"Grinnell College is combining learning analytics with human-intelligence networks to increase student retention and completion. Social and psychological factors linked to learning data help predict a student's success." writes
At Grinnell College, we believe we can achieve a deeper understanding of the factors that contribute to persistence and completion on our campus and at other institutions by examining the intersection of campus culture, the results of mixed-methods research, and our work with other colleges and universities regarding the art and science of interventions.
Liberal arts colleges such as Grinnell provide students an opportunity to discover intellectual and personal interests and acquire vital skills in an intimate, residential setting shaped by close interactions with faculty. Classes in the liberal arts tradition are often small and inquiry driven; students typically have access to excellent research opportunities, libraries, laboratories, and infrastructure. Yet the liberal arts model also faces significant challenges in terms of finances, access, sustainability, technology, and public scrutiny. To succeed in this environment, liberal arts colleges need to make compelling arguments regarding cost, value, and quality. They also need to devote renewed attention to questions of student retention and success, demonstrating an ability to deliver an outstanding education that enables students to learn, thrive, complete their degrees at high rates, and find meaningful work.
Colleges and universities have long relied on human-intelligence networks made up of faculty, professional advisors, other administrators, and students themselves to find the best balance of challenge and support for individualized learning and to monitor student progress. Because of the favorable ratios of staff to students at small, residential campuses, such networks continue to be a primary strength for those institutions.
Meanwhile, analytics offers new opportunities to improve student retention and success. Learning analytics has been defined as "the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs."1 With the advent of analytics techniques including data mining and machine learning, liberal arts colleges are in a position to join with other institutions that are developing or enhancing early-alert systems and predictive models based on these techniques.2 Grinnell is working to integrate learning analytics with existing human-intelligence networks so that alerts, predictive models, and outreach to students might be improved. We see this integration, or "blending" work, as an example of "augmentation" as defined in a recent book by Thomas Davenport and Julia Kirby:3
Augmentation means starting with what minds and machines do individually today and figuring out how that work could be deepened rather than diminished by a collaboration between the two. The intent is never to have less work for those expensive, high-maintenance humans. It is always to allow them to do more valuable work.Special Challenges for Small Schools
Based on several years of work with predictive modeling for persistence and completion at Grinnell, we have identified three special challenges that we are currently addressing. First, we have had little in the way of comprehensive, high-frequency data such as that which could be provided by a robust, campus-wide implementation of a learning management system. Although such a system is available, it is not widely used—or used to its full potential—by the majority of faculty on our campus. Second, because Grinnell is a selective college, our persistence and completion rates are relatively high; as a result, we continually encounter the "small n" problem and a lack of statistical significance in our analyses of those who do not persist. Third, the majority of our attrition occurs among students who are not in academic trouble—that is, they have B or better GPAs. As a result, we believe social-psychological factors play a significant role in persistence and completion on our campus and at peer institutions. Having identified these challenges, our efforts focus on enhancing our human-intelligence networks, our use of analytical tools, and the synergies at the intersection of the two.
Two Useful Frameworks: Attrition as a Complex Syndrome and a Model for Thriving
At many U.S. colleges and universities, challenges to retention are often primarily associated with two factors: preparedness and financial resources. Many students fail to complete degrees because they are unable to handle the academic demands they face. They lack time-management and organizational skills, they arrive from underfunded secondary school systems that leave them without the writing and quantitative training they need, and they find themselves overwhelmed in the classroom. In other cases, students and families borrow to their limits and, faced with escalating tuition costs and competing demands, discover that they are unable to manage the financial load. Such forces can affect liberal arts colleges as well, but challenges to retention at these institutions often illustrate a series of different factors that are not so easily identified or confronted. With this challenge in mind, a holistic approach to the analysis of the student experience can be particularly valuable.
Source: EDUCAUSE Review