Ce diaporama a bien été signalé.
Nous utilisons votre profil LinkedIn et vos données d’activité pour vous proposer des publicités personnalisées et pertinentes. Vous pouvez changer vos préférences de publicités à tout moment.
Research design, philosophy and 
methods 
Mark Reed
Plan 
• Choosing your research topic: where are you? 
• Research philosophy: what is knowledge? 
• Research design
1 What is knowledge?
Data 
• Raw numbers & 
facts 
Information 
• Useful data (that 
has been analysed/ 
interpreted) 
Knowledge 
• Information...
Different ways of viewing and 
constructing knowledge... 
Universal truth generated 
by reducing the world to 
its constit...
Different types of knowledge... 
Knowledge Type 
Implicit 
(not yet articulated) 
Local 
Informal 
Novice 
Tacit 
(cannot ...
Different types of knowledge... 
Knowledge Type 
Implicit 
(not yet articulated) 
Local 
Informal 
Novice 
Tacit 
(cannot ...
Different ways of 
managing 
knowledge... 
Knowledge 
Transfer 
Producers Users 
Producers Users 
One-way flow of 
existin...
2 Research design
How to choose research design 
Choice influenced by: 
• Research questions you want to answer 
• Epistemology 
• Preferenc...
Designing to questions 
The questions you can answer will depend on: 
• Existing data availability 
• Can you measure/coll...
Epistemology 
• How do you perceive knowledge, how it is 
generated and what constitutes valid 
knowledge? 
• Positivists:...
Qualitative versus quantitative 
• Examples of reasons to choose qualitative 
versus quantitative in different contexts? 
...
Qualitative or quantitative? 
• Depending on research question and 
epistemology, qual/quant may be obvious 
• Alternative...
Writing up research design 
• Methodology chapter: difference between 
research design and methods 
• Create a sub-section...
3 Methods
Should I use or collect Primary or 
secondary Data?
Primary data 
• Primary data is collected by you, first-hand
Secondary data 
• Secondary data has been collected by someone else, 
and you are using it “second-hand”
What should I use? 
• For your dissertation it is safest to focus on 
primary data collection 
– Easier to demonstrate ori...
Qualitative or quantitative?
What is qualitative? 
• Understanding the quality or nature of things, 
rather than their quantity 
– Good for asking “why...
Examples of qualitative 
– Examples of qualitative data collection methods: 
• Open-ended questions in questionnaires 
• S...
What is quantitative? 
• Understanding the quantity of things – being able to 
quantify relationships and describe them 
m...
Examples or quantitative 
• Examples of quantitative data collection 
methods: 
– Ecological and soil-based survey techniq...
Qualitative or quantitative? 
– I need to ask mainly what, where and when 
questions 
– I need to understand exactly how s...
Qualitative or quantitative? 
– I need to ask why questions 
– I want an in-depth understanding of the issue 
– I want to ...
Qualitative or quantitative? 
– All of the above! 
– MIXES METHODS APPROACH
Quantitative Methods
Quantitative research design 
• Representing reality 
– Systematic e.g. transects 
– Random and random stratified (i.e. ra...
Quantitative data collection 
• Counting things… 
• Closed ended question surveys with large 
samples e.g. via internet 
•...
Quantitative data analysis 
– Descriptive statistics e.g. mean, median, standard 
deviation, percentages 
– Parametric sta...
Qualitative Methods
Qualitative research design 
• Purposive sampling 
– Selecting respondents on the basis of pre-defined categories 
that co...
Qualitative data collection 
• Understanding the quality/nature of things… 
• Open ended question surveys with large 
samp...
Qualitative data analysis 
– Different types of content analysis and ways of 
summarising large bodies of text 
• Key word...
Triangulation 
• Simply “checking” your data and interpretation 
of results 
• Commonly used to increase the reliability o...
Summary 
• Primary or secondary? 
• Qualitative or quantitative? 
– Research design 
– Data collection methods 
– Analysis...
Prochain SlideShare
Chargement dans…5
×

