Social class and education: the relationship between social class and engagement with education.

This study explores the relationship between social class and engagement with education. A qualitative approach was used in the investigation. Four participants narrated their stories of their journey through the education system. Three participants were at Bachelor of Arts level in a community education centre and one at Masters Degree level in an Institute of Technology. A focus group, comprising women from an English/Literacy class in a community education centre was conducted using the following themes which emerged as significant in the narratives: • Social and cultural norms • Conditions in the classroom (a) the State (b) the teacher • Parental support • Community education The four narratives and a summary of the findings from the focus group is also given. They are then analysed under the themes already mentioned. The findings demonstrate that although there is a strong relationship between social class and engagement with education, the other four factors are quite significant. In order to ensure a more equitable education system, the State must take responsibility for the legislation which impacts on education. It is also responsible for the provision of remedial services and these should be available to all children who need them. Teachers must be aware of the importance of their role in providing a classroom environment which is conducive to learning. The study emphasised the importance of parental support in children’s education and the need for the government to support parents in their efforts to do this by the provision of parenting courses and other services which would benefit families in this regard. All the participants were unanimous in their praise of community education and how it had impacted positively on their lives. It is imperative therefore that the government reconsiders its decisions to reduce funding for worthwhile services such as family support projects and community education

Digital footprints: Creation, implication, and higher education

Twenty-first century higher education instructors are continually tasked to review, align, pilot, adopt, infuse, and evaluate new technology tools and resources into curricula rich with standards regardless of course format (online/distance, hybrid, and face-to-face courses). Demands often overwhelm instructors who cannot assume that all students approach technology with the same levels of expertise increases constantly with new multimedia developments. Before courses begin, instructors should pilot these tools and applications to determine accessibility, types of support students may need, as well as determine what types of digital footprints students will leave behind. Digital footprints are unique data trails Internet users leave behind intentionally or unintentionally. Communicating expertise regarding digital footprints is imperative; information shared via the Internet (even when deleted) is never retractable - thus creating implications for students enrolled in school as well as graduates searching for employment

Social class and education: the relationship between social class and engagement with education.

This study explores the relationship between social class and engagement with education. A qualitative approach was used in the investigation. Four participants narrated their stories of their journey through the education system. Three participants were at Bachelor of Arts level in a community education centre and one at Masters Degree level in an Institute of Technology. A focus group, comprising women from an English/Literacy class in a community education centre was conducted using the following themes which emerged as significant in the narratives: • Social and cultural norms • Conditions in the classroom (a) the State (b) the teacher • Parental support • Community education The four narratives and a summary of the findings from the focus group is also given. They are then analysed under the themes already mentioned. The findings demonstrate that although there is a strong relationship between social class and engagement with education, the other four factors are quite significant. In order to ensure a more equitable education system, the State must take responsibility for the legislation which impacts on education. It is also responsible for the provision of remedial services and these should be available to all children who need them. Teachers must be aware of the importance of their role in providing a classroom environment which is conducive to learning. The study emphasised the importance of parental support in children’s education and the need for the government to support parents in their efforts to do this by the provision of parenting courses and other services which would benefit families in this regard. All the participants were unanimous in their praise of community education and how it had impacted positively on their lives. It is imperative therefore that the government reconsiders its decisions to reduce funding for worthwhile services such as family support projects and community education

A Fuzzy/Neural Approach to Cost Prediction with Small Data Sets

The project objective in this work is to create an accurate cost estimate for NASA engine tests at the John C. Stennis Space Center testing facilities using various combinations of fuzzy and neural systems. The data set available for this cost prediction problem consists of variables such as test duration, thrust, and many other similar quantities, unfortunately it is small and incomplete. The first method implemented to perform this cost estimate uses the locally linear embedding (LLE) algorithm for a nonlinear reduction method that is then put through an adaptive network based fuzzy inference system (ANFIS). The second method is a two stage system that uses various ANFIS with either single or multiple inputs for a cost estimate whose outputs are then put through a backpropagation trained neural network for the final cost prediction. Finally, method 3 uses a radial basis function network (RBFN) to predict the engine test cost

A Fuzzy/Neural Approach to Cost Prediction with Small Data Sets

The project objective in this work is to create an accurate cost estimate for NASA engine tests at the John C. Stennis Space Center testing facilities using various combinations of fuzzy and neural systems. The data set available for this cost prediction problem consists of variables such as test duration, thrust, and many other similar quantities, unfortunately it is small and incomplete. The first method implemented to perform this cost estimate uses the locally linear embedding (LLE) algorithm for a nonlinear reduction method that is then put through an adaptive network based fuzzy inference system (ANFIS). The second method is a two stage system that uses various ANFIS with either single or multiple inputs for a cost estimate whose outputs are then put through a backpropagation trained neural network for the final cost prediction. Finally, method 3 uses a radial basis function network (RBFN) to predict the engine test cost

Visual Interest Prediction with Attentive Multi-Task Transfer Learning

Visual interest & affect prediction is a very interesting area of research in the area of computer vision. In this paper, we propose a transfer learning and attention mechanism based neural network model to predict visual interest & affective dimensions in digital photos. Learning the multi-dimensional affects is addressed through a multi-task learning framework. With various experiments we show the effectiveness of the proposed approach. Evaluation of our model on the benchmark dataset shows large improvement over current state-of-the-art systems

Developing and Implementing an Online Course Framework

Integration of technology tools and resources is imperative when working with today’s students as many are expecting to encounter various apps and media-based software in the curriculum. It is important, however, to have a clear purpose for integrating technology into the classroom; technology should not be integrated into the curriculum simply for the sake of doing so! To assist with purposeful integration, faculty members from Nova Southeastern University and St. Thomas University created a Technology Integration Learning Community (TILC); an online professional learning community where members teach each other about the latest and greatest technological tools and share ideas for integration into the curriculum. Anytime an instructor is thinking of integrating technology into a classroom, it is important to use a model or framework as a guide to enhance the objectives or outcomes as well as ensure accessibility for all students. Therefore, the TILC developed The TILC Online Course Framework (TOCF), based on the ASSURE model (Smaldino, Lowther, Russell, & Mims, 2016), to guide this technology integration

The strategic economic governance of Greater Manchester's local labour market by the local state: implications for young workers

This article explores how work and employment conditions for young workers are affected by the actions of the state at the spatial scale of the locality. The article argues that young workers have experienced deteriorating labour market conditions following shifts in the form which capitalist accumulation takes in the UK. This shift has altered the composition of the national state which has in turn led to changes in how it regulates both local labour markets and the economic strategies of the local state. One result of these changes is the diffusion of neoliberal labour market reforms which have led to negative material consequences for young workers; these are manifest in the expansion of low-waged work concentrated in a small number of sectors, and characterized by an intensified labour process