Good practice guide in learning and teaching

Once again this publication is produced to celebrate and promote good teaching and learning support and to offer encouragement to those imaginative and innovative staff who continue to wish to challenge students to learn to maximum effect. It is hoped that others will pick up some good ideas from the articles contained in this volume. We have again changed our approach for this 2006/07 edition (our fourth) of the Aston Business School Good Practice Guide. As before, some contributions were selected from those identifying interesting best practice on their Annual Module reflection forms in 2005/2006. Other contributors received HELM (Research Centre in Higher Education Learning and Management) small research grants in 2005/2006. Part of the conditions were for them to write an article for this publication. We have also been less tight on the length of the articles this year. Some contributions are, therefore, on the way to being journal articles. HELM will be working with these authors to help develop these for publication. The themes covered in this year?s articles are all central to the issues faced by those providing HE teaching and learning opportunities in the 21st Century. Specifically this is providing support and feedback to students in large classes, embracing new uses of technology to encourage active learning and addressing cultural issues in a diverse student population. Michael Grojean and Yves Guillaume used Blackboard™ to give a more interactive learning experience and improve feedback to students. It would be easy for other staff to adopt this approach. Patrick Tissington and Qin Zhou (HELM small research grant holders) were keen to improve the efficiency of student support, as does Roger McDermott. Celine Chew shares her action learning project, completed as part of the Aston University PG Certificate in Teaching and Learning. Her use of Blackboard™ puts emphasis on the learner having to do something to help them meet the learning outcomes. This is what learning should be like, but many of our students seem used to a more passive learning experience, so much needs to be done on changing expectations and cultures about learning. Regina Herzfeldt also looks at cultures. She was awarded a HELM small research grant and carried out some significant new research on cultural diversity in ABS and what it means for developing teaching methods. Her results fit in with what many of us are experiencing in practice. Gina leaves us with some challenges for the future. Her paper certainly needs to be published. This volume finishes with Stuart Cooper and Matt Davies reflecting on how to keep students busy in lectures and Pavel Albores working with students on podcasting. Pavel?s work, which was the result of another HELM small research grant, will also be prepared for publication as a journal article. The students learnt more from this work that any formal lecture and Pavel will be using the approach again this year. Some staff have been awarded HELM small research grants in 2006/07 and these will be published in the next Good Practice Guide. In the second volume we mentioned the launch of the School?s Research Centre in Higher Education Learning and Management (HELM). Since then HELM has stimulated a lot of activity across the School (and University) particularly linking research and teaching. A list of the HELM seminars for 2006/2007 is listed as Appendix 1 of this publication. Further details can be obtained from Catherine Foster (c.s.foster@aston.ac.uk), who coordinates the HELM seminars. For 2006 and 2005 HELM listed, 20 refereed journal articles, 7 book chapters, 1 published conference papers, 20 conference presentations, two official reports, nine working papers and £71,535 of grant money produced in this research area across the School. I hope that this shows that reflection on learning is alive and well in ABS. We have also been working on a list of target journals to guide ABS staff who wish to publish in this area. These are included as Appendix 2 of this publication. May I thank the contributors for taking time out of their busy schedules to write the articles and to Julie Green, the Quality Manager, for putting the varying diverse approaches into a coherent and publishable form and for agreeing to fund the printing of this volume.

Good practice guide in learning and teaching

Once again this publication is produced to celebrate and promote good teaching and learning support and to offer encouragement to those imaginative and innovative staff who continue to wish to challenge students to learn to maximum effect. It is hoped that others will pick up some good ideas from the articles contained in this volume. We had changed our editorial approach in drawing together the articles for this 2005/6 edition (our third) of the ABS Good Practice Guide. Firstly we have expanded our contributors beyond ABS academics. This year?s articles have also been written by staff from other areas of the University, a PhD student, a post-doctoral researcher and staff working in learning support. We see this as an acknowledgement that the learning environment involves a range of people in the process of student support. We have also expanded the maximum length of the articles from two to five pages, in order to allow greater reflection on the issues. The themes of the papers cluster around issues relating to diversity (widening participation and internationalisation of the student body), imaginative use of new technology (electronic reading on BlackboardTM ) and reflective practitioners, (reflection on rigour and relevance; on how best to train students in research ethics, relevance in the curriculum and the creativity of the teaching process) Discussion of efforts to train the HE teachers of the future looks forward to the next academic year when the Higher Education Academy?s professional standards will be introduced across the sector. In the last volume we mentioned the launch of the School?s Research Centre in Higher Education Learning and Management (HELM). Since then HELM has stimulated a lot of activity across the School (and University) particularly linking research and teaching. A list of the HELM seminars is listed as an appendix to this publication. Further details can be obtained from Catherine Foster (c.s.foster@aston.ac.uk) who coordinates the HELM seminars. HELM has also won its first independent grant from the EU Leonardo programme to look at the effect of business education on employment. In its annual report to the ABS Research Committee HELM listed for 2004 and 2005, 11 refereed journal articles, 4 book chapters, 3 published conference papers, 18 conference papers, one official reports and £72,500 of grant money produced in this research area across the School. I hope that this shows that reflection on learning is live and well in ABS. May I thank the contributors for taking time out of their busy schedules to write the articles and to Julie Green, the Quality Manager, for putting our diverse approaches into a coherent and publishable form.

