NUT2004 : Academic and Professional Skills for Nutrition 2
- Offered for Year: 2020/21
- Module Leader(s): Dr Edward Okello
- Lecturer: Dr Anthony Watson, Dr Helen Mason, Dr Kirsten Brandt, Dr Gerry O'Brien, Dr Dennis Prangle, Mr Karl Christensen
- 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
Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.
Teaching Activities
Category | Activity | Number | Length | Student Hours | Comment |
---|---|---|---|---|---|
Structured Guided Learning | Lecture materials | 15 | 2:00 | 30:00 | Lecture material delivered via various means-recaps, short recordings, formative activities non-sync |
Structured Guided Learning | Lecture materials | 5 | 1:00 | 5:00 | Lecture material delivered via various means-recaps, short recordings, formative activities non-sync |
Guided Independent Study | Assessment preparation and completion | 1 | 38:00 | 38:00 | Preparation of qualitative analysis assignment |
Guided Independent Study | Assessment preparation and completion | 1 | 10:00 | 10:00 | Preparation of abstract. Online Non-synchronous |
Guided Independent Study | Assessment preparation and completion | 1 | 30:00 | 30:00 | Career planning and preparation for placement. Online Non-synchronous |
Guided Independent Study | Assessment preparation and completion | 1 | 20:00 | 20:00 | Preparation of quantitative analysis assignment. Non-synchronous |
Structured Guided Learning | Academic skills activities | 3 | 2:00 | 6:00 | Support for advanced quantitative and statistical techniques |
Structured Guided Learning | Academic skills activities | 1 | 2:00 | 2:00 | Support for project management skills |
Structured Guided Learning | Academic skills activities | 2 | 1:00 | 2:00 | Support for career development and applying for placements. Online non-synchronous |
Guided Independent Study | Directed research and reading | 1 | 13:00 | 13:00 | Background reading to develop understanding and research. Non-synchronous |
Scheduled Learning And Teaching Activities | Small group teaching | 2 | 2:00 | 4:00 | Advanced quantitative and statistical techniques (S1, online synchronous) |
Scheduled Learning And Teaching Activities | Small group teaching | 1 | 2:00 | 2:00 | Small group session on career development (S1, online synchronous) |
Scheduled Learning And Teaching Activities | Small group teaching | 2 | 2:00 | 4:00 | Computer sessions – advanced quantitative and statistical techniques (S1, PIP) |
Scheduled Learning And Teaching Activities | Small group teaching | 2 | 2:00 | 4:00 | Seminar sessions to develop writing and presentation (S2, online synchronous) |
Scheduled Learning And Teaching Activities | Workshops | 6 | 1:00 | 6:00 | Workshops to support numeracy development (S2, online synchronous) |
Scheduled Learning And Teaching Activities | Fieldwork | 1 | 4:00 | 4:00 | Visit to food industry: multistage food processing (S2, PIP off-campus) |
Guided Independent Study | Reflective learning activity | 1 | 8:00 | 8:00 | Reflections on fieldwork activities - visits to food industries |
Guided Independent Study | Independent study | 6 | 2:00 | 12:00 | Reviewing lecture notes. Non-synchronous |
Total | 200:00 |
Teaching Rationale And Relationship
• Lecture materials will provide an introduction to the module and provide information about using the internet to search for scientific literature, including use of scientific databases, and the critical analysis of such sources. They will provide information about qualitative and quantitative research methods used within nutrition, marketing and psychology.
• Computer-based practical sessions to develop their data analysis skills.
• Tutorials will provide students with the opportunity to develop their data handling skills using calculations, spreadsheets.
• Maths tutorials will provide students with the opportunity to develop their data handling skills using calculations.
• Self-guided study and independent learning will enable students to develop their skills in qualitative and quantitative research methods where they will collect relevant data which they will subsequently use in computer-based sessions for data manipulation in spreadsheets and carry out basic statistical tests and learn how to understand, present and describe tables and graphs.
• Self-directed study and independent learning also includes reading lecture notes and texts, preparation for practical sessions and tutorials, using learning resources on the Web. Skills practiced include critical thinking, active learning, goal setting and planning, information literacy and independence.
Assessment Methods
Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.
The format of resits will be determined by the Board of Examiners
Other Assessment
Description | Semester | When Set | Percentage | Comment |
---|---|---|---|---|
Practical/lab report | 1 | M | 30 | Quantitative assessment |
Design/Creative proj | 2 | M | 50 | Qualitative on-line assessment - design and evaluate a discussion board or blog (2500 words) |
Research paper | 2 | M | 20 | Effective abstract writing (300 words) |
Formative Assessments
Description | Semester | When Set | Comment |
---|---|---|---|
Written exercise | 1 | M | Curriculum vitae and cover letter, and placement-planning brief. |
PC Examination | 1 | M | Online proficiency test |
PC Examination | 1 | M | Career Service Online Interview Simulator |
Assessment Rationale And Relationship
• Quantitative assignment will assess the students’ ability to record and analyse data; their ability to carry out scientific calculations choose the appropriate statistical test; their ability to use software (Excel spreadsheets, graphical software, statistics software; and finally to present data effectively.
• Qualitative assignment will assess the students’ ability to research and find relevant material, to critically evaluate the content and study design of published scientific information, to communicate that information effectively and in a concise manner, and finally to use their creative skills in designing the discussion board/blog.
• Abstract will assess students’ writing skills, information literacy skills, evaluation of experimental design and ability to write a well-structured abstract on a scientific topic. This also links to graduate skills and career development skills.
• Although there is some repetition in assessment of LOs, this is the nature of the skills module whereby skills learned are applied to many aspects of work.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- NUT2004's Timetable