Evidence based practice is an essential component of responsive and responsible health policy, strategy, leadership, service provision and coordination of action for health. To scrutinise the knowledge that informs and guides practice, the practitioner needs to be research-literate. This module explores the different ways in which data can be collected, analysed and interpreted so that students become more confident in carrying out these activities themselves, as well as increasing their ability to critique the research carried out by others. In particular, students will be able to reflect on the most suitable research methods for their particular research question, understanding that the data collected has implications for the analysis that can be carried out and the types of question that can be answered.
This module takes place over ten weeks with a two or three hour class each week. Students are first introduced to the difference between quantitative and qualitative research, how they differ and how they complement each other. Sessions 2 -5 then focus on quantitative methods including research design, the importance of research ethics and the design of questionnaires. Sessions 3-5 are in a computer lab during which a range of descriptive and inferential data analysis techniques are introduced using SPSS. In sessions 6-9 approaches to qualitative data collection and analysis are explored, including a computer lab class which introduces the use of NVivo as an example of qualitative data analysis software. The final week introduces the concept of mixed methods research and its relevance in public health research.
Module Aims
This module aims to provide students with a range of techniques for collecting, analysing and interpreting data. It combines a theoretical with a practical approach to enable students to fully understand the collection and analysis process so that they are able to make informed decisions when designing and carrying out research.
Learning Outcomes
On completing this module a student will be able to:
1) Debate the use of particular research methods in response to specific research questions.
2) Design and develop data collection instruments and critically reflect on their value and suitably.
3) Identify and debate the ethical implications of research.
4) Explain and carry out a range of data analysis using appropriate computer software.
5) Interpret the findings of statistical and qualitative analysis and relate this to their field.
This module takes place over ten weeks with a two or three hour class each week. Students are first introduced to the difference between quantitative and qualitative research, how they differ and how they complement each other. Sessions 2 -5 then focus on quantitative methods including research design, the importance of research ethics and the design of questionnaires. Sessions 3-5 are in a computer lab during which a range of descriptive and inferential data analysis techniques are introduced using SPSS. In sessions 6-9 approaches to qualitative data collection and analysis are explored, including a computer lab class which introduces the use of NVivo as an example of qualitative data analysis software. The final week introduces the concept of mixed methods research and its relevance in public health research.
Module Aims
This module aims to provide students with a range of techniques for collecting, analysing and interpreting data. It combines a theoretical with a practical approach to enable students to fully understand the collection and analysis process so that they are able to make informed decisions when designing and carrying out research.
Learning Outcomes
On completing this module a student will be able to:
1) Debate the use of particular research methods in response to specific research questions.
2) Design and develop data collection instruments and critically reflect on their value and suitably.
3) Identify and debate the ethical implications of research.
4) Explain and carry out a range of data analysis using appropriate computer software.
5) Interpret the findings of statistical and qualitative analysis and relate this to their field.