For I agree with you that there is a natural aristocracy among men. The grounds of this are virtue and talents… There is also an artificial aristocracy founded on wealth and birth, without either virtue or talents; for with these it would belong to the first class. The natural aristocracy I consider as the most precious gift of nature for the instruction, the trusts, and government of society. And indeed it would have been inconsistent in creation to have formed man for the social state, and not to have provided virtue and wisdom enough to manage the concerns of the society… The artificial aristocracy is a mischievous ingredient in government, and provision should be made to prevent it’s ascendancy. Thomas Jefferson to John Adams Oct. 28, 1813
Civitas Learning Acquires…
In early February 2016, our slight return to the subject of outsourcing student success in higher education overlooked Civitas Learning’s acquisition of a company called College Scheduler, an enterprise described as “the leader in schedule planning solutions for students and institutional stakeholders.” Heralded as the “first acquisition following a growth investment of up to $60 million in September 2015, led by the global private equity firm Warburg Pincus,” the addition of College Scheduler into the fold of Civitas Learning undoubtedly will figure as an important marker in for-profit companies’ strategies to entice higher education to outsource student success.
While prior acquisitions by Civitas Learning augmented its communication features in order to facilitate student engagement and interventions, the integration of College Scheduler into its analytics solutions provides the venture-capital funded startup with the technology to track the registration choices and patterns of the nation’s college students. With 173 institutional clients at the time of the acquisition – across many if not all sectors of higher education – Civitas Learning purchased a key resource to build its own proprietary data system with student-level records of enrollment and progress-to-degree at multiple institutions across the nation.
Originally devised to simplify scheduling for students and administrators, College Scheduler provides a “cloud-based platform” to record college-course offerings and the registration of students at the client institutions. The platform integrates with the three most common student information systems (SIS), indicating that that the course master files, annual course offerings, and registration behaviors of students for most institutions in the country may be recorded in its scheduling system. In addition, the system tracks appointments and attendance at orientations and advising sessions. While Civitas Learning will not have direct insight into grades or learning outcomes for student registrations in their system (unless institutions willingly upload the SIS grade rosters and/or learning outcomes assessments), the technology will allow Civitas Learning to develop its own algorithms to track student persistence from term-to-term and, for first-time freshmen, fall-to-fall retention at hundreds of colleges and universities in the country.
As we suggested in our original piece on Outsourcing Student Success, “every student has an array of different probabilities of success that varies with every institution in the country. Little is known how these differential probabilities of success are distributed across institutions because opposition to institutional accountability and multi-institutional research has effectively constrained institutional research to the local outcomes at particular institutions.”
Civitas Learning has overcome those traditional constraints with a single acquisition.
More astonishing, a for-profit enterprise with over $75 million in venture capital will be able to calculate the array of probabilities for student success at the course level for each institution that has fallen into its orbit – an analysis of institutional performance that no higher education scholar or institutional researcher in the country may now perform. To be clear what this means, Civitas Learning will be able to integrate its 200+ indicators of student success – whether solicited from the client institutions or directly from students – with the enrollment and persistence records in its College Scheduler records.
If not able to calculate predictions for grade attainment, Civitas Learning nonetheless will be able to project the likelihood of student persistence from term-to-term or fall-to-fall at the same institution given a student’s “indicators” and enrolled courses. Ultimately, using all student profiles, Civitas Learning will be to show each student serviced by College Scheduler the likelihood of persistence associated with each course option. If Civitas Learning obtains grade outcomes, it will be able to show each student the probabilities to earn an A, B, C, etc., etc., in each course offered at his or her college. In other words, students will be recommended and potentially select the optimal path to degree completion and/or GPA attainment based on the likelihood of success in each course a student takes at a particular college.
On the surface, this would be an admiral feature for students, but the bugs eventually could cripple the larger mission of student success.
On the one hand, students will be “optimized” to select the path of least resistance through college programs. In an institution with predictors of student success attached to courses and programs, students may more easily identify the faculty members with disproportional pass rates and the programs with the least onerous curriculum. Students may progress year-to-year, but with no assurance of the acquisition of student learning outcomes, the students may be repeatedly channeled into the next optimal choice of courses or program. As we conjectured last fall, the “optimizations” may result eventually in student registration sorting at the institutional level. As no two English 101 courses are the same, Civitas Learning will be able to show a student using College Scheduler which institution offers him or her the English 101 course or communications degree program that affords the highest probability of persistence and success – before submitting one application.
Ultimately, though, data science of student success at the course-level will never be able to demonstrate that its analytics solutions and student decision-making optimizations have produced an educated, competent college graduate from the enrollment records alone. The probability of student success or persistence through a series of courses carries no necessary relationship to the probability of student learning outcomes in a college program.
On the other hand, artificial distinctions of “academic preparedness” and “student engagement” inherent to the current student-level records and “indicators” of student success will be subsumed into the recommendations offered to individual students. Those who possess the wealth and cultural capital (“birth”) to pick an institution or college program a la carte without regard for costs will certainly benefit from the data science of student success. Most students, however, if Civitas Learning indeed goes so far as to show students their probabilities for success based on “indicators,” soon will learn the dismal probabilities for earning a college degree at an institution before registering for a single course. As students optimize their college attendance and “degree maps,” the inequity of outcomes inherent to the structure and operation of higher education institutions today will likely become exacerbated. The inequality of artificial distinctions for economic and cultural capital will then parade around as the inequality of natural distinctions for virtue and talents.
This is to say, while a college education at the institutions serviced by a proprietary system of data science for student success may attain modest gains in the rate of degree completion, the degrees themselves may increasingly fail to signify merit or accomplishment in a professional field of knowledge.
In the final analysis – whether its Hobsons, Datatel, Civitas Learning, or some other pie-eyed vendor of disruptive innovation – data analytics provided by for-profit vendors of student success are doomed to operate at such a superficial level of student records and outcomes that the discovery of unicorns should be regarded as a more likely event than the disruptive innovation of higher education. Vendors of student success may prove to be profitable enterprises for venture capital investors and higher education advocates-cum-entrepreneurs. Serious higher education scholars and institutional researchers nonetheless must regard the production of competent college graduates as far beyond the purview of the methods and solutions of data science for student success at this time.