Curriculum and beyond: Mathematics support for first year life science students

The move into higher education is a real challenge for students from all educational backgrounds, with the adaptation to a new curriculum and style of learning and teaching posing a daunting task. A series of exercises were planned to boost the impact of the mathematics support for level four students and was focussed around a core module for all students. The intention was to develop greater confidence in tackling mathematical problems in all levels of ability and to provide more structured transition period in the first semester of level 4. Over a two-year period the teaching team for Biochemistry and Molecular Biology provided a series of structured formative tutorials and “interactive” online problems. Video solutions to all formative problems were made available, in order that students were able to engage with the problems at any time and were not disadvantaged if they could not attend. The formative problems were specifically set to dovetail into a practical report in which the mathematical skills developed were specifically assessed. Students overwhelmingly agreed that the structured formative activities had broadened their understanding of the subject and that more such activities would help. Furthermore, it is interesting to note that the package of changes undertaken resulted in a significant increase in the overall module mark over the two years of development

An Investigation of Introductory Physics Students Approach to Problem Solving

This paper outlines ongoing research investigating students’ approaches to quantitative and qualitative problem solving in physics. This is an empirical study, which was conducted using a phenomenographic approach to analyse and interpret data from individual semi-structured interviews with students from introductory physics courses. The result of the study thus far is a preliminary set of hierarchical categories that describe the students’ problem-solving approaches when faced with various physics problems. The findings from the research presented here indicate that many introductory students in higher education do not approach problem solving in a strategic manner and many do not try to link or use their physics knowledge in order to solve problems

Critical success factors for e-learning implementation in Egyptian public universities: a stakeholders\u27 analysis

Higher education is witnessing major change worldwide and new methods of learning are emerging. Modern technologies are affecting the way educational institutions address learning challenges through presenting innovative solutions. E-learning is a form of education to which attention has increased worldwide. Flexibility provided by e-learning is makes it possible for universities around the world to enroll an increased number of students to meet the needs of all learners. The higher education system in Egypt faces several challenges which hinder it from development. It has become important for Egypt to strive to use new technologies to develop and strengthen higher education. Nevertheless, the take-up and use of e-learning in Egypt is still in its early stages and many difficulties and challenges need to be addressed in order for e-learning to be widely adopted. The present thesis studies the current situation of e-learning implementation and adoption at Egyptian public universities. The study analyzes the prospects of benefiting from e-learning in Egypt to minimize the problems facing the higher education system. The study further points out challenges that hinder the take up of e-learning and highlights the critical success factors needed in order to implement e-learning successfully in Egypt. Qualitative data was collected through conducting face-to-face semi-structured interviews with 21 top management officials, strategic planners, information technology experts, instructional designers, and professors teaching e-learning courses from different public universities. The thesis concludes with a set of policy recommendations in order to successfully implement e-learning in the higher education system

Breaking organizational barriers for greening Australian campuses

Sustainability is an issue for everyone. For instance, the higher education sector is being asked to take an active part in creating a sustainable future, due to their moral responsibility, social obligation, and their own need to adapt to the changing higher education environment. By either signing declarations or making public statements, many universities are expressing their desire to become role models for enhancing sustainability. However, too often they have not delivered as much as they had intended. This is particularly evident in the lack of physical implementation of sustainable practices in the campus environment. Real projects such as green technologies on campus have the potential to rectify the problem in addition to improving building performance. Despite being relatively recent innovations, Green Roof and Living Wall have been widely recognized because of their substantial benefits, such as runoff water reduction, noise insulation, and the promotion of biodiversity. While they can be found in commercial and residential buildings, they only appear infrequently on campuses as universities have been very slow to implement sustainability innovations. There has been very little research examining the fundamental problems from the organizational perspective. To address this deficiency, the researchers designed and carried out 24 semi-structured interviews to investigate the general organizational environment of Australian universities with the intention to identify organizational obstacles to the delivery of Green Roof and Living Wall projects. This research revealed that the organizational environment of Australian universities still has a lot of room to be improved in order to accommodate sustainability practices. Some of the main organizational barriers to the adoption of sustainable innovations were identified including lack of awareness and knowledge, the absence of strong supportive leadership, a weak sustainability-rooted culture and several management challenges. This led to the development of a set of strategies to help optimize the organizational environment for the purpose of better decision making for Green Roof and Living Wall implementation

