A critical examination of the effectiveness of faculty-based student learning support

This thesis presents an investigation into the effectiveness of faculty-based student learning support and comprises three volumes. Volume 1 provides an overview of the background literature, research methodology, ethical and reliability considerations linked to two projects whose overarching theme is the support and improvement of the student experience. The overview begins with an outline of the aim of this thesis, followed by a synopsis of the literature concerning student support in higher education and the use of technology to support learners. The methodological framework is then discussed and a brief introduction to the projects is provided. The overview concludes with an exploration of the effectiveness of faculty-based student learning support and the presentation of a new blended approach to the organisation, delivery and typology of advising. This seeks to demonstrate the strength of a blended approach and thus makes a contribution to the practice, theory and method of supporting student learning. Volume 2 discusses the Advice Shop project and considers the processes, methods and ethics of this student learning support. A summary of eight interventions is presented together with details of how the project was subsequently rolled out across the University. A consideration of the organisational model and personnel involved in student advising is also offered. The volume concludes with student and staff feedback and a discussion of how the project aims have been achieved. Evidence of the research output and components of practice relating to Project 1 can be found in Volume2 Part 2. Volume 3 presents a discussion of Project 2 - the use of technology to support learners. The project presents two technology-enhanced interventions - an electronic student attendance monitoring scheme, and the development of two online learner support tools using QuestionMark Perception as the delivery software. The methods and ethical considerations used to establish and implement these interventions are present together with feedback from students and staff. The volume concludes with a discussion of how the aims of the project have been achieved. Evidence of the research output and components of practice relating to Project 2 can be found in Volume 3 Part 2

Uncertainty explicit assessment of off-the-shelf software: A Bayesian approach

Assessment of software COTS components is an essential part of component-based software development. Poorly chosen components may lead to solutions of low quality and that are difficult to maintain. The assessment may be based on incomplete knowledge about the COTS component itself and other aspects (e.g. vendor’s credentials, etc.), which may affect the decision of selecting COTS component(s). We argue in favor of assessment methods in which uncertainty is explicitly represented (‘uncertainty explicit’ methods) using probability distributions. We provide details of a Bayesian model, which can be used to capture the uncertainties in the simultaneous assessment of two attributes, thus, also capturing the dependencies that might exist between them. We also provide empirical data from the use of this method for the assessment of off-the-shelf database servers which illustrate the advantages of ‘uncertainty explicit’ methods over conventional methods of COTS component assessment which assume that at the end of the assessment the values of the attributes become known with certainty

Software reliability and dependability: a roadmap

Shifting the focus from software reliability to user-centred measures of dependability in complete software-based systems. Influencing design practice to facilitate dependability assessment. Propagating awareness of dependability issues and the use of existing, useful methods. Injecting some rigour in the use of process-related evidence for dependability assessment. Better understanding issues of diversity and variation as drivers of dependability. Bev Littlewood is founder-Director of the Centre for Software Reliability, and Professor of Software Engineering at City University, London. Prof Littlewood has worked for many years on problems associated with the modelling and evaluation of the dependability of software-based systems; he has published many papers in international journals and conference proceedings and has edited several books. Much of this work has been carried out in collaborative projects, including the successful EC-funded projects SHIP, PDCS, PDCS2, DeVa. He has been employed as a consultant t

Sensitivity Analysis for a Scenario-Based Reliability Prediction Model

As a popular means for capturing behavioural requirements, scenariosshow how components interact to provide system-level functionality.If component reliability information is available, scenarioscan be used to perform early system reliability assessment. Inprevious work we presented an automated approach for predictingsoftware system reliability that extends a scenario specificationto model (1) the probability of component failure, and (2) scenariotransition probabilities. Probabilistic behaviour models ofthe system are then synthesized from the extended scenario specification.From the system behaviour model, reliability predictioncan be computed. This paper complements our previous work andpresents a sensitivity analysis that supports reasoning about howcomponent reliability and usage profiles impact on the overall systemreliability. For this purpose, we present how the system reliabilityvaries as a function of the components reliabilities and thescenario transition probabilities. Taking into account the concurrentnature of component-based software systems, we also analysethe effect of implied scenarios prevention into the sensitivity analysisof our reliability prediction technique

Towards the Formal Reliability Analysis of Oil and Gas Pipelines

It is customary to assess the reliability of underground oil and gas pipelines in the presence of excessive loading and corrosion effects to ensure a leak-free transport of hazardous materials. The main idea behind this reliability analysis is to model the given pipeline system as a Reliability Block Diagram (RBD) of segments such that the reliability of an individual pipeline segment can be represented by a random variable. Traditionally, computer simulation is used to perform this reliability analysis but it provides approximate results and requires an enormous amount of CPU time for attaining reasonable estimates. Due to its approximate nature, simulation is not very suitable for analyzing safety-critical systems like oil and gas pipelines, where even minor analysis flaws may result in catastrophic consequences. As an accurate alternative, we propose to use a higher-order-logic theorem prover (HOL) for the reliability analysis of pipelines. As a first step towards this idea, this paper provides a higher-order-logic formalization of reliability and the series RBD using the HOL theorem prover. For illustration, we present the formal analysis of a simple pipeline that can be modeled as a series RBD of segments with exponentially distributed failure times.Comment: 15 page

Estimating the reliability of composite scores

In situations where multiple tests are administered (such as the GCSE subjects), scores from individual tests are frequently combined to produce a composite score. As part of the Ofqual reliability programme, this study, through a review of literature, attempts to: look at the different approaches that are employed to form composite scores from component or unit scores; investigate the implications of the use of the different approaches for the psychometric properties, particularly the reliability, of the composite scores; and identify procedures that are commonly used to estimate the reliability measure of composite scores

Reliability modeling of a 1-out-of-2 system: Research with diverse Off-the-shelf SQL database servers

Fault tolerance via design diversity is often the only viable way of achieving sufficient dependability levels when using off-the-shelf components. We have reported previously on studies with bug reports of four open-source and commercial off-the-shelf database servers and later release of two of them. The results were very promising for designers of fault-tolerant solutions that wish to employ diverse servers: very few bugs caused failures in more than one server and none caused failure in more than two. In this paper we offer details of two approaches we have studied to construct reliability growth models for a 1-out-of-2 fault-tolerant server which utilize the bug reports. The models presented are of practical significance to system designers wishing to employ diversity with off-the-shelf components since often the bug reports are the only direct dependability evidence available to them

Uncertainty explicit assessment of off-the-shelf software: Selection of an optimal diverse pair

Assessment of software COTS components is an essential part of component-based software development. Sub-optimal selection of components may lead to solutions with low quality. The assessment is based on incomplete knowledge about the COTS components themselves and other aspects, which may affect the choice such as the vendor's credentials, etc. We argue in favor of assessment methods in which uncertainty is explicitly represented (`uncertainty explicit' methods) using probability distributions. We have adapted a model (developed elsewhere by Littlewood, B. et al. (2000)) for assessment of a pair of COTS components to take account of the fault (bug) logs that might be available for the COTS components being assessed. We also provide empirical data from a study we have conducted with off-the-shelf database servers, which illustrate the use of the method