Technological barriers to learning : designing hybrid pedagogy to minimise cognitive load and maximise understanding

Information and Communication Technologies (ICTs) provide great promise for the future of education. In the Asia-Pacific region, many nations have started working towards the comprehensive development of infrastructure to enable the development of strong networked educational systems. In Queensland there have been significant initiatives in the past decade to support the integration of technology in classrooms and to set the conditions for the enhancement of teaching and learning with technology. One of the great challenges is to develop our classrooms to make the most of these technologies for the benefit of student learning. Recent research and theory into cognitive load, suggests that complex information environments may well impose a barrier on student learning. Further, it suggests that teachers have the capacity to mitigate against cognitive load through the way they prepare and support students engaging with complex information environments. This chapter compares student learning at different levels of cognitive load to show that learning is enhanced when integrating pedagogies are employed to mitigate against high-load information environments. This suggests that a mature policy framework for ICTs in education needs to consider carefully the development of professional capacities to effectively design and integrate technologies for learning.

Static load modelling and voltage stability indices

This paper analyzes the performance of some of the widely used voltage stability indices, namely, singular value, eigenvalue, and loading margin with different static load models. Well-known ZIP model is used to represent loads having components with different power to voltage sensitivities. Studies are carried out on a 10-bus power system and the New England 39-bus power system models. The effects of variation of load model on the performance of the voltage stability indices are discussed. The choice of voltage stability index in the context of load modelling is also suggested in this paper.

A framework for predicting the residual load carrying capacity of concrete structures exposed to aggressive environments

Reinforced concrete structures are susceptible to a variety of deterioration mechanisms due to creep and shrinkage, alkali-silica reaction (ASR), carbonation, and corrosion of the reinforcement. The deterioration problems can affect the integrity and load carrying capacity of the structure. Substantial research has been dedicated to these various mechanisms aiming to identify the causes, reactions, accelerants, retardants and consequences. This has improved our understanding of the long-term behaviour of reinforced concrete structures. However, the strengthening of reinforced concrete structures for durability has to date been mainly undertaken after expert assessment of field data followed by the development of a scheme to both terminate continuing degradation, by separating the structure from the environment, and strengthening the structure. The process does not include any significant consideration of the residual load-bearing capacity of the structure and the highly variable nature of estimates of such remaining capacity. Development of performance curves for deteriorating bridge structures has not been attempted due to the difficulty in developing a model when the input parameters have an extremely large variability. This paper presents a framework developed for an asset management system which assesses residual capacity and identifies the most appropriate rehabilitation method for a given reinforced concrete structure exposed to aggressive environments. In developing the framework, several industry consultation sessions have been conducted to identify input data required, research methodology and output knowledge base. Capturing expert opinion in a useable knowledge base requires development of a rule based formulation, which can subsequently be used to model the reliability of the performance curve of a reinforced concrete structure exposed to a given environment.

Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur

Introduction: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (Nmm−1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived froma single 2D radiographic image. Methods: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. Results: The coefficient of determination (R2%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. Conclusions: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry. Crown Copyright © 2009 Published by Elsevier Ltd on behalf of IPEM. All rights reserved

Load during prosthetic gait : is direct measurement better than inverse dynamics?

The knee forces and moments estimated by inverse dynamics and directly measured by a multiaxial transducer were compared during the gait of a transfemoral amputee. The estimated and directly measured forces and moments were relatively close. However, 3D inverse dynamics estimated only partially the forces and moments associated with the deformation of the prosthetic foot and locking of knee mechanism.

Application of system dynamics for evaluating truck load regulations in Anhui, China

In the critical situation of prevailing overweight transportation and crag-fast enforcement in Chinese highway networks, this paper develops a methodological framework for truck weight regulation (TWR) evaluation using System Dynamics (SD). Composed of five interrelated subsystems, the framework is able to capture the highway, vehicle and freight variables that influence the effect of TWR and transportation efficiency over time. It specifically describes the development and use of the Truck Weight Regulation Evaluating Model (TWREM) for the highway freight system in Anhui province, China. Three policy alternatives are analyzed: 1) tolerant policy approach, which allows heavy-duty freight activity to continue in its current state, and is shown to lead to nearly catastrophic results; 2) rigid policy approach, which would terminate all heavy-duty freight activities immediately, and is shown to be economically infeasible; and 3) moderate policy approach, which advocates a gradual reduction of heavy-duty freight activities to a moderate state. The simulation results shows that the moderate policy approach is the most appropriate option to solve the social and economic problems arising from the activities of the heavy-duty freight transportation in Anhui. In addition, some suggestions of TWR policy in China are also made in this paper.

Adaptive load shedding and regional protection

The requirement for improved efficiency whilst maintaining system security necessitates the development of improved system analysis approaches and the development of advanced emergency control technologies. Load shedding is a type of emergency control that is designed to ensure system stability by curtailing system load to match generation supply. This paper presents a new adaptive load shedding scheme that provides emergency protection against excess frequency decline, whilst minimizing the risk of line overloading. The proposed load shedding scheme uses the local frequency rate information to adapt the load shedding behaviour to suit the size and location of the experienced disturbance. The proposed scheme is tested in simulation on a 3-region, 10-generator sample system and shows good performance.

Assessment of Speech Dialog Systems using Multi-Modal Cognitive Load Analysis and Driving Performance Metrics

In this paper, cognitive load analysis via acoustic- and CAN-Bus-based driver performance metrics is employed to assess two different commercial speech dialog systems (SDS) during in-vehicle use. Several metrics are proposed to measure increases in stress, distraction and cognitive load and we compare these measures with statistical analysis of the speech recognition component of each SDS. It is found that care must be taken when designing an SDS as it may increase cognitive load which can be observed through increased speech response delay (SRD), changes in speech production due to negative emotion towards the SDS, and decreased driving performance on lateral control tasks. From this study, guidelines are presented for designing systems which are to be used in vehicular environments.

Utilizing robustness of positive buck-boost converter against input voltage and load current disturbances

A Positive Buck- Boost (PBB) converter is a known DC-DC converter that can operate in step up and step down modes. Unlike Buck, Boost, and Inverting Buck Boost converters, the inductor current of a PBB can be controlled independently of its voltage conversion ratio. In other words, the inductor of PBB can be utilised as an energy storage unit in addition to its main function of energy transfer. In this paper, the capability of PBB to store energy has been utilised to achieve robustness against input voltage fluctuations and output current changes. The control strategy has been developed to keep accuracy, affordability, and simplicity acceptable. To improve the efficiency of the system a Smart Load Controller (SLC) has been suggested. Applying SLC extra current storage occurs when there is sudden loads change otherwise little extra current is stored.

Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur

Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (N mm− 1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived from a single 2D radiographic image. This ex-vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD.