Module JXH-3058:
Research Skills for Medics

Module Facts

Run by School of Sport, Health and Exercise Sciences

20 Credits or 10 ECTS Credits

Semester 1

Organiser: Dr Ross Roberts

Overall aims and purpose

This module forms an essential element underpinning all the other modules within the School. It provides students with an understanding of the nature of science and the application of the scientific method to the study of sport, exercise and health, and fundamental skills in data management, analysis and interpretation. The module is split into two separate but inter-related halves.

Part A Computational Statistics - The purpose of this module is for students to understand research processes in sport, health, and exercise sciences covering computational statistics 1 Computational Skills 2 Computer (SPSS) Skills 3 Subject specific interpretational skills

Part B Research Methods & Design - examines the fundamental assumptions underlying both quantitative and qualitative research approaches, sampling, validity, reliability, and experimental design.

Course content

The purpose of this module is for students to understand research processes in sport, health, and exercise sciences covering Computational Statistics and Research Methods. In Part A students will cover ANOVA and regression based analyses In Part B students will cover data management in SPSS, quantitative research methods, and qualitative research methods and analysis module failure that prevents you passing the year will require resit assessment and attendance at Supplementary Assessment Week (exact date TBC but expected to be in July 2019)

Assessment Criteria


good level of understanding presented


acceptable level of understanding presented


excellent level of understanding presented

Learning outcomes

  1. Understand the principles underlying measurement in quantitative research

  2. Demonstrate an understanding of the principles underlying variance testing (e.g., ANOVA) and regression (simple and multiple regression)

  3. Understand sampling procedures

  4. Interpret the main features of SPSS computer printout from ANOVA and regression analyses.

  5. Understand the principles of experimental design

  6. Appreciate how different philosophies about ways of knowing influence one’s approach to research design

  7. Carry out basic procedures in the analysis of qualitative data

  8. Organise data in an SPSS spreadsheet.

Assessment Methods

Type Name Description Weight
Part A Midterm Exam 25
Part B Midterm Exam 20
Part B Coursework 25
Part B SAQ Exam (JAN) 30

Teaching and Learning Strategy


Part A 11 2 hour lectures

Practical classes and workshops

Part B 2 1 hour practicals

Private study

Part B private study to include reading, formative assessments, updating portfolio/ notes, exam preparation

Practical classes and workshops

Part A 4 1 hour practical sessions


Part B 11 2 hour lectures + 5 online 30 minute lectures

Private study

Part A - private study to include attendance at enhancement sessions, reading, updating portfolio/notes, exam preparation and assignment completion


Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Information retrieval - Able to access different and multiple sources of information
  • Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.

Subject specific skills

  • research and assess paradigms, theories, principles, concepts and factual information, and apply such skills in explaining and solving problems
  • critically assess and evaluate data and evidence in the context of research methodologies and data sources
  • describe, synthesise, interpret, analyse and evaluate information and data relevant to a professional or vocational context
  • demonstrate evidence of competence in the scientific methods of enquiry, and interpretation and analysis of relevant data and statistical outputs.


Courses including this module

Compulsory in courses: