By Jim Goes and Marilyn Simon
The concept and importance of alignment in dissertation development is of paramount concern in many doctoral programs. Alignment refers to careful articulation of major proposal and dissertation elements in such a way that the proposal and dissertation narrative flows logically and consistently across different elements of the study. Reviewers are increasingly challenging doctoral learners to demonstrate alignment before their proposals or dissertations will be approved.
The key to successful alignment is to make certain that each major element is logically consistent, and fits with the problem, purpose, and other elements of the study. For example, a qualitative methodology would not fit with a problem that is inherently quantitative, such as testing the relationship between variable ‘scores’ on two Likert-type scales. Similarly, it would make little sense to propose a correlational test for data that are primarily textual and descriptive, such as one would find in a qualitative study. Both cases would present an alignment problem – the nature of the data does not align with the proposed analytical approach. Such data could potentially be quantified by coding particular responses using a set of established codes, followed by testing correlations or relationships using the coded data.
Each major element of the proposal needs to be logically and methodologically aligned with other elements. For example, research questions need to be aligned with hypotheses, hypotheses with the proposed theory or conceptual model, and tests, if any, should flow logically from the way in which hypotheses are constructed. A phenomenological design could be used to determine how a group of people perceive their lived experiences around a particular phenomenon. The problem, purpose, and research questions would need to be in alignment with this determination. In this case, the subjectivity of the data leads to difficulties in establishing reliability and validity of approaches and information, and does not produce generalizable data.
General methodology textbooks usually do not provide sufficient grounding for specific designs and methodologies. It is of great importance to review and cite texts and peer-reviewed journal articles of methodological thought leaders that elucidate the nuances of the specific methodology you choose for your study. For example, Yin for case studies, Moustakas for phenomenological studies, Glaser and Straus for grounded theory studies, and Stephenson for Q-methodology studies. See the sources below for additional guidance on achieving alignment in your dissertation. The HAT tool is particularly useful in tracking alignment through various iterations of proposal and dissertation development.