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Key Concept Exercise- Review of qualitative research design

Key Concept Exercise:
Review of qualitative research design

While neither quantitative nor qualitative approaches can be
considered completely without bias, qualitative methodologies and methods are,
by far, the more subjective of the two.

In all research, the presence of the researcher, their
choices and their interpretations, have a bearing on the work undertaken and
data collection methods chosen.

Qualitative researchers have a greater level of involvement
drawing on their own backgrounds, experiences and perceptions in their
interpretation of the data collected. Qualitative research, therefore, has a
degree of ‘built-in’ bias which should be acknowledged in a research study.

To prepare for this Key Concept Exercise:

Read the Required Learning Resources for Week 7
Return to your qualitative research designs from last week

To complete this Key Concept Exercise:

By Day 3 (Friday)
In approximately 500 words

Critically reflect on the types of qualitative data
collection methods that you could use in your research, considering their
benefits and limitations.
Consider how you might overcome the challenges that you may
encounter when implementing research using qualitative methodology, including
the management and analysis of data.

By Day 3 (Friday), submit your Key Concept Exercise to the
Turnitin Link provided.

Be sure to read over your Key Concept Exercise before
submitting it to your Instructor. Make sure the spelling and grammar are
correct and the language, citing and referencing you use when providing your
opinion are appropriate for academic writing.

To submit your Key Concept Exercise to Turnitin, click the
“View/Complete” link for Week 7 Key Concept Exercise — Turnitin.

YOU MUST READ THE ATTACHED TO KNOW WHAT YOU WILL WRITE ABOUT,
following:

Module Text
Collis, J. & Hussey, R. (2013)
Business Research: A Practical Guide for Undergraduate
and Postgraduate
Students. 4th
3ed. London:
Palgrave-MacMillan.
Chapter 8, ‘Analysing Qualitative data’ (pp. 153-175)
Chapter 9, ‘Integrated collection and analysis methods’ (pp.
176-194)

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