After the MOOC comes the GAIN - Global Adaptive Instructional Network

Concurrent Session 6
Streamed Session

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Session Materials

Brief Abstract

The static MOOC model has not evolved since its widespread adoption in 2012.  This session will explore the development of a dynamic Global Adaptive Instructional Network (GAIN) to create the means to personalize the learning experience for every learner everywhere.

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Presenters

Lead Presenter: Dale Johnson, Arizona State University

Dale P. Johnson is the director of digital innovation for the University Design Institute at Arizona State University. He works with university leaders to develop and implement digital solutions to enable student success. Those efforts have earned him the 2016 Sally M. Johnstone Award from WCET recognizing his thought leadership, excellence in practice, and demonstrated leadership capabilities. In 2018, he was honored by the IMS Global Learning Consortium with an outstanding service award for his leadership of the adaptive courseware community of practice. Mr. Johnson has spoken on the topic of digital innovation in higher education at more than 20 conferences in the USA, Rwanda, Brazil, South Korea, Germany, Mexico, Russia and Vietnam, and led workshops on the subject at numerous universities. He has a bachelor of science in design degree from ASU and a master in public policy degree from Harvard University, a learning path that combined his interests in design, engineering and education policy. In his spare time, he enjoys traveling and building things. He’s traveled to more than 40 countries, studied in Barcelona for a year as a Rotary Foundation Ambassadorial Scholar, and built his own solar home in Phoenix.

Extended Abstract

In this session, we will explore the idea of developing a Global Adaptive Instructional Network (GAIN).  This network will create a marketplace for faculty to share instructional resources, profit from their intellectual property, and configure their own courses in the platform.  Using those instructional resources, the GAIN will employ adaptive techiques to recommend the right lesson to the right student at the right time in order to enable student success in a course.  This will result in the personalization of the instructional process in contrast to the existing static MOOC model where all students have the same learning experience.