Efficient Bayesian inference for learning in the Ising linear perceptron and signal detection in CDMA

Efficient new Bayesian inference technique is employed for studying critical properties of the Ising linear perceptron and for signal detection in code division multiple access (CDMA). The approach is based on a recently introduced message passing technique for densely connected systems. Here we study both critical and non-critical regimes. Results obtained in the non-critical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first-order transition line that ends in a continuous phase transition point. Finite size effects are also studied. © 2006 Elsevier B.V. All rights reserved.

An integrated multiple criteria decision making approach for resource allocation in higher education

Resource allocation is one of the major decision problems arising in higher education. Resources must be allocated optimally in such a way that the performance of universities can be improved. This paper applies an integrated multiple criteria decision making approach to the resource allocation problem. In the approach, the Analytic Hierarchy Process (AHP) is first used to determine the priority or relative importance of proposed projects with respect to the goals of the universities. Then, the Goal Programming (GP) model incorporating the constraints of AHP priority, system, and resource is formulated for selecting the best set of projects without exceeding the limited available resources. The projects include 'hardware' (tangible university's infrastructures), and 'software' (intangible effects that can be beneficial to the university, its members, and its students). In this paper, two commercial packages are used: Expert Choice for determining the AHP priority ranking of the projects, and LINDO for solving the GP model. Copyright © 2007 Inderscience Enterprises Ltd.

Strategic planning differences among multiple stakeholder orientation profiles

Despite being a significant topic in the literature, research into stakeholder interests is at an early stage. Although a company has an orientation to each stakeholder group these orientations exist simultaneously, giving a multiple stakeholder orientation profile (MSOP). We theorize that firms with different MSOPs will approach their strategic planning in different ways. We tested our predictions in UK companies, and found that indeed there are many strategic planning differences among different MSOPs. The most striking differences are in learning and innovative management, but there are also differences in objectives, competitive positioning and sustainable competitive advantage. Implications for theory and practice are presented.

Learning with other health professions in the United Kingdom MPharm degree:Multidisciplinary and placement education

This paper reviews the approach to multidisciplinary and placement education in UK schools of pharmacy. The methodology involved triangulation of course documentation, staff interviews and a final year student survey. Staff members were supportive of multidisciplinary learning. The advantages were development of a wider appreciation of the students? future professional role and better understanding of the roles of other professional groups. The barriers were logistics (student numbers; multiple sites; different timetables), the achievement of balanced numbers between disciplines and engagement of students from all participating disciplines. Placement education was offered by all schools, predominantly in hospital settings. Key problems were funding and the lack of staff resources. Currently, multidisciplinary learning within the UK for pharmacy students is inadequate and is coupled with relatively low levels of placement education. In order for things to change, there should be a review of funding and support from government and the private sector employers.

Enhancing student learning experience through a novel electronic coursework assessment and feedback management system

Recent National Student Surveys revealed that many U.K. university students are dissatisfied with the timeliness and usefulness of the feedback received from their tutors. Ensuring timeliness in marking often results in a reduction in the quality of feedback. In Computer Science where learning relies on practising and learning from mistakes, feedback that pin-points errors and explains means of improvement is important to achieve a good student learning experience. Though suitable use of Information and Communication Technology should alleviate this problem, existing Virtual Learning Environments and e-Assessment applications such as Blackboard/WebCT, BOSS, MarkTool and GradeMark are inadequate to support a coursework assessment process that promotes timeliness and usefulness of feedback while maintaining consistency in marking involving multiple tutors. We have developed a novel Internet application, called eCAF, for facilitating an efficient and transparent coursework assessment and feedback process. The eCAF system supports detailed marking scheme editing and enables tutors to use such schemes to pin-point errors in students' work so as to provide helpful feedback efficiently. Tutors can also highlight areas in a submitted work and associate helpful feedback that clearly links to the identified mistakes and the respective marking criteria. In light of the results obtained from a recent trial of eCAF, we discuss how the key features of eCAF may facilitate an effective and efficient coursework assessment and feedback process.

"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.

