Building statistical capacity among Science research students

1. Building statistical capacity among Science research students Glenys Bishop

2. Statistical Consulting Unit • Consulting support is available, free of charge, to Honours and graduate students and staff in all parts of the University. • advice on statistical aspects of the design of research studies • advice and assistance in data collection and handling, statistical modelling and the presentation of results • collaborative student and staff research • formal supervision of MPhil and PhD students • courses designed to make researchers aware of modern statistical practice.

3. Consulting Clients (to 31 October 2010) Total number 262 • Level • Discipline

4. Short Courses • Number • Four 3-day courses each year (different topics) • One 2-day tailored course • Total attendance 60-70 each year • Purpose and Result • Raise awareness of statistical issues • Lead to higher demand for consulting service • Resource intensive • e.g. 3-day course five days preparation, three staff during the course for lecturing and tutoring

5. 4.2 consultants

6. Concerns • Consultants: many students do not have enough statistical knowledge for a meaningful discussion • Dean of Science: the lack of statistical knowledge of Science students

7. Outcome Make an on-line introductory Statistics course available to all Science honours and graduate students Concerns • Consultants: many students do not have enough statistical knowledge for a meaningful discussion • Dean of Science: the lack of statistical knowledge of Science students

8. On-line Course Considerations • Subject matter conceptual, not formula-driven • Ensure relevance by using examples from ANU research • Use facilities available in ANU where possible • Minimum maintenance for the SCU • Support from Science staff • Engage students

9. Computer Assisted Statistics Texts

10. Computer Assisted Statistics Texts • Modern with dynamic illustrations of concepts • Students can try things in a dynamic environment • Very few formulae, except in the advanced e-books • Supported by an active Statistics lecturer • Exercises for much of the introductory material; more being developed • Interesting international data sets of a scientific nature • Creative commons licence: can be downloaded to local website

11. Relevance • Case Study: data set with description • Chose several data sets with at least one categorical and two numerical variables • Requested permission to use • Wrote description that researcher checked • Conducted model analyses for two of them

12. Introductory Statistics Online • Select topics for about 30 hours of student time • Course set up in Wattle supporting Moodle • For each topic write objectives select teaching materials and exercises from CAST include case studies where possible compose quiz how long did this topic take? • Pre-course quiz • Final assignment, using a case study • News, discussion, Introduction forums • Course evaluation

13. Putting It All Together • Seminar to Honours and Graduate Student Coordinators in Science • Call for enrolments and enrol students • Start discussions, make announcements • Answer student questions • Make corrections where necessary • Workload • 140 hours to set up, • 1 hour per week maintenance for 10 weeks

14. Enrolments in ISO *16 people involved

15. On-line Course Considerations Subject matter conceptual, not formula-driven (CAST) Ensure relevance by using examples from ANU research (Case studies) Use facilities available in ANU where possible (Moodle via Wattle) Minimum maintenance for the SCU (1-2 hours per week) Support from Science staff Engage students

16. Topics for Discussion • Voluntary vs compulsory of a not-for-credit course • Encouraging students to take a voluntary online course • Engaging students in an online environment • Minimum amount of staff input • Scope of the topics chosen • Developing skills outside the research student's chosen discipline • Ease of implementation and constraints of the university environment