In this week’s edition of The Job (an Open Campus newsletter written by Paul Fain), I read about a very broad proposal to create an applied science to support working learners. The proposal was launched by Stanford University and the National Science Foundation (NSF).
Over four weeks in July, Stanford hosted four virtual convenings with participants from many colleges and universities as well as a few outside entities. The topics of these meetings were:
- Collaborating to serve working learners
- How might applied research serve working learners
- Building learning science
- Envisioning the future
The premise for these convenings is that most academic research focuses on analyzing and writing about the academic success and persistence of traditional, full-time college students. At the same time, the majority of college students today are working adults (a point that I have made in numerous blog posts as well as published academic papers for years).
An overview white paper for the Stanford conference points out that despite recognition of the need to learning opportunities for working adults, “the nation is without shared scientific or policy goals for serving this vast population and lacks protocols for the cross-sector collaborative activity this service requires.”
Targeted outcomes of the virtual conference were to “include the specification of (a) a taxonomy of the kinds of people and life circumstances that comprise the broad category of ‘working learners’, (b) applied research goals whose pursuit will serve to improve the educational and occupational success of working learners, and (c) templates for cross-sector sharing of data, expertise, and infrastructure to pursue this applied research.”
Figure 1 below was included in the conference’s white paper to describe the characteristics and needs of working adult learners. It is from Regina Deil-Amen’s chapter “The ‘Traditional’ College Student: A Smaller and Smaller Minority and Its Implications for Diversity and Access Institutions” in the book, Remaking College: The Changing Ecology of Higher Education.
Figure 1 is used to make the case that the population of working learners is diverse and complex. In addition to illustrating some of the demographic characteristics of working learners, Figure 1 also includes items related to preparedness and attendance. All the factors in this illustration have been found to influence college student persistence and retention over the years.
While Figure 1 provides a reasonable depiction of much of the research regarding student persistence, the writers of the white paper argue that much more cross-functional research is needed, far beyond the current work that researches academic progress. Figure 2, shown below, was used to illustrate their expectations for the formation of an applied science of research related to working learners.
Many years ago, I began a quest to learn as much as I could about online learner persistence and retention. Through my experience as president of an online university as well as formal academic research and publication, I learned much about what influenced the attendance and persistence patterns of online, working adult learners. Most of my work would be included in the circle on the right in Figure 2, although I continue to write about issues related to data and data infrastructure in the circle at the bottom.
Without going back and reviewing my papers, I’ll cite a few items that my research uncovered over the years and see if readers know of similar findings.
My taxonomy of a working learner would create two groups: those under 25 years old and those over 25 years old. I would include in the definition a requirement that they work full-time (32 hours or more each week).
There are substantial differences between the college attendance patterns of online learners under 25 and those 25 and over. As a researcher, I’d prefer to study the 25 and over group. Through my research as well as through conversations with other leaders of largely online student universities, the working learner who is over 25 has more risk factors (married, with dependents, etc.), but may also have more motivation to complete a degree.
Many working learners who are 25 and older do not meet the definition of first-time, full-time student or either of those two components separately. Over the years, many leaders of adult-centric institutions have stated and written that the Department of Education’s data collection and statistical reporting should be different for institutions with a small percentage of first-time, full-time students. Perhaps this initiative can lead to a more resolute definition and reporting delineating the difference between the two student populations.
Included in my earliest research findings regarding student persistence is that online students who transferred their credits to the receiving institution were more likely to graduate. Naturally, those students would not be included in the first-time student definition.
Later research using longitudinal data of five and 10 years post-start for the same student datasets indicated that transfer credit is not a statistically significant factor over the longer period for completion. However, an indirect outcome of this finding is that few working learners are full-time students, given that many learners take six to 10 years to earn a four-year degree.
I have advocated for the federal student aid (FSA) system to change to better meet the needs of working adult learners. My research indicates that even though there are financial incentives for learners to meet the full-time attendance requirements, few did so and a high percentage of those who attempted a full course load did not do well academically while also shouldering the burden of a full-time work schedule as well as family obligations.
It is extremely difficult for working learners who have settled into a routine of taking classes at a pace that fits into their work (and family) schedule(s) to increase the number of classes that they take in order to graduate faster. Most of the current student persistence and retention research is sociology-based (the right-hand circle in Figure 2), but in this case, there may be opportunities for cognitive psychology and neuroscience research as well (the left-hand circle in Figure 2).
The authors of the white paper make an excellent point that an applied science of working learners must recognize that “learning happens in a wide range of organizational contexts: in traditional college and university classrooms, but also in workplace training and mentoring programs, through military and other public services, and in an ever-growing array of online instructional and certification opportunities provided by business and non-profit organizations of every description.”
Early research findings related to online learner data from students attending American Public University System (APUS) were that there were no significant differences in graduation rates between the race of students. At the time, a substantial majority of APUS students (90%) were either active-duty military students or veterans.
I made an educated guess that the mentorship available to servicemembers of all races influenced this outcome, which was different than findings at many other institutions. Years later, after the population of non-military affiliated students increased at APUS, the outcomes shifted in a way similar to other institutions.
The white paper states that the new science must recognize that learning is a longitudinal process. It accurately calls for “coordination among the many sites through which learners pass, and among the public and proprietary systems that aggregate information about the educational experiences and employment histories of learners.”
In 2010, APUS partnered with Walmart to provide postsecondary education to its U.S. employees. A unique feature of the partnership included an evaluation of the training and on-the-job learning for many different employee jobs by APUS faculty. Academic credit was awarded for some employees based on a “transcript” of the training and on-the-job learning provided to APUS by Walmart and through competency exams supported by a review course.
It’s clear to me that partnerships like the one I’ve described will be important in the future as artificial intelligence (AI) impacts many jobs. The applied science of working learners would propose devising mechanisms to allow for coordinating employer data like that to educators.
The ultimate outcome of Stanford’s and the NSF’s proposal to create a coordinated scientific study of working learners is to understand what kind of programs work, for whom, and why. My colleagues at APUS and elsewhere in the working adult-serving, online postsecondary education community know that understanding the answers to those questions is complicated. As mission-driven educators committed to the working adult learner, we are glad to participate in the discussions, contribute to the research, and work collaboratively to identify trouble spots and practical solutions.