Musculoskeletal Research: Data collection and analysis

The details
Sport, Rehabilitation and Exercise Sciences (School of)
Colchester Campus
Postgraduate: Level 7
Monday 13 January 2025
Friday 21 March 2025
07 October 2022


Requisites for this module



Key module for

DIP B164MO Musculoskeletal Practice,
MSC B164MO Musculoskeletal Practice

Module description

In this module you will explore theoretical and practical issues in relation to data collection and analysis with specific emphasis on research in the musculoskeletal specialism. You will acquire skills needed to plan mixed methods research and analyse data. A defining feature of the module is that the research principles that are encountered will constantly be applied to real musculoskeletal clinical settings.
The majority of the resources you will need, and the learning activities you will undertake will be delivered online via 'Moodle'; this is essentially a way of providing a structured set of web pages, associated resources and tools for discussion.
As most students are in full-time employment and located some distance to the university, this module enables remote study using e-learning technology, (Moodle). For your study on this module you will be drawing on printed material, a variety of web resources including video clips, and data analysis software. You will also engage in virtual tutorials with the module tutor and fellow students.

Module aims

This module will help you to develop rigorous data collection and analysis skills to support research in musculoskeletal medicine. You will be required to apply a rich understanding of the quantitative and qualitative paradigms and their contribution to mixed methods research.

Module learning outcomes

1. Design a simple mixed methods research study informed by systematic knowledge and comprehensive understanding of research theories and principles.
2. Design appropriate qualitative and quantitative data collection tools that are compliant with appropriate ethical standards and governance requirements.
3. Effectively utilise software to carry out either quantitative data or qualitative data analysis, justifying decisions and creating appropriate output/frameworks and generating conclusions commensurate with the data.
4. Present work in a professional manner, competently expressed and edited and using language appropriate to the musculoskeletal professional discipline and required ethical standards. Use appropriate citation and referencing protocols ensuring that evidence presented is proportionate to the strength of claims made.

Module information

Module Content:

The module is organised into two topics,
1. Collecting Quantitative and Qualitative data. (3 weeks)
2. Analysing Qualitative and Quantitative data (6 weeks)

Each topic has a set of learning outcomes to help you focus your reading
Topic 1: Collecting Data for Quantitative and Qualitative Research
To understand how to construct and use questionnaires
To know how to plan and carry out interviews (including focus groups)
Topic 2: Analysing Qualitative and Quantitative Data
To know how to analyse qualitative data using qualitative data analysis software
To know how to undertake quantitative data analysis using quantitative data analysis software

Learning and teaching methods

This module is delivered entirely by e-learning. The students are expected to dedicate the equivalent of one day a week in time to this module. This module provides the opportunity to develop on line learning skills in a supported environment, as it is recognised that students are not equally fluent in using social media and online research methods. The module is provided fully through an online learning platform utilising a variety of on line teaching and learning methods to suit a range of student knowledge and competencies in both research and on line learning. The initial activities will be highly structured thus supporting confidence and competence in using on line media, with increasing opportunities for you to manage, contribute and structure your engagement with the materials as the module progresses. The module will be supported through access to a named tutor who will monitor your progress through the on line programme and provide support as necessary. The module will require a minimum of one day per week for study.


This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Assignment 1 - Mixed Methods Research Design    70% 
Coursework   Assignment 2 - Data Analysis    30% 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
100% 0%


Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Sue Innes, email:
Dr Sue Innes, Dr Bernard Liew



External examiner

Mr Myles Butler
Sheffield Hallam University
Senior Lecturer Team Lead
Available via Moodle
No lecture recording information available for this module.


Further information

* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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