Improving Learning: Reconsidering Student Assessment Globally

Learning assessment plays a critical role in helping to improve learning under different conditions and in varying situations, as an integral part not just of the teaching–learning process, but also of the larger policy environment. While the objective of each type of assessment may differ, its fundamental purpose remains that of helping to determine progress made by each learner in their individual learning path so as to be able to guide and support further development (Masters 2013). Most importantly, utilizing the data emerging from an assessment is critical to its success. The effort of undertaking an assessment is lost when the results of that assessment are not acted upon, whether in the classroom or in policy making

Target Value Design: The Challenge of Value Generation

Target Value Design (TVD) is a management approach that aims to maximize value in the framework of a pre-established cost target. TVD views AEC (Architecture, Engineering and Construction) as a complex system and transforms the current design practice upside down. In spite of the existing studies, applying TVD in the context of AEC still represents a major challenge. Creating a structure that enables and measures value generation to the client is part of this challenge. However, despite the contributions already made by TVD, the results and implications related to value generation remain poorly documented. To throw light on value generation in the TVD context, it is useful to understand how the TVD and lean construction literature considers the concept of value. Thus, this study uses a literature review to understand the TVD background, as well as the main contributions made by studies carried out using this approach. The TFV (Transformation, Flow, Value) theory is considered as a baseline to understand the value generation. This paper reports a study that seeks to contribute to the challenge of adjusting the method of TVD to make value generation more explicit

A Hybrid Approach of Fuzzy C-means Clustering and Neural network to make Energy-Efficient heterogeneous Wireless Sensor network

The Wireless sensor network has been highly focused research area in recent times due to its wide applications and adaptability to different environments. The energy-constrained sensor nodes are always under consideration to increase their lifetime. In this paper we have used the advantages of two approaches i.e. fuzzy c-means clustering and neural network to make an energy efficient network by prolonging the lifetime of network. The cluster formation is done using FCM to form equally sized clusters in network and the decision of choosing cluster head is done using neural network having input distance from basestation, heterogeneity and energy of the node. Our Approach has successfully increased the lifetime and data capacity of the network and outperformed different approaches applied to the network present in literature

Artificial neural network analysis of teachers��� performance against thermal comfort

This is an accepted manuscript of an article published by Emerald in International Journal of Building Pathology and Adaptation on 17/04/2020, available online at: https://doi.org/10.1108/IJBPA-11-2019-0098 The accepted manuscript may differ from the final published version.Purpose: The impact of thermal comfort in educational buildings continues to be of major importance in both the design and construction phases. Given this, it is also equally important to understand and appreciate the impact of design decisions on post-occupancy performance, particularly on staff and students. This study aims to present the effect of IEQ on teachers��� performance. This study would provide thermal environment requirements to BIM-led school refurbishment projects. Design: This paper presents a detailed investigation into the direct impact of thermal parameters (temperature, relative humidity and ventilation rates) on teacher performance. In doing so, the research methodological approach combines explicit mixed-methods using questionnaire surveys and physical measurements of thermal parameters to identify correlation and inference. It was conducted through a single case study using a technical college based in Saudi Arabia. Findings: Findings from this work were used to develop a model using an Artificial Neural Network to establish causal relationships. Research findings indicate an optimal temperature range between 23��C and 25��C, with a 65% relative humidity and 0.4m/s ventilation rate. This ratio delivered optimum results for both comfort and performance

Development of Relationship Model between Occupant Productivity and Indoor Environmental Quality in Office Buildings in Qatar

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of PhilosophyThe green building and sustainability revolution from the early 21st century provided a significant improvement in building performance and reduced their carbon footprint. When building and operational costs are compared, personnel cost accounts for 85% of the operational cost of any organisation. Major green building guidelines across the world discuss human comfort and health aspects but don’t focus on human productivity in the office or other building typology. This gap presented an excellent opportunity to develop a model that establishes the relationship between indoor environmental quality and occupant productivity in office buildings. The study was conducted in Doha, Qatar using experiment and survey using 90 sensors in 15 zones in an office building for a period of nine month. Occupant productivity was captured using online survey with nine questions. Occupant response was analysed against various indoor environmental quality parameters using Response Surface Methodology to outline various relationships. Research study achieved its aim and objectives and produced eight innovative equations that represent the relationship between various indoor environmental factors and occupant productivity. Results also indicate that outside temperature and humidity have an indirect impact on occupant productivity; while temperature, relative humidity and light levels have the most significant impact on productivity. Lux levels have an indirect effect on an occupant’s perception of temperature, and outdoor relative humidity has an indirect effect on thermal comfort. Indoor environmental quality factors have direct impact on occupant productivity. This study’s unique focus and research design can be used to extend occupant productivity studies in different types of buildings in different climatic regions. It has provided a substantial contribution to the knowledge gap that existed between indoor environmental quality and occupant productivity. Future researchers can use this study to investigate occupant productivity and indoor environment further

Impact of Using Online Health Management Tools on Patient Perception of Healthcare Quality: A Multiple Chronic Conditions and Generational Perspective

While access and adoption issues related to online health management tools (OHMT) have been studied in healthcare contexts, questions remain about whether and how their use impacts patients’ perceptions of healthcare. Drawing on technology affordance and media synchronicity frameworks, we explore how the existence of multiple chronic conditions (MCC) and differences in usage pattern due to patient’s generation impact these relationships. Utilizing HINTS data, this study provides empirical support for a positive relationship between utilization of electronic personal health records (e-PHRs) and healthcare quality perceptions, albeit with a caveat that patients with greater healthcare needs as well as millennial and younger generations do not seem to enjoy the same benefits from increased use of e-PHRs. Furthermore, asynchronous patient-provider electronic communication is yet to achieve positive perceptions of better healthcare quality for most users. This research bears implications for personalization and customization of OHMT to account for variations in patients’ healthcare needs and usage patterns

Target costing in construction: a comparative study

Target costing is an approach for the development of new products in the automobile industry, aimed at reducing their life-cycle costs while ensuring quality, reliability and other client requirements, by examining all possible ideas for cost reduction at the product planning, research and development and prototyping phases. Prior studies have attempted to adapt the manufacturing target costing process to the project-based nature of the construction industry. This paper aims to provide insights for future target costing implementations in the public sector projects. A qualitative comparison of three studies is performed through the lens of a set of target costing influencing factors. Similarities and differences revealed in the comparison suggest that factors related to supplier-base strategy and to the nature of customer are potentially relevant to future target costing implementations in public sector projects