Research design, philosophy and methods

Presentation by Prof Mark Reed

  • Soyez le premier à commenter

Research design, philosophy and methods

  1. 1. Research design, philosophy and methods Mark Reed
  2. 2. Plan • Choosing your research topic: where are you? • Research philosophy: what is knowledge? • Research design
  3. 3. 1 What is knowledge?
  4. 4. Data • Raw numbers & facts Information • Useful data (that has been analysed/ interpreted) Knowledge • Information that is known by an individual/group Wisdom • “Constructive” use of knowledge (Matthews, 1997) • “Use of knowledge ...to achieve a common good” (Sternberg, 2001)
  5. 5. Different ways of viewing and constructing knowledge... Universal truth generated by reducing the world to its constituent parts to test hypotheses Knowledge as a social construction leading to multiple realities
  6. 6. Different types of knowledge... Knowledge Type Implicit (not yet articulated) Local Informal Novice Tacit (cannot be articulated) Traditional Generalised/Universal Formal Expert Explicit (articulated) Scientific Raymond CM, Fazey I, Reed MS, Stringer LC, Robinson GM, Evely AC (2010) Integrating local and scientific knowledge for environmental management: From products to processes. Journal of Environmental Management 91: 1766-1777 Extent to which knowledge is locally generated/relevant versus universal Extent to which knowledge generated via formal, codified processes Extent to which those generating knowledge are regarded as experts Extent to which knowledge is articulated and accessible to others Extent to which knowledge is embedded in and reflects traditional cultural values/norms, or in the scientific method
  7. 7. Different types of knowledge... Knowledge Type Implicit (not yet articulated) Local Informal Novice Tacit (cannot be articulated) Traditional Generalised/Universal Formal Expert Explicit (articulated) Scientific Epistemology Raymond CM, Fazey I, Reed MS, Stringer LC, Robinson GM, Evely AC (2010) Integrating local and scientific knowledge for environmental management: From products to processes. Journal of Environmental Management 91: 1766-1777 Extent to which knowledge is locally generated/relevant versus universal Extent to which knowledge generated via formal, codified processes Extent to which those generating knowledge are regarded as experts Extent to which knowledge is articulated and accessible to others Extent to which knowledge is embedded in and reflects traditional cultural values/norms, or in the scientific method Post-modern Positivist
  8. 8. Different ways of managing knowledge... Knowledge Transfer Producers Users Producers Users One-way flow of existing knowledge Knowledge Exchange Producers Users Two-way flow of existing knowledge Knowledge generation Producers Producers generate or co-generate knowledge together Know-ledge Storage Knowledge application Users Users apply knowledge gained through transfer or exchange and provide feedback to or become producers of knowledge Reed MS, Fazey I, Stringer LC, Raymond CM, Akhtar-Schuster M, Begni G, Bigas H, Brehm S, Briggs J, Bryce R, Buckmaster S, Chanda R, Davies J, Diez E, Essahli W, Evely A, Geeson N, Hartmann I, Holden J, Hubacek K, Ioris I, Kruger B, Laureano P, Phillipson J, Prell C, Quinn CH, Reeves AD, Seely M, Thomas R, van der Werff Ten Bosch MJ, Vergunst P, Wagner L (2011) Knowledge management for land degradation monitoring and assessment: an analysis of contemporary thinking. Land Degradation & Development
  9. 9. 2 Research design
  10. 10. How to choose research design Choice influenced by: • Research questions you want to answer • Epistemology • Preferences towards qualitative/quantitative
  11. 11. Designing to questions The questions you can answer will depend on: • Existing data availability • Can you measure/collect relevant new data? – Skills, equipment, time etc. • The more focused your question, the easier it will be to design your research
  12. 12. Epistemology • How do you perceive knowledge, how it is generated and what constitutes valid knowledge? • Positivists: define hypotheses and quantify, proving beyond doubt • Post-modernists: more open-ended research questions and qualitative, providing a range of perspectives to build credible arguments
  13. 13. Qualitative versus quantitative • Examples of reasons to choose qualitative versus quantitative in different contexts? • Benefits/challenges of mixing both?
  14. 14. Qualitative or quantitative? • Depending on research question and epistemology, qual/quant may be obvious • Alternatively, start with a qual/quant preference and select research questions accordingly • More on choosing qual/quant later
  15. 15. Writing up research design • Methodology chapter: difference between research design and methods • Create a sub-section for both • Explain your design and methods in enough detail for someone else to replicate • Justify your choice – theoretically and/or empirically
  16. 16. 3 Methods
  17. 17. Should I use or collect Primary or secondary Data?
  18. 18. Primary data • Primary data is collected by you, first-hand
  19. 19. Secondary data • Secondary data has been collected by someone else, and you are using it “second-hand”
  20. 20. What should I use? • For your dissertation it is safest to focus on primary data collection – Easier to demonstrate originality – Harder to fall into trap of writing extended lit review • Supplement your primary data with secondary data to check/deepen your analysis – Handy if you don’t think you’ve got enough primary data
