Adaptive learning: What is it and how does it improve student performance?

 

Adaptive learning: What is it?

Each student's abilities and performance are taken into account while designing courses, readings, practice exercises, and examinations using the "adaptive learning" approach.

Personalized learning is made possible by artificial intelligence and machine learning, which "adapt" each learner's learning path in real time. The data gathered by adaptive learning software can then be reviewed by administrators and faculty to determine the needs of individual students or groups of students enrolled in a course. In order to achieve such needs during a term, they could then adjust training and a course in between terms. Similarly, students can use information about their performance and skills to adjust their learning methods.

The platform or underlying technology that numerous courses may be built on is frequently referred to as "adaptive learning software." Adaptive courseware is a term used to describe a set of online lessons and practice problems for a particular course that utilize an underlying adaptive learning system. Publishers of adaptive courseware frequently develop a library of lessons, practice problems, content, and assessments on a particular subject from which instructors can select, organize, and alter for their own course.

According to Every Learner Everywhere and its network partners, adaptive learning has the potential to enhance equality in higher education, particularly for students who are Black, Latino, Indigenous, or affected by poverty, by improving course outcomes and lowering the cost of course materials.

That prospect does, however, come with certain limitations. Schools are receiving "faux adaptive" software that falls short of expectations, and algorithmic bias may make software a tool that widens rather than reduces equity inequities. Even with top-notch technologies, successful adaptive learning outcomes depend on several factors, such as implementation guided by research and student-centered, equity-focused instructional design.

What Is the Process of Adaptive Learning?

At its most basic level, adaptive learning software assesses a student's understanding of a subject or skill in real time and then dynamically adjusts the next lesson or practice activity that is assigned to that student in order to boost learning.

For example, think about a unit in a college course that covers 10 new concepts and concludes with an examination before the class moves on to the next one. Assume that the quiz's historical average score is 70% and that there are 100 students in the class.

Expert teachers know that there is no conventional explanation for why 30% of exam questions are missed, even though there is an average score. It could be that:

• The final three ideas in the unit were difficult for Student A to understand;
• Student C may have had a single essential concept that impacted 30% of their score, while Student B struggled to understand three distinct concepts.
• The fact that the "new" ideas weren't novel at all caused Student D to become uninterested;
• Additionally, it's possible that Student E missed crucial classes because of work or family obligations rather than having an issue with the content.

A college instructor committed to individualized learning faces the challenge of understanding and satisfying the needs of each of those students before the unit exam is over and the class moves on to the next unit.

Adaptive learning software works by quickly identifying the particular concepts or skills that are critical to each student's growth. Additionally, some software tools evaluate students' comprehension of the material, distinguishing between "performance data" and "engagement" data, such as logins and time spent on task. After applying artificial intelligence and machine learning techniques to analyze data on the learning paths and performance of previous students, the adaptive learning software then shows what it believes to be the optimal review or practice exercise for each current learner.

As a result, each student utilizing adaptive learning courseware will have unique, nonlinear learning paths. One student will see a reminder and a few new practice questions from a bank of quiz questions, while another will receive the original lecture on a certain topic and another will be directed to more resources for a different concept.

In its hypothetical unit quiz example, the adaptive learning program may increase the average quiz score over the historical norm. Better learning outcomes at the end of the term and throughout the degree program should result from more students understanding the topic.

In the meantime, the adaptive learning software provides information that the teacher may use to adjust their lectures before moving on to the next unit, as well as information that each student can use to understand and direct their own progress.

Advantages of Flexible Education

When applied appropriately, adaptive learning can offer tailored learning tactics such as scaffolding, adaptability, and targeted instruction and resources. In a study of adaptive learning pilot projects funded by Every Learner Everywhere, faculty reported using the technology to support evidence-based teaching practices, such as clear learning objectives, low-stakes formative assessments, immediate feedback on practice activities, and information on how to improve.

Other potential advantages of adaptive learning include:

• As a result, students might be more successful and self-sufficient. When students receive data from adaptive learning software about their strengths and weaknesses, they know where to concentrate their efforts.
• It allows students to study at their own pace by skipping over previously taught material and going over and studying other topics more slowly.
• Student involvement may rise if classes and activities are tailored to each student's requirements and readiness level.
• It could be a cost-effective alternative to expensive textbooks.
• It provides a framework that guarantees that lessons, practice problems, assessments, and course objectives are consistent with one another and shows students how each course component relates to the course's objectives. When students are having trouble understanding a subject, faculty may also evaluate whether certain teaching components aren't well aligned with the objectives.
• The timely and relevant data it provides can be used by administrators and faculty to assess how well specific subpopulations in a course are performing. This essay on dissecting learning data suggests that this could be a highly successful strategy for identifying and resolving barriers to equity for students from marginalized communities and those experiencing poverty.
• Teachers and administrators can give timely, targeted assistance by recognizing which students or even sections of a multi-section course require attention.
• It assists instructors and administrators in making continuous changes by comparing data from different semesters.