Research and Professional Skills

Module summary

Module code: BIOT1004
Level: 5
Credits: 15
School: Engineering and Science
Department: Science
Module Coordinator(s): Bruce Alexander

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 chemical, forensics and pharmaceutical sciences data.
• To provide students with the relevant tools to plan, and carry out 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

On successful completion of this module student will be able to:

1. Identify, select and apply appropriate statistical methods for analytical data interpretation.
2. Understand the importance of critical analysis in analytical research and data presentation.
3. 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.
4. Appropriate use of analysis software, data recording, data management and presentation, and bibliographic management.

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