Every industry, from health sciences to marketing to manufacturing, is using Artificial Intelligence (AI) to facilitate the delivery of mass-personalization, yet education has been slow in its adoption. These smart systems create personalized solutions targeted to meet the unique needs of every individual.
Artificial Intelligence-based technologies have the potential of serving as tools for educators to provide personalized learning. However, for mass-personalization to work, institutions first need to align their leadership. In his feature session What Is It Going to Take to Move from Mass-Production to Mass-Personalization?, during the recent Online Learning Consortium virtual event, Dale Johnson, Director of Digital Innovation at Arizona State University, addressed the issue of mass personalization in higher education.
Johnson explored factors such as faculty development, policy innovation, pedagogical transformation, and technology adoption. Johnson gave higher ed leadership attending the virtual portion of the conference an overview into how higher education leadership can successfully accelerate the implementation of mass-personalization in education.
From mass-production to mass-personalization: Are we there yet?
Johnson said the structure of the current educational system can be traced back to Ancient Greece, where the amphitheater was a primary means for mass-production of education courses. “One hundred and fifty years ago, we were still using amphitheaters, 50 years ago, we had amphitheaters. Even 20 years ago, we switched to whiteboards but we were using amphitheaters. And today, many of our students are still utilizing that same technology overlaid with the new technology,” he said.
The layering of technology on the old mass-production model is not transforming the teaching or the learning process sufficiently, according to the institutional research conducted by ASU. “We need to get away from that mass-production model layered with technologies,” said Johnson.
What is mass-personalization for education?
Johnson reinforced the idea that with mass-personalization professors can deliver the right lesson to the right student at the right time. “This goes to the heart of the uniqueness of every student,” he said. Instead of assuming everyone was at the same starting point in the curriculum and instructors advancing whether the students were ready or not, ASU introduced new principles of action.
In order to design principles for action, higher education leaders must align and work as a team, Johnson explained. ASU developed design principles to guide the college algebra transformation program which resulted in the following model:
- Each student has unique learning needs
- Students learn best by solving problems —not by watching someone else solve them
- Students must demonstrate mastery of each lesson to advance
- Professors must use diagnostic data to provide individualized instruction
- Course design must provide a test-when-ready process for summarize assessments
Mass-personalization software does not replace the professor. It makes the professor better, more focused on the students. “ASU’s mass-personalization module enables student success,” Johnson said, and it follows these objectives:
- Improve critical thinking and problem-solving by doing 60 minutes of math problem-solving daily
- Increase student-subject mastery by helping 90 percent of students get C or better
- Increase student retention by reducing withdrawal rate to under 5 percent
- Improve instruction insight
- Identify struggling students by week two
According to Johnson, ASU’s freshman retention in 2020 was 89,4 percent, very close to their goal of 90 percent. He believes that the model of mass-production --to deliver the same lesson to all students at the same time-- does not work and it has never worked. The reason is simple: Because as individuals, students are all different.
Reversing the educational process by building a new model that will make the existing model obsolete
In 2016, Arizona State University (ASU) began its transformation from mass-production to mass-personalization in college algebra by reversing the relationship between technology and teaching. According to Dale Johnson, by 2017, almost 1,000 additional students had successfully completed the course in addition to the ones who had completed it in the past.
Rather than the professor being at the center of the instructional process delivering content to students who later on can use technology to practice the lessons, ASU’s new approach places the technology at the center of the instructional process. This change is revolutionizing the future of higher education.
Aligning leadership toward successful mass-personalization
ASU’s main goal with mass-personalization is to deliver the right lesson to the right student at the right time. In order to achieve this, ASU had to realize the individuality of each student and design principles for action. And to do this, ASU had to align its leadership.
Johnson explained that in order to succeed during the transformation adopting mass-personalization, leadership in institutions must work together aligning the leadership on four levels. In addition, instructors must trust the technology to deliver instruction and insight.