A Model for Differentiating Support for Online Doctoral Dissertation Candidates
- 11:15 AM to 12:00 PM
Concurrent Session 5

Brief Abstract

Doctoral attrition has been a perennial concern across disciplines and decades with distance (DE) education doctoral programs consistently experiencing higher attrition than traditional/residential programs. To addresses this issue, we propose a mentorship model of differentiated support for online doctoral candidates depending on the candidate’s knowledge, skill, and level of self-direction.

Extended Abstract

Overview

Differentiation is an educational strategy that involves tailoring instruction and support to meet individual student needs. The philosophy behind differentiation is that one size does not fit all - educators need to vary their instruction and support depending on learner readiness, level of achievement, interest, and background (Tomlinson, 1999; Sousa & Tomlinson, 2011). While differentiation is widely accepted and broadly practiced in P -12 educational settings, we propose a model for differentiating support for doctoral candidates in the dissertation phase of the degree based on the skills and knowledge they bring to the process as well as their level of self-direction.

Relevance

The proliferation of online learning resulted in explosive growth in distance education (DE) doctoral programs. Over the past two decades the number of Americans with a doctoral degree more than doubled from 2.1 million in 2001 to 4.7 million in 2021 (United States Census Bureau, 2022). While doctoral degree dropout rates have consistently hovered between 40% to 60% across disciplines and decades (Zhou & Okahana, 2019), DE program dropout rates consistently exceed residential program dropout rates (Bawa, 2016). Recognizing that doctoral attrition represents a profound loss for the individual who departs as well as for the institution, researchers have been examining the factors associated with doctoral student attrition and persistence and have identified factors at the individual and institutional level (Spaulding & Rockinson-Szapkiw, 2012, Rockinson-Szpakiw, Spaulding, & Bade, 2014; Rockinson-Szpakiw, Spaulding, & Spaulding, 2016).

While there are a myriad of individual factors associated with doctoral persistence which include knowledge and skill (e.g., writing, statistics), time-management, motivation, support (familial and social), and ability to manage stress, one of the most salient factors is whether the student has made the transition from autonomous to self-directed learner (Ponton, 2014). While success in coursework is dependent on students engaging in autonomous learning, success in the dissertation is dependent on students engaging in self-directed learning (Ponton, 2014). Students who do not make the transition from being an autonomous to a self-directed learner struggle with the more unstructured nature of the dissertation phase of doctoral studies. According to Ponton (2014), "the doctoral student must be able to completely regulate personal learning that involves self-diagnosing deficiencies in knowledge or skills, self-creating learning activities (includes identifying appropriate resources) to alleviate such deficiencies, self-motivating participation in these activities, self-reflecting upon whether or not desired levels of learning are being realized, and self- creating any necessary adjustments to the activities" (p. 108).

Doctoral persistence is not only predicated on individual factors, but programmatic and institutional factors also play a tremendous role. While the quality of advising, the implementation of a cohort model, and program fit and flexibility (i.e., asynchronous course offerings) all play a role, the greatest institutional factor associated with persistence is the quality of the candidate/chair relationship. Effective faculty mentorship in the dissertation stage of the degree program is one of the greatest predictors of doctoral student success (Brill, Balcanoff, Land, Gogarty, & Turner, 2014; Reedy, Taylor-Dunlop, 2015).

Naturally, a doctoral candidate who has not become a self-directed learner by the dissertation stage requires a different type and level of support than the self-directed learner. The situation is further complicated if the candidate demonstrates any skill or knowledge deficits that will need remediation (e.g., composition skills, research skills, etc.). This student is at risk for attrition and will likely require a high level of support from a dissertation chair/advisor to be successful (i.e., persist to completion).

Thus, the purpose of this presentation is to address high attrition in DE doctoral programs by proposing a mentorship model of differentiated support for doctoral candidates entering the dissertation stage depending on the candidate’s knowledge, skill, and level of self-directed learning. We identify four quadrants of doctoral candidate characteristics (high skill/knowledge & self-directed; low skill/knowledge & self-directed; high skill/knowledge & low self-direction; low skill/knowledge & low self-direction) and propose a differentiated set of strategies for supporting dissertation candidates depending on what quadrant they fall under.

Engagement

After providing an overview of the doctoral attrition problem and introducing our Mentorship Model of Differentiated Support for Doctoral Candidates in DE Programs (see Figure 1), we will distribute four case studies representative of the four quadrants of doctoral candidate characteristics. Participants will work in groups to generate strategies for supporting the candidate based on individual characteristics.