Good Foundations: An Analysis of the Configurations of Factors Affecting Success in Non-Traditional Students on a Foundation Programme

Good Foundations: An Analysis of the Configurations of Factors Affecting Success in Non-Traditional Students on a Foundation Programme Abstract In the last decade, there has been a strong focus on educational policies to improve social mobility with universities required to demonstrate through their Fair Access Agreements what action they are taking with regard to making Higher Education available to underrepresented groups. The literature review presented here used the ideas of Bourdieu to examine which groups are underrepresented in Higher Education and to explore to what extent this underrepresentation may be attributed to poor initial education, recruitment bias on the part of institutions or an alienation on behalf of the learner with the dominant culture found in Higher Education. Some of the different approaches to widening participation were considered, focusing on the role of Foundation Programmes in order to site the programme analysed in this thesis in the range of widening participation activity generally and the national Foundation Programme sector specifically. The literature on graduateness and academic thinking skills was explored as a way of articulating a desirable outcome for degree preparation in a research intensive university. This then led to an examination of the issues around teaching and learning for non-traditional students. The research described in this thesis was conducted on the factors affecting successful outcomes for students studying on the Foundation Programme at Durham University using both available audit-style demographic and academic outcome data for seven cohorts of Foundation students and a more in-depth analysis of one cohort. The data were analysed using the relatively novel approach of Qualitative Comparative analysis as this case-led approach retains the nuances within the data and allows for the variety of different combinations of factors within individual students. The results show that there were a range of combinations of factors leading to a successful outcome for students, that previous qualifications were not necessary for success, but that attitudinal factors, as measured using a Conscientiousness Index, were important. A link was established between an ability to use concepts of evidence, a high average score on the Foundation Programme and achievement of a good honours degree. The implications of the results were then considered in respect of taking a deficit approach to remedy gaps in initial education, aspects of recruitment policy for non-traditional students and managing diversity of learner identity

Reverse logistics service development of independent non-profit organization for reuse of computers: case - The Helsinki Metropolitan Area Reuse Centre Ltd.

Motivation for this thesis comes from the need to move towards circular economy, and the possibilities of better reuse of computers for the sake of the environment. Additionally, there is a clear lack of research concerning independent non-profit organizations in the reverse logistics arena. The aim of the research is to fill that gap and to examine the opportunities in computer reuse. The research questions were formulated to find answers to the surfaced questions: What are the drivers for engagement in reverse logistics? What different kinds of service models are there in the reverse logistics field? How reverse logistics systems are implemented? The methods used in this study are a literature review and a single case study method. First, a systematic literature review was conducted with the related search terms of product recovery management, reverse logistics, and third party logistics. Single case study method was used to gain insight into the drivers for engagement, type of business model and implementation of reverse logistics of a non-profit company. The reverse logistics operations development project for the case company, The Helsinki Metropolitan Area Reuse Centre Ltd., allowed to answer the questions presented and to build relevant knowledge about the subject. As a result, it was found that general characteristics of reverse logistics and its implementation apply no matter the circumstances. However, the case study shows that the drivers for engagement in reverse logistics of non-profit organization can differ greatly from traditional profit-seeking companies. For a non-profit company, the environmental and social aspects of the triple bottom line weigh more, and the financial incentives weigh less. Further, the independent role of a reverse logistics operator in the market imposes needs for active communication to reach consumers and collaborative companies alike, for the ends of acquiring more input products

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Public Health

Public health can be thought of as a series of complex systems. Many things that individual living in high income countries take for granted like the control of infectious disease, clean, potable water, low infant mortality rates require a high functioning systems comprised of numerous actors, locations and interactions to work. Many people only notice public health when that system fails. This book explores several systems in public health including aspects of the food system, health care system and emerging issues including waste minimization in nanosilver. Several chapters address global health concerns including non-communicable disease prevention, poverty and health-longevity medicine. The book also presents several novel methodologies for better modeling and assessment of essential public health issues

Configurational explanation of marketing outcomes : a fuzzy-set qualitative comparative analysis approach

