Sequentially Structured Dissertation Model for Timely Student Completion: Evidence for Best Practice
Time to completion in the Psychology PhD program was significantly lower for students in a sequentially structured dissertation sequence (DSE) focused on quality of research, increased student/chair interaction and timely completion compared to other cohorts who experienced a traditional sequence or transition between the two.
Due to the Covid-19 pandemic, most universities in the US shifted to partially or fully online courses. The impact on higher degree research students has been profound, and for many has involved online mentorship, data collection, and defense. These events underscore the importance of identifying best practices and aligning programmatic formatting for success of online students. Indeed, doctoral programs can vary widely by institution in their structure and specific program requirements (Castelló et al., 2017). There is some initial evidence of efficacy for a sequentially structured dissertation process model that leads to timely completion by promoting strategic goal-setting, sustained commitment, and motivated performance despite challenges and obstacles that may arise. Essentially, a sequentially structured model encourages a mindset of conscientiousness and intentionality that is not emphasized in other institutions. Students must constantly keep track of their progress – how far they’ve come and how far they need to go. Students may be more likely to remain focused on their doctoral goal pursuit because they know there are time limits. By staying conscientious throughout a structured dissertation experience, students emphasize to themselves that the dissertation is a prominent, valuable goal pursuit.
Research was conducted at a completely online non-profit university granting doctoral degrees to a very diverse and underserved student body. Students at this open-enrollment university are largely female, African American, employed full-time, with average age of 47. Until 2016, the university utilized a traditional dissertation sequence format based on milestone document completion where students were allowed to continue enrollment in dissertation courses without time limits. Based on institutional data, in 2016 the university implemented a sequentially structured dissertation model based on successful completion of course-based deliverables, evaluated against a faculty-created rubric by 3-member dissertation committees. There were many parties involved in the development of this new sequential model (referred to as the Doctoral Student Experience, or DSE), which focused on timely completion, quality of research, and regular interaction with a committee chair. The course sequence includes a Prospectus course, and 4 sequential dissertation course blocks (with up to 12 additional supplemental courses).
This Doctoral Student Experience (DSE) model involves three broad stages: preparation and approval of the Dissertation Proposal (DP) which includes Chapters 1, 2, and 3; conducting the study’s research (IRB approval and data collection); and preparation and approval of the final Dissertation Manuscript (DM) which includes chapters 1, 2, and 3 with the addition of chapters 4 and 5 to complete the manuscript, culminating in the dissertation oral defense. Within each course, students submit progress on specified dissertation components to scaffold learning. This allows for ongoing feedback, communication, and an iterative process of revision while students construct components of each chapter. Each chapter of the dissertation must meet minimum standards on an associated rubric, scored by committee chair and subject matter expert, for students to progress to the next course sequence block. At the Proposal and Manuscript stages, a third committee member, the Academic Reader, provides rubric-based evaluation. In this theory-focused dissertation process, the student identifies a researchable problem substantiated through evidence, proposes and conducts original research.
