Adaptive Learning: Is it changing the educational landscape?

Adaptive Learning is a new learning model that has the potential to transform the way students access and engage with educational content. This learning model utilizes technology to personalize learning for students as it uses data analysis to determine what educational content is conveying the knowledge it sets out to provide. At its core, adaptive learning is driven by data. This new learning model “can respond to a student’s interactions in real-time by automatically providing the student with individual support” ( Adaptive Learning can be both content driven and assessment driven. Content driven adaptive learning means that “the dashboard output links a specific course’s content inventory within a system of standards or learning sequences” ( Assessment driven adaptive learning may include real-time adjustments to content based on student performance. Proponents of adaptive learning claim that it has the capability “to significantly innovate teaching and learning in remarkable ways” ( Adaptive Learning strategies include personalized lessons and assessments, and allow for educators to analyze data concerning student habits related to student success. 

The following video provides more insight on adaptive learning and how it can be used:


Teaching approaches including pedagogy, andragogy, and heutagogy, differ from one another in the way that learning is administered. Pedagogy refers to the method and practice of teaching, specifically with children. Within pedagogy, the curriculum is likely to be very structured. A student may have limited resources,  and will most likely be dependent on an instructor for information, motivation, and scheduled curriculum (usergeneratededucation). In this learning environment, students are learning with the goal of advancing to a new level. Andragogy also refers to the method and practice of teaching, however focusing on adult students. Students learning from an andragogy approach are most likely a bit more independent. In this approach, motivation stems internally from the student, and the role of an instructor is not to create rigid curriculum, but rather to guide students and create a collaborative environment. Students begin learning either to further advance their skills to complete tasks successfully, or when they experience a “need to know” (usergeneratededucation). A third learning paradigm, heutagogy, differs the most from the previous two, in that is focuses on learning that can occur anywhere in different creative ways. Heutagogy can be defined as the study of self-determined learning. Within heutagogy, learners are interdependent, learning from not just an instructor but also each other. Learning is not mapped out within heutagogy, and learners do not only focus on solving problems, but also engage in learning through interaction with others, reflections, and experiences, and the role of an instructor is to help develop a student’s learning capability. Overall, the three differ from one another in the ways students and teachers interact, in the individual motivations and goals of students, and how learning is structured, as mentioned above. 

That all being said, Adaptive Learning falls into both the pedagogy and andragogy learning paradigms. First of all, Adaptive Learning still works within a course curriculum set by an instructor. A student is still dependent on the resources provided by the instructor, which is one aspect of a pedagogical approach, and along with that, motivation is still largely derived from external courses, fitting within the pedagogy paradigm. Although education through Adaptive Learning may still be structured by an instructor and foster dependence, Adaptive Learning may also fall into the andragogy paradigm. Lessons that are adaptive provide a personalized learning experience that will not necessarily be mapped out by an instructor. As students within the andragogy paradigm are independent and learn on a need-to-know basis, adaptive lessons provide information based on what areas students have shown to be struggling in. The Knewton company is building an adaptive platform that will do just that. The company’s site explains that “Beyond ordinary homework assignments, students who didn’t show mastery of the concepts they were learning received adaptive follow-up assignments powered by Knewton. These adaptive assignments present a personalized sequence of questions designed to address each student’s individual strengths and weaknesses” (Knewton). Adaptive learning provides students with the power to focus on areas of interest as well as areas that they may be struggling in.

In the future, I believe that there may be mixed reactions to Adaptive Learning. First of all, although I believe that adaptive learning can be a powerful tool in higher education, it seems like there may be some push back, from faculty and students. Students may see extra lessons that have adaptive to their performance as unnecessary, and faculty may view real-time updates on course material as making their jobs as educators irrelevant. In a survey conducted after testing adaptive technology on students, only 33 percent of undergraduate students said they were satisfied with the software (Inside Higher Ed). Instead of simply rejecting the model as a whole, educators should learn all they can about adaptive learning technology, and provide clear information to students about how it works, as well as its benefits. In a blog post about adaptive learning, the author states, “one reason that you need to understand how it works is that you need to decide how much you trust the software to do what it claims it can do” ( Secondly, despite minor concerns, adaptive learning technology can absolutely increase student success, which will make it appealing to educators in the future. Using data to tailor lessons to students has the potential to increase student success by providing information based on what the needs of students are. In a study conducted by Knewton, scores were compared between two groups of students, one group using adaptive learning and one using traditional methods. The results showed that “improvement increases with more use of adaptive assignments” as they saw an average increase of four percentage points (Knewton). This increase in performance is also helping to reduce the gap between high performing students and low performing students. Lastly, some say a benefit of adaptive learning is that it may lower costs for institutions while substituting instructor labor with technology, however that has not yet been shown to be completely true. Inside Higher Ed found that “course costs in most cases increased the first time instructors started using adaptive learning software, though when the instructors offered the courses a second and third time, costs fell in seven out of 10 cases” (Inside Higher Ed). So there is hope for the future that costs may begin to fall.

In a final note, as I have previously mentioned, Adaptive Learning falls into the pedagogy and andragogy learning paradigms, but I am interested to see how it may continue to grow and begin to meet qualifications of a heutagogy model. The Knewton company website briefly mentions the organization of educational content by tags on their adaptive platform, which is an interesting concept that may increase student independence and foster a new way of learning. Students, especially millennial students, are most likely already familiar with searching for content using tags, so it makes sense to apply that idea to education. I believe that would be one step closer to creating an environment where students can learn anywhere, anytime, and from many different sources, as would occur in a heutagogical paradigm. I would like to see this shift occur within Adaptive Learning.


For more information, check out the following sites:

Adaptive Learning Technology: What It Is, Why It Matters

What Faculty Should Know About Adaptive Learning


Related Vocabulary:

Adaptive Learning Adaptive learning utilizes technology to increase student success; A form of personalized learning that utilizes observation to create informed educational decisions aimed at improving student success
Big Data New sources of large and complex sets of information that are being utilized for analyzation
Competency Based Learning A strategy that creates flexibility in the way students earn credit in a course and increases opportunities for personalized learning
Student-generated Content Content that is produced by or added to by any web user/the general public
Hybrid Learning Courses that utilize both face-to-face learning and online learning in ways that complement both styles
MOOC(s) A Massive Open Online Course is a model that allows for educational content to be delivered to anyone who desires to take a course; MOOCs have no limit on who can participate or how many students can participate
Open Educational Resources Open Educational Resources (OER) use the internet to share and spread educational content, providing free accessible information that is making education more accessible around the world
Differentiated Learning Using programs and tools that use creative methods to deliver educational content based on individual learning styles of each student
Prior Learning Assessments A prior learning assessment is an evaluation tool that allows for students to earn credit for knowledge gained through either informal or formal past education.
Game-based Learning Game-based learning creates virtual environments that are relevant to students and allows for students to interact with course material multiple times in a risk free setting–what-it-is-why-it-works-and-where-its-going.html
Gamification Using game design and mechanics to drive motivation and increase student engagement in learning
DIY U DIY U is a book written about the changing future of higher education with the incorporation of new technologies
Flipped Classroom A reverse teaching method where lectures are viewed at home by students, and class time is spent working on projects/exercises
Connectivism A way of learning that utilizes the ideas of defining something in a social and cultural context
Content Curation Gathering and organizing educational information on an area of interest and representing it
Digital or virtual badges Virtual badges are representation of skills earned that can be displayed online, allowing a person to verify skills

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