An assessment of web-based textbook supplementary material to support student learning

There is an increasing trend by publishers to provide supplementary learning materials with text books in order to improve the learning experience and thus ultimately improve text book sales. This study will aim to establish the use of these materials and their relevance to students in terms of supporting student learning. The materials include multiple choice test banks, animated demonstrations, simulations, quizzes and electronic versions of the text. The study will focus on the extensive library of web-based learning materials available on the ‘WileyPlus’ web platform which accompanies the textbook ‘Operations Management’, 2nd edition authored by A. Greasley and published by John Wiley and Sons Ltd.

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.

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.

Creative thinking experimentations for entrepreneurship with a disruptive, personalised and mobile game-based learning ecosystem

Based on an unprecedented need of stimulating creative capacities towards entrepreneurship to university students and young researchers, this paper introduces and analyses a smart learning ecosystem for encouraging teaching and learning on creative thinking as a distinct feature to be taught and learnt in universities. The paper introduces a mashed-up authoring architecture for designing lesson-plans and games with visual learning mechanics for creativity learning. The design process is facilitated by creativity pathways discerned across components. Participatory learning, networking and capacity building is a key aspect of the architecture, extending the learning experience and context from the classroom to outdoor (co-authoring of creative pathways by students, teachers and real-world entrepreneurs) and personal spaces. We anticipate that the smart learning ecosystem will be empirically evaluated and validated in future iterations for exploring the benefits of using games for enhancing creative mindsets, unlocking the imagination that lies within, practiced and transferred to multiple academic tribes and territories.

Knowledge discovery using multiple sources of biological data

The primary aim of this dissertation is to develop data mining tools for knowledge discovery in biomedical data when multiple (homogeneous or heterogeneous) sources of data are available. The central hypothesis is that, when information from multiple sources of data are used appropriately and effectively, knowledge discovery can be better achieved than what is possible from only a single source. ^ Recent advances in high-throughput technology have enabled biomedical researchers to generate large volumes of diverse types of data on a genome-wide scale. These data include DNA sequences, gene expression measurements, and much more; they provide the motivation for building analysis tools to elucidate the modular organization of the cell. The challenges include efficiently and accurately extracting information from the multiple data sources; representing the information effectively, developing analytical tools, and interpreting the results in the context of the domain. ^ The first part considers the application of feature-level integration to design classifiers that discriminate between soil types. The machine learning tools, SVM and KNN, were used to successfully distinguish between several soil samples. ^ The second part considers clustering using multiple heterogeneous data sources. The resulting Multi-Source Clustering (MSC) algorithm was shown to have a better performance than clustering methods that use only a single data source or a simple feature-level integration of heterogeneous data sources. ^ The third part proposes a new approach to effectively incorporate incomplete data into clustering analysis. Adapted from K-means algorithm, the Generalized Constrained Clustering (GCC) algorithm makes use of incomplete data in the form of constraints to perform exploratory analysis. Novel approaches for extracting constraints were proposed. For sufficiently large constraint sets, the GCC algorithm outperformed the MSC algorithm. ^ The last part considers the problem of providing a theme-specific environment for mining multi-source biomedical data. The database called PlasmoTFBM, focusing on gene regulation of Plasmodium falciparum, contains diverse information and has a simple interface to allow biologists to explore the data. It provided a framework for comparing different analytical tools for predicting regulatory elements and for designing useful data mining tools. ^ The conclusion is that the experiments reported in this dissertation strongly support the central hypothesis.^

Best practices in exemplary service delivery: A multiple case study of service quality

The purpose of this study was to explain how exemplary service providers in luxury hotels provide consistently excellent service. Using a case study framework, the study investigated the service provider's strategies and concepts of service delivery, the importance and implementation of organizational and individual controls, and the role of training and learning. The study identified barriers to service provision and characteristics of the exemplary individuals that affect their ability to deliver luxury service. This study sought to better understand how exemplary service providers learn, think about, and do their work. The sample population of three Five-Diamond-Award winning resorts was selected for their potential for learning about the phenomenon of interest. The results demonstrate that exemplary service providers possess individual characteristics that are enhanced by the organizations for which they work. Exemplary service providers are often exemplary communicators who are emotionally generous and genuinely enjoy helping and serving others. Exemplary service organizations treat their employees as they treat their customers, as suggested by the Service-Profit Chain (Heskett, Sasser & Schlesinger, 1997). Further, they have systems and standards to guarantee satisfactory service experiences for every guest. They also encourage their service providers to personalize their service delivery and to seek opportunities to delight their guests, using a combination of controls, traditions and cultural values. Several customer service theories are discussed in relationship to whether they were or were not supported by the data. The study concluded that the delivery of exemplary service is a complex phenomenon that requires successful interactions between guests, service providers and the organization. A Model of Exemplary Service Delivery is presented and discussed that demonstrates the components of service quality as shown in the data. The model can be used by practitioners seeking to create, enhance, or evaluate their service quality, and by researchers seeking insights into the complex concepts in service quality research. Implications for future research are discussed.

