What is Adaptive Learning and Why Has It Fallen Short So Far
When no two people have the same fingerprints, how can one teaching method work for everybody present in a class?
Students of the new generation are quite versatile and expect to learn in a similar manner. This discussion about no one size fits all led to the development of Adaptive Learning. When a student in a classroom has some trouble understanding a topic or a question, the teacher can make him/her understand it by giving a personal example to simplify things.
But larger classroom strength restricts this ability, to do so, a limited number of students or a greater number of teachers, either of the two is required, which is fundamentally not possible to do in an academic institution. Adaptive learning comes to the rescue. Adaptive learning is the modern-age technology that acts as a one-to-one instructor with the aim of emulating and supporting teachers and educators to enhance the learning experience of every student.
In a classroom, the course taught remains the same for every student, but the content to facilitate learning varies according to the learner’s level and speed of understanding, present knowledge, experience, and performance. This system leverages the technology of analytics and finely grained data. This helps the system to tailor the content according to their responses and works in real-time.
Even though it has been termed as a magic pill by an expert from the industry, the institutions utilizing its benefits are relatively low in number. What could be the reason for that? Why are academic institutions and course providers not making use of this technology to enhance the student experience and add a competitive advantage to their organization?
The institutions are optimistic about adopting adaptive learning, but only to an extent. It is a new branch of digital education, due to this reason, not many studies or research have been conducted proving the actual effectiveness of adaptive learning systems. There is a lack of evidence of effectiveness that makes it difficult for the institutions to put in their trust and money into this system. The credibility of this technology is yet to be proved and that is one of the major reasons why it has fallen so short so far.
Another reason for its lack of adoption is the cost that this technology comes at and with. Adaptive learning technology is created based on algorithms to cater to the personal and specific needs of the user. A lot of technological and research cost has gone into the development of this technology and that is why it is relatively expensive. Institutes are seen partnering to tailor the creation of these systems, but it involves high-risk pouring resources in hopes of creating solutions for the students.
As the education industry is also moving towards automation, there has been noticed a shift from the plain old teaching to managing learning and correctly and cognitively delivering information and education. Adopting adaptive requires dedication and commitment from both the parties – the educators or teacher and the learners or students. The educators will have to commit to changing their traditional ways of teaching and instruction patterns, which they usually resist. And, the students will also have to put in their dedication towards mastering the topics because these systems are based on the mastery format. This means a student cannot move on to the next topic if he or she has not mastered the on-going one. The students are at the mercy of the technology, instead of teachers. This makes them lose motivation because they come to a standstill until they achieve expertise.
Adaptive Learning solutions require Learning Management Software to act as a host. This is an added cost of adoption and maintenance. These together generate a lot of extensive data that needs to be stored and analysed. This is another challenge faced by the teachers. Most teachers do not possess analytical knowledge and skills that are required to analyse this data and also to store it. The data is stored in databases, while there is a constant change in the topography. They will have to learn how to analyse the student patterns data, which is again a factor contributing to demotivation and is faced by resistance. But all of this does not change the fact that adaptive learning is an algorithm-based expert-model that demystifies content and provides significant remediation to students to make them excel in a particular topic and course. This personalized courseware is quite popular in discussions, and with further studies proving its effectiveness, it will become popular in institutions actually adopting them too.