Good practice guide in learning and teaching

This is the second edition of our Aston Business School (ABS) Good Practice Guide and the enthusiasm of the contributors appears undiminished. I am again reminded that I work with a group of very committed, dedicated and professional colleagues. Once again this publication is produced to celebrate and promote good teaching across the School 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. Contributors to this Guide were not chosen because they are the best teachers in the School, although they are undoubtedly all amongst my colleagues who are exponents of enthusiastic and inspiring approaches to learning. The Quality Unit approached these individuals because they declared on their Annual Module Reflection Forms that they were doing something interesting and worthwhile which they thought others might find useful. Amongst those reading the Guide I am sure that there are many other individuals who are trying to operate similar examples of good practice in their teaching, learning and assessment methods. I hope that this publication will provoke these people into providing comments and articles of their own and that these will form the basis of next year’s Guide. It may also provoke some people to try these methods in their own teaching. The themes of the articles this year can be divided into two groups. The first theme is the quest to help students to help themselves to learn via student-run tutorials, surprise tests and mock examinations linked with individual tutorials. The second theme is making learning come to life in exciting practical ways by, for example, hands-on workshops and simulations, story telling, rhetorical questioning and discussion groups. A common theme is one of enthusiasm, reflection and commitment on behalf of the lecturers concerned. None of the approaches discussed in this publication are low effort activities on the part of the facilitator, but this effort is regarded as worthwhile as a means of creating greater student engagement. As Biggs (2003)[1] says, in his similarly inspiring way, students learn more the less passive they are in their learning. (Ref). The articles in this publication bear witness of this and much more. Since last year Aston Business School has launched its Research Centre in Higher Education Learning and Management (HELM) which is another initiative to promote excellent learning and teaching. Even before this institution has become fully operational, at least one of the articles in this publication has seen the light of day in the research arena and at least two others are ripe for dissemination to a wider audience via journal publication. More news of our successes in this activity will appear in next year’s edition. May I thank the contributors for taking time out of their busy schedules to write the articles this summer, and to Julie Green who runs the ABS Quality Unit, for putting our diverse approaches into a coherent and publishable form and for chasing us when we have needed it! I would also like to thank Ann Morton and her colleagues in the Centre for Staff Development who have supported this publication. During the last year the Centre has further stimulated the learning and teaching life of the School (and the wider University) via their Learning and Teaching Week and sponsorship of Teaching Quality Enhancement Fund (TQEF) projects. Pedagogic excellence is in better health at Aston than ever before – long may this be because this is what life in HE should be about.

How good are citizen weather stations? Addressing a biased opinion

The UK is home to a dense network of Citizen Weather Stations (CWS) primarily set up by members of the public. The majority of these stations record air temperature, relative humidity and precipitation, amongst other variables, at sub-hourly intervals. This high resolution network could have benefits in many applications, but only if the data quality is well characterised. Here we present results from an intercomparison field study, in which popular CWS models were tested against Met Office standard equipment. The study identifies some common instrumental biases and their dependencies, which will help us to quantify and correct such biases from the CWS network.