Forging futures? Engineering in the primary school curriculum

Starting with the research question, "How can the Primary School Curriculum be developed so as to spark Children's Engineering Imaginations from an early age?" this paper sets out to critically analyse the issues around embedding Engineering in the Primary School Curriculum from the age of 5 years. Findings from an exploratory research project suggest that in order to promote the concept of Engineering Education to potential university students (and in doing so begin to address issues around recruitment / retention within Engineering) there is a real need to excite and engage children with the subject from a young age. Indeed, it may be argued that within today's digital society, the need to encourage children to engage with Engineering is vital to the future sustainable development of our society. Whilst UK Government policy documents highlight the value of embedding Engineering into the school curriculum there is little or no evidence to suggest that Engineering has been successfully embedded into the elementary level school curriculum. Building on the emergent findings of the first stage of a longitudinal study, this paper concludes by arguing that Engineering could be embedded into the curriculum through innovative pedagogical approaches which contextualise project-based learning experiences within more traditional subjects including science, history, geography, literacy and numeracy.

In silico prediction of peptide-MHC binding affinity using SVRMHC

The binding between peptide epitopes and major histocompatibility complex (MHC) proteins is a major event in the cellular immune response. Accurate prediction of the binding between short peptides and class I or class II MHC molecules is an important task in immunoinformatics. SVRMHC which is a novel method to model peptide-MHC binding affinities based on support rector machine regression (SVR) is described in this chapter. SVRMHC is among a small handful of quantitative modeling methods that make predictions about precise binding affinities between a peptide and an MHC molecule. As a kernel-based learning method, SVRMHC has rendered models with demonstrated appealing performance in the practice of modeling peptide-MHC binding.

Is Bologna working? Employer and graduate reflections of the quality, value and relevance of business and management education in four European Union countries

This article focuses on the relevance of undergraduate business and management higher education from the perspectives of recent graduates and graduate employers in four European countries. Drawing upon the findings of an empirical qualitative study in which data was collated and analysed using grounded theory research techniques, the paper draws attention to graduates' and employers' perceptions of the value of higher education in equipping students with discipline-specific skills and knowledge as well as softer 'generic' skills. It also highlights the importance of formal 'work-based' learning within undergraduate curricula in providing students with the skills and experiences required by employers operating within a global workplace. © 2014 John Wiley & Sons Ltd.

Collaborative design of assessment criteria to improve undergraduate student engagement and performance

Student engagement is vital in enhancing the student experience and encouraging deeper learning. Involving students in the design of assessment criteria is one way in which to increase student engagement. In 2011, a marking matrix was used at Aston University (UK) for logbook assessment (Group One) in a project-based learning module. The next cohort of students in 2012 (Group Two) were asked to collaboratively redesign the matrix and were given a questionnaire about the exercise. Group Two initially scored a lower average logbook mark than Group One. However, Group Two showed the greatest improvement between assessments, and the quality of, and commitment to, logbooks was noticeably improved. Student input resulted in a more defined, tougher mark scheme. However, this provided an improved feedback system that gave more scope for self-improvement. The majority of students found the exercise incorporated their ideas, enhanced their understanding, and was useful in itself.

A branch and efficiency algorithm for the optimal design of supply chain networks

Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.