Effects of repeated readings on reading abilities of English language learners with specific learning disabilities

This study investigated the effects of repeated readings on the reading abilities of 4, third-, fourth-, and fifth-grade English language learners (ELLs) with specific learning disabilities (SLD). A multiple baseline probe design across subjects was used to explore the effects of repeated readings on four dependent variables: reading fluency (words read correctly per minute; wpm), number of errors per minute (epm), types of errors per minute, and answer to literal comprehension questions. Data were collected and analyzed during baseline, intervention, generalization probes, and maintenance probes. Throughout the baseline and intervention phases, participants read a passage aloud and received error correction feedback. During baseline, this was followed by fluency and literal comprehension question assessments. During intervention, this was followed by two oral repeated readings of the passage. Then the fluency and literal comprehension question assessments were administered. Generalization probes followed approximately 25% of all sessions and consisted of a single reading of a new passage at the same readability level. Maintenance sessions occurred 2-, 4-, and 6-weeks after the intervention ended. The results of this study indicated that repeated readings had a positive effect on the reading abilities of ELLs with SLD. Participants read more wpm, made fewer epm, and answered more literal comprehension questions correctly. Additionally, on average, generalization scores were higher in intervention than in baseline. Maintenance scores were varied when compared to the last day of intervention, however, with the exception of the number of hesitations committed per minute maintenance scores were higher than baseline means. This study demonstrated that repeated readings improved the reading abilities of ELLs with SLD and that gains were generalized to untaught passages. Maintenance probes 2-, 4-, and 6- weeks following intervention indicated that mean reading fluency, errors per minute, and correct answers to literal comprehensive questions remained above baseline levels. Future research should investigate the use of repeated readings in ELLs with SLD at various stages of reading acquisition. Further, future investigations may examine how repeated readings can be integrated into classroom instruction and assessments.

The use of a computer graphic organizer for persuasive composition writing by Hispanic students with specific learning disabilities

Many culturally and linguistically diverse (CLD) students with specific learning disabilities (SLD) struggle with the writing process. Particularly, they have difficulties developing and expanding ideas, organizing and elaborating sentences, and revising and editing their compositions (Graham, Harris, & Larsen, 2001; Myles, 2002). Computer graphic organizers offer a possible solution to assist them in their writing. This study investigated the effects of a computer graphic organizer on the persuasive writing compositions of Hispanic middle school students with SLD. A multiple baseline design across subjects was used to examine its effects on six dependent variables: number of arguments and supporting details, number and percentage of transferred arguments and supporting details, planning time, writing fluency, syntactical maturity (measured by T-units, the shortest grammatical sentence without fragments), and overall organization. Data were collected and analyzed throughout baseline and intervention. Participants were taught persuasive writing and the writing process prior to baseline. During baseline, participants were given a prompt and asked to use paper and pencil to plan their compositions. A computer was used for typing and editing. Intervention required participants to use a computer graphic organizer for planning and then a computer for typing and editing. The planning sheets and written composition were printed and analyzed daily along with the time each participant spent on planning. The use of computer graphic organizers had a positive effect on the planning and persuasive writing compositions. Increases were noted in the number of supporting details planned, percentage of supporting details transferred, planning time, writing fluency, syntactical maturity in number of T-units, and overall organization of the composition. Minimal to negligible increases were noted in the mean number of arguments planned and written. Varying effects were noted in the percent of transferred arguments and there was a decrease in the T-unit mean length. This study extends the limited literature on the effects of computer graphic organizers as a prewriting strategy for Hispanic students with SLD. In order to fully gauge the potential of this intervention, future research should investigate the use of different features of computer graphic organizer programs, its effects with other writing genres, and different populations.