Skip to main content

Module

NUT2004 : Academic and Professional Skills for Nutrition 2

  • Offered for Year: 2020/21
  • Module Leader(s): Dr Edward Okello
  • Lecturer: Mr Karl Christensen, Dr Anthony Watson, Dr Helen Mason, Dr Kirsten Brandt, Dr Gerry O'Brien, Dr Dennis Prangle
  • Owning School: Biomedical, Nutritional and Sports Scien
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 10
Semester 2 Credit Value: 10
ECTS Credits: 10.0

Aims

To provide students progressing from stage 1 (NUT1001) to stages 2/3 with advanced competencies in academic and professional skills relevant to their degree programmes. In particular the students will:-

•       Develop advanced scientific skills to enable independent learning at a HE level; in particular how to find, analyse, synthesise and present information appropriately in preparation for their research projects.

•       Develop advanced skills in operating computer software within a Windows environment in the context of reporting the output of research.

•       Introduce the application of advanced statistical techniques to nutrition data.

•       Introduce students to practical skills essential to students studying the nutritional sciences.

•       Develop wider key skills and encourage students to reflect on how these skills can be applied throughout their university career and beyond.

Outline Of Syllabus

•       Career development sessions: Project management skills (using Mind View, Mind map, Gantt charts etc) and placement skills (effective CV writing, job searching, pre-interview applications and proficiency tests, and interview technique.

•       Advanced literature research skills: library search strategy, plagiarism, referencing using Endnote, critical review and impact assessment of papers.

•       Experimental design, basic data manipulation, interpretation and presentation.

•       Ethics and ethical approval for nutritional intervention studies, including power calculations and sample size.

•       Qualitative data analysis: participant observation, interviews, focus groups, text analysis, thematic analysis and discussion boards.

•       Quantitative data analysis: data transformations, discrete and continuous data.

•       Advanced statistical analysis of data: parametric and non-parametric data analysis.

•       Advanced presentation of research data: MS Office: MS Word, MS Excel, MS PowerPoint, MS Publisher.

Teaching Methods

Module leaders are revising this content in light of the Covid 19 restrictions.
Revised and approved detail information will be available by 17 August.

Assessment Methods

Module leaders are revising this content in light of the Covid 19 restrictions.
Revised and approved detail information will be available by 17 August.

Reading Lists

Timetable