Evaluation of creative problem solving abilities in undergraduate structural engineers through interdisciplinary problem based learning

For a structural engineer, effective communication and interaction with architects cannot be underestimated as a key skill to success throughout their professional career. Structural engineers and architects have to share a common language and understanding of each other in order to achieve the most desirable architectural and structural designs. This interaction and engagement develops during their professional career but needs to be nurtured during their undergraduate studies. The objective of this paper is to present the strategies employed to engage higher order thinking in structural engineering students in order to help them solve complex problem-based learning (PBL) design scenarios presented by architecture students. The strategies employed were applied in the experimental setting of an undergraduate module in structural engineering at Queen’s University Belfast in the UK. The strategies employed were active learning to engage with content knowledge, the use of physical conceptual structural models to reinforce key concepts and finally, reinforcing the need for hand sketching of ideas to promote higher order problem-solving. The strategies employed were evaluated through student survey, student feedback and module facilitator (this author) reflection. The strategies were qualitatively perceived by the tutor and quantitatively evaluated by students in a cross-sectional study to help interaction with the architecture students, aid interdisciplinary learning and help students creatively solve problems (through higher order thinking). The students clearly enjoyed this module and in particular interacting with structural engineering tutors and students from another discipline

IMPLEMENTING BACK PAIN TREATMENT PATHWAYS IN CLINICAL PRACTICE: QUALITATATIVE ANALYSIS OF STAKEHOLDER PERCEPTIONS

Background
Evidence-based practice advocates utilising best current research evidence, while reflecting patient preference and clinical expertise in decision making. Successfully incorporating this evidence into practice is a complex process. Based on recommendations of existing guidelines and systematic evidence reviews conducted using the GRADE approach, treatment pathways for common spinal pain disorders were developed.

Aims
The aim of this study was to identify important potential facilitators to the integration of these pathways into routine clinical practice.

Methods
A 22 person stakeholder group consisting of patient representatives, clinicians, researchers and members of relevant clinical interest groups took part in a series of moderated focus groups, followed up with individual, semi-structured interviews. Data were analysed using content analysis.

Results
Participants identified a number of issues which were categorized into broad themes. Common facilitators to implementation included continual education and synthesis of research evidence which is reflective of everyday practice; as well as the use of clear, unambiguous messages in recommendations. Meeting additional training needs in new or extended areas of practice was also recognized as an important factor. Different stakeholders identified specific areas which could be associated with successful uptake. Patients frequently defined early involvement in a shared decision making process as important. Clinicians identified case based examples and information on important prognostic indicators as useful tools to aiding decisions.

Conclusion
A number of potential implementation strategies were identified. Further work will examine the impact of these and other important factors on the integration of evidence-based treatment recommendations into clinical practice.

Directional genetic differentiation and relative migration

Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. As information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum-likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user-friendly web application called divMigrate-online introduced in this study. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.