Mapping teaching, learning and assessment in the MPharm in UK schools of pharmacy

Aim To undertake a national study of teaching, learning and assessment in UK schools of pharmacy. Design Triangulation of course documentation, 24 semi-structured interviews undertaken with 29 representatives from the schools and a survey of all final year students (n=1,847) in the 15 schools within the UK during 2003–04. Subjects and setting All established UK pharmacy schools and final year MPharm students. Outcome measures Data were combined and analysed under the topics of curriculum, teaching and learning, assessment, multi-professional teaching and learning, placement education and research projects. Results Professional accreditation was the main driver for curriculum design but links to preregistration training were poor. Curricula were consistent but offered little student choice. On average half the curriculum was science-based. Staff supported the science content but students less so. Courses were didactic but schools were experimenting with new methods of learning. Examinations were the principal form of assessment but the contribution of practice to the final degree ranged considerably (21–63%). Most students considered the assessment load to be about right but with too much emphasis upon knowledge. Assessment of professional competence was focused upon dispensing and pharmacy law. All schools undertook placement teaching in hospitals but there was little in community/primary care. There was little inter-professional education. Resources and logistics were the major limiters. Conclusions There is a need for an integrated review of the accreditation process for the MPharm and preregistration training and redefinition of professional competence at an undergraduate level.

Driving licensing renewal policy using neural network-based probabilistic decision support system

This paper investigates neural network-based probabilistic decision support system to assess drivers' knowledge for the objective of developing a renewal policy of driving licences. The probabilistic model correlates drivers' demographic data to their results in a simulated written driving exam (SWDE). The probabilistic decision support system classifies drivers' into two groups of passing and failing a SWDE. Knowledge assessment of drivers within a probabilistic framework allows quantifying and incorporating uncertainty information into the decision-making system. The results obtained in a Jordanian case study indicate that the performance of the probabilistic decision support systems is more reliable than conventional deterministic decision support systems. Implications of the proposed probabilistic decision support systems on the renewing of the driving licences decision and the possibility of including extra assessment methods are discussed.

Knowledge engineering for mental-health risk assessment and decision support

Mental-health risk assessment practice in the UK is mainly paper-based, with little standardisation in the tools that are used across the Services. The tools that are available tend to rely on minimal sets of items and unsophisticated scoring methods to identify at-risk individuals. This means the reasoning by which an outcome has been determined remains uncertain. Consequently, there is little provision for: including the patient as an active party in the assessment process, identifying underlying causes of risk, and eecting shared decision-making. This thesis develops a tool-chain for the formulation and deployment of a computerised clinical decision support system for mental-health risk assessment. The resultant tool, GRiST, will be based on consensual domain expert knowledge that will be validated as part of the research, and will incorporate a proven psychological model of classication for risk computation. GRiST will have an ambitious remit of being a platform that can be used over the Internet, by both the clinician and the layperson, in multiple settings, and in the assessment of patients with varying demographics. Flexibility will therefore be a guiding principle in the development of the platform, to the extent that GRiST will present an assessment environment that is tailored to the circumstances in which it nds itself. XML and XSLT will be the key technologies that help deliver this exibility.

An expert system for the development of a health and safety policy/risk assessment in the plastics industry

Health and safety policies may be regarded as the cornerstone for positive prevention of occupational accidents and diseases. The Health and Safety at Work, etc Act 1974 makes it a legal duty for employers to prepare and revise a written statement of a general policy with respect to the health and safety at work of employees as well as the organisation and arrangements for carrying out that policy. Despite their importance and the legal equipment to prepare them, health and safety policies have been found, in a large number of plastics processing companies (particularly small companies), to be poorly prepared, inadequately implemented and monitored. An important cause of these inadequacies is the lack of necessary health and safety knowledge and expertise to prepare, implement and monitor policies. One possible way of remedying this problem is to investigate the feasibility of using computers to develop expert system programs to simulate the health and safety (HS) experts' task of preparing the policies and assisting companies implement and monitor them. Such programs use artificial intelligence (AI) techniques to solve this sort of problems which are heuristic in nature and require symbolic reasoning. Expert systems have been used successfully in a variety of fields such as medicine and engineering. An important phase in the feasibility of development of such systems is the engineering of knowledge which consists of identifying the knowledge required, eliciting, structuring and representing it in an appropriate computer programming language.

