Adaptive education is a method of teaching and learning in which the teaching mechanism (typically a digital platform) adapts to the learner. While tests have already been developed that become more or less difficult depending on the participants’ answers, adaptive teaching in the learning environment is used for more than assessment. Eduventures describes it aptly as, “heavily automated digital learning platforms driven by predictive modeling, learning analytics, and the latest research in brain science, cognition and pedagogy.” While the idea of adapting educational delivery to meet student’s unique needs and abilities is nothing new, using technology as the central drive of these efforts is more contemporary.
Adaptive education is often adopted in online and remedial learning environments, which have traditionally been in great need of personalized and tailored learning enhancement. STEM fields have frequently been a focus for adaptive education systems and it has also been used in post-secondary settings. While some forms of adaptive learning systems can be used in isolation online, some interaction with and guidance from an in-person instructor is usually included and helpful. Adaptive education is often delivered through web or mobile apps, desktop apps and/or can be integrated into curriculum in any subject.
In some cases, an instructor may come to serve as more of a coach or tutor, encouraging a student who is participating in a self-guided learning experience. In this role, teachers can be more receptive to their students, who become more empowered learners. Rather than delivering content, teachers can teach problem-solving skills, review material with students and help them to attain mastery. Ideally, the data from the adaptive learning tech can help teachers to know where students are stuck and where they are succeeding. As students provide responses and feedback to questions, experiences and tasks, both directly to the teacher and through the learning platform, their educational experience becomes increasingly more personalized—it adapts to them.
CogBooks is one example of a cloud-based adaptive learning system. When educational institutions use CogBooks, educators have access to up-to-date, real-time data on how their students are progressing. The platform aims to increase the proficiency and efficiency of the time teachers spend working with students—their site claims it will “minimize the time you spend managing students and maximize their preparedness for class, freeing you up to do more of what you do best — teach.” CogBooks shares that a pilot study at Arizona University had positive results: students success went up 24 percent, dropouts went down 90 percent and student reviews were 80 percent positive. This platform received a $2 million grant from The Bill and Melinda Gates Foundation to create more courses in higher education.
Carnegie Mellon’s Open Learning Initiative (OLI) is another example of adaptive learning tech. It offers free online courses, whose designs are based on the university’s extensive research into best practices. The courses align learning materials with student experiences and performance and provide continuous, personalized feedback. Eduventures shared that students using this platform in an introductory statistics course had similar test scores and learned the content in half as much time. They also point out that not all schools can carry out adaptive education programs to the premiere level that Carnegie Mellon can and that the platforms are traditionally expensive for institutions to set up and run.
As technology races forward and evolves quickly, there will undoubtedly be many forms of educational tech that come and go. Data-driven, digital adaptive learning seems to be earning a valid position among other more traditional teaching methods and it will be interesting to see where and how it is utilized in the future.
Written by Julia Travers
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