As marketing, as a function and a process, is required to explain itself with more transparency, new tools and comprehensive analysis processes must be created and adopted, so that marketing performance and its determinants can systematically be understood and developed. In this dissertation, I present fuzzy-set qualitative comparative analysis (‘FS/QCA’; Ragin, 2000; Fiss, 2008; Rihoux and Ragin, 2009; and others) as a novel approach to assessing marketing performance. My key argument is that the fuzzy-set qualitative comparative analysis research approach and methodology can be used to explain marketing outcomes as results of configurations of causal conditions in specific contexts, yielding managerially relevant knowledge that would otherwise be difficult to access and interpret. The broad aim of this dissertation is to supplement the range of marketing management support systems, modeling approaches, and marketing performance assessment systems to provide better knowledge-driven decision support. The analytical premises of FS/QCA and its applications in fields of study related to marketing position it as a candidate to overcome some key challenges faced in marketing performance analysis: dealing with causal complexity, heterogeneity, asymmetry, configurationality, contextuality, and qualitative meaning. To draw together the research approach, the methodology, and the marketing performance management perspective, I specify a synthetic research process, configurational explanation of marketing outcomes (‘CEMO’), comprising the theoretical and empirical steps required for analysis. I demonstrate how the configurational explanation process was successfully carried out in two empirical contexts to generate results that are valid, reliable, and contribute knowledge that is directly relevant within the chosen context. The key contribution of this study is intended to be methodological: a specification of an analysis process for accessing a new type of contextually relevant knowledge about causal mechanisms that shape marketing performance. New knowledge accessible with CEMO provides opportunities for staging more effective marketing actions and, ultimately, an opportunity for better marketing performance

Formal Linguistic Models and Knowledge Processing. A Structuralist Approach to Rule-Based Ontology Learning and Population

2013 - 2014The main aim of this research is to propose a structuralist approach for knowledge processing by means of ontology learning and population, achieved starting from unstructured and structured texts. The method suggested includes distributional semantic approaches and NL formalization theories, in order to develop a framework, which relies upon deep linguistic analysis... [edited by author]XIII n.s

A case-based reasoning approach to improve risk identification in construction projects

Risk management is an important process to enhance the understanding of the project so as to support decision making. Despite well established existing methods, the application of risk management in practice is frequently poor. The reasons for this are investigated as accuracy, complexity, time and cost involved and lack of knowledge sharing. Appropriate risk identification is fundamental for successful risk management. Well known risk identification methods require expert knowledge, hence risk identification depends on the involvement and the sophistication of experts. Subjective judgment and intuition usually from par1t of experts’ decision, and sharing and transferring this knowledge is restricted by the availability of experts. Further, psychological research has showed that people have limitations in coping with complex reasoning. In order to reduce subjectivity and enhance knowledge sharing, artificial intelligence techniques can be utilised. An intelligent system accumulates retrievable knowledge and reasoning in an impartial way so that a commonly acceptable solution can be achieved. Case-based reasoning enables learning from experience, which matches the manner that human experts catch and process information and knowledge in relation to project risks. A case-based risk identification model is developed to facilitate human experts making final decisions. This approach exploits the advantage of knowledge sharing, increasing confidence and efficiency in investment decisions, and enhancing communication among the project participants

Using Case-Based Reasoning for Simulation Modeling in Healthcare

The healthcare system is always defined as a complex system. At its core, it is a system composed of people and processes and requires performance of different tasks and duties. This complexity means that the healthcare system has many stakeholders with different interests, resulting in the emergence of many problems such as increasing healthcare costs, limited resources and low utilization, limited facilities and workforce, and poor quality of services. The use of simulation techniques to aid in solving healthcare problems is not new, but it has increased in recent years. This application faces many challenges, including a lack of real data, complicated healthcare decision making processes, low stakeholder involvement, and the working environment in the healthcare field. The objective of this research is to study the utilization of case-based reasoning in simulation modeling in the healthcare sector. This utilization would increase the involvement of stakeholders in the analysis process of the simulation modeling. This involvement would help in reducing the time needed to build the simulation model and facilitate the implementation of results and recommendations. The use of case-based reasoning will minimize the required efforts by automating the process of finding solutions. This automation uses the knowledge in the previously solved problems to develop new solutions. Thus, people could utilize the simulation modeling with little knowledge about simulation and the working environment in the healthcare field. In this study, a number of simulation cases from the healthcare field have been collected to develop the case-base. After that, an indexing system was created to store these cases in the case-base. This system defined a set of attributes for each simulation case. After that, two retrieval approaches were used as retrieval engines. These approaches are K nearest neighbors and induction tree. The validation procedure started by selecting a case study from the healthcare literature and implementing the proposed method in this study. Finally, healthcare experts were consulted to validate the results of this study