A model for self-directed problem-based learning for renal therapeutics

Objective To introduce a new approach to problem-based learning (PBL) for self-directed learning in renal therapeutics. Design This 5-week course, designed for large student cohorts using minimal teaching resources, was based on a series of case studies and subsequent pharmaceutical care plans, followed by intensive and regular feedback from the instructor. Assessment Assessment of achievement of the learning outcomes was based on weekly-graded care plans and peer review assessment, allowing each student to judge the contributions of each group member and their own, along with a written case-study based examination. The pharmaceutical care plan template, designed using a “tick-box” system, significantly reduced staff time for feedback and scoring. Conclusion The proposed instructional model achieved the desired learning outcomes with appropriate student feedback, while promoting skills that are essential for the students' future careers as health care professionals.

Problem-based learning approaches in meteorology

Problem-Based Learning, despite recent controversies about its effectiveness, is used extensively as a teaching method throughout higher education. In meteorology, there has been little attempt to incorporate Problem-Based Learning techniques into the curriculum. Motivated by a desire to enhance the reflective engagement of students within a current field course module, this project describes the implementation of two test Problem-Based Learning activities and testing and improvement using several different and complementary means of evaluation. By the end of a 2-year program of design, implementation, testing, and reflection and re-evaluation, two robust, engaging activities have been developed that provide an enhanced and diverse learning environment in the field course. The results suggest that Problem-Based Learning techniques would be a useful addition to the meteorology curriculum and suggestions for courses and activities that may benefit from this approach are included in the conclusions.

Using problem-based learning in a chemistry practical class for pharmacy students and engaging them with feedback

Objective: To introduce a new approach to problem based learning (PBL) used in the context of medicinal chemistry practical class teaching pharmacy students. Design: The described chemistry practical is based on independent studies by small groups of undergraduate students (4-5), who design their own practical work taking relevant professional standards into account. Students are carefully guided by feedback and acquire a set of skills important to their future profession as healthcare professionals. This model has been tailored to the application of PBL in a chemistry practical class setting for a large student cohort (150 students). Assessment: The achievement of learning outcomes is based on the submission of relevant documentation including a certificate of analysis, in addition to peer assessment. Some of the learning outcomes are also assessed in the final written examination at the end of the academic year. Conclusion: The described design of a novel PBL chemistry laboratory course for pharmacy students has been found to be successful. Self-reflective learning and engagement with feedback were encouraged, and students enjoyed the challenging learning experience. Skills that are highly essential for the students’ future careers as healthcare professionals are promoted.

Tensor regression based on linked multiway parameter analysis

Classical regression methods take vectors as covariates and estimate the corresponding vectors of regression parameters. When addressing regression problems on covariates of more complex form such as multi-dimensional arrays (i.e. tensors), traditional computational models can be severely compromised by ultrahigh dimensionality as well as complex structure. By exploiting the special structure of tensor covariates, the tensor regression model provides a promising solution to reduce the model’s dimensionality to a manageable level, thus leading to efficient estimation. Most of the existing tensor-based methods independently estimate each individual regression problem based on tensor decomposition which allows the simultaneous projections of an input tensor to more than one direction along each mode. As a matter of fact, multi-dimensional data are collected under the same or very similar conditions, so that data share some common latent components but can also have their own independent parameters for each regression task. Therefore, it is beneficial to analyse regression parameters among all the regressions in a linked way. In this paper, we propose a tensor regression model based on Tucker Decomposition, which identifies not only the common components of parameters across all the regression tasks, but also independent factors contributing to each particular regression task simultaneously. Under this paradigm, the number of independent parameters along each mode is constrained by a sparsity-preserving regulariser. Linked multiway parameter analysis and sparsity modeling further reduce the total number of parameters, with lower memory cost than their tensor-based counterparts. The effectiveness of the new method is demonstrated on real data sets.

Ethnographic methodologies for construction research: knowing, practice and interventions

Ethnographic methodologies developed in social anthropology and sociology hold considerable promise for addressing practical, problem-based research concerned with the construction site. The extended researcher-engagement characteristic of ethnography reveals rich insights, yet is infrequently used to understand how workplace realities are lived out on construction sites. Moreover, studies that do employ these methods are rarely reported within construction research journals. This paper argues that recent innovations in ethnographic methodologies offer new routes to: posing questions; understanding workplace socialities (i.e. the qualities of the social relationships that develop on construction sites); learning about forms, uses and communication of knowledge on construction sites; and turning these into meaningful recommendations. This argument is supported by examples from an interdisciplinary ethnography concerning migrant workers and communications on UK construction sites. The presented research seeks to understand how construction workers communicate with managers and each other and how they stay safe on site, with the objective of informing site health-and-safety strategies and the production and evaluation of training and other materials.