  21. 21. Qualitative or quantitative?
  22. 22. What is qualitative? • Understanding the quality or nature of things, rather than their quantity – Good for asking “why” questions and gaining an in-depth understanding of many different perspectives on an issue (i.e. often subjective) – Not so suited to statistical analysis and clear-cut, “objective” answers – Typically use quite small sample sizes (e.g. 20 interviews and a focus group) – Can be flexible – adapt your methods as you go
  23. 23. Examples of qualitative – Examples of qualitative data collection methods: • Open-ended questions in questionnaires • Semi-structured interviews • Focus groups • Participant observation • In-depth case studies – Examples of qualitative data: • Transcripts, audio, interview notes, documents – Examples of qualitative analysis: • Content analysis e.g. Grounded Theory Analysis
  24. 24. What is quantitative? • Understanding the quantity of things – being able to quantify relationships and describe them mathematically or in terms of their statistical significance – Good when you need to be able to answer a research question with precision, determine if there is a relationship between two things (x varies with y) or you need to determine something is statistically significant – Harder to determine causality (x causes y to vary) and answer “why” questions – Typically large data sets (min 50 data points, ideally >100) – Inflexible – have to stick to and replicate your method
  25. 25. Examples or quantitative • Examples of quantitative data collection methods: – Ecological and soil-based survey techniques e.g. counting plants in quadrats or along transects – Experiments – Closed questions in questionnaires e.g. Likert scale and categorical or numerical questions • Examples of quantitative analysis – Calculating percentages, means & standard deviations – Statistical analyses
  26. 26. Qualitative or quantitative? – I need to ask mainly what, where and when questions – I need to understand exactly how something has changed or might change in future – I need to understand if something influences something else – I need to know of something is significantly greater or lesser than something else – The people reading my research want a precise or “objective” answer to my research questions – PROBABLY QUANTITATIVE
  27. 27. Qualitative or quantitative? – I need to ask why questions – I want an in-depth understanding of the issue – I want to understand what happens in one particular area in-depth – I want to interview people – I want to consider differing perspectives – I don’t like numbers – PROBABLY QUALITATIVE
  28. 28. Qualitative or quantitative? – All of the above! – MIXES METHODS APPROACH
  29. 29. Quantitative Methods
  30. 30. Quantitative research design • Representing reality – Systematic e.g. transects – Random and random stratified (i.e. random within different groups such as socio-economic classes or habitats)
  31. 31. Quantitative data collection • Counting things… • Closed ended question surveys with large samples e.g. via internet • Ecological and soil-based techniques e.g. chemical analysis or counting plants in quadrats
  32. 32. Quantitative data analysis – Descriptive statistics e.g. mean, median, standard deviation, percentages – Parametric statistics (sample size >50, not too much variation) • Significant differences e.g. T-Test • Correlations e.g. regression • Multi-variate e.g. multiple-regression, ordination – Non-parametric (sample size <50, lots of variation) • Significant differences e.g. Mann Whitney U • Correlations e.g. Pearson Product Moment Correlation
  33. 33. Qualitative Methods
  34. 34. Qualitative research design • Purposive sampling – Selecting respondents on the basis of pre-defined categories that cover key aspects of your research question • Snowball sampling – Keep interviewing within a category till no new ideas – Get respondents to recommend others for you to interview • Case studies – Common in qualitative research – In-depth understanding of a particular case from which you may be able to generalise more widely – Multiple cases representing different perspectives, locations or components of your issue
  35. 35. Qualitative data collection • Understanding the quality/nature of things… • Open ended question surveys with large samples e.g. via internet • Semi-structured interviews with small samples (e.g. 12-20 people) • Participant observation – transcripts and behaviour • Make sure you get informed consent from respondents
  36. 36. Qualitative data analysis – Different types of content analysis and ways of summarising large bodies of text • Key word counts (aggregating synonyms) • Coding for themes – preset or emergent (Grounded Theory Analysis) • Discourse analysis to capture context and power relations • Recursive abstraction – summarising and summarising summaries and so on, to reach core themes
  37. 37. Triangulation • Simply “checking” your data and interpretation of results • Commonly used to increase the reliability of qualitative studies • Is there another way of collecting data to answer the same question a different way? – Follow your interviews with a focus group – Follow up historical documents to check an oral history
  38. 38. Summary • Primary or secondary? • Qualitative or quantitative? – Research design – Data collection methods – Analysis methods – Triangulation

×