An assessment of factors affecting performance and growth of new technology based firms in the UK

New Technology Based Firms (NTBF) are considered to be important for the economic development of a country in regards to both employment growth and innovative activity. The latter is believed to contribute significantly to the increase in productivity and therefore the competitiveness of UK’s economy. This study contributes to the above literature by investigating two of the factors believed to limit the growth of such firms in the UK. The first concerns the existence of a ‘knowledge gap’ while the second the existence of a ‘financial gap’. These themes are developed along three main research lines. Firstly, based upon the human capital theory initially proposed by Backer (1964) new evidence is provided on the human capital characteristics (experience and education) of the current UK NTBF entrepreneurs. Secondly, the causal relationship between general and specific human capital (as well as their interactions) upon the company performance and growth is investigated via its traditional direct effect as well as via its indirect effect upon the access to external finance. Finally, more light is shed on the financial structure and the type of financial constraints that high-tech firms face at start-up. In particular, whether a financial gap exists is explored by distinguishing between the demand and the supply of external finance as well as by type of external source of financing. The empirical testing of the various research hypotheses has been obtained by carrying out an original survey of new technology based firms defined as independent companies, established in the past 25 years in R&D intensive sectors. The resulting dataset contains information for 412 companies on a number of general company characteristics and the characteristics of their entrepreneurs in 2004. Policy and practical implications for future and current entrepreneurs and also providers of external finance are provided.

Assessment of the impact of discharges from surface water sewers on receiving water quality

A broad based approach has been used to assess the impact of discharges to rivers from surface water sewers, with the primary objective of determining whether such discharges have a measurable impact on water quality. Three parameters, each reflecting the effects of intermittent pollution, were included in a field work programme of biological and chemical sampling and analysis which covered 47 sewer outfall sites. These parameters were the numbers and types of benthic macroinvertebrates upstream and downstream of the outfalls, the concentrations of metals in sediments, and the concentrations of metals in algae upstream and downstream of the outfalls. Information on the sewered catchments was collected from Local Authorities and by observation of the time of sampling, and includes catchment areas, land uses, evidence of connection to the foul system, and receiving water quality classification. The methods used for site selection, sampling, laboratory analysis and data analysis are fully described, and the survey results presented. Statistical and graphical analysis of the biological data, with the aid of BMWP scores, showed that there was a small but persistent fall in water quality downstream of the studied outfalls. Further analysis including the catchment information indicated that initial water quality, sewered catchment size, receiving stream size, and catchment land use were important factors in determining the impact. Finally, the survey results were used to produce guidelines for the estimation of surface water sewer discharge impacts from knowledge of the catchment characteristics, so that planning authorities can consider water quality when new drainage systems are designed.

User interface design support for the development of knowledge-based systems

The present scarcity of operational knowledge-based systems (KBS) has been attributed, in part, to an inadequate consideration shown to user interface design during development. From a human factors perspective the problem has stemmed from an overall lack of user-centred design principles. Consequently the integration of human factors principles and techniques is seen as a necessary and important precursor to ensuring the implementation of KBS which are useful to, and usable by, the end-users for whom they are intended. Focussing upon KBS work taking place within commercial and industrial environments, this research set out to assess both the extent to which human factors support was presently being utilised within development, and the future path for human factors integration. The assessment consisted of interviews conducted with a number of commercial and industrial organisations involved in KBS development; and a set of three detailed case studies of individual KBS projects. Two of the studies were carried out within a collaborative Alvey project, involving the Interdisciplinary Higher Degrees Scheme (IHD) at the University of Aston in Birmingham, BIS Applied Systems Ltd (BIS), and the British Steel Corporation. This project, which had provided the initial basis and funding for the research, was concerned with the application of KBS to the design of commercial data processing (DP) systems. The third study stemmed from involvement on a KBS project being carried out by the Technology Division of the Trustees Saving Bank Group plc. The preliminary research highlighted poor human factors integration. In particular, there was a lack of early consideration of end-user requirements definition and user-centred evaluation. Instead concentration was given to the construction of the knowledge base and prototype evaluation with the expert(s). In response to this identified problem, a set of methods was developed that was aimed at encouraging developers to consider user interface requirements early on in a project. These methods were then applied in the two further projects, and their uptake within the overall development process was monitored. Experience from the two studies demonstrated that early consideration of user interface requirements was both feasible, and instructive for guiding future development work. In particular, it was shown a user interface prototype could be used as a basis for capturing requirements at the functional (task) level, and at the interface dialogue level. Extrapolating from this experience, a KBS life-cycle model is proposed which incorporates user interface design (and within that, user evaluation) as a largely parallel, rather than subsequent, activity to knowledge base construction. Further to this, there is a discussion of several key elements which can be seen as inhibiting the integration of human factors within KBS development. These elements stem from characteristics of present KBS development practice; from constraints within the commercial and industrial development environments; and from the state of existing human factors support.

