November 2024 — Search and compare the best Adaptive Learning Platform for your school. Compare customer reviews, features and pricing, or learn more in our Adaptive Learning Guide.
Strengthen your understanding of adaptive learning systems and discover EdTech Impact’s top-rated solutions with our in-depth guide.
We've been evaluating the EdTech marketplace since 2019, empowering educators to make informed decisions, and to help providers increase the quality of their products.
Read more about our mission, our quality framework and reviewer guidelines to learn how we keep EdTech Impact a collaborative and trustworthy place for everyone.
#10 in Adaptive Learning
Free TrialPaid
0-4, 5-7, 8-10, 11-13, 14-16
#13 in Adaptive Learning
Free TrialPaid
5-7, 8-10, 11-13, 14-16, 17-18, 19+
#16 in Adaptive Learning
Free VersionFree TrialPaid
5-7, 8-10, 11-13, 14-16
1 award
In recent years, growing classroom sizes have significantly affected the ability of educators to personalise their learning. However, with the emergence of adaptive learning platforms in education, schools have been afforded the perfect remedial solution.
This guide will cover:
Adaptive learning platforms use data-driven insights and algorithms to create an effectively personalised learning experience for every student. Through real-time adjustments to content, pace, and instruction, they allow learners to progress at their own pace and focus on areas where they need extra support.
In essence, adaptive learning platforms serve as responsive learning aids, delivering precisely tailored course materials and assessments to enhance student achievement.
To ensure the proper personalisation of adaptive learning paths, the technology must initially familiarise itself with the student’s foundational knowledge. This understanding is typically achieved through a digital diagnostic assessment or by integrating pre-existing student data.
Adaptive learning platforms can vary in their approach to diagnostic assessment. While some may assess students on their overall content mastery, others will focus on unit topics and subtopics, which are then distributed throughout a course.
Once the student completes the diagnostic assessment, adaptive learning machine learning relies on measurable criteria, termed “adaptivity factors,” to determine the most effective adaptation for the individual. These factors influence the content, pace, and difficulty of future assessments and teaching resources delivered to the student.
Finally, throughout an individual’s learning, adaptive learning solutions leverage data analysis, algorithms, and AI to deliver real-time adjustments to course material. This ensures the student’s needs are always targeted through personalised administering of content.
For instance, when a student demonstrates misconceptions in a specific subject matter, real-time hints and tips may be provided to guide them toward the correct answer.
Conversely, if a student exhibits signs of struggling in a particular area, the adaptive learning platform will allocate additional material and tasks until mastery of the content is attained. Meanwhile, a learner who exhibits a strong understanding of a topic will be expedited to a new area that fosters further advancement in their learning.
Adaptive learning platforms prioritise student progress, ensuring advancement occurs only after reaching a minimum performance level. This approach prevents any student from being left behind.
So, students who have achieved proficiency can accelerate or intensify their study challenges, while slower learners can adjust the pace to revisit material as needed.
Thus, adaptive learning empowers students to take control of their education, fostering a classroom environment where learners develop confidence and ownership over their learning journey.
Preparing teaching materials tailored to each student’s unique needs demands significant time and effort—resources often scarce for teachers. Adaptive learning research offers a solution by efficiently performing this labour-intensive task, enabling teachers to reclaim valuable time.
So, instead of constantly trying to figure out each student’s level of knowledge — which can vary daily and across classes — an adaptive learning course allows you to easily decode what each student knows or needs to work on.
This shift allows teachers to redirect classroom time from traditional lectures and quizzes to assigning targeted homework assignments. Freed from routine tasks, educators can introduce engaging activities, foster discussions on common misconceptions, or organise collaborative projects to deepen student understanding.
Ultimately, adaptive learning in education enables educators to focus on classroom dynamics, nurturing students’ personal development and well-being—areas that may have been overlooked previously.
Ultimately, adaptive learning in education enables educators to focus on classroom dynamics, nurturing personal development and wellbeing – areas that may not have been afforded sufficient attention previously.
Due to their association with tests, large volumes of continuous questions can be intimidating to students. However, incorporating diverse content and less formal testing methods within adaptive learning platforms can sustain students’ willingness and capacity to engage with course material.
Adaptive learning solutions offer a range of digital content formats, including text, videos, quizzes, and interactive exercises, serving as both formal and informal assessment tools.
Digital Familiarity: Today’s learners are accustomed to using technology in their daily lives. Consequently, integrating adaptive learning materials into the classroom feels natural to them and is likely to be more engaging than traditional paper-based textbooks.
Unfortunately, as humans, we are prone to forming biased opinions about students based on past experiences. This can inevitably influence what we think they can and cannot do, and therefore how we elect to teach them. Adaptive learning platforms, however, operate free from such biases.
These systems provide completely objective evaluations, devoid of preconceived judgments about students. As a result, adaptive learning materials can be delivered consistently and impartially, ensuring fairness in the educational process.
An adaptive learning course gathers invaluable data at a detailed level, enabling teachers to pinpoint specific areas of student progress and need. Additionally, they offer panoramic reporting, unveiling common strengths and weaknesses across the entire class.
Moreover, predictive analytics within adaptive learning algorithms forecast a student’s future performance, identify knowledge gaps, and provide insights into what individuals or classes need to focus on to prevent further academic setbacks. These algorithms furnish actionable metrics on each student’s proficiency and study habits, enabling educators to tailor instruction effectively and guide students toward defined learning objectives
Educators often refer to this phenomenon as the “Swiss cheese effect,” wherein knowledge gaps persist and hinder students as they advance into new subjects. For instance, deficiencies in core algebra skills can impede later success in chemistry.
Ultimately, adaptive learning platforms show teachers exactly where students are struggling – helping educators more easily identify and close these gaps before they exacerbate.
Adaptive learning platforms are an increasingly popular EdTech solution. Not only do they offer multiple advantages, but their technology is easily implemented.
This buyers’ guide, by providing a precise set of questions for effectively embedding adaptive learning in the classroom, teaches you how to navigate this ever-growing market.
Remember to stay organised as you compare solutions by making notes and scoring each solution in a spreadsheet. Best of luck!
Updated on: 26 February 2024