Adaptive Learning Systems: Everything you Need to Know

In recent years, growing classroom sizes have significantly affected the ability of educators to personalise their learning.

However, with the emergence of adaptive learning systems in education, schools have been afforded the perfect remedial solution.

In this article, we will cover: 

• What adaptive learning systems are
• How adaptive learning machine learning works
• Why adaptive learning paths are essential to the classroom

What are Adaptive Learning Systems

Adaptive learning systems are educational tools that leverage the power of data, algorithms, and AI to provide students with a uniquely personalised learning experience. They continuously monitor student performance – typically by way of assessments – and subsequently make content adjustments based on the level of progress achieved.

In essence, adaptive learning systems are responsive learning tools that help students improve their attainment by administering targeted course materials and assessments.

How does Adaptive Learning Work

To ensure adaptive learning paths are appropriately personalised, the technology must first become familiarised with a student’s baseline knowledge. This understanding is typically achieved through a digital diagnostic assessment; however, certain tools, if required, can incorporate pre-existing student data instead.

Did you know: Adaptive learning systems don’t always follow the same approach to diagnostic assessment. Whilst some test students on their entire content mastery, others focus on unit topics and subtopics and are therefore segmented throughout a course.

Once the student has completed this diagnostic assessment, adaptive learning machine learning relies on measurable criteria – known as “adaptivity factors” – to determine how best to adapt to the specific individual. This dictates the content, pace, and difficulty of future assessments and teaching resources that are 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 example, where misconceptions around a specific subject matter are demonstrated, real-time hints and tips may guide the user towards the correct answer.

Alternatively, if a student is showing clear signs of struggling in a specific area, the adaptive learning system will assign more material and tasks to complete until content mastery has been achieved. Meanwhile, a learner who has demonstrated a thorough understanding of a topic will be fast-tracked to a new area that advances their learning.

Benefits of Adaptive Learning

Adaptive Learning Paths Improve Student Confidence

Adaptive learning systems are designed to ensure no student is left behind, meaning course progression is only actioned or suggested once a minimum level of performance has been achieved.

So, whilst students with proficient topic understanding are equipped to speed up or increase the challenge of their study, slower learners can pause and replay their program at a more appropriate intensity.

This means an adaptive learning course can empower students to become active learners, allowing them to develop a real sense of ownership over their education, and subsequently helping the classroom become an environment of self-assured learners.

Adaptive Learning Strategies Save Vital Teacher Time

Generating teaching material that addresses every student’s unique needs takes a lot of preparation – time that most teachers don’t have. With adaptive learning research, the program can perform this time-consuming task for you (and at a much faster rate!). 

So, instead of constantly trying to figure out each student’s level of knowledge — which changes from day to day and even class to class — an adaptive learning course allows you to easily decode what each student knows or needs to work on.

This means that rather than spending the class period lecturing or administering quizzes, teachers can assign targeted homework assignments to facilitate deeper understanding among each student. And with this freed up time during class, educators can introduce fun and creative lessons, encourage discussion based on common misconceptions, or set up group projects to challenge and enhance student learning.

Ultimately, adaptive learning in education allows you to focus on classroom dynamics, assessing personal character and wellbeing – important areas that may not have been given sufficient attention under normal circumstances.

Varied Adaptive Learning Materials Improve Engagement

Due to their association with tests, large volumes of continuous questions can be intimidating to students. However, content variety and less “formal” testing allows students to participate in high-volume learning without destroying their willingness and capacity to engage with course material.

With adaptive learning solutions, various digital content – such as text, videos, quizzes, and interactive exercises – can be administered as formal and informal methods of assessment.

Digital Familiarity: The current generation are accustomed to using technology in their personal lives. As a result, using adaptive learning materials in the classroom will seem natural – and most likely feel more engaging than reading a traditional paper-based textbook.

Adaptive Learning Machine Learning Forms Impartial Judgements

Unfortunately, as humans, we can naturally form biased opinions about students based on past situations and events. This can, inevitably, influence what we think our students can and cannot do, and therefore how we elect to teach them. Thankfully, adaptive learning systems do not harbour any preconceived judgments about students.

Thanks to their completely objective evaluations, adaptive learning materials can be delivered in a consistent and unbiased manner.

Adaptive Learning Algorithms Support Formative Assessment Evaluations

An adaptive learning course collects highly valuable data at a granular level, enabling the teacher to focus on a student’s specific areas of progress and need. It also provides reporting on a panoramic level, allowing educators to surface common strengths and weaknesses of the whole class.

What’s more, predictive analytics can estimate a student’s future performance, detect gaps in knowledge, and help educators understand what exactly an individual or class needs to work on before a student falls further behind. This is delivered through adaptive learning algorithms that provide actionable metrics about each individual student’s proficiency, study habits, and more, allowing educators to effectively differentiate instruction and guide students toward specific learning goals.

Experts have called this the “Swiss cheese effect”, where holes in knowledge persist over time, haunting students as they move forward into new areas of study. For example, if a student is unable to balance equations and lacks other core algebra skills, they may suffer later in chemistry.

Ultimately, adaptive learning systems show teachers exactly where students are struggling – helping educators more easily identify and close these gaps before they get worse.

Top 10 Adaptive Learning Systems

EdTech Impact hosts a wide range of adaptive learning apps and adaptive learning solutions for classroom implementation. To help you kickstart your research into this technology, these are our ten highest-rated adaptive learning systems:

	SAM Learning Thousands of pre-made learning activities across GCSE and KS3 subjects with various activity types, such as quizzes, tests, and real-world scenarios.
	Educake Online assessment and revision platform for secondary school students, allowing teachers to administer specification-matched materials.
	Century Reduces teacher workload and accelerates student learning by identifying learning gaps and filling them with recommended content instantly.
	Atom Prime Teacher-made content, automated marking, adaptive technology, and at-a-glance student performance analyses to save teachers time.
	Lexia Reading Software Lets students dictate when, where, and how their literacy learning takes place, and provides reports that enable tailored instruction.
	Tassomai Tailored multiple-choice micro-quizzes that are complimented by concise explainer videos and curated links to external resources.
	Spellzone An eReader app featuring finger tracking, text to voice, and letter colouring, KOBI is an excellent reading tool for learners with dyslexia or ADHD.
	Maths-Whizz Suite Virtual tutor that mimics effective human behaviours by assessing students across various math topics and creating targeted learning plans.
	Eedi Combines AI-powered learning paths with live tutor support to overcome personalisation obstacles and teacher shortages in education.
	Learning by Questions A classroom app featuring curriculum-aligned question sets and instant feedback to enhance learning, as well as automated marking.

Closing Thoughts

Adaptive learning systems 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!

So, now that you’re familiarised with adaptive learning systems, why not explore the wealth of adaptive learning technology solutions available on EdTech Impact?