Editor’s Note: This blog is based on the author’s doctoral capstone done while she was in residence at the Carnegie Foundation. The full capstone is titled, “Walking the Talk, Teaching the Talk: Building a Collective Learning System at the Carnegie Foundation for the Advancement of Teaching” and was submitted to the Harvard Graduate School of Education.
Carnegie’s work rests on the assumption that we need to increase the rate of learning in order to reach the high aspirations we have for the education system–to provide quality education to the millions of children across the country. In our Networked Improvement Communities (NICs), we aim to “learn our way into better systems.” A key component of that vision is being able to build on the learning of others. We are all familiar with the lament of “not wanting to reinvent the wheel,” yet if you have been around education long enough, you have probably seen efforts that seemingly “reinvent the flat tire.” Despite living in a time of connectivity and open access to information, we still struggle with getting the right information to the right people at the right time. We are “information rich, but knowledge poor.” At Carnegie we’ve been studying knowledge management in an effort to address this problem, both within our organization and in the NICs we support.
Knowledge management has a natural fit within NICs because they aspire to produce knowledge that can improve practice and expedite the spread and use of that knowledge. In his original conception of NICs, Doug Engelbart argued that the collective IQ, or “how well people can work together to solve important problems,” depends on their ability to engage in “concurrent development, integration, and application of knowledge.” His description prefigures how the American Productivity and Quality Center, a leading voice in the field, defines knowledge management. They define it as, “a systematic effort to enable information and knowledge to grow, flow, and create value. The discipline is about creating and managing the process to get the right knowledge to the right people at the right time and help people share and act on information in order to improve organizational performance” (O’Dell & Hubbert, 2011, p. 2). Both of these definitions sounded promising, and over the course of the last year we began to explore the knowledge management needs for Carnegie and for our NICs. We also studied what has been learned from previous efforts in other organizations.
The first lesson that came through loud and clear was that many organizations have made the mistake of thinking of knowledge as a set of assets to be managed. This view leads to an over reliance on tools like repositories and lessons learned databases. The theory being that if we can get everything codified and ordered, then the knowledge will travel. This has proven to be insufficient for many reasons. One of the most significant reasons is that such an approach does little to account for how people learn and use knowledge. Here is where our own expertise as educators offered a particularly useful lens. We knew we needed to consider how adults learn, and in particular how they learn in the workplace, if we were to be successful in our efforts. We also know quite a bit about the human processes that structure the use of new knowledge. All these considerations needed to be accommodated in a truly effective knowledge management system.
Design Principles for a Collective Learning System
Rather than design a knowledge management system for Carnegie, I proposed that we need what I called a Collective Learning System (CLS). I define it as a set of interrelated social practices (routines, norms, roles, and processes) supported by technology tools that facilitate the learning necessary to achieve a group’s mission. It provides a means to increase capacity in an organization or in a multi-organizational structure such as a NIC. The name and the definition show a disposition towards social practices and learning which is more in line with the highly collaborative work of NICs. My current thinking about what Carnegie’s Collective Learning System should include is outlined in the seven principles that follow:
1. Attend to practical knowledge and appropriate processes for learning it.
Different types of knowledge call for different types of learning experiences. Given its work, Carnegie’s knowledge needs tend more towards practical knowledge, or the know-how needed to enact improvement. Efforts to teach and learn this practical knowledge need to follow what is known about adult learning.
2. Provide guidance on the social structures needed.
It is not enough to say that people should share knowledge; a CLS should articulate the social structures needed to support learning. Social structures include, but are not limited to, protocols, norms, physical setting, facilitation, and documentation.
3. Attend to psychological safety and lower barriers to entry.
Efforts should be made to create a space wherein people feel safe to learn and fail. A CLS will include conversations with people across different levels of the organization and of unequal power. Social practices should allow the person with the relevant expertise or insight to express it regardless of their status. Designs should allow for people to enter the learning process in various ways since different people learn and express themselves in different ways.
4. Embed the learning processes in the work.
Whenever possible, learning should be embedded in the actual work of practitioners. This will retain the context that generated the knowledge and where it will need to be applied, maximizing the depth of understanding and utility of the learning.
5. Take a system perspective.
Processes should aim to focus attention to all relevant components of the system. And, in crafting social processes, input should be sought from all relevant parties in the system.
6. Integrate learning from across the organization.
Knowledge is being created across the boundaries of units inside the Foundation and outside it. A CLS needs to serve as an integrator across these boundaries. While the work will continue to occur across boundaries, and it would be ineffective to have everyone involved in all the work, collective learning requires integration in order to maximize learning.
7. Take advantage of technology to the extent appropriate.
Technology, especially that which facilitates real-time collaboration, should be utilized when appropriate. However, technology should not aim to eliminate the human learning experience.
Although this is an ambitious list, in the sprit of improvement science, we’ve started small by iterating on the design of specific processes like after action reviews and failure analyses. As with all work at Carnegie, we will continue to learn our way into this problem.