The development of a formative scenario-based computer assisted assessment tool in psychology for teachers: The PePCAA project

Formative computer assisted assessment has become increasingly attractive in Higher Education where providing useful feedback to large numbers of students can be difficult. However, the nature of such assessments has often been limited to objective questions such as multiple-choice. This paper reports on the development and initial trialling of a more innovative, formative use of computer assisted assessment in a Higher Education context. The European funded PePCAA (Pedagogical Psychology Computer Assisted Assessment) project developed a series of scenario-based computer-delivered formative assessments of pedagogical psychology for teachers and trainee teachers, using a range of software features, including the addition of confidence measurement. The project had a two-fold aim: to provide a tool to improve understanding of pedagogical psychology and to explore the potential of more innovative techniques of computer assisted assessment to motivate students and to assess deeper learning. The combination of computer-delivered formative assessment with innovative question styles and confidence ratings is believed to be unique for pedagogical psychology. Scenarios were based on realistic classroom situations and focused on problem solving or on utilising best practice. The PePCAA Learning Assessment Circle (PLAC) provided a framework for indexing the kinds of processes required of users. In the UK, small scale trialling involved a total of 23 teacher trainees such that each assessment was attempted by about seven participants. Participants completed evaluation questionnaires after each assessment. Responses from learners indicated that the UK scenarios were generally very well received and had at least partly achieved the aim of stimulating deeper learning. Transfer of assessments between countries proved more difficult than expected. The next stage of development should be to conduct a larger pilot, thus allowing full investigation of the reliability and validity of the assessments. There is also scope for further development of the PePCAA approach and for its application in other subjects.     

Identifying discriminating variables between teachers who fully integrate computers and teachers with limited integration

Given the prevalence of computers in education today, it is critical to understand teachers’ perspectives regarding computer integration in their classrooms. The current study surveyed a random sample of a heterogeneous group of 185 elementary and 204 secondary teachers in order to provide a comprehensive summary of teacher characteristics and variables that best discriminate between teachers who integrate computers and those who do not. Discriminant Function Analysis indicated seven variables for elementary teachers and six for secondary teachers (accounting for 74% and 68% of the variance, respectively) that discriminated between high and low integrators. Variables included positive teaching experiences with computers; teacher’s comfort with computers; beliefs supporting the use of computers as an instructional tool; training; motivation; support; and teaching efficacy. Implications for support of computer integration in the classroom are discussed.     

Characterising effective eLearning resources

The widespread availability of digital learning resources in a variety of media formats offers the possibility to make a profound difference in education. This potential has not been fully realised for range of interrelated reasons. In this paper we study the key characteristics of learning resources that have proved effective in changing learning and teaching, and relate them to existing frameworks for understanding resources. We outline the relationships between resources, their users, and the way they are used, and explore issues that influence practitioners in choosing a particular resource. Our study is based on a review of resources for e-learning and chemistry in post-compulsory education, undertaken for the UK Joint Information Systems Committees (JISC), as part of a wider study examining ‘The Effectiveness of Resources, Tools and Support Services used by Tutors in Designing and Delivering E-Learning Activities’.     

On the information modeling for the electronic operation of supply chains: A maritime case study

Nowadays, the manufacturing industry is adopting modern information technologies in order to optimize their business process and to achieve integration with supply chain partners that are geographically dispersed, by expanding the physical limits of their business globally. The growth of the World Wide Web and the advantages of the software technologies arising from it render this goal possible. This paper discusses how modern information technology, particularly the ISO 10303—STEP and eXtensible Markup Language—XML, can be utilized jointly to support the communication of different partners. An approach to support enterprise operation through efficient data exchanges, by adopting modern data modeling techniques for integration among partners worldwide and using the web as a communication layer, is described. The paper deals particularly with the ship repair industry as a case study of these problems and suggests a feasible solution.     

A supply network-modelling system for a small- to medium-sized manufacturing company

During the late 1990s and early 2000s, the profile of global manufacturing has experienced many changes. There is anecdotal evidence that many western manufacturing companies have chosen to expand their manufacturing base across geographical boundaries. The common reasons sited for these ventures are to exploit less expensive labour markets, to establish a presence in expanding markets and in response to the threat of new competition. Whilst a global manufacturing base can prove to have many cost and sales benefits, there are also many disadvantages. Logistics operations can often increase in complexity leading to higher reliance on planning and effective interpretation of demand data. In response, systems modelling has remerged as a fertile research area after many years. Many modelling and simulation techniques have been developed, but these have had very limited practical success. The authors have identified that majority of these simulation techniques rely upon a detailed market structure being known, when this is rarely the case. This paper describes the outcome of a research project to develop of a pragmatic set of tools to gather, assess and verify supply chain structure data. A hybrid collection of technologies are utilised to assist these operations and to build a dynamic supply network model.     

