Infusing instructional design principles into an active student-centred social learning framework

Social and participatory media offer a plethora of ways for students to communicate, collaborate, and learn in schools. Using a social learning approach, Casey (2013a) investigated ways that social media could be integrated into Australian public high school classrooms to enhance student learning. In the process, she developed a social learning framework as discussed in Casey (2013b). Similarly, Davidson-Shivers and Hulon (2013; Hulon & Daidson-Shivers, 2013) suggest ways to employ ID principles to prepare college instructors and pre-service teachers to integrate technology into classrooms. Prior to that, Davidson-Shivers with Rasmussen (2006) developed an instructional design (ID) model for creating effective Web-based learning environments. Through collaboration, Casey and Davidson-Shivers consider a wide range of social learning and instructional design principles and approaches to help develop frameworks for new media integration that can work within varying levels of education.

Greater cognitive effort for better learning : tailoring an instructional design for learners with different levels of knowledge and motivation

The capacity limitation of working memory is a widely recognised determinant of human learning. A cognitive load exceeding the capacity hampers learning. Cognitive load can be controlled by tailoring an instructional design to levels of learner prior knowledge. However, such as design does not necessarily motivate to use the available capacity for better learning. The present review examines literatures on the effects of instructional design, motivation, emotional state, and expertise level on cognitive load and cognitive effort, which ultimately affect working memory performance and learning. This examination suggests further studies on the effects of motivation and negative emotional states on the use of working memory. Prospective findings would help better explain and predict individual differences in the use of working memory for cognitive learning and task performance.

Full-order observer design for nonlinear complex large-scale systems with unknown time-varying delayed interactions

This article is concerned with the problem of state observer for complex large-scale systems with unknown time-varying delayed interactions. The class of large-scale interconnected systems under consideration is subjected to interval time-varying delays and nonlinear perturbations. By introducing a set of argumented Lyapunov–Krasovskii functionals and using a new bounding estimation technique, novel delay-dependent conditions for existence of state observers with guaranteed exponential stability are derived in terms of linear matrix inequalities (LMIs). In our design approach, the set of full-order Luenberger-type state observers are systematically derived via the use of an efficient LMI-based algorithm. Numerical examples are given to illustrate the effectiveness of the result

Robust nonlinear controller design for three-phase grid-connected photovoltaic systems under structured uncertainties

This paper presents a robust nonlinear controller design for a three-phase grid-connected photovoltaic (PV) system to control the current injected into the grid and the dc-link voltage for extracting maximum power from PV units. The controller is designed based on the partial feedback linearization approach, and the robustness of the proposed control scheme is ensured by considering structured uncertainties within the PV system model. An approach for modeling the uncertainties through the satisfaction of matching conditions is provided. The superiority of the proposed robust controller is demonstrated on a test system through simulation results under different system contingencies along with changes in atmospheric conditions. From the simulation results, it is evident that the robust controller provides excellent performance under various operating conditions. © 2014 IEEE.

Optimal design of traffic signal controller using neural networks and fuzzy logic systems

This paper aims at optimally adjusting a set of green times for traffic lights in a single intersection with the purpose of minimizing travel delay time and traffic congestion. Neural network (NN) and fuzzy logic system (FLS) are two methods applied to develop intelligent traffic timing controller. For this purpose, an intersection is considered and simulated as an intelligent agent that learns how to set green times in each cycle based on the traffic information. The training approach and data for both these learning methods are similar. Both methods use genetic algorithm to tune their parameters during learning. Finally, The performance of the two intelligent learning methods is compared with the performance of simple fixed-time method. Simulation results indicate that both intelligent methods significantly reduce the total delay in the network compared to the fixed-time method.

