Research and Professional Skills in Life Science

Module summary

Module code: RESE1132
Level: 5
Credits: 15
School: Engineering and Science
Department: Science
Module Coordinator(s): Susan Force

Specification

Aims

To provide the necessary background for students to appreciate the relevance and importance of rigorous analytical data and the methods required to process data within their disciplines. • To provide students with the relevant tools to plan, and carry out and report investigations in an appropriate manner. • To gain an understanding of the skills and attributes required for a graduate to be successful in the employment market and in their own personal growth.

Learning outcomes

1. Identify, select and apply appropriate statistical software and methods for analytical data interpretation.
2. Identify the health, safety and ethics considerations associated with undertaking research.
3. Apply the skills necessary to undertake their final year project and produce a submission as specified in the final year project module.
4. Employ self-reflection to identify strengths and weaknesses in the student’s skillset and adopt a plan to develop themselves and prepare for the employment market. This should reflect the University Greenwich Graduate Attributes, Sustainable Development and research informed learning.

Indicative content

Students will typically encounter subjects taken from the following topics, either through formal lectures and workshops, or through activities linked to the Employability and Personal Development Planning ePortfolio: Numerical and Analytical skills • Analysing data, presenting reports Selection and use of computer software for Data Collation, Storage and Management; An introduction to Data: Types and formats of analytical data; An Introduction to Univariate Data Analysis Distributions and Probabilities Hypothesis testing; Inferential statistics: Parametric tests including t-test, F-test, ANOVA, Pearson’s correlation. An Introduction to data modelling and regression analysis Trend analysis; Detection of outliers Enquiry based Learning and Research Scientific methods & principles of scientific investigation; Communication • Written • Oral • Presentations Data presentation and visualisation Networking and interview skills; Digital literacy / Information technology • ICT packages • Social media knowledge • Online marketing and business knowledge Word processing. Excel and other statistical packages with functions to support activities above Development of a professional profile, e.g. LinkedIn. Information literacy Bibliographic databases and reference management Professionalism • Cultural competence • Ethics • Respect for others. Reflection and action planning Enterprise, creativity and environmental awareness Design and development of processes, systems, services and products Introductory Quality management and assurance – e.g. ISO 17025:2005 Learning Using Feedback and Exam Skills and Techniques Using reflection to enhance exams; what have I learnt from feedback

Teaching and learning activity

The module will be taught largely through lectures and laboratory-based work. The theoretical principles will be explored in the lectures and the laboratory work will make practical use of the principles by allowing students to work their way through data relevant to their degree subject. For the personal development planning component of the module, the learning is largely self-directed with some opportunity for face-to-face lectures and ongoing support by personal tutors/academic mentors. The student is required to share with their personal tutors their reflections and plans.

Assessment

Portfolio: Learning outcomes: Learning outcome 4. Weighting: 25%. Pass Mark 40%. Employability & Personal Development Planning Portfolio: Student designed/tutor agreed portfolio including reflective study and employment focussed activities.

Quiz: Learning outcomes: 1, 2, 3. Weighting 75%. Passmark 40%. Selection of VLE quiz question types appropriate for LOs 1, 2 and 3.