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2019/20 Taught Postgraduate Module Catalogue

FOOD5333M Research Project: Masters Students

80 creditsClass Size: 170

Module manager: Dr Celia Ferreira

Taught: 1 Oct to 30 Sep (12mth) View Timetable

Year running 2019/20

Pre-requisite qualifications

A BSc degree in chemistry, biochemistry, biological sciences or related science, or chemical engineering.

Module replaces

FOOD5405M and FOOD5071M

This module is not approved as an Elective

Module summary

This module trains students in essential research skills and enables them to carry out a research project within a subject specialism within the School. The module will firstly demonstrate the importance of the scientific method and research design for successful problem solving so that students will be confident in information retrieval, literature evaluation, data interpretation, statistical analysis and scientific writing. Focus on statistics and laboratory training will be related to the research specialism. Students will then utilise these skills in completing a research project.


The module aims to:
1) ) foster students ability to be self-evaluative and to identify their training needs through completion a personal development plan;
2) develop research skills relevant to research and graduate employment in food science and nutrition, including information retrieval, literature evaluation, research design and hypothesis testing, generic laboratory skills, data interpretation, statistical analysis using the statistical software package R, scientific writing and oral presentation skills;
3) apply fundamental scientific principles to solve problems in food and nutrition research.

Learning outcomes
Learning outcomes
Upon completion of the module, students will be better able to:
1) evaluate their own competencies and skills and identify needs for further training as part of a personal development plan;
2) demonstrate information retrieval skills, including the use of literature databases and critically evaluate information in order to draw appropriate conclusions;
3) apply the scientific method of hypothesis-led research and select an appropriate research design to investigate a relevant issue/problem;
4) complete a laboratory, computer or survey based project;
5) demonstrate data analysis skills including methods in data manipulation;
6) perform advanced statistical analysis on data with the use of appropriate R commands;
7) demonstrate written communication and oral presentation skills in the context of scientific dissemination.

Skills outcomes
- Practical skills relevant to research/employment in food science and nutrition.
- Information retrieval and evaluation.
- Scientific writing.
- Qualitative and quantitative methods of data analysis.
- Use the programming language R to perform statistical analysis and use appropriate graphical representations to correctly interpret statistical results.


Students will firstly identify their own needs for training but will need to demonstrate competency and skill in all areas of the syllabus.
The first part of the module will be taught through a series of workshops that will include: literature retrieval and how to avoid plagiarism, literature evaluation, the scientific method and scientific design, hypothesis testing, practical experimentation, data interpretation, scientific writing and oral presentation skills.
For statistical analysis, R studio, basic statistical procedures, tests and linear modelling will be introduced, then one or more of the following advanced techniques will be covered dependent on research project specialism: Design of Experiments and Response Surface Methodology; Logistic models and Generalized linear models; Multivariate Analysis - Principal Component Analysis, Factor Analysis, Cluster Analysis; Meta-Analysis (Mean, OR and RR data formats).
The application of these fundamental scientific principles will then be used to solve problems in food or nutrition research. Students will be given a choice of research topics relevant to the research activity of the School and, in some cases, suggested by industrial companies.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Computer Class102.0020.00
Independent online learning hours15.00
Private study hours729.00
Total Contact hours56.00
Total hours (100hr per 10 credits)800.00

Private study

- Preparation of personal development plan, and end of module review: 6 hours
- Preparation for workshops: 15 hours
- Preparation for practical sessions: 3 hours
- Completion of literature skills workbook: 30 hours
- Completion of data analysis assessment: 30 hours
- Completion of assignment on practical laboratory sessions: 30 hours.
- Preparation for initial presentation: 15 hours
- Individual experimental research project, including preparation of literature review, data analysis, scientific research paper and final presentation: 600 hours

Opportunities for Formative Feedback

Formative feedback will be provided during training sessions and workshops, and written feedback will be provided for assignments, which will allow students to improve for their final research project.

Methods of assessment

Assessment typeNotes% of formal assessment
Written WorkLiterature skills workbook, research proposal, literature review10.00
Online AssessmentData handling and statistics10.00
AssignmentScientific paper10.00
In-course AssessmentContinuous assessment of laboratory work20.00
Investigative ProjectDissertation at end of study40.00
Oral PresentationInitial and final oral presentation10.00
Total percentage (Assessment Coursework)100.00


Reading list

The reading list is available from the Library website

Last updated: 03/07/2019


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