All our life we focus on the fact that there is no end to learning. Though sometimes we all read and learn about the same things, we learn in our own unique pace and method. According to this huge education, a group/ class of learners is made to learn a standard course in a pace consistent for the entire class, but the truth is that we all have our individually unique pace of learning. Because of this, when a group of students are delivered the same lessons at the same pace, few students lag in comprehension while few others might learn faster.
The field of education is changing, and the change from whole-class instruction to interactive learning is already underway plus adaptive learning is helping to transform the education landscape in exciting ways. Adaptive learning is a concept wherein every student is provided with their own individual path of learning depending on how much they already know or what they need to know and the amount of time they need to comprehend a particular concept. It enables students to adjust their learning experience in line with their personal goals, for content that is relevant to them. Adaptive learning and teaching methods offer an opportunity to deliver personalized educational experiences, providing a path to navigate the uncertain waters ahead.
What is Adaptive Learning?
Adaptive learning has been with us for a while now. The history of this technology has been rooted in cognitive psychology, beginning with the work of behaviorist B.F. Skinner in the 1950s, and continuing through the artificial intelligence movement of the 1970s. Now, technologies once confined to research laboratories are being adopted by progressive industries. As a proven learning modality, it’s being used in many different environments to teach and train more effectively.
This type of learning is a computer-based and/or online educational system that modifies the presentation of material in response to student performance. The top rated systems capture fine-grained data and use learning analytics to enable human tailoring of responses. The associated learning management systems (LMS) provide comprehensive administration, documentation, tracking and reporting progress, and user management.
Problems that Adaptive Learning Systems Hope to Solve
Intelligent adaptive learning systems are quickly emerging but are still in experimental stages. The intended design of these data-adaptive solutions seeks to enable differentiated instruction at a personalized level of learning. New approaches to diagnostic and formative assessment design making use of adaptive intelligence are becoming more common. Adaptive learning systems are designed to dynamically adjust to the level or type of course content based on an individual student’s abilities or skill attainment, in ways that accelerate a learner’s performance with both automated and instructor interventions. These adaptive systems achieve this by helping to address learning challenges such as varying student learning ability, diverse student backgrounds, and resource limitations. The intent of these machine learning systems is to use proficiency and determine what a student really knows and to accurately and logically move students through a sequential learning path to prescribed learning outcomes and skill mastery. These specific features will transform first-generation digital learning systems. The advantages include, but are not limited to, the following:
- Automated processes of student assessment and the predictive analysis result in significant faculty time efficiencies.
- Adaptive systems have the potential to solve the primary and perennial problem in public education: the overwhelming challenge of teachers or faculty being responsible for accomplishing learning mastery among a demographically diverse set of students.
- Adaptive systems address the fundamentally different levels of prior knowledge, as well as course content progression based on students’ skill and outcomes mastery measurement, decreasing faculty load in teaching and remediation to teaching and facilitating.
- Executed effectively, the cost efficiencies in automated feedback and remediation without formal instructor intervention have shown major improvements in student learning.
- Adaptive systems encourage student ownership of their learning through automated feedback cycles prompting them to take action and advance independently of the class instructor.
- Adaptive systems conform to individual students’ varied lifestyles versus students having to conform to the system.
- Adaptive systems empower faculty. Rich data analysis of student progression enables faculty to continually improve course design.
- Traditional assessment methods inform both faculty and students too late in the learning cycle. Using timely and comprehensive data-driven feedback, adaptive systems can inform in real time.
Benefits of Adaptive Learning Technology
Adaptive learning has long been a part of education. The basic concept is simple: Coursework should be adapted to meet the individual needs of each student. Every teacher has experience modifying curriculum in some way to help students access information. Nowadays technology can help make the adaptations easier and more streamlined.
Many of the benefits that adaptive technology offers in online courses also apply to traditional classrooms. However, the nature of online learning means that some of the challenges adaptive learning helps to address are especially relevant to online students. When teachers and students don’t interact with each other regularly in person, as often happens with online courses, having a tool that helps pick up the slack becomes that much more important.
