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Module

NUT2004 : Academic and Professional Skills for Nutrition 2

  • Offered for Year: 2020/21
  • Module Leader(s): Dr Edward Okello
  • Lecturer: Dr Kirsten Brandt, Dr Gerry O'Brien, Dr Dennis Prangle, Mr Karl Christensen, Dr Anthony Watson, Dr Helen Mason
  • 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
Guided Independent StudyAssessment preparation and completion120:0020:00Preparation of quantitative analysis assignment. Non-synchronous
Guided Independent StudyAssessment preparation and completion130:0030:00Career planning and preparation for placement. Online Non-synchronous
Guided Independent StudyAssessment preparation and completion110:0010:00Preparation of abstract. Online Non-synchronous
Guided Independent StudyAssessment preparation and completion138:0038:00Preparation of qualitative analysis assignment
Structured Guided LearningLecture materials51:005:00Lecture material delivered via various means-recaps, short recordings, formative activities non-sync
Structured Guided LearningLecture materials152:0030:00Lecture material delivered via various means-recaps, short recordings, formative activities non-sync
Structured Guided LearningAcademic skills activities21:002:00Support for career development and applying for placements. Online non-synchronous
Guided Independent StudyDirected research and reading113:0013:00Background reading to develop understanding and research. Non-synchronous
Structured Guided LearningAcademic skills activities12:002:00Support for project management skills
Structured Guided LearningAcademic skills activities32:006:00Support for advanced quantitative and statistical techniques
Scheduled Learning And Teaching ActivitiesSmall group teaching22:004:00Seminar sessions to develop writing and presentation (S2, online synchronous)
Scheduled Learning And Teaching ActivitiesSmall group teaching22:004:00Computer sessions – advanced quantitative and statistical techniques (S1, PIP)
Scheduled Learning And Teaching ActivitiesSmall group teaching12:002:00Small group session on career development (S1, online synchronous)
Scheduled Learning And Teaching ActivitiesSmall group teaching22:004:00Advanced quantitative and statistical techniques (S1, online synchronous)
Scheduled Learning And Teaching ActivitiesWorkshops61:006:00Workshops to support numeracy development (S2, online synchronous)
Guided Independent StudyReflective learning activity18:008:00Reflections on fieldwork activities - visits to food industries
Scheduled Learning And Teaching ActivitiesFieldwork14:004:00Visit to food industry: multistage food processing (S2, PIP off-campus)
Guided Independent StudyIndependent study62:0012:00Reviewing lecture notes. Non-synchronous
Total200:00
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 report1M30Quantitative assessment
Design/Creative proj2M50Qualitative on-line assessment - design and evaluate a discussion board or blog (2500 words)
Research paper2M20Effective abstract writing (300 words)
Formative Assessments
Description Semester When Set Comment
Written exercise1MCurriculum vitae and cover letter, and placement-planning brief.
PC Examination1MOnline proficiency test
PC Examination1MCareer 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