State estimation using model order reduction for unstable systems

The problem of state estimation occurs in many applications of fluid flow. For example, to produce a reliable weather forecast it is essential to find the best possible estimate of the true state of the atmosphere. To find this best estimate a nonlinear least squares problem has to be solved subject to dynamical system constraints. Usually this is solved iteratively by an approximate Gauss–Newton method where the underlying discrete linear system is in general unstable. In this paper we propose a new method for deriving low order approximations to the problem based on a recently developed model reduction method for unstable systems. To illustrate the theoretical results, numerical experiments are performed using a two-dimensional Eady model – a simple model of baroclinic instability, which is the dominant mechanism for the growth of storms at mid-latitudes. It is a suitable test model to show the benefit that may be obtained by using model reduction techniques to approximate unstable systems within the state estimation problem.

The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part III: the shortwave flux feedback

Previous studies using coupled general circulation models (GCMs) suggest that the atmosphere model plays a dominant role in the modeled El Nin ̃ o–Southern Oscillation (ENSO), and that intermodel differences in the thermodynamical damping of sea surface temperatures (SSTs) are a dominant contributor to the ENSO amplitude diversity. This study presents a detailed analysis of the shortwave flux feedback (aSW) in 12 Coupled Model Intercomparison Project phase 3 (CMIP3) simulations, motivated by findings that aSW is the primary contributor to model thermodynamical damping errors. A ‘‘feedback decomposition method,’’ developed to elucidate the aSW biases, shows that all models un- derestimate the dynamical atmospheric response to SSTs in the eastern equatorial Pacific, leading to un- derestimated aSW values. Biases in the cloud response to dynamics and the shortwave interception by clouds also contribute to errors in aSW. Changes in the aSW feedback between the coupled and corresponding atmosphere-only simulations are related to changes in the mean dynamics. A large nonlinearity is found in the observed and modeled SW flux feedback, hidden when linearly cal- culating aSW. In the observations, two physical mechanisms are proposed to explain this nonlinearity: 1) a weaker subsidence response to cold SST anomalies than the ascent response to warm SST anomalies and 2) a nonlinear high-level cloud cover response to SST. The shortwave flux feedback nonlinearity tends to be underestimated by the models, linked to an underestimated nonlinearity in the dynamical response to SST. The process-based methodology presented in this study may help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GCMs.

Trust and relational embeddedness: exploring a paradox of trust pattern development in key supplier relationships

This paper explores the role of trust as an enabler and constraint between buyers and suppliers engaged in long-term relationships. According to the relational view, cooperative strategies require trust-based mutual commitments to co-create value. However, complete pictures of the positive and negative outcomes from trust development have yet to be fully developed. In particular, trust as an originator of path dependent constraints resulting from over embeddedness is yet to be integrated into the relational view. We use a case-based methodology to explore whether trust is an optimizing phenomenon in key supplier relationships. Two cases where trust development processes demonstrate a paradox of trust-building behaviors cultivate different outcomes constraining value co-creation.

Measuring the value of “all play and no work”: can rigorous assessment of simulation games drive innovative teaching in construction?

The construction field is dynamic and dominated by complex, ill-defined problems for which myriad possible solutions exist. Teaching students to solve construction-related problems requires an understanding of the nature of these complex problems as well as the implementation of effective instructional strategies to address them. Traditional approaches to teaching construction planning and management have long been criticized for presenting students primarily with well-defined problems - an approach inconsistent with the challenges encountered in the industry. However, growing evidence suggests that employing innovative teaching approaches, such as interactive simulation games, offers more active, hands-on and problem-based learning opportunities for students to synthesize and test acquired knowledge more closely aligned with real-life construction scenarios. Simulation games have demonstrated educational value in increasing student problem solving skills and motivation through critical attributes such as interaction and feedback-supported active learning. Nevertheless, broad acceptance of simulation games in construction engineering education remains limited. While recognizing benefits, research focused on the role of simulation games in educational settings lacks a unified approach to developing, implementing and evaluating these games. To address this gap, this paper provides an overview of the challenges associated with evaluating the effectiveness of simulation games in construction education that still impede their wide adoption. An overview of the current status, as well as the results from recently implemented Virtual Construction Simulator (VCS) game at Penn State provide lessons learned, and are intended to guide future efforts in developing interactive simulation games to reach their full potential.