Substances hazardous to health:the nature of the expertise associated with competent risk assessment

This research investigated expertise in hazardous substance risk assessment (HSRA). Competent pro-active risk assessment is needed to prevent occupational ill-health caused by hazardous substance exposure occurring in the future. In recent years there has been a strong demand for HSRA expertise and a shortage of expert practitioners. The discipline of Occupational Hygiene was identified as the key repository of knowledge and skills for HSRA and one objective of this research was to develop a method to elicit this expertise from experienced occupational hygienists. In the study of generic expertise, many methods of knowledge elicitation (KE) have been investigated, since this has been relevant to the development of 'expert systems' (thinking computers). Here, knowledge needed to be elicited from human experts, and this stage was often a bottleneck in system development, since experts could not explain the basis of their expertise. At an intermediate stage, information collected was used to structure a basic model of hazardous substance risk assessment activity (HSRA Model B) and this formed the basis of tape transcript analysis in the main study with derivation of a 'classification' and a 'performance matrix'. The study aimed to elicit the expertise of occupational hygienists and compare their performance with other health and safety professionals (occupational health physicians, occupational health nurses, health and safety practitioners and trainee health and safety inspectors), as evaluated using the matrix. As a group, the hygienists performed best in the exercise, and this group were particularly good at process elicitation and at recommending specific control measures, although the other groups also performed well in selected aspects of the matrix and the work provided useful findings and insights. From the research, two models of HSRA have been derived, an HSRA aid, together with a novel videotape KE technique and interesting research findings. The implications of this are discussed with respect to future training of HS professionals and wider application of the videotape KE method.

Cues and knowledge structures used by mental-health professionals when making risk assessments

Background: Research into mental-health risks has tended to focus on epidemiological approaches and to consider pieces of evidence in isolation. Less is known about the particular factors and their patterns of occurrence that influence clinicians’ risk judgements in practice. Aims: To identify the cues used by clinicians to make risk judgements and to explore how these combine within clinicians’ psychological representations of suicide, self-harm, self-neglect, and harm to others. Method: Content analysis was applied to semi-structured interviews conducted with 46 practitioners from various mental-health disciplines, using mind maps to represent the hierarchical relationships of data and concepts. Results: Strong consensus between experts meant their knowledge could be integrated into a single hierarchical structure for each risk. This revealed contrasting emphases between data and concepts underpinning risks, including: reflection and forethought for suicide; motivation for self-harm; situation and context for harm to others; and current presentation for self-neglect. Conclusions: Analysis of experts’ risk-assessment knowledge identified influential cues and their relationships to risks. It can inform development of valid risk-screening decision support systems that combine actuarial evidence with clinical expertise.

A method for automatically eliciting node weights in a hierarchical knowledge-based structure for reasoning with uncertainty

Hierarchical knowledge structures are frequently used within clinical decision support systems as part of the model for generating intelligent advice. The nodes in the hierarchy inevitably have varying influence on the decisionmaking processes, which needs to be reflected by parameters. If the model has been elicited from human experts, it is not feasible to ask them to estimate the parameters because there will be so many in even moderately-sized structures. This paper describes how the parameters could be obtained from data instead, using only a small number of cases. The original method [1] is applied to a particular web-based clinical decision support system called GRiST, which uses its hierarchical knowledge to quantify the risks associated with mental-health problems. The knowledge was elicited from multidisciplinary mental-health practitioners but the tree has several thousand nodes, all requiring an estimation of their relative influence on the assessment process. The method described in the paper shows how they can be obtained from about 200 cases instead. It greatly reduces the experts’ elicitation tasks and has the potential for being generalised to similar knowledge-engineering domains where relative weightings of node siblings are part of the parameter space.

