1st INCF Workshop on Needs for Training in Neuroinformatics

The INCF workshop on Needs for Training in Neuroinformatics was organized by the INCF National Node of the UK. The scope of the workshop was to provide as overview of the current state of neuroinformatics training and recommendations for future provision of training. The report presents a summary of the workshop discussions and recommendations to the INCF

Novel Statistical Analysis in the Context of a Comprehensive Needs Assessment for Secondary STEM Recruitment

There is a myriad of career opportunities stemming from science, technology, engineering, and mathematics (STEM) disciplines. In addition to careers in corporate settings, teaching is a viable career option for individuals pursuing degrees in STEM disciplines. With national shortages of secondary STEM teachers, efforts to recruit, train, and retain quality STEM teachers is greatly important. Prior to exploring ways to attract potential STEM teacher candidates to pursue teacher training programs, it is important to understand the perceived value that potential recruits place on STEM careers, disciplines, and the teaching profession. The purpose of this study was to explore students’ perceptions of the usefulness of STEM disciplines and their value in supporting students’ careers. A novel statistical method was utilized, combining exploratory-factor analysis, the analysis of variance, generalized estimating equation evaluations under the framework of a generalized linear model, and quantile regression. Using the outputs from each statistical measure, students’ valuation of each STEM discipline and their interest in pursuing teaching as a career option were assessed. Our results indicate a high correlation of liking and perceived usability of the STE disciplines relative to careers. Conversely, our results also display a low correlation of the liking and perceived usability of mathematics relative to future careers. The significance of these diametrically related results suggests the need for promotion of the interrelatedness of mathematics and STE

Integrating Data Science into a General Education Information Technology Course: An Approach to Developing Data Savvy Undergraduates

The National Academies recommend academic institutions foster a basic understanding of data science in all undergraduates. However, data science education is not currently a graduation requirement at most colleges and universities. As a result, many graduates lack even basic knowledge of data science. To address the shortfall, academic institutions should incorporate introductory data science into general education courses. A general education IT course provides a unique opportunity to integrate data science education. Modules covering databases, spreadsheets, and presentation software, already present in many survey IT courses, teach concepts and skills needed for data science. As a result, a survey IT course can provide comprehensive introductory data science education by adding a data science module focused on modeling and evaluation, two key steps in the data science process. The module should use data science software for application, avoiding the complexities of programming and advanced math, while enabling an emphasis on conceptual understanding. We implemented a course built around these ideas and found that the course helps develop data savvy in students

Mathematics learning support and dyslexia

This research identifies, through an extensive series of exploratory and explanatory case studies, the mathematical difficulties that might be encountered by dyslexic engineering students. It details support mechanisms that may be put in place to help these students reach their full potential and makes suggestions for the introduction of measures at institutional level to ensure compliance with current legislation. This is an area, identified from the literature search, that has not, until now, been the focus of any substantial research activity and thus the findings form an original and significant contribution to knowledge in this field. The findings are not only intrinsically interesting but will also be of use to practitioners of mathematics, support staff, staff developers and policy makers in higher education. A literature review gives historical background on the development of education in general, and mathematics in particular, in the UK. The main theories and problems associated with developmental dyslexia are also given. Surveys were undertaken to determine the extent of mathematics learning support in UK universities and also to determine the extent of the provision of mathematics support to dyslexic students. Using case study research and by providing one-to-one mathematics support, the difficulties encountered by dyslexic students were investigated. Related work is an exploratory study into the use of different media combinations in Computer Assisted Assessment. Additionally, an in-depth case study of the Mathematics Learning Support Centre at Loughborough University has been undertaken and is reported in detail with recommendations for changes suggested. The results of this research show that mathematics learning support is widespread and often essential to bridge the gap between school mathematics and university level mathematics but specialist mathematical support for dyslexic students is rarely available. It is determined that dyslexic students can be impeded in their learning and understanding of mathematics as a direct result of their dyslexia. Recommendations for further study in some areas and future lines of inquiry in others are suggested