Missing the mark: A view of research skills available in recent graduates in the region Ric Coe Head, Research Support Unit,

2 x 2 2 ways we see graduates: –as young employees –as postgraduate students attached for thesis work 2 sources of information: –informal survey of senior scientists Question: what are the key improvements you would like to see in the way universities prepare students for research? –15 years experience

Overall… Much diversity between universities, faculties and individuals BUT also clear consensus on some common areas for improvement Universities in other regions maybe do no better, and change is not easy BUT that is no reason not to try

The research process observe reflect generalise plan

O Need practical skills –Lab –field –particularly in social sciences (survey ≠ questionaire+sample!) Get used to data handling –structuring –entry –checking

O  R Data analysis: make it real –can not tune to specific problem –looking for recipes rather than principles –“Lost in data” –Confidence to explore Narrow software skills –expect to be taught not learn –data analytical topics (eg statistics, econometrics, GIS) still taught without computers –no institutional commitment despite heroic individual efforts

R Learning from data analysis –What do results tell you of the problem? –Insights into processes? Making conclusions which are conclusions –based on evidence –not unsupported general statements

R  G

G Familiarity with key current literature Make the connection between theory learnt and data collected Notice contradictions between new evidence and current theory Challenging current positions Suggest reasons and update understanding Writing and publishing –all aspects of science writing –content, logic, structure, style, rules and ethics –not supported by university staff

G  P Learn to use ‘systems thinking’ – using current theory and understand to map out a complex problem and identify research routes Ability to formulate ‘useful’ hypotheses –non-obvious –based on G (not alchemy) –advance the problem solving –distinction between the scientific hypotheses and the uninteresting null hypotheses of statistical analysis.

P Understand the logic of an investigation Use appropriate rather than ‘recipe’ methods eg: –what is compared? –what are the units? –what is measured? –how many and where? –how are all these determined from the objectives and hypotheses?

P  O

O Need practical skills –Lab –field –particularly in social sciences (survey ≠ questionaire+sample!) Get used to data handling –structuring –entry –checking

Summary Not just statistics – but that is important.statistics Key elements: –thinking –debating and challenging –connecting theory and practice No one said students need more subject matter content!!

K-S-A GoodNeeds improvement Knowledgesubject matterscientific method Skillsproblem solving field and lab data handling writing Attitudecommitmentquestioning challenging timid afraid of mistakes

Results of participatory planning of a research methods course Stakeholders participation Multidisciplinary research team Delivery pathways – training, extension, demonstration Impact pathways, +/- impacts Baselines and monitoring Funding Gender HIV and other conditioning factors Problem domain and real understanding of the problem New science The research! These are the summarised items that groups identified in relation to the five case studies, each group coming up with 2-4 items after about 40 minutes discussion. return