Academic Advice in Science & Engineering
Undergraduate and postgraduate taught students in Science & Engineering can make an appointment or come to a class with the Effective Learning Adviser for the College (or one of his Graduate Teaching Assistants) to talk about anything related to their academic work. Common topics include:
- academic writing (essays, lab reports, research proposals)
- critical analysis
- scientific presentations
- time and project management
- effective, evidence-based study and revision methods
James Rowe
Effective Learning Adviser (College of Science & Engineering)
Class Timetables
Live Classes (Semester 2)
Science Dissertation Writing (for CoSE & MVLS students)
This course is designed for science students undertaking their dissertation, but feel free to use it if you are earlier in your degree as well. It covers what to expect from your dissertation and how to produce a high quality research report.
This particular course is led jointly by the Effective Learning Advisers for MVLS and for Science & Engineering, with sessions on using LaTeX from the Maths Adviser.
> Moodle page for this series (includes slides and any recordings)
| Date | Time | Class title | Class description | Venue |
| Tue 27 Jan | 15:00-16:00 | Your Dissertation: Beginning to End | This class examines what the whole dissertation process looks like, from choosing a title to handing in your finished product. | Rankine: 108 LT |
| Mon 2 Feb | 10:00-12:00 | Introduction to Writing with LaTeX | LaTeX is a popular typesetting system used by people all over the world who need to include mathematical formulae or diagrams in their writing. This interactive session will demonstrate the basics before then giving you a chance to make your own documents and ask any questions you have. Please bring a laptop or device with you. | St Andrew's Building: 337 |
| Tue 3 Feb | 15:00-16:00 | Writing a Literature Review | This class will explore the process of finding and critically analysing journal articles, as well as how to incorporate academic literature into your writing. | Rankine: 108 LT |
| Fri 6 Feb | 14:00-16:00 | Introduction to Writing with LaTeX (online repeat) | LaTeX is a popular typesetting system used by people all over the world who need to include mathematical formulae or diagrams in their writing. This interactive session will demonstrate the basics before then giving you a chance to make your own documents and ask any questions you have. | Zoom Link |
| Tue 10 Feb | 15:00-16:00 | Developing a Methodology | We outline things to consider when designing your research methods and discuss how to write your methods chapter. | Rankine: 108 LT |
| Tue 17 Feb | 15:00-16:00 | Presenting your Findings | This class looks at the most effective way of discussing your data and writing about your results in the context of your field. | Rankine: 108 LT |
| Tue 24 Feb | 15:00-16:00 | Editing and Proofreading | The class looks at the stages of editing and proofreading that you need to complete in order to achieve a polished and professional dissertation. | Rankine: 108 LT |
Maths Drop-Ins (for any UofG student)
Open to any student with any maths question (other than Honours level mathematics courses).
Just turn up with the problem you’re working on and your relevant course notes.
> Moodle page for Maths advice
Introduction to Statistics (Using R Studio)
This series is for any student who will be working with data as part of their assignments, project, or dissertation. It will cover some fundamental concepts in statistics as well as how to use R Studio, a widely used statistical environment, to perform and present analyses. This particular course will be led by the Statistics Adviser. Both online and in-person options are available.
> Moodle page for this series (includes slides and any recordings)
| Date | Time | Class Title | Class Description | Venue or Zoom Link |
| Wed 21 Jan | 13:00-14:00 | Introduction to R Studio (Part 1) | This session introduces students to R Studio, a powerful statistical environment used by many to conduct simple and more complex statistical analysis,as well as produce meaningful and impactful graphs.(Part 1) | 42 Bute Gardens:915 |
| Thu 22 Jan | 10:00-11:00 | Introduction to R Studio (Part 1) | Online repeat | Zoom link |
| Wed 28 Jan | 13:00-14:00 | Introduction to R Studio (Part 2) | This session introduces students to R Studio, a powerful statistical environment used by many to conduct simple and more complex statistical analysis,as well as produce meaningful and impactful graphs.(Part 2) | 42 Bute Gardens:915 |
| Thu 29 Jan | 10:00-11:00 | Introduction to R Studio (Part 2) | Online repeat | Zoom link |
| Wed 4 Feb | 13:00-14:00 | Descriptive Statistics | This session covers basic statistical terminology, along with measures of central tendency, variation, and position of a data set. | 42 Bute Gardens:915 |
| Thu 5 Feb | 10:00-11:00 | Descriptive Statistics | Online repeat | Zoom link |
| Wed 11 Feb | 13:00-14:00 | Probability | This session covers the basic rules of probability, along with some examples of discrete probability distributions. | 42 Bute Gardens:915 |
| Thu 12 Feb | 10:00-11:00 | Probability | Online repeat | Zoom link |
| Wed 18 Feb | 13:00-14:00 | Hypothesis Testing | This session covers hypothesis testing, along with some continuous probability distributions used for hypothesis testing. | 42 Bute Gardens:915 |
| Thu 19 Feb | 10:00-11:00 | Hypothesis Testing | Online repeat | Zoom link |
| Wed 4 Mar | 13:00-14:00 | Simple and Multiple Linear Regression | This session covers simple and multiple linear regression, along with graphical tools to describe said regression. | 42 Bute Gardens:915 |
| Thu 5 Mar | 10:00-11:00 | Simple and Multiple Linear Regression | Online repeat | Zoom link |
| Wed 11 Mar | 13:00-14:00 | Logistic Regression | This session covers logistic regression, along with graphical tools to describe said regression. | 42 Bute Gardens:915 |
| Thu 12 Mar | 10:00-11:00 | Logistic Regression | Online repeat | Zoom link |
| Wed 18 Mar | 13:00-14:00 | Flexible Regression | This session covers flexible regression, along with graphical tools to describe said regression. | 42 Bute Gardens:915 |
| Thu 19 Mar | 10:00-11:00 | Flexible Regression | Online repeat | Zoom link |
Pre-recorded classes and online materials
These classes offer a mix of online materials and resources you can work through at your own pace. Some are classes held in the previous semester. All contain useful resources, sometimes including recordings of past live classes. Check back regularly for updates.
