Lecture 4 Flashcards
4 Principles for Designing MM
1) Recognise MM designs can be fixed and emergent
2) Identify approach to design
3) Match design to research problem
4) Explicit about why MM
Fixed
Predetermined and planned
Emergent
Design changes during process
3 Design Approaches
1) Typology based
2) Dynamic approach
3) Synergistic approach
Typology based
emphasises classification of useful MM designs and selection based on predefine design
Dynamic Approach
Emphasises selection based on RQ
Synergistic Approach
Combines both and equal value of strands
4 Key Decisions in choosing MM
1) Level of interaction between strands
2) Priority of strands
3) Timing of strands
4) Where and how to mix strands
3 Variations of when to Merge Data
1) merge
2) Connect
3) Embed
6 Major MM Designs
1) Convergent parallel designs
2) Explanatory sequential design
3) Exploratory sequential design
4) Embedded design
5) Transformative design
6) multiphase design
3 Characteristics of Convergent Design
1) Qual & Quant data collected concurrently
2) Data analysed separately
3) Two databases merged during interpretation
2 Purposes of Convergent Design
1) Obtain complex understanding from 2 databases
2) Corroborate results from different methods
3 Reasons to use Convergent Design
1) Need to collect both data in one visit to field
2) Both types of data have equal value
3) Both qual and quant research skills
2 Strengths of Convergent Design
1) Efficient
2) Lends itself to a team
3 Challenges of Convergent Design
1) Effort and expertise
2) Sample and sample size issues
3) Difficult to converge two sets of data
2 Characteristics of Explanatory Design
1) Quant collection and analysis then qual collection and analysis
2) Quant results shape qual RQ
2 Purposes of Explanatory Design
1) Qual data to explain quant results
2) Quant data to select best participants for Qual
Philosophical assumptions for convergent
Pragmatism
4 Reasons for Explanatory Design
1) Quant oriented
2) Know important variables and instruments available
3) Participants available for second collection
4) New questions emerge from quant
Philosophical assumption for explanatory design
Post-positivism then constructivism but ultimately pragmatism
4 Strengths to Explanatory Design
1) Appealing to Quant researchers
2) Straightforward to implement two separate phases
3) Final report can be written in 2 stages
4) Lends itself to emergent approaches
4 Challenges to Explanatory Design
1) Time consuming
2) Approval hard when 2nd phase cannot be specified
3) What to follow-up on
4) How to select participants
2 Characteristics of Exploratory Design
1) Qual then Quant
2) Qualitative shapes Quantitative
2 Purposes of Exploratory Design
1) Explore first because theories not known
2) Develop instrument or typology not yet known