Curl Constraint-Preserving Reconstruction and the Guidance it Gives for Mimetic Scheme Design

Several important PDE systems, like magnetohydrodynamics and computational electrodynamics, are known to support involutions where the divergence of a vector field evolves in divergence-free or divergence constraint-preserving fashion. Recently, new classes of PDE systems have emerged for hyperelasticity, compressible multiphase flows, so-called first-order reductions of the Einstein field equations, or a novel first-order hyperbolic reformulation of Schrödinger’s equation, to name a few, where the involution in the PDE supports curl-free or curl constraint-preserving evolution of a vector field. We study the problem of curl constraint-preserving reconstruction as it pertains to the design of mimetic finite volume (FV) WENO-like schemes for PDEs that support a curl-preserving involution. (Some insights into discontinuous Galerkin (DG) schemes are also drawn, though that is not the prime focus of this paper.) This is done for two- and three-dimensional structured mesh problems where we deliver closed form expressions for the reconstruction. The importance of multidimensional Riemann solvers in facilitating the design of such schemes is also documented. In two dimensions, a von Neumann analysis of structure-preserving WENO-like schemes that mimetically satisfy the curl constraints, is also presented. It shows the tremendous value of higher order WENO-like schemes in minimizing dissipation and dispersion for this class of problems. Numerical results are also presented to show that the edge-centered curl-preserving (ECCP) schemes meet their design accuracy. This paper is the first paper that invents non-linearly hybridized curl-preserving reconstruction and integrates it with higher order Godunov philosophy. By its very design, this paper is, therefore, intended to be forward-looking and to set the stage for future work on curl involution-constrained PDEs

Adaptive scaling of evolvable systems

Neo-Darwinian evolution is an established natural inspiration for computational optimisation with a diverse range of forms. A particular feature of models such as Genetic Algorithms (GA) [18, 12] is the incremental combination of partial solutions distributed within a population of solutions. This mechanism in principle allows certain problems to be solved which would not be amenable to a simple local search. Such problems require these partial solutions, generally known as building-blocks, to be handled without disruption. The traditional means for this is a combination of a suitable chromosome ordering with a sympathetic recombination operator. More advanced algorithms attempt to adapt to accommodate these dependencies during the search. The recent approach of Estimation of Distribution Algorithms (EDA) aims to directly infer a probabilistic model of a promising population distribution from a sample of fitter solutions [23]. This model is then sampled to generate a new solution set. A symbiotic view of evolution is behind the recent development of the Compositional Search Evolutionary Algorithms (CSEA) [49, 19, 8] which build up an incremental model of variable dependencies conditional on a series of tests. Building-blocks are retained as explicit genetic structures and conditionally joined to form higher-order structures. These have been shown to be effective on special classes of hierarchical problems but are unproven on less tightly-structured problems. We propose that there exists a simple yet powerful combination of the above approaches: the persistent, adapting dependency model of a compositional pool with the expressive and compact variable weighting of probabilistic models. We review and deconstruct some of the key methods above for the purpose of determining their individual drawbacks and their common principles. By this reasoned approach we aim to arrive at a unifying framework that can adaptively scale to span a range of problem structure classes. This is implemented in a novel algorithm called the Transitional Evolutionary Algorithm (TEA). This is empirically validated in an incremental manner, verifying the various facets of the TEA and comparing it with related algorithms for an increasingly structured series of benchmark problems. This prompts some refinements to result in a simple and general algorithm that is nevertheless competitive with state-of-the-art methods

A Functional Model For Information Exploration Systems

Information exploration tasks are inherently complex, ill-structured, and involve sequences of actions usually spread over many sessions. When exploring a dataset, users tend to experiment higher degrees of uncertainty, mostly raised by knowledge gaps concerning the information sources, the task, and the efficiency of the chosen exploration actions, strategies, and tools in supporting the task solution process. Provided these concerns, exploration tools should be designed with the goal of leveraging the mapping between user's cognitive actions and solution strategies onto the current systems' operations. However, state-of-the-art systems fail in providing an expressive set of operations that covers a wide range of exploration problems. There is not a common understanding of neither which operators are required nor in which ways they can be used by explorers. In order to mitigate these shortcomings, this work presents a formal framework of exploration operations expressive enough to describe at least the majority of state-of-the-art exploration interfaces and tasks. We also show how the framework leveraged a new evaluation approach, where we draw precise comparisons between tools concerning the range of exploration tasks they support.Comment: 27 page