Management control systems and organisational learning: the effects of design and use

Purpose – The purpose of this paper is to present a study on relationships between the design of management control systems (MCS), the use of MCS and organisational learning (OL). Design/methodology/approach – This study adopted a survey method. A written questionnaire was prepared and mailed out to collect quantitative data. After analysis of the empirical results, follow-up interviews were conducted to develop a deeper understanding of the empirical results. Findings – Findings of the study show that both the design and use of MCS are significantly associated with levels of OL activities in organisations, and the use of MCS is found to be a more influential factor in OL. Originality/value – This paper contributes to the accounting literature by providing empirical evidence on the relative impacts of the design and use of MCS on OL activities in organisations and the interaction between the design and use of MCS in influencing OL.

A new algorithm to design minimal multi-functional observers for linear systems

Designing minimum possible order (minimal) observers for Multi-Input Multi-Output (MIMO) linear systems have always been an interesting subject. In this paper, a new methodology to design minimal multi-functional observers for Linear Time-Invariant (LTI) systems is proposed. The approach is applicable, and it also helps in regulating the convergence rate of the observed functions. It is assumed that the system is functional observable or functional detectable, which is less conservative than assuming the observability or detectability of the system. To satisfy the minimality of the observer, a recursive algorithm is provided that increases the order of the observer by appending the minimum required auxiliary functions to the desired functions that are going to be estimated. The algorithm increases the number of functions such that the necessary and sufficient conditions for the existence of a functional observer are satisfied. Moreover, a new methodology to solve the observer design interconnected equations is elaborated. Our new algorithm has advantages with regard to the other available methods in designing minimal order functional observers. Specifically, it is compared with the most common schemes, which are transformation based. Using numerical examples it is shown that under special circumstances, the conventional methods have some drawbacks. The problem partly lies in the lack of sufficient numerical degrees of freedom proposed by the conventional methods. It is shown that our proposed algorithm can resolve this issue. A recursive algorithm is also proposed to summarize the observer design procedure. Several numerical examples and simulation results illustrate the efficacy, superiority and different aspects of the theoretical findings.

New H∞ control design for polytopic systems with mixed time-varying delays in state and input

This paper concerns with the problem of state-feedback H∞ control design for a class of linear systems with polytopic uncertainties and mixed time-varying delays in state and input. Our approach can be described as follows. We first construct a state-feedback controller based on the idea of parameter-dependent controller design. By constructing a new parameter-dependent Lyapunov-Krasovskii functional (LKF), we then derive new delay-dependent conditions in terms of linear matrix inequalities ensuring the exponential stability of the corresponding closed-loop system with a H∞ disturbance attenuation level. The effectiveness and applicability of the obtained results are demonstrated by practical examples.

Design of state observers for interconnected time-delay systems via a coordinate transformation approach

This paper considers the design of state observers for interconnected time-delay systems using a coordinate transformation method. Through such a transformation, the system that has interconnection and state delays is metamorphosed into a new system that injects time-delay information into its input and output terms, before reintroducing them back into the latter system, effectively coupling the delay terms into the IO injection terms and eliminating the delay values from the state variables. Next, full-order and reduced-order observers are designed based on the transformed system. Finally, the observed states of the transformed system that correspond to the original system is used to deduce the estimates of the original system. A numerical example is provided of an interconnected time-delay system.

Considering the chemical energy requirements of the tri-n-propylamine co-reactant pathways for the judicious design of new electrogenerated chemiluminescence detection systems

The introduction of a 'co-reactant' was a critical step in the evolution of electrogenerated chemiluminescence (ECL) from a laboratory curiosity to a widely utilised detection system. In conjunction with a suitable electrochemiluminophore, the co-reactant enables generation of both the oxidised and reduced precursors to the emitting species at a single electrode potential, under the aqueous conditions required for most analytical applications. The most commonly used co-reactant is tri-n-propylamine (TPrA), which was developed for the classic tris(2,2'-bipyridine)ruthenium(ii) ECL reagent. New electrochemiluminophores such as cyclometalated iridium(iii) complexes are also evaluated with this co-reactant. However, attaining the excited states in these systems can require much greater energy than that of tris(2,2'-bipyridine)ruthenium(ii), which has implications for the co-reactant reaction pathways. In this tutorial review, we describe a simple graphical approach to characterise the energetically feasible ECL pathways with TPrA, as a useful tool for the development of new ECL detection systems.