Postgraduate taught 

Bioinformatics MSc/PgDip/PgCert

Teaching, Assessments, and Intended Outcomes of MSc Bioinformatics

Teaching, Assessments, and Intended Outcomes of MSc Bioinformatics

Learning and Teaching Approaches Used in This Programme

  • lectures (both didactic and interactive)
  • interactive tutorials
  • computer practical classes, software demonstrations and exercises
  • guided independent study
  • individual and group presentations
  • field trips
  • small project work
  • a substantial project (MSc only)

Assessment Methods Used in This Programme

  • coursework essays and written exercises
  • written examinations - essay questions, short answer questions and small problem analysis
    questions
  • computer laboratory reports
  • written reports on small projects
  • group and individual presentations
  • computer lab performance during the main project (MSc only)
  • written report on the main project (MSc only)
  • viva examination on the main project (MSc only)

 

Study protocols, types of teaching and timetables:

  • For 10, 15 and 20 credit courses, 100 hours, 150 hours and 200 hours of work by the student, respectively, are assumed, including time spent in private study and time spent preparing for assessments and in assessment.
  • For the 10 credit courses, there will be generally be about 15-25 hours of contact time with teachers (for the 20 credit courses, it will be about 25-40 contact hours). Types of teaching will vary between courses, but most will have at least 5-10 hours of lectures and tutorials/student presentations and at least 5-10 hours of supervised computer practical. Students will be expected to do many more hours on the computer themselves working from worksheets etc., with staff and demonstrators on hand to supervise progress at intervals, and course leaders helping to round things off at the end of each course.
  • In Semester 1, we have to fit in with the School of Computing Science timetable and their two courses are long and thin, running for a few hours each week over most of the semester. The two School of Life Sciences courses therefore operate similarly.
  • In Semester 2, the 10 and 20 credit optional courses are ‘short and concise’ - the teaching takes place over 3 weeks (10 credit courses) or over 5 weeks (20 credit courses) during the teaching term (January to early May), and you are only studying one course at any one time. Where there are optional courses up against each other in the same timetable slot, any course with fewer than 5 students enrolled will probably not run.
  • The project in the summer lasts for 14 weeks. Students are embedded in the research group of their supervisor and the project occupies them full-time. Although meetings with the supervisor and team will be regular, a high level of independence in the design and execution of the work is expected (increasing as the project goes on) from the student. Projects may be carried out within Glasgow, elsewhere in the UK, or in any approved lab worldwide.

Rationale for the Programme - what needs are we hoping to meet?

The rationale behind the programme included the following thoughts about what students on the programme and its graduates will need (in addition to other factors thought important by the academic staff contributing to the programme):

What do the students want their own attributes to be after the degree programme?

  • generic skills pertinent to employability in any employment sector
  • practical computing skills, including programming
  • a solid conceptual foundation for data analysis in post-genome biology
  • knowledge of programming languages they could use again in a range of jobs, or in further study
  • competency (via hands-on experience) in a range of bioinformatics and analysis tools commonly used in post-genome biology

What are the unique selling points (USPs) and key features of our programme?

  • the scenario-based Semester 2 course system, which deeply embeds real, local research stories in the teaching
  • exposure to approaches involving integrative analysis over multiple omics levels - the ‘Polyomics’ (a.k.a. ‘multiomics’) approach
  • the high quality projects where students are embedded in what may be world-leading groups in their fields and are working on solutions to real research problems and questions
  • the fact that over the last few years, graduates of this programme have had a high rate of success in getting PhD Studentships or employment as core Bioinformaticians