Contrast matching and discrimation in human vision

The aim of this work was to investigate human contrast perception at various contrast levels ranging from detection threshold to suprathreshold levels by using psychophysical techniques. The work consists of two major parts. The first part deals with contrast matching, and the second part deals with contrast discrimination. Contrast matching technique was used to determine when the perceived contrasts of different stimuli were equal. The effects of spatial frequency, stimulus area, image complexity and chromatic contrast on contrast detection thresholds and matches were studied. These factors influenced detection thresholds and perceived contrast at low contrast levels. However, at suprathreshold contrast levels perceived contrast became directly proportional to the physical contrast of the stimulus and almost independent of factors affecting detection thresholds. Contrast discrimination was studied by measuring contrast increment thresholds which indicate the smallest detectable contrast difference. The effects of stimulus area, external spatial image noise and retinal illuminance were studied. The above factors affected contrast detection thresholds and increment thresholds measured at low contrast levels. At high contrast levels, contrast increment thresholds became very similar so that the effect of these factors decreased. Human contrast perception was modelled by regarding the visual system as a simple image processing system. A visual signal is first low-pass filtered by the ocular optics. This is followed by spatial high-pass filtering by the neural visual pathways, and addition of internal neural noise. Detection is mediated by a local matched filter which is a weighted replica of the stimulus whose sampling efficiency decreases with increasing stimulus area and complexity. According to the model, the signals to be compared in a contrast matching task are first transferred through the early image processing stages mentioned above. Then they are filtered by a restoring transfer function which compensates for the low-level filtering and limited spatial integration at high contrast levels. Perceived contrasts of the stimuli are equal when the restored responses to the stimuli are equal. According to the model, the signals to be discriminated in a contrast discrimination task first go through the early image processing stages, after which signal dependent noise is added to the matched filter responses. The decision made by the human brain is based on the comparison between the responses of the matched filters to the stimuli, and the accuracy of the decision is limited by pre- and post-filter noises. The model for human contrast perception could accurately describe the results of contrast matching and discrimination in various conditions.

"No one said girls could do engineering":a fresh look at an old problem

Previous work has drawn attention to what, in many respects, appears to be an insurmountable problem, the lack of women and girls in engineering. The debate about why young women are not attracted to engineering mostly focuses around issues of gender, with the profession stereotypically perceived as being more suitable for men. In seeking to investigate why this should be the case a participatory research approach was adopted in which two 17 year old female High School students were employed to interview their peers about their perceptions of engineering as a career. This paper presents some of the emergent findings of this research. In total twenty teenage girls from two city centre Schools were interviewed. The two teenage researchers developed the questions themselves, focusing on issues they identified as being important factors informing girls’ views of engineering. This approach provided a ‘new’ perspective – looking at the topic through the eyes of the target sample group. By drawing attention to some of the issues around gender and engineering, this paper contributes to current debates in this area – in doing so it provides a fresh look at an old problem and offers some workable solutions for ‘how to get more girls into engineering’.

Breaking down barriers:teenage girls’ perceptions of engineering as a study and career choice

Background: Stereotypically perceived to be an ‘all male’ occupation, engineering has for many years failed to attract high numbers of young women [1,2]. The reasons for this are varied, but tend to focus on misconceptions of the profession as being more suitable for men. In seeking to investigate this issue a participatory research approach was adopted [3] in which two 17 year-old female high school students interviewed twenty high school girls. Questions focused on the girls’ perceptions of engineering as a study and career choice. The findings were recorded and analysed using qualitative techniques. The study identified three distinctive ‘influences’ as being pivotal to girls’ perceptions of engineering; pedagogical; social; and, familial. Pedagogical Influences: Pedagogical influences tended to focus on science and maths. In discussing science, the majority of the girls identified biology and chemistry as more ‘realistic’ whilst physics was perceived to more suitable for boys. The personality of the teacher, and how a particular subject is taught, proved to be important influences shaping opinions. Social Influences: Societal influences were reflected in the girls’ career choice with the majority considering medical or social science related careers. Although all of the girls believed engineering to be ‘male dominated’, none believed that a woman should not be engineer. Familial Influences: Parental influence was identified as key to career and study choice; only two of the girls had discussed engineering with their parents of which only one was being actively encouraged to pursue a career in engineering. Discussion: The study found that one of the most significant barriers to engineering is a lack of awareness. Engineering did not register in the girls’ lives, it was not taught in school, and only one had met a female engineer. Building on the study findings, the discussion considers how engineering could be made more attractive to young women. Whilst misconceptions about what an engineer is need to be addressed, other more fundamental pedagogical barriers, such as the need to make physics more attractive to girls and the need to develop the curriculum so as to meet the learning needs of 21st Century students are discussed. By drawing attention to the issues around gender and the barriers to engineering, this paper contributes to current debates in this area – in doing so it provides food for thought about policy and practice in engineering and engineering education.