Principles of Scientific Writing
This course provides useful guidance on the core skills science students need in order to write effectively.
> Moodle page for this series (includes slides and any recordings)
This course includes one live class:
| Wed 4 Feb | 12:00-13:00 | Artificial Intelligence | This class will explore some classifications of artificial intelligence (AI), key elements of the UofG AI guidance, and critiques of various example AI outputs. | 5 The Square: 330 Gloag LT |
Moodle course includes:
| Referencing and Plagiarism | |
| Sourcing Evidence from the Literature | |
| Approaching Writing | |
| Critical Reading | |
| Creating an Argument | |
| Data, Graphs, and Figures | |
| Structure | |
| Editing | |
| Using Feedback |
Assessments at UofG (for CoSE & MVLS students)
This course provides an introduction to the purpose, structure, and expectations of various different assessment formats. You can find useful and practical advice on a range of assessment types, including some that centre around academic writing skills (e.g. essays, lab reports, reviews) and some that focus on scientific communication skills (presentations, posters, blogs, podcasts).
Exams and Academic Development (for CoSE & MVLS students)
This course includes one live class:
| Tue 24 Mar | 15:00-16:00 | Exam Revision Strategies | This class will offer advice on: how to put together a revision plan, how to revise effectively, and how to approach an exam. | Rankine: 108 LT |
But there are lots of asynchronous resources on the Moodle which you can access anytime:
| Class Title | Class Description |
| Lectures, labs, and tutorials | We discuss how to approach your classes in a strategic way so that you get the most out this valuable time with your lecturers. |
| Working in groups | Group work is an integral part of many degree courses. This class will show you how to get the most out of assessed and informal group work. |
| Exam revision strategies | We will show you the best revision strategies, and how to combine them to the best effect in the weeks before an exam. |
| Avoiding procrastination | Procrastination is normal! But this class will help if you feel that it is getting in the way of your studies. |
Higher / A Level Maths Refreshers
This series covers the maths skills needed for any student who has Higher (or A Level) Maths as a prerequisite for their course. This particular course will be led by the Maths Adviser.
> Moodle page for this series (includes slides and any practice question)
This series took place last semester, but the materials for the following classes are available at the Moodle link above.
| Title | Description |
| Graphs |
This session covers how to relate graphs to real world processes. |
| Algebra | This session covers algebraic manipulation, inequalities and simultaneous equations. |
| Powers and Logarithms | This session covers powers and logarithms. |
| Straight Lines and Quadratics | This session covers straight line and quadratic equations. |
| Functions | This session covers functions including composition and inverses. |
| Differentiation | This session covers differentiation, including optimisation. |
| Integration | This session covers the basics of integration. |
| Trigonometry | This session covers trig graphs, identities and how to solve trig equations. |
| Vectors | This session covers the basics of vectors including addition, scalar multiplication and the dot product. |
Appointments
Undergraduate and PGT students can make an appointment with one of the advising team (GUID required). The booking diary shows appointments available in the next 21 days only.
All appointments will take place online.
Dr James Rowe
James is the Effective Learning Adviser for the College of Science and Engineering, working within Student Learning Development (SLD).
He has a MMath from the University of St Andrews. His PhD is in category theory and algebraic geometry, studied for at the University of Glasgow.
Teaching Requests
James currently lectures on several degrees across Science & Engineering.
To find out what teaching he can offer on your course, get in touch by email.
Room 308
McMillan Reading Room
University Avenue
University of Glasgow
G12 8QQ