1. Students get a real-time response to their work.
Online students tend to work on their own schedules, completing assignments whenever they can find the time. Adaptive learning technology can help recognize the challenge they’re having and provide additional resources to help them work through it on their own, especially at times when a professor isn’t available to give help.
Students can also get a clearer idea of when they’re ready to move on. If they’re rushing to complete their work, it can be easy for students to assume they’ve understood what’s in a chapter and jump ahead – unless they have to take a quick quiz that shows what information they’ve retained. Adaptive learning tech will let them know when they need to slow down a bit and pay closer attention to the material.
2. Teachers get data with insights into student needs.
It can be difficult enough to keep up with the various progress levels of a class full of students they see every day, so recognizing the progress of online students can seem downright impossible for teachers. Especially when the only communication they may have with students is via email and Skype.
Adaptive learning technology tracks what and how each student is doing so that teachers can keep up with each student’s progress. If one student’s acing everything they do, the teacher know don’t need any intervention. But another student who is having a hard time getting past one particular lesson could be a signal to teachers to offer help the student extra help.
3. It decreases the risk of students falling behind and giving up.
Many students in the United States fail to complete school. 7% of high school students drop outbefore graduation and nearly half of the students who start college don’t finish within six years. Many of those students who don’t make it to graduation day are the kind of non-traditional students attracted to online learning.
Students trying to balance college with other big life responsibilities are going to have a hard time keeping up with the work. If they fall behind or especially struggle to get past a particular hurdle, they’re more likely to give up. Adaptive tech can help them get past those hurdles with a little extra help, or can alert the teacher in time to step in, so those students are more likely to receive their diplomas.
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4. It can make the already minimal interactions between faculty and online students more productive.
When students don’t have access to in-class time and office hours, making the most of any interaction they have with professors is paramount. Teachers don’t want to waste time on the stuff students already know, when what they need is specific help with this one thing that they just can’t figure out. The data produced by adaptive learning tech allows faculty to steer those conversations in the directions most important to helping the student succeed.
5. The technology actively uses research about how people learn.
Teachers know a lot about how students learn, but research has produced so much scientific data on learning that’s hard to remember and implement everything. Data like exactly how many times a person should encounter a piece of information in order to remember it, or what kind of time intervals there should be between encountering a fact and being quizzed on it, are easily programmed into adaptive tech.
The most powerful adaptive learning solutions constantly collect data over time so they can refine how well the product works and become even more valuable to student users. Every student using these products is getting the benefit of the data the technology collected on students that came before.
Future of Education with Adaptive Learning Technology
For all the years that adaptive learning has been in the market, there have been predictions that it is the future of education. The reason why it is given so much importance is because of its inclusiveness. It is disregarding of the level of interest, socioeconomic background or age. Adaptive learning has excellent chances to become the leading teaching and learning strategy in academic institutions, especially in institutions where students with physical or mental disabilities attend classes. These institutions have been for a long time under pressure in regards to improving student outcomes, and analysts believe that adaptive learning will become the primary education system. In order to understand the endless opportunities adaptive learning offers, and will offer in the future, it is essential to understand what is powering adaptive learning systems:
- Natural Language Processing (NLP) Programs:
These programs are intended to process and organize written content based on the input, listening and interpreting user feedback.
2. Conversational Interfaces:
These interfaces provide and enable communication on a more human level while using adaptive learning technologies that are AI or VR-powered. This would create a more meaningful intent from the learner.
3. Machine Learning Algorithms:
These are intended to build personalized pathways, monitor feedback and provide dynamic visualizations, which would in turn also provide valuable insight for both teachers and students
Since the inception of adaptive technology, there have been speculations that it will soon replace teachers and only provide online mentors and tutors. Even so, many believe that this scenario is just impossible, especially when it comes to working with impaired or disabled students. Of course, the improvement in technologies becoming more human has been incredible, but teaching professionals are indispensable, especially if we want the adaptive learning process to function in the future as well.
While AI-powered adaptive learning has limited data reach and mitigates with internal and cultural obstacles. The machine doesn’t understand the feeling and thoughts of a disabled student like the teacher or mentor does. Either way, the teacher can use AI and VR technologies to their advantage and perform their responsibilities in the best way. Having said that, there will always be a need for collaboration human and machine for adaptive learning to reach success.