The Learning Incubator: a Vanderbilt Endeavor (LIVE)
Innovations in how we teach, train, and learn using new digital platforms
Computational technology has transformed almost every aspect of our lives from transportation to healthcare to communication—every aspect except for education. While technology is being used throughout K-12, higher education, and corporate training, it has not resulted in rapid improvements for learning experiences or outcomes. Rather than transform learning, technology has been bolted onto the basic formula of instruction; digitally replacing or enhancing the textbook or the teacher.
Everything we know about teaching and learning tells us that the formulas we have been following are flawed, dysfunctional, and often inequitable. Propping up a flawed system by bolting on technology will not work. We need a new way of thinking about technology’s role in teaching and learning, one that looks to capitalize on the speed, systematicity, and ubiquity of computing to re-think human learning while integrating comprehensive learning theories that re-imagine how technologies can be designed to fit with how, where, and why we learn.
The focus here on learning, and not teaching, is deliberate and important. One thing that has become clear in recent years is that learning happens everywhere and across one’s lifespan. Even children only spend 18.5% of their time in a formal educational setting (NRC, 2009). The rest of our lives we learn in informal spaces, opportunistically snatching up moments to further our own goals and the goals of the communities within which we participate. The solution to our learning dilemma requires a seamless integration of lifelong learning and technology that advances the ability of humans and human processes to learn and adapt.
Figure published in Learning Science in Informal Environments: People, Places, and Pursuits (NRC, 2009)
LIVE is intended to become a unique combination of:
- Scholars who understand learning across the lifespan and organizational development across contexts (e.g., schools, homes, museums, communities, government agencies, industry, etc.); and
- Computer scientists and engineers who design cutting edge, advanced technologies that transform what is possible and re-imagine practice as usual.
LIVE will leverage Vanderbilt’s signature theory of Consequential Learning, innovative design processes, and computational thinking to forge new forms of partnership that:
- Incubate digital platforms, tools, and socio-technical solutions,
- Produce new models of computer-mediated teaching and learning,
- Address socially relevant and urgent problems of practice and research,
- Empower learners, individually and in groups.
LIVE will emphasize partnerships that leverage nascent technologies to solve current problems. Prime examples involve the use of mixed and augmented reality to anticipate and problem-solve future-of-work or future-of-learning problems.
Education: Solve the critical engagement problem through immersion in compelling virtual worlds and digital stories that bring to life the excitement of taking action, making choices, and connecting the digital world and the real world. Already at the forefront of immersing students in mixed reality simulations, Vanderbilt scholars are:
- Cultivating curiosity-fueled learning in a phenomenon like pollination by allowing students to become virtual bees that investigate the virtual life of bees from the inside.
- Creating virtual robotic worlds where high school students learn advanced computing concepts, from machine learning to cybersecurity, by competing and collaborating to solve challenging problems.
Work: Use AR and VR to solve the need for lifelong and lifewide learning by enabling more effective, lower cost, integrated learning that enhances rather than disrupts the workplace.
- Rather than a few weeks of training segregated from those doing the actual work, a reimagined “basic” training that would enable workers new to a career to learn by doing—on an on-demand basis, throughout their career. Artificial intelligence and machine learning would be leveraged to develop performance metrics and feedback that promotes continual improvement.