Dissipativity of discrete-time BAM stochastic neural networks with Markovian switching and impulses

This paper addresses the problem of global exponential dissipativity for a class of uncertain discrete-time BAM stochastic neural networks with time-varying delays, Markovian jumping and impulses. By constructing a proper Lyapunov–Krasovskii functional and combining with linear matrix inequality (LMI) technique, several sufficient conditions are derived for verifying the global exponential dissipativity in the mean square of such stochastic discrete-time BAM neural networks. The derived conditions are established in terms of linear matrix inequalities, which can be easily solved by some available software packages. One important feature presented in our paper is that without employing model transformation and free-weighting matrices our obtained result leads to less conservatism. Additionally, three numerical examples with simulation results are provided to show the effectiveness and usefulness of the obtained result.     

Improving educational outcomes & reducing absenteeism at remote villages with mobile technology and WhatsAPP: Findings from rural India

Reduction of teacher and student absenteeism, together with consistent teacher support and training, are critical factors in improving the quality of education in rural India. As part of an ongoing project involving schools and educational centers in rural areas spread across 21 Indian states, this study investigated how implementation of two simple, accessible technologies could not only reduce absenteeism but also increase teachers’ effectiveness and improve student performance. In addition to students and teachers, key stakeholders included educational coordinators who provided support and monitoring regarding use of WhatsApp and two additional apps designed specifically to support simple educational improvements. In our study we coded and analyzed nine months of messages (n?=?8968), both photographs and texts, posted by 26 participants. The number of text messages related to attendance was strongly positively correlated with frequency of interactions between coordinators and teachers. Our approach resulted in increased teacher and student attendance, as well as improvements in lessons and other planned educational activities. This model functions well in rural settings where there is poor internet connectivity and lack of supporting infrastructure. Remote schools can easily adopt this tablet-based model to reduce teacher absenteeism, improve teaching techniques, improve educational resources, and increase student performance.     

Teacher opinions on performance pay: Evidence from India

The practical viability of performance-based pay programs for teachers depends critically on the extent of support the idea will receive from teachers. We present evidence on teacher opinions with regard to performance-based pay from teacher interviews conducted in the context of an experimental evaluation of a program that provided performance-based bonuses to teachers in the Indian state of Andhra Pradesh. We report four main findings in this paper: (1) over 80% of teachers had a favorable opinion about the idea of linking a component of pay to measures of performance, (2) exposure to an actual incentive program increased teacher support for the idea, (3) teacher support declines with age, experience, training, and base pay, and (4) the extent of teachers’ stated ex ante support for performance-linked pay (over a series of mean-preserving spreads of pay) is positively correlated with their ex post performance as measured by estimates of teacher value addition. This suggests that teachers are aware of their own effectiveness and that implementing a performance-linked pay program could not only have broad-based support among teachers but also attract more effective teachers into the teaching profession.     

Modelling diffusion of a personalized learning framework

A new modelling approach for diffusion of personalized learning as an educational process innovation in social group comprising adopter-teachers is proposed. An empirical analysis regarding the perception of 261 adopter-teachers from 18 schools in India about a particular personalized learning framework has been made. Based on this analysis, teacher training (TT) has been identified as one of the dominant factor which can significantly influence decision by teachers to adopt the educational innovation. Different situations corresponding to fixed and time dependent dynamic carrying capacity of potential adopter-teachers at any time have been developed. New generalized models capturing the growth dynamics of the innovation diffusion process in conjunction with the evolutionary carrying capacity of potential adopters are investigated. The coupled dynamics allows forecasting the likelihood of success or failure of new educational innovation in a given context. Different scenarios for TT are considered based on??constant growth rate model; proportional growth rate model; stratified growth rate model. The proposed modelling framework would be of great interest to education policy makers as it has the potential to predict the likelihood of success or failure of new educational innovation.