What is Productive Persistence?
The Carnegie Foundation defines “productive persistence” as the tenacity + good strategies students need to be academically successful. Many students work hard in developmental math classes—studying long hours, nights and weekends—yet many of them do so using ineffective strategies. Others simply withdraw effort soon after the course begins. To help more students be academically successful, we want them to continue to persist when faced with challenges (tenacity) and to do so efficiently and effectively (good strategies).
How can students’ motivation and engagement be affected reliably, at scale, and by diverse practitioners?
One of the most promising new ideas for promoting community college student success involves the use of psychological strategies to improve student motivation, engagement, and achievement. But the crucial question is how can students’ motivation and engagement be affected reliably, at scale, and by diverse practitioners? In general, the field does not know. Within the field of research, there is a limited set of precise psychological interventions that have had encouraging effects in randomized experiments, but they have almost never been tested with community college students and, at least in the published literature, almost always have been tested at a small scale. Within the field of practice, many community college professors espouse anecdotes about effective student engagement tactics, but they lack substantial evidentiary basis for these practices. Given this, it was not surprising there was no coherent framework that unites the research and practice traditions.
Carnegie’s Productive Persistence work aims to do three things:
- Provide a comprehensive but actionable framework for improvement.
- Develop measures of the components of that framework.
- Organize a community of researchers and practitioners to build an evidentiary basis for practices that reliably improve student motivation and engagement at scale.
In order to combine the views of practitioners and researchers into a shared "theory of action," we developed a common framework that guides our work. This framework is both a visual representation of a system that we wish to change as well as a common language for improvement. The productive persistence framework was developed during a 90-day inquiry cycle that scanned the field for related efforts. Specifically, several hundred potential “drivers” were identified in conversations with students, developmental math faculty and researchers. This list was reduced to roughly 20 actionable drivers. The model was then “tested” and refined in discussions with faculty, researchers, college counselors and students. After some initial use, the model was tested again in January 2012, at a convening of expert practitioners and psychologists hosted at the Carnegie Foundation, which included Carol Dweck, Sian Beilock, Geoffrey Cohen, Deborah Stipek, and others.
Learn more about our common framework in this primer.
Measurement and Results
In order to improve something, it must be measurable.
The purpose of the common framework is to enable faculty and researchers to engage in improvement efforts around the drivers of student success. Improvement, however, requires measurement. Therefore a set of measures of the drivers of productive persistence was created. After a thorough scan of the field and using best-practices in survey design methodology a 26 item student survey was created that takes roughly three minutes to answer. This survey is embedded in the Pathway's online platform. In this way, drivers of students’ motivation and engagement can be assessed efficiently and practically on a regular basis. Initial results suggest this brief set of items are highly predictive of increased student success outcomes, such as successful course completion, increased academic performance and higher rates of retention and persistence.
A Network in which to Conduct Improvement Research
The objective of the productive persistence line of work is creating an evidence base for practices that reliably improve community college student motivation and engagement at scale, in the hands of diverse practitioners.
Specifically, productive persistence consists of two parallel lines of development work:
Carnegie Alpha Labs: Bringing Research into Practice
In an effort to promote research-based practice, the Carnegie Foundation developed alpha labs under the direction of Carnegie Fellow Jim Stigler. Within each Alpha Lab are researchers who partner with a community college to test interventions that address specific skills and mindsets necessary for success in the classroom. Additional information on alpha labs can be found at the alpha labs website.
Currently, there are three alpha labs:
- Anxiety - Dr. Sian Beilock and Seattle Central Community College
- Threat Reappraisal - Dr. Jeremy Jamieson and Cuyahoga Community College
- Mindsets - Dr. David Yeager and Austin Community College
Faculty Productive Persistence Subnetwork: Bringing Practice into Research
Carnegie’s Productive Persistence (PP) Subnetwork is employing the tools of improvement science—using real student data, creating new ways to analyze that data, and conducting research in their classrooms—to specifically address the problem of student motivation, tenacity, and skills for success in the Community College Pathways (CCP).
The Productive Persistence subnetwork is a cross-college collaborative of faculty members and Carnegie researchers and staff who are organized to problem solve the improvement of specific drivers that determine whether a student remains in the classroom and is successful.
Productive Persistence Subnetwork 2012 – 2013: Creating Social Ties/Belonging
Leading up to the fall term, the Productive Persistence subnetwork used results from previous Productive Persistence surveys and the research literature to identify three drivers that affect students’ social ties in the classroom: a sense of belonging, a sense that professors care about them, and their feelings of comfort in asking questions. These drivers were selected because data from Pathways students indicated that these were closely related to pass rates (C or better) and persistence rates (students enrolling in the next term of Statway).
Read more about the Productive Persistence subnetwork here: Productive Persistence Newsletter Vol 1.