Research Design
This research employs a sequential explanatory mixed-methods design, combining quantitative surveys with qualitative interviews to provide comprehensive insights into how AI is reshaping SEO careers.
Research Timeline
Phase 1: Literature Review
3 months - Analysis of 150+ academic papers
Phase 2: Survey Development
2 months - Pilot testing with 50 professionals
Phase 3: Data Collection
4 months - 500+ survey responses, 30 interviews
Phase 4: Analysis & Validation
3 months - Statistical analysis and thematic coding
Data Collection Methods
Quantitative Methods
- Online Survey: 100+ questions covering skills, AI usage, career outcomes
- Likert Scales: Validated instruments for measuring career resilience
- Statistical Analysis: Regression, factor analysis, correlation matrices
- Sample Size: n=500+ for statistical power of 0.95
Qualitative Methods
- Semi-Structured Interviews: 30 in-depth conversations with industry leaders
- Thematic Analysis: Identifying patterns in career adaptation strategies
- Case Studies: Deep dives into successful AI adoption stories
- Content Analysis: Review of industry reports and thought leadership
Ensuring Research Rigor
Validity
Content validity through expert review, construct validity via factor analysis
Reliability
Cronbach's alpha > 0.8 for all scales, test-retest reliability confirmed
Triangulation
Multiple data sources and methods to ensure comprehensive findings
Ethical Considerations
This research was conducted with the highest ethical standards:
- IRB approval obtained from the institutional review board
- Informed consent collected from all participants
- Data anonymized and stored securely
- Participants' right to withdraw respected at all stages
- Findings shared transparently with the professional community
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