Questionnaire design: some tips on generating meaningful data

At the November 2011 meeting of our Bioscience Pedagogic Research group, attention was focused on Questionnaire Design. Emma Angell, from the University’s SAPPHIRE group (Social science APPlied to Healthcare Improvement REsearch) shared some tips she had picked up during a two-day course which she had attended in May 2011. The course took place at the London School of Economics and was led by Jon Krosnick of Stanford University, and Emma was keen to stress that credit for the insights was his not hers!

As the website advertising the original course points out: “Surveys and questionnaires are a common way of gathering data in the social sciences. The structuring, wording and ordering of questions has traditionally been viewed as an art, not a science, best guided by intuition. But in recent years, it has become clear that this is an antiquated and even dangerous view that does not reflect the accumulation of knowledge throughout the social sciences about effective question-asking. Intuition often leads us astray in the questionnaire design field, as becomes clear when putting intuitions to the test via scientific evaluation. A large body of relevant scientific studies has now accumulated, and when taken together, the findings point to a series of formal rules for how best to design questions.”

Emma talked us through a number of potential problems with questionnaires that can undermine the legitimacy of the data they generate. In gathering questionnaire-based data, we hope that the person surveyed is able to interpret the meaning of the question, searches for the most appropriate pre-set response (or offers a thorough and accurate open text response) and in so doing gives a true reflection of their views and/or experiences.  To do so will require them to search thoroughly for an appropriate memory and to convert that information into an  answer that correlates with the question asked. If they are doing this, then they are “optimising”.

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Effective Learning in the Life Sciences

The book was edited by David Adams, Director of the UK Centre of Biosciences until September 2011

Today I have received my copy of Effective Learning in the Life Sciences: how students can achieve their full potential. As the subtitle implies, the book is targeted first and foremost at students wanting to make the most of their time at university, and at academics helping them to reach that goal.

1. Creativity (David Adams and Kevin Byron)

2. Problem solving: developing critical, evaluative, and analytical thinking skills (Tina Overton)

3. In the laboratory (Pauline Millican and David Adams)

4. Fieldwork (Julie Peacock, Julian Park and Alice Mauchline)

5. In vivo work (David Lewis)

6. Research projects (Martin Luck)

7. Maths and stats for biologists (Dawn Hawkins)

8. E-learning for biologists (Jo Badge, Jon Scott and Terry McAndrew)

9. Bioethics (Chris Willmott)

10. Assessment, feedback and review (Steve Maw and Paul Orsmond)

11. Communication in the biosciences (Joanna Verran and Maureen Dawson)

12. Bioenterprise (Lee Beniston, David Adams and Carol Wakeford)