Trust in consumer-to-consumer electronic commerce

We developed a model of consumer-to-consumer (C2C) e-commerce trust and tested it. We expected that two influences: internal (natural propensity to trust [NPT] and perception of web site quality [PWSQ]) and external (other's trust of buyers/sellers [OTBS] and third party recognition [TPR]) would affect an individual's trust in C2C e-commerce. However contrary to studies of other types of e-commerce, support was only found for PWSQ and TPR; we therefore discussed possible reasons for this contradiction. Suggestions are made of ways to help e-commerce site developers provide a trustworthy atmosphere and identify trustworthy consumers.     

Forming processes control by means of artificial intelligence techniques

Forming processes are manufacturing processes that use force and pressure in order to modify the shape of a material part until obtaining the final product. The wide range of non-linear factors that drive this sort of processes make them very complex and extremely difficult to be controlled. Traditional control techniques, like PID controllers, have not offered a reliable solution when global control has been pursued and the figure of the operator still remains present in most of the forming facilities. On the other hand, although operators have demonstrated to be a very successful strategy when controlling this type of processes, the actual market evolution towards the fabrication of more complex parts, made of lower formability materials at higher production rates, is decreasing their capacity of reaction when solving the daily problems. Thus, the development of new global control systems based not on traditional control techniques and mathematical models but on the control strategy that has been used successfully for many years, the control through the experience and knowledge is now even more necessary. In the present work, an intelligent control system based on one of the main techniques within the artificial intelligence, expert systems, has been developed. The main purpose of this intelligent control system is to emulate the decisions that expert operators take but in a quicker and more reliable way. The developed intelligent control system has been installed in a blanking facility and very good results have been achieved.     

Invariant and attracting sets of impulsive delay difference equations with continuous variables

The aim of this paper is to study the invariant and attracting sets of impulsive delay difference equations with continuous variables. Some criteria for the invariant and attracting sets are obtained by using the decomposition approach and delay difference inequalities with impulsive initial conditions.     

Extended stochastic gradient identification algorithms for Hammerstein–Wiener ARMAX systems

An extended stochastic gradient algorithm is developed to estimate the parameters of Hammerstein–Wiener ARMAX models. The basic idea is to replace the unmeasurable noise terms in the information vector of the pseudo-linear regression identification model with the corresponding noise estimates which are computed by the obtained parameter estimates. The obtained parameter estimates of the identification model include the product terms of the parameters of the original systems. Two methods of separating the parameter estimates of the original parameters from the product terms are discussed: the average method and the singular value decomposition method. To improve the identification accuracy, an extended stochastic gradient algorithm with a forgetting factor is presented. The simulation results indicate that the parameter estimation errors become small by introducing the forgetting factor.     

Model of Frequency Analysis in the Visual Cortex and the Shape from Texture Problem

This paper addresses the question: at the level of cortical cells present in the primary area V1, is the information sufficient to extract the local perspective from the texture? Starting from a model of complex cells in visual area V1, we propose a biologically plausible algorithm for frequency analysis applied to the shape from texture problem. First, specific log-normal filters are designed in replacement of the classical Gabor filters because of their theoretical properties and of their biological plausibility. These filters are separable in frequency and orientation and they better sample the image spectrum which makes them appropriate for any pattern analysis technique. A method to estimate the local frequency in the image, which discards the need to choose the best local scale, is designed. Based on this frequency analysis model, a local decomposition of the image into patches leads to the estimation of the local frequency variation which is used to solve the problem of recovering the shape from the texture. From the analytical relation between the local frequency and the geometrical parameters, under perspective projection, it is possible to recover the orientation and the shape of the original image. The accuracy of the method is evaluated and discussed on different kind of textures, both regular and irregular, with planar and curved surfaces and also on natural scenes and psychophysical stimuli. It compares favorably to the best existing methods, with in addition, a low computational cost. The biological plausibility of the model is finally discussed.