The Power of Adaptive Learning
MESSAGE FROM THE VP OF IT
Many years ago as a computer science teacher I had a classroom of students with a plethora of challenges... I mean opportunities. Generally there were 32 students from about as many countries, had varying levels of education in technology, some spoke excellent English, some spoke English as a second language, and others only spoke broken English with little to no knowledge of technical vocabulary. All of them needed to pass this class in order to move on in their major… did I mention they could only retake the class once else they needed to change majors? These students were generally very motivated to learn and pass the class, but the traditional teaching methods were not working.
In a very rudimentary way I tried to create a learning environment where they could pass the final exam, which by the way, was offered in many different formats: written, oral, and practical. Each semester I attempted to quickly determine several key learning factors to how they would be successful in the course. After a few years of developing a variety of learning, teaching, and testing aids/tools, the students began to be successful regardless of language, subject matter knowledge, or learning styles. But this was a lot of work for just one course, especially one that frequently changed content every few years.
The good news, personalized or adaptive learning is starting to show up in “mainstream” learning management tools including Instructure’s Canvas, which Weber State University uses.
“Adaptive learning in its fundamental form is a methodology that changes the pedagogical approach toward a student based on the student’s input and a predefined response. Educators recognize this as instruction based on the student’s success on previous levels of attainment. Adaptive learning more recently is being associated with a large-scale collection of learning data and statistically based pedagogical responses, and can be seen as a subset of personalized learning that includes such approaches as affective and somatic computing.”
“The real value of adaptive learning lies in the metadata attached to each learning “morsel.” That is why we see open tools for tagging so that anyone can tag educational content, even open educational resources (OER), to the fine-grained level that is needed for true adaptive learning (a type of crowdsourcing and big data collection). That learning morsel must then be combined with enough empirical data of students trying to master the topic to give statistically valid “personalized learning.”
According to Gartner, mainstream adoption and creation of a critical mass of these “morsels”, is still two to five years away.
“Adaptive learning has the potential to solve at least part of the biggest problem that faces education today: cost-effective scalability with retained and preferably improved quality.”
“The ultimate aim of adaptive learning in education is to enhance the learning experience of the student, which should result in tangible results such as higher grades, faster throughput and higher retention, preferably at lower cost to the student. A key accomplishment would be if adaptive learning enabled outcomes based on “any paced” learning. These results will benefit students, institutions and society.” Hype Cycle for Education, 2014, Jan-Martin Lowndahl, Gartner
As Chris Dede wrote in his article in the “Connected Age” issue of EDUCAUSE Review: “The primary barriers to [transformation] are not conceptual, technical, or economic. The primary barriers are psychological, political, and cultural. . . . Whether we have the professional commitment and the societal will to actualize such a vision remains to be seen.”
“Three years ago, I was asked to come up with a model for higher education in the future. As I looked at the world then, my experience told me that a linear path forward, from where an institution was at that time to where it might be in the future, standing alone, was likely a pathway to failure for most. So I assembled an informal team of innovative yet practical thinkers and posed the question: “If you could start with a clean slate, what is the institution and organizational structure that you would start with?”
After looking for a starting point for the conversation, we settled on the following additional questions:
- What would a learning model look like if higher education was situated not as a required passage but, rather, as a collaborator for clarifying and supporting the needs, desires, and goals of the learner?
- What would a learning model look like if it included certificates and degrees but only as an option (unless required by professional standards or law)?
- What would a learning model look like if learners could use existing resources to understand learning requirements and to design their own learning pathways with the support of mentors?
- What would a learning model look like if career and academic needs were treated as equal and complementary?
- What would a learning model look like if it was organized to begin with the learner’s current knowledge and build toward the learner’s goals?” Chris Dede, ed., “Connecting the Dots: New Technology-Based Models for Postsecondary Learning,” EDUCAUSE Review 48, no. 5 (September/October 2013).
Back to my classroom, many years ago. The need and desire for personalized learning paths and adaptive learning are not new. Thanks to wonderful tools that allow for classroom capture, the Internet, learning management tools, and social networking such as YouTube, the world of adaptive, personalized learning is not so far away.