes of applying generic skills. Most also describe certain aspects of the outcomes of taking a deep approach to learning. Critical thinking and argument correspond most closely to the outcomes of complex learning. At lower levels of performance, use of language and structuring describe the outcomes of applying transferable skills. At higher levels of performance, they describe the outcomes of taking a deep approach to learning. We propose that the type of learning required to meet the core criteria is most usefully and accurately conceptualized as the learning of complex skills, and that this provides a conceptual framework for maximizing the benefits of using assessment criteria as part of teaching. © 2006 Taylor & Francis.