Calibration of consumer knowledge of the web

Calibration of consumer knowledge of the web refers to the correspondence between accuracy and confidence in knowledge of the web. Being well-calibrated means that a person is realistic in his or her assessment of the level of knowledge that he or she possesses. This study finds that involvement leads to better calibration and that calibration is higher for procedural knowledge and common knowledge, as compared to declarative knowledge and specialized knowledge. Neither usage, nor experience, has any effect on calibration of knowledge of the web. No difference in calibration is observed between genders. But, in agreement with previous findings, this study also finds that males are more confident in their knowledge of the web. The results point out that calibration could be more a function of knowledge-specific factors and less that of individual-specific factors. The study also identifies flow and frustration with the web as consequences of calibration of knowledge of the web and draws the attention of future researchers to examine these aspects.

Situation-specific cognitive behavioural self-therapy for erroneously suspected allergy or intolerance to a food:a short self-assessment tool

The recall of personal experiences relevant to a claim of food allergy or food intolerance is assessed by a psychologically validated tool for evidence that the suspected food could have caused the adverse symptom suffered. The tool looks at recall from memory of a particular episode or episodes when food was followed by symptoms resulting in self-diagnosis of food allergy or intolerance compared to merely theoretical knowledge that such symptoms could arise after eating the food. If there is detailed recall of events that point to the food as a potential cause of the symptom and the symptom is sufficiently serious, the tool user is recommended to seek testing at an allergy clinic or by the appropriate specialist for a non-allergic sensitivity. If what is recalled does not support the logical possibility of a causal connection between eating that food and occurrence of the symptom, then the user of the tool is pointed to other potential sources of the problem. The user is also recommended to investigate remedies other than avoidance of the food that had been blamed.

An online assessment and development tool for business incubators:optimising business-incubation management practice, performance and impact, Project Report

This project is focused on exchanging knowledge between ABS, UKBI and managers of business incubators in the UK. The project relates to exploitation of extant knowledge-base on assessing and improving business incubation management practice and performance and builds on two earlier studies. It addresses a pressing need for assessing and benchmarking business incubation input, process and outcome performance and highlighting best practice. The overarching aim of this project was to obtain proof-of-concept for a business incubation performance assessment and benchmarking online tool, fine-tune it and put it in use by nurturing a community of business incubation management practice, aligned by the resultant tool. The purpose was to offer an appropriate set of measures, in areas identified by relevant research on business incubation performance management and impact as critical, against which: 1.The input and process performance of business incubation management practice can be assessed and benchmarked within the auspices of a community of incubator managers concerned with best practice 2.The outcome performance and impact of business incubators can be assessed longitudinally. As such, the developed online assessment framework is geared towards the needs of researchers, policy makers and practitioners concerned with business incubation performance, added value and impact.

Using XML and XSLT for flexible elicitation of mental-health risk knowledge

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge. © 2007 Informa UK Ltd All rights reserved.

Representing the assessment process for psychodynamic psychotherapy within a computerized model of human classification

This research describes a computerized model of human classification which has been constructed to represent the process by which assessments are made for psychodynamic psychotherapy. The model assigns membership grades (MGs) to clients so that the most suitable ones have high values in the therapy category. Categories consist of a hierarchy of components, one of which, ego strength, is analysed in detail to demonstrate the way it has captured the psychotherapist's knowledge. The bottom of the hierarchy represents the measurable factors being assessed during an interview. A questionnaire was created to gather the identified information and was completed by the psychotherapist after each assessment. The results were fed into the computerized model, demonstrating a high correlation between the model MGs and the suitability ratings of the psychotherapist (r = .825 for 24 clients). The model has successfully identified the relevant data involved in assessment and simulated the decision-making process of the expert. Its cognitive validity enables decisions to be explained, which means that it has potential for therapist training and also for enhancing the referral process, with benefits in cost effectiveness as well as in the reduction of trauma to clients. An adapted version measuring client improvement would give quantitative evidence for the benefit of therapy, thereby supporting auditing and accountability. © 1997 The British Psychological Society.