Use of Big Data for Adaptive Learning: How Analytics are Shaping Specialized Education

Introduction

In this era of technological advancements, many software and strategies have been introduced to enhance the quality of education.

Big data has been used in other sectors, including education, and is mainly focused on adaptive learning. Data collection provides information about each student, which helps teachers discover insights and knowledge to shape new learning models and concepts.

Thanks to these new developments, every student can now get the education they need and deserve. In this article, we discuss what Adaptive Learning is and the role of big data in education.

What Is Adaptive Learning?

Adaptive learning is a powerful tool that personalizes lessons to suit the need of each student by using data. By tracking individual strengths and weaknesses, it helps identify levels of engagement, performance, and areas for improvement.

As students interact with the platform, real-time data is collected to adjust the learning experience based on their learning style.

Gamification in education enhances adaptive learning by making the process more interactive and engaging. It encourages students to stay involved while the system continually gathers data to refine and personalize their learning journey. Additionally, Big Data provides in-depth analytics on students and their environment, enabling these platforms to improve continuously.

The Role of Big Data in Adaptive Learning Systems,

Big Data is shaping the future of artificial intelligence as it automates and accelerates data presentation tasks to train AI algorithms.

Without Big Data, adaptive learning platforms wouldn’t have the information needed to personalize the learning experience of each student.

The systems collect information such as students’ approach to learning, learning behaviors, and how they engage in tasks. All this information is added to the big data pool so that their algorithm can find patterns, which are then used to ensure future learning methods fit the students’ strengths.

With big data, the systems can detect subtle signs, such as a student taking too long to answer a question. The system can do something to help, like make the next question easier or give a hint to pass the question.

Adaptive Learning systems also have trackers that study how long it takes a student to succumb to distractions. This gives the system an idea of the student’s attention span and uses the information to break down future lessons.

The Importance of Adaptive Learning

Adaptive Learning can benefit teachers and students in several ways. So, let’s look at its importance in education.

1. Improved Engagement: Traditional teaching styles often fail to engage students because they focus only on giving information, not on how students understand it. An Adaptive Learning System considers both the content of the learning material and how students process it. It keeps students engaged by assigning tasks with personalized difficulty, deadline, and assessment style. This leads students to actively participate in class rather than feeling bored or frustrated.

2. Faster Progress: According to the US Census Bureau, educational attainment in the United States is at its highest since 1940. This is a positive aspect but it comes with its problem, which is carrying the entire class along without slowing down.

These platforms allow teachers to break their classes into groups with similar learning patterns. By doing so, the teachers can give the required attention to each group, thereby increasing the learning pace.

3. Improved Understanding: With the traditional teaching method, it is hard to ensure every student in the class understands what they are being taught. The teachers only ask generally if students understand and most of the time the students are too shy to answer.

This is eliminated when students have personalized apps for learning. Adaptive learning platforms analyze students’ learning patterns, identify where improvement is needed, and ensure they understand these parts before moving to the next.

4. Real-Time Feedback to Help Teachers: These learning platforms analyze students’ performance and provide feedback to help teachers address challenges and elevate learning experiences. With access to this information, teachers can discover knowledge gaps in students and deliver instruction more practically and efficiently.

5. Compatible With a Variety of Learning Styles: As said earlier, students have individual and varied learning styles. To improve student retention, schools must consider their learning style when teaching.

Visual learning, for example, is considered the most effective learning style, but it is rarely used in schools.

With Adaptive Learning apps, students can choose different learning styles like aural( e.g., audio materials), visual (e.g., diagrams, charts), or Kinesthetic (e.g., experiments, role playing). This allows students to receive lessons in the way that most appeals to them.

Examples of Adaptive Learning Software

The following are some of the popular adaptive learning softwares:

• Knewton: This tool provides insights about the specific part of the learning material each student doesn’t understand and suggests how to help them to teachers.
• CogBooks: CogBooks is an AI tool that develops personalized content, and continuous assessment, and provides data-driven feedback to improve students’ learning experience.
• Smart Sparrow: This is a digital learning platform that empowers educators to deliver learning experiences that lead to better learner outcomes.
• Impelsys Scholar ALS: This learning platform improves students’ learning experience by allowing them to self-monitor, break down course contents and provide reports to the teacher.

Wrapping up: The Future of Big Data in Adaptive Learning

The world has witnessed the application of big data in many aspects of life, but now is the time to apply it in the classroom.

According to Astute Analytica, there will be massive adoption of adaptive learning in schools and universities worldwide. Therefore, teachers who do not want to be left behind should use these platforms to implement teaching styles that align with student needs. This will allow them to focus on the necessary resources and support needed to improve.

Finally, Big data will allow institutions to use technology to advance the quality of their educational content to take learning to the next level. Likewise, they can take advantage of the adoption of AI in education software to personalize learning experiences.