Postgraduate Course: Professional and Research Skills in Practice (PGGE11238)
|School||School of Geosciences
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||This course is designed to equip MSc students with relevant professional and research skills for both their MSc programme, and also for future employment and further advanced studies. The content covers general academic skills including scientific writing and delivering talks, as well as developing research skills that span the research process: developing research questions, planning, data collection, data analysis and interpretation. These skills will be partly taught and assessed during semester 1, as well as during the study tour component. Both qualitative and quantitative skills will be covered, in order to equip graduates with knowledge across a range of topics and disciplines, and to instil an interdisciplinary and holistic approach to research and associated skills. Due to COVID impacts, we are currently planning for field trips to the UK based (either residential or a series of one-day excursions), though this is obviously subject to change.
The following lists the general topics to be addressed in each week of the semester 1 component. Each topic will utilise a combination of recorded lectures and demonstrations, alongside exercises to be completed using real-life datasets and on-campus and/or online tutorials. Some weeks will include non-assessed exercises for immediate formative feedback, for example online multiple-choice tests, or peer review. The statistical aspects will be taught using R, but materials to support doing the exercises (and assessments) in Minitab (or Excel if possible) and NVIVO (for qualitative analysis) will also be supplied. You can complete the assessments in whatever package you find most useful.
1. Methods of enquiry: the scientific method and alternative approaches. Intro to R exercises.
2. Critical thinking: application in use of literature and other information sources. Intro to OpenRefine for data management.
3. Writing and speaking skills for academia and the workplace. R exercises.
4. CV preparation and jobhunting. Data basics: types, distributions, variability, summarising, description and graphing exercises
5. Asking research questions and formulating hypotheses, research design and sampling (experimental and survey approaches)
6. Quantitative analysis techniques
7. Qualitative analysis techniques
8. Multivariate and time series data and analysis techniques
9. Presenting results and writing revisited: application to example datasets
10. Ethical and moral issues in research; Risk assessment in research
11. Study tour planning
Please note that in light of possible COVID issues, the above topics are subject to change. Although the course can be run completely remotely, if possible we will have additional on-campus classes (repeated online).
┐ R/R Studio (https://rstudio.com/products/rstudio/download/) free for PC, Mac, Ubuntu etc
┐ OpenRefine (https://openrefine.org/) free for PC, Mac and Linux
┐ Minitab (https://www.ed.ac.uk/information-services/computing/desktop-personal/software/staff-students) available from the university once you have matriculated (along with other packages that may be useful in other courses/dissertation)
┐ NVIVO ┐ also available from the above university link, for qualitative analysis
The fieldtrip(s) will take place after the end of semester 2 and will be tailored to a particular cohort of students. Where possible, data collection in the field will take place, building on pre-tour planning. This data will at least be partly analysed for presentation as part of group projects. Where primary data collection is not possible during the fieldtrip, students will examine secondary data in the context of visits and discussions. Furthermore detailed analysis of data either collected on the visit, or supplied to fit the subject of tour visits, will be analysed and presented in a final report.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| Students MUST be on one of the following PGT programmes: MSc in Environmental Protection and Management, MSc in Food Security, MSc in Soils and Sustainability, MSc in Sustainable Plant Health
|Additional Costs|| Costs of travel, accommodation and subsistence on the study tour will be covered by the Programme fees paid, however incidental/personal expenses during the study tour will be met by the student concerned.
Course Delivery Information
|Academic year 2020/21, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 44,
Seminar/Tutorial Hours 8,
Supervised Practical/Workshop/Studio Hours 8,
Fieldwork Hours 40,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
Submission semester 1
Coursework 1 - individual seminar presentation on selected topic of interest, to include a poster or other short written component (20%).
Submission semester 2
Coursework 2 - individual analysis of supplied dataset(s), to demonstrate data summary, analysis and interpretation skills across a restricted range of datatypes and questions (30%).
Submission during/after fieldtrip
Coursework 3 - group collection/collation of data (primary or secondary) during study tour, and group presentation of results (10%).