Theoretical Underpinnings to the Sequentially Structured Model
Most universities utilize common stages (i.e., 5 chapters) of the dissertation, but traditional models typically place less emphasis on timeliness. The temporally-framed goal progressions of the DSE provide a type of “aft wind” nudging the students forward in a time-bound process, which allows them to better evaluate their progress in measurements of time (see Husman & Lens, 1999). Other models may leave students more vulnerable to being “at-risk” and, may consequently experience greater attrition. The DSE model is enhanced for student and institution alike by implementing accountability measures such as attendance checks, which may serve to promote relatedness to the chair and the institution (see Deci & Ryan, 2017). Relatedness, is a sense of “connectedness” or “being known and understood,” identified by Deci and Ryan as a key psychological component of motivation. Furthermore, identifying a student as at-risk sooner rather than later is likely to more promptly renew their engagement in goal striving, a key determinant of performance (Ericsson et al., 1993; Locke & Bryan, 1969; Locke & Latham, 2002; Rothkopf & Billington, 1979; Wood & Locke, 1990), whereas an at-risk student that goes unnoticed may continue to pay substantial tuition without much academic progress. Such students may be more likely to have negative perceptions of their experiences with institutions, which could decrease goal commitment. Goal commitment of doctoral students must be understood and supported by institutions and dissertation chairs if students are to remain motivated to perform until they complete the doctorate; without commitment to goals, students’ goals do not imply enhanced motivation or performance (see Locke & Latham, 1990, 1991). Finally, the DSE encourages engagement between chair and doctoral student, presenting the groundwork for a mentor-mentee dynamic, wherein the chair may serve as what Ericsson (2018) might refer to as an expert mentor or what Vygotsky (1998) would refer to as a knowledgeable other, who is integral to the student’s success in academic and, often, emotionally supportive ways. Finally, the DSE model promotes student and institutional progress, awareness, and reflection processes due to the consistent sequential course endings and beginnings, such that students, chairs, and other institutional players remain more cognizant of students’ progression over time. Students are consistently encouraged to be reflective (Fishbein & Azjein, 1975) of their doctoral progress and intentional about changes they may need to implement to achieve improved goal task performance. Such reflective processes are emphasized by motivational and psychological principles of intentional behavior as illustrated in (a) deliberate practice, which has been tied to academic performance and expertise (Ericsson (1993), (b) conscientiousness, which has been linked to academic performance (Poropat, 2009), and (c) mindfulness, which improves emotional regulation (Erisman & Roemer, 2010; Hill & Updegraff, 2012; Nielsen & Kaszniak, 2006). The DSE model’s structure motivates the student to be cognizant of the “ticking clock” of their courses without adding overbearing pressure to finish in an overly tight, restrictive schedule.
Institutional data for the Psychology PhD program from 2013-2020 included 430 graduating students. 2013-2016 gradating cohorts reflected students who experienced the previous dissertation sequence (n=182); a non-structured traditional model. Students graduating 2017-2018 reflected students who experienced the transition from the previous sequence to the DSE (n=124). Students graduating 2019-2020 experienced only the DSE model (n=131). The outcome of interest for this study was number of days in the dissertation sequence. This variable reflected the number of days from a students’ first vested dissertation course start date to the date of successful dissertation defense. In this sample, scores ranged from 149-2426 days enrolled in the dissertation sequence. Square root transformation was used to obtain equal variances to meet ANOVA assumption.
There was a statistically significant difference between dissertation sequence cohorts as determined by one-way ANOVA, F (2, 434) = 17.72, p <.001. Cohen’s D was calculated (Lenhard & Lenhard, 2016) and a medium effect size of .68 was obtained. Tukey post hoc test revealed that days in the dissertation sequence was significantly lower for the DSE cohort compared to the previous sequence cohort (p < .001, d = .70) and transition cohort (p < .01, d = .43). There was no statistically significant difference between the previous sequence cohort and transition cohort (p = .082).
Timely completion of the dissertation is important in many ways. Prolonging completion of a dissertation research project can result in the research being outdated and therefore less relevant to the field, result in additional financial obligations and might prevent timely career advances. Lastly, delaying a dissertation research project can result in significant additional stress for candidates. Therefore, it is important to create a modality that supports students in timely completion of their dissertation research. The DSE model was developed to support students in this effort. These results suggest a more structured, high engagement, dissertation sequence positively impacts time to completion for Psychology PhD students at an online, open-enrollment, non-profit university. In addition, previous results of a pilot study showed no statistically significant difference in the quality of dissertations between this university and Dissertation Benchmark Alliance Schools (Ackerman et al., 2020).
Following WASC Senior College and University Commission reaccreditation visit to the university in February 2021, the Commission issued a letter stating the following “The Commission commends NCU in particular for the following: Creating best practices in the areas of doctoral dissertation quality… Sustaining an inclusive educational and work environment and seeking new means of supporting diverse students and underserved populations” (WASC Senior College and University Commission, 2021, March).
As more higher education research students must utilize online settings to complete their degree, universities must implement best practices to support student success and support faculty in remote teaching. In the future, based on institutional data [assessment and completion data], additional refinement of the DSE might be suggested. For example, some students struggle to complete the proposal stage during that sequential course block. The university is collecting data on potential changes to the sequence to further facilitate timely completion of the dissertation proposal.