Found in 2-4% of methodology chapters. If your research questions ask "how" but your methods collect numbers, your committee sees a fundamental design flaw.
Ensure the stated methodology aligns with the research questions and data collection methods.
Methodology alignment means your research questions, research design, data collection methods, and data analysis procedures all point in the same direction. When a student writes exploratory "how" questions but proposes a survey with Likert scales, or asks about numerical relationships but plans to conduct interviews, the committee sees a misalignment that threatens the entire study's validity.
This issue usually emerges when students change their research questions during the writing process but don't fully update the methodology chapter to match. You started with qualitative questions, switched to mixed methods after your committee meeting, updated Chapter 1, but Chapter 3 still describes a purely qualitative design. Or you refined your questions to be more specific, but your data collection instruments still target the broader original questions.
Alignment needs to be explicit, not implied. Your committee wants to trace a clear line from each research question to the specific data source that will answer it, to the specific analysis technique that will process that data. If you have three research questions, your methodology chapter should clearly state which data collection method addresses which question and which analysis technique will be applied to that data.
Committees flag mismatches between research questions and methodology as a fundamental design flaw that undermines the entire study.
This qualitative study used surveys with Likert scales to measure participant attitudes.
This qualitative study used semi-structured interviews to explore participant experiences and perspectives.
A "relationship" question implies quantitative measurement, not qualitative interviews.
RQ1: What is the relationship between teacher self-efficacy and student achievement? Methodology: Semi-structured interviews with 12 participants.
RQ1: What is the relationship between teacher self-efficacy and student achievement? Methodology: Correlational analysis of Teacher Sense of Efficacy Scale scores and standardized test results from 150 participants.
A "how do people experience" question requires qualitative analysis, not statistical tests.
RQ: How do principals experience the transition to remote leadership? Data analysis: Descriptive statistics and t-tests.
RQ: How do principals experience the transition to remote leadership? Data analysis: Thematic analysis of interview transcripts using Braun and Clarke's (2006) six-phase approach.
Mixed data types require a mixed methods design, not a purely qualitative label.
RQ1 addresses perceptions (interviews). RQ2 addresses outcomes (test scores). Design: Qualitative phenomenology.
RQ1 addresses perceptions (interviews, qualitative). RQ2 addresses outcomes (test scores, quantitative). Design: Explanatory sequential mixed methods (Creswell & Plano Clark, 2018).
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