Griffith University

About: Griffith University is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 13830 authors who have published 49318 publications receiving 1420865 citations.

Interpretations of criteria‐based assessment and grading in higher education

Abstract: The increasing use of criteria‐based approaches to assessment and grading in higher education is a consequence of its sound theoretical rationale and its educational effectiveness. This article is based on a review of the most common grading policies that purport to be criteria‐based. The analysis shows that there is no common understanding of what criteria‐based means or what it implies for practice. This has inhibited high‐quality discourse, research and development among scholars and practitioners. Additionally, the concepts of ‘criteria’ and ‘standards’ are often confused and, despite the use of criteria, the fundamental judgments teachers make about the quality of student work remain subjective and substantially hidden from the students’ view. As they stand, none of the approaches identified in the survey is fully capable of delivering on the aspirations of criteria‐based grading. Shifting the primary focus to standards and making criteria secondary could, however, lead to substantial progress.

Food webs: reconciling the structure and function of biodiversity

Abstract: The global biodiversity crisis concerns not only unprecedented loss of species within communities, but also related consequences for ecosystem function. Community ecology focuses on patterns of species richness and community composition, whereas ecosystem ecology focuses on fluxes of energy and materials. Food webs provide a quantitative framework to combine these approaches and unify the study of biodiversity and ecosystem function. We summarise the progression of food-web ecology and the challenges in using the food-web approach. We identify five areas of research where these advances can continue, and be applied to global challenges. Finally, we describe what data are needed in the next generation of food-web studies to reconcile the structure and function of biodiversity.

Colloquium: The Einstein-Podolsky-Rosen paradox: From concepts to applications

Abstract: This Colloquium examines the field of the Einstein, Podolsky, and Rosen (EPR) gedanken experiment, from the original paper of Einstein, Podolsky, and Rosen, through to modern theoretical proposals of how to realize both the continuous-variable and discrete versions of the EPR paradox. The relationship with entanglement and Bell's theorem are analyzed, and the progress to date towards experimental confirmation of the EPR paradox is summarized, with a detailed treatment of the continuous-variable paradox in laser-based experiments. Practical techniques covered include continuous-wave parametric amplifier and optical fiber quantum soliton experiments. Current proposals for extending EPR experiments to massive-particle systems are discussed, including spin squeezing, atomic position entanglement, and quadrature entanglement in ultracold atoms. Finally, applications of this technology to quantum key distribution, quantum teleportation, and entanglement swapping are examined.

How effective is the Grey Wolf optimizer in training multi-layer perceptrons

Abstract: This paper employs the recently proposed Grey Wolf Optimizer (GWO) for training Multi-Layer Perceptron (MLP) for the first time. Eight standard datasets including five classification and three function-approximation datasets are utilized to benchmark the performance of the proposed method. For verification, the results are compared with some of the most well-known evolutionary trainers: Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolution Strategy (ES), and Population-based Incremental Learning (PBIL). The statistical results prove the GWO algorithm is able to provide very competitive results in terms of improved local optima avoidance. The results also demonstrate a high level of accuracy in classification and approximation of the proposed trainer.