The cyber challenge: a robotics project to enthuse

Robotics is a key theme in many of the degrees offered in Systems Engineering. The topic has proved useful in attracting students to the University, and it also provides the basis of much practical and project work throughout the degrees. This paper focuses on one aspect, a Part 2 project in which students doing various degrees work together to develop a mobile robot which is controlled remotely to navigate an environment and perform specific tasks. In addition to providing practical experience of relevant academic topics, this project helps to contribute to key teaching and learning priorities including problem based learning, motivation and important employability skills.

Thinking out of the box – skills for work

Since the Dearing Report .1 there has been an increased emphasis on the development of employability and transferable (‘soft’) skills in undergraduate programmes. Within STEM subject areas, recent reports concluded that universities should offer ‘greater and more sustainable variety in modes of study to meet the changing demands of industry and students’.2 At the same time, higher education (HE) institutions are increasingly conscious of the sensitivity of league table positions on employment statistics and graduate destinations. Modules that are either credit or non-credit bearing are finding their way into the core curriculum at HE. While the UK government and other educational bodies argue the way forward over A-level reform, universities must also meet the needs of their first year cohorts in terms of the secondary to tertiary transition and developing independence in learning.

Societal transformation in response to global environmental change: a review of emerging concepts

The study of societal transformation in response to environmental change has become established, yet little consensus exists regarding the conceptual basis of transformation. This paper aims to provide structure to the dialog on transformation, and to reflect on the challenges of social research in this area. Concepts of transformation are identified through a literature review, and examined using four analytical criteria. It is found that the term ‘transformation’ is frequently used merely as a metaphor. When transformation is not used as a metaphor, eight concepts are most frequently employed. They differ with respect to (i) system conceptualization, (ii) notions of social consciousness (deliberate/emergent), and (iii) outcome (prescriptive/descriptive). Problem-based research tends to adopt concepts of deliberate transformation with prescriptive outcome, while concepts of emergent transformation with no prescriptive outcome tend to inform descriptive-analytical research. Dialog around the complementarities of different concepts and their empirical testing are priorities for future research.

Discontinuous Galerkin methods for the p-biharmonic equation from a discrete variational perspective

We study discontinuous Galerkin approximations of the p-biharmonic equation for p∈(1,∞) from a variational perspective. We propose a discrete variational formulation of the problem based on an appropriate definition of a finite element Hessian and study convergence of the method (without rates) using a semicontinuity argument. We also present numerical experiments aimed at testing the robustness of the method.

Linking classroom learning and research to advance ideas about social-ecological resilience

There is an increasing demand in higher education institutions for training in complex environmental problems. Such training requires a careful mix of conventional methods and innovative solutions, a task not always easy to accomplish. In this paper we review literature on this theme, highlight relevant advances in the pedagogical literature, and report on some examples resulting from our recent efforts to teach complex environmental issues. The examples range from full credit courses in sustainable development and research methods to project-based and in-class activity units. A consensus from the literature is that lectures are not sufficient to fully engage students in these issues. A conclusion from the review of examples is that problem-based and project-based, e.g., through case studies, experiential learning opportunities, or real-world applications, learning offers much promise. This could greatly be facilitated by online hubs through which teachers, students, and other members of the practitioner and academic community share experiences in teaching and research, the way that we have done here.

Dystrophin analysis using a panel of anti-dystrophin antibodies in Duchenne and Becker muscular dystrophy.

Dystrophin, the protein product of the Duchenne muscular dystrophy (DMD) gene, was studied in 19 patients with Xp21 disorders and in 25 individuals with non-Xp21 muscular dystrophy. Antibodies raised to seven different regions spanning most of the protein were used for immunocytochemistry. In all patients specific dystrophin staining anomalies were detected and correlated with clinical severity and also gene deletion. In patients with Becker muscular dystrophy (BMD) the anomalies detected ranged from inter- and intra-fibre variation in labelling intensity with the same antibody or several antibodies to general reduction in staining and discontinuous staining. In vitro evidence of abnormal dystrophin breakdown was observed reanalysing the muscle of patients, with BMD and not that of non-Xp21 dystrophies, after it has been stored for several months. A number of patients with DMD showed some staining but this did not represent a diagnostic problem. Based on the data presented, it was concluded that immunocytochemistry is a powerful technique in the prognostic diagnosis of Xp21 muscular dystrophies.