MindShift: Self-Testing, Shared Learning, and the Future of Education
A better way to study through self-testing and distributed practice
By Rebecca Tenney, MindShift
Education policymakers are finding ways to keep up with the changing, digital changes to educational research. From the Internet of Things (IoT) to Personalized Learning to Massive Open Online Courses (MOOCs), experts are working to find the best ways to incorporate a variety of research into the classroom.
In this age of information abundance, educators and researchers can access almost anything they want, whenever they want it. Devices and services make it possible to continuously test, learn, and improve.
However, education policymakers still often struggle to better understand how this can translate into a system of learning. New and innovative ideas can be pushed through research departments and quickly disrupted by new and innovative ideas. As a result, the rapid speed of research is often not recognized enough when education policies are being discussed or developed.
Efforts to maintain pace
Historically, one of the greatest barriers to speed is a lack of data. In most institutions, an undergraduate student is usually allowed to transfer out of a major just once after a few years. Academic statistics and flow charts are not the easiest tools for tracking change and direction. When there is less data, there is less trust and belief that the pace of change can be maintained.
Using self-testing and distributed learning can fill this gap. Instead of only using the traditional lab to test a hypothesis, experts can actually measure data with an entire community of researchers who live and work in the same place.
The integration of this type of peer-reviewed (peer-reviewed peer review is a consultative discussion) testing across research areas and departments at a university can spur a slow (pace) change through the data itself. Peer-reviewed research can facilitate knowledge transfer, collaboration, and virtual (distributed) human collaboration. Peer-reviewed research can provide a direct path for teachers to start bridging the gap between theory and practice through human sharing and data sharing.
In a 2015 presidential campaign, former Texas Governor Rick Perry (R) said, “There’s a big difference between communicating with data, and trying to make statements about the universe out of data.” Even large institutions with thousands of researchers can experience a disruption to their research if it is not continuously and openly available to everyone, even the general public.
Developing this type of open access research is at the core of both the Open Education Initiative (EOI) and the Consortium for Online Learning Research (COLLR). The goal of both of these initiatives is to focus on the future of education, not the past.
Individual colleges and universities can work together with research departments to create new opportunities to enhance their curriculums, community, and teaching. Data-driven changes are an immediate must for educational leaders who believe in equity, academic freedom, and making learning a student-centered experience, while also consistently delivering on necessary standards.
Communicating with data
One of the greatest challenges in keeping pace with the pace of change is the current practice of having students test anonymously and testing hundreds or thousands of students at the same time, with few methodological controls. Additionally, a survey may not include enough representative demographics, or may provide inaccurate results. Even if anonymous, testing is very expensive and is not completely secure.
Self-testing enables researchers to gather direct data on many different outcomes, anonymously, and on a large scale. Therefore, metrics are built directly into the outcome of testing. By focusing on researching outcomes instead of just collecting information, researchers can take control of the research process and yield better, more impactful data.
During investigations, expert teams can then quickly analyze the resulting data from each set of tests. Collecting data during independent activities allows for more efficient use of technology and shared data management to minimize costs, and it gives researchers a solid baseline to build on. As a result, we can move from the verification and reporting portion of research to ongoing discovery and implementation of new concepts and tools.
The benefits of self-testing go well beyond the tangible improvements to research, education, and teaching. Studies like the amazing Powerpaper Series and recent Vanderbilt University study on student learning progress shows that self-testing improves student success. If schools and universities adopt self-testing and distributed learning, we will continue to improve educational research and learning so that we can effectively adapt to the ever-changing, ever-mobile world of education.
Rebecca Tenney is the President of Netexus, a NYC-based education technology company and the founder of ScholarsNet, a digital course development and publishing platform for higher education faculty.