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DRPS : Course Catalogue : School of Engineering : Postgrad (School of Engineering)

Postgraduate Course: Research Skills (IDCORE) (PGEE11183)

Course Outline
SchoolSchool of Engineering CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThis course introduces several areas of key research skills: Quantitative methods and the statistical design of experiments; searching, reviewing and writing scientific papers; poster presentation; and procedures and process for conducting hydrodynamic laboratory tests. These skills sets are designed to equip research engineers for undertaking research projects in industry.
Course description Research Skills is taught in two blocks, the first in semester one has the following lectures:
1. Introduction to Descriptive Statistics and Probability
2. Hypothesis testing (tests on the mean)
3. One-way and two-way ANOVA
4. Experimental design
5. How to write a Scientific Paper
6. Python Programming (5 Lectures)

Hydrodynamic Testing will cover the following topics:
1. Facilities for testing ORE devices
2. Model Testing and Scaling
3. Transducers and Data Acquisition
4. Challenges of testing ORE devices
5. Uncertainty Analysis

The students will take part in three laboratory sessions:
1. Waves
2. Small-scale OWC
3. Large-scale OWC
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2019/20, Not available to visiting students (SS1) Quota:  None
Course Start Full Year
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 18, Seminar/Tutorial Hours 20, Supervised Practical/Workshop/Studio Hours 4, Feedback/Feedforward Hours 1, Formative Assessment Hours 1, Summative Assessment Hours 10, Other Study Hours 44, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 0 )
Additional Information (Learning and Teaching) Self study
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Coursework 100%
Statistics Assignment (week 1) 30%
Paper critique and abstract (week 1) 20%
Laboratory Report (week 2) 40%
Presentation (week 2) 10%
Feedback 1 one-hour feedback session on the statistics assignment will be scheduled during week 1, peer marking will be used to review the work.
Feedback on Hydrodynamic testing will be given with groups after the presentations.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Evaluate information thoroughly; identifying assumptions, detecting false logic or reasoning and defining terms accurately in order to make an informed judgement, conduct research and enquiry into relevant issues through research design, the collection and analysis of quantitative and qualitative data, synthesising and reporting
  2. Be familiar with ICT literacy/data and information management and analysis to support their research and enquiry and have the ability to produce clear, structured written work
  3. Identify appropriate facility type for a model test of an ORE device and scale data from model scale to full scale
  4. Identify suitable instrumentation and data acquisition systems
  5. Devise an experiment plan suitable for a device at a given TRL; analyse experiment data and estimate uncertainty
Reading List
1. Stephen B Heard, The Scientist¿s Guide to Writing, Princeton University press, April 2016
2. Paul J Silva, How to Write a Lot: A Practical Guide to Productive Academic Writing, American Psychological Association, 2018
3. William Navidi, Statistics for Scientists and Engineers, 4th Edition, McGraw Hill, 2015.
4. Dan E. Kelley. Oceanographic Analysis with R. Springer-Verlag, New York, October 2018
5. Matthias Kohl. Introduction to statistical data analysis with R., London, 2015
6. Christian Hill, Learning Scientific Programming with Python, Cambridge University Press, 2015
Additional Information
Graduate Attributes and Skills Not entered
KeywordsQuantitative,experimental design,scientific literature,Python,Hydrodynamic model testing
Course organiserProf David Ingram
Tel: (0131 6)51 9022
Course secretaryDr Katrina Tait
Tel: (0131 6)51 9023
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