Breakfast skipping is associated with cyberbullying and school bullying victimization:a school-based cross-sectional study

Breakfast skipping is a health concern that has well-known negative consequences physically and psychologically. It is therefore important to understand why children skip breakfast. The purpose of this study was to establish whether the experience of bullying and cyberbullying impacts upon breakfast skipping and to further evaluate whether the inability for youths to cope with bullying victimization affects their mental health (depression), and in turn predicts breakfast skipping. Data were obtained from the Eastern Ontario 2011 Youth Risk Behaviour Survey, a cross-sectional regional school-based survey of middle and high school students (11-20 years old) across the five counties of Eastern Ontario, Canada (N = 3035). Self-reported data about children's experiences of bullying victimization, breakfast eating habits, socio-economical status, depression, and other risk behaviours were analysed. Approximately half of the participants (50.4%) reported not eating breakfast on a regular basis: 26.3% and 24.1% reported often (usually eat breakfast three times or more per week) and frequent (usually eat breakfast twice a week or less) breakfast skipping behaviour, respectively. Victims of both cyberbullying and school bullying presented greater likelihood of often (adjusted relative risk ratio (RR) = 1.55; 95% confidence interval (CI) = 1.17-2.06) and frequent (RR = 1.97; 95% CI = 1.28-3.03) breakfast skipping. Mediation analysis further showed that depression fully mediated the relationship between school bullying victimization and frequent breakfast skipping. Moreover, depression partially mediated the associations between both cyberbullying and school bullying with frequent breakfast skipping. These findings highlight the potential interrelationships between cyberbullying, school bullying and depression in predicting unhealthy breakfast skipping behaviour in children. © 2014 Elsevier Ltd.

What do schoolgirls think of engineering? A critique of conversations from a participatory research approach

Whilst statistics vary, putting the percentage of women engineers at between 6%[1] and 9% [2] of the UK Engineering workforce, what cannot be disputed is that there is a need to attract more young women into the profession. Building on previous work which examined why engineering continues to fail to attract high numbers of young women[3,4] and starting with the research question "What do High School girls think of engineering as a future career and study choice?", this paper critiques research conducted utilising a participatory approach[5] in which twenty semi-structured in depth interviews were conducted by two teenage researchers with High School girls from two different schools in the West Midlands area of the UK. In looking at the issues through the eyes of 16 and 17 year old girls, the study provides a unique insight into why girls are not attracted to engineering. © American Society for Engineering Education, 2014.

A Bayesian neural network algorithm identifies patients in whom post-EVAR surveillance may be unnecessary

Lifelong surveillance is not cost-effective after endovascular aneurysm repair (EVAR), but is required to detect aortic complications which are fatal if untreated (type 1/3 endoleak, sac expansion, device migration). Aneurysm morphology determines the probability of aortic complications and therefore the need for surveillance, but existing analyses have proven incapable of identifying patients at sufficiently low risk to justify abandoning surveillance. This study aimed to improve the prediction of aortic complications, through the application of machine-learning techniques. Patients undergoing EVAR at 2 centres were studied from 2004–2010. Aneurysm morphology had previously been studied to derive the SGVI Score for predicting aortic complications. Bayesian Neural Networks were designed using the same data, to dichotomise patients into groups at low- or high-risk of aortic complications. Network training was performed only on patients treated at centre 1. External validation was performed by assessing network performance independently of network training, on patients treated at centre 2. Discrimination was assessed by Kaplan-Meier analysis to compare aortic complications in predicted low-risk versus predicted high-risk patients. 761 patients aged 75 +/− 7 years underwent EVAR in 2 centres. Mean follow-up was 36+/− 20 months. Neural networks were created incorporating neck angu- lation/length/diameter/volume; AAA diameter/area/volume/length/tortuosity; and common iliac tortuosity/diameter. A 19-feature network predicted aor- tic complications with excellent discrimination and external validation (5-year freedom from aortic complications in predicted low-risk vs predicted high-risk patients: 97.9% vs. 63%; p < 0.0001). A Bayesian Neural-Network algorithm can identify patients in whom it may be safe to abandon surveillance after EVAR. This proposal requires prospective study.