Coursework 4 - critical review of topic addressed during study tour, to include appropriate analysis of any data collected (or secondary data), and suggestions for further research (including proposed methods) (40%).
||Given the nature of this course, in dealing with key skills that are fundamental to academic and professional work, all assessments are designed to be formative in that feedback should be applicable to assessments on other courses, and in particular should be apply to the dissertation component. All work will be marked and the marks/feedback released to the students in line with the School of Geosciences policies.
|No Exam Information
On completion of this course, the student will be able to:
- Apply professional techniques and standards to their written and oral communications.
- Identify areas of interest or knowledge gaps, and clearly articulate
- Plan appropriate experimental or survey techniques to address research questions, and carry out appropriate data collection.
- Identify and address as appropriate any ethical, moral or risk assessment issues arising from such research.
- Analyse data using appropriate techniques and tools, and draw logical and valid conclusions from the results.
|General texts such as those listed below will provide reading across the course, but specific reading will be supplied for each topic addressed. |
Aron, A. and Aron, E. (2002) Statistics for the Behavioural and Social Sciences: a Brief Course, 2nd ed. Prentice Hall International.
Buzant, T. & Buzant, B. (2010). The Mind Map Book: unlock your creativity, boost your memory, change your life. Harlow, Essex: Pearson Education Ltd.
Clewer, A and Scarisbrick, D. (2001) Practical Statistics and Experimental Design for Plant and Crop Science. Wiley.
Creme, P & Lea, M.R. (2008). Writing at University: a guide for students (3rd Edn). Maidenhead, Berks: Open University Press
Dey, I. (1993) Qualitative Data Analysis: A User-Friendly Guide For Social Scientists. Routledge.
Ennos R (2007) Statistical and Data Handling Skills in Biology. Pearson.
Ford E.D. (2000) Scientific Method for Ecological Research. Cambridge University Press.
Fowler, J., Cohen, L. and Jarvis, P. (1998) Practical Statistics for Field Biology, 2nd ed. Wiley.
Grafen A & Hails R (2002) Modern statistics for the Life Sciences. Oxford University Press, Oxford;
Graff, G & Birkenstein, C (2014). They Say/I┐ll Say. The Moves that Matter in Academic Writing. Norton & Co.
Hughes IG & Hase TPA (2010) Measurements and their Uncertainty, Oxford University Press, Oxford.
Mead, R., Curnow, R.N. and Hasted, A.M. (2003) Statistical Methods in Agriculture and Experimental Biology, 3rd ed. Chapman & Hall.
Peck, J. (2012) The Student┐s Guide to Writing. Palgrame Manmillan.
Pentecost, A. (1999) Analysing Environmental Data. Longman.
Rees, D. G. (2000) Essential Statistics. Chapman & Hall.
Rowntree, D. (2003) Statistics without Tears. Penguin
Ruxton, G.D. and Colegrave, N. (2006) Experimental Design for the Life Sciences, 2nd ed. Oxford University Press.
Salkind, N.J. (2007) Statistics for People who (Think They) Hate Statistics: Excel Edition. Sage.
Sharp, J.A., Peters, J. and Howard, K. (2002) The Management of a Student Research Project, 3rd ed. Gower.
Smith, P. (2000) Writing an Assignment: Effective Ways to Improve Your Research and Presentation Skills. Oxford.
Solomon, G. (2013) Just Write It! How to Develop Top-Class University Writing Skills. OUP.
Townend, J. (2002) Practical Statistics for Environmental and Biological Scientists.; Wiley.
Veal, A. J. (1997) Research Methods for Leisure and Tourism: A Practical Guide. Financial Times Management, London.
Wardlaw, A.C. (2000) Practical Statistics for Experimental Biologists, 2nd ed. Wiley.
|Graduate Attributes and Skills
||This course will develop the following graduate attributes as defined by the University of Edinburgh:
Mindset attributes developed are those of enquiry and lifelong learning through development of research skills, with communication skills developing outlook and aspiration mindsets. Graduate attribute skills that are developed are those of research and enquiry, and personal and intellectual autonomy - both primarily through engagement with the research process. Communications and personal effectiveness skills are developed throughout the course.
|Course organiser||Dr Alistair Hamilton
Tel: 0131 535 4417
|Course secretary||Mrs Elspeth Martin
Tel: 0131 535 4198