Disengagement remains a problem in both traditional and online classrooms. An uninteresting one-size-fits-all learning approach is one of the significant factors contributing to student disengagement.
But thanks to the transformative role of technology in education, its ability to personalize learning experiences helps educators enhance their teaching methods beyond the traditional textbook-based- instruction.
Based on a forecast, the market for Global Personalized Learning will experience significant growth in the next few years. In particular, the market’s value is anticipated to exceed $2 billion by 2024.
What’s more, proper usage of big data analytics and artificial intelligence (AI) will further improve the market.
Read on to learn the role of AI in personalizing student learning experiences and how educational institutions can leverage it to resolve some of the most common educational issues.
Learning Behavior Insights Using Data Analytics
A substantial amount of student data is the critical ingredient of personalized learning. Teachers must familiarize themselves with each learner to understand their needs and adapt their instruction accordingly.
AI-enabled adaptive learning makes that possible. By using data analytics, adaptive learning platforms enable educators to assess learners’ strengths, weaknesses, and learning behaviors.
AI algorithms can analyze and interpret extensive amounts of student data. These may include their performance on assessments and engagements with learning materials. With real-time insights into students’ learning behavior, educators can easily fine-tune their strategies.
Likewise, AI-enabled adaptive learning systems use the analysis to adjust the learning material’s content, pace, and difficulty level to suit the learner’s needs. It also gives personalized suggestions and materials to assist students in areas they’re struggling with.
Early Learning Gap Detection Via Predictive Analytics
AI algorithms cannot only track a student’s progress. They can also uncover patterns and trends related to learners’ performance and behavior using predictive analytics. Based on student responses, the system can analyze the learning requirements.
Through such analyses, it’s possible to predict how the student will perform in the future or identify areas where they will encounter difficulties. Educators can detect early gaps in learning and provide timely interventions for at-risk students with targeted resources.
Since predictive analytics also offer personalized learning resources, students can focus on challenging areas, reinforcing their comprehension and retention.
Personalized Assistance By Employing Chatbots
With educational AI chatbots, learners can get personalized assistance with their learning tasks, concerns, and areas of interest. These software programs utilize natural language processing and generation to engage with learners through text or voice.
They can provide accurate and valuable guidance since they can understand and analyze student responses. Whether learners need help with specific subjects or areas, chatbots can give targeted advice by analyzing the student’s learning history.
Immersive Learning Through AR and VR
Using computer graphics and sensors, augmented reality (AR) and virtual reality (VR) enable students to practice their skills in a simulated environment. They allow them to learn from their errors in a safe and controlled setting.
However, these technologies can also customize the simulation based on the student’s preferences, actions, and feedback using AI algorithms. For instance, AI enables one or more cameras to provide motion-tracking data, making the AR or VR experience seamlessly blend with the learner’s point of view.
Leverage AI To Personalize Student Learning Experiences
Educational institutions must leverage AI tools to make learning more personal and helpful for students. But it’s important to remember that it should not replace human educators. Emotional support and human guidance remain indispensable for fostering student learning development.
Additional experimentation and research are essential to successfully implement AI tools in educational institutions. While there are still areas to work on, educators can now use adaptive learning platforms and AI-powered tutoring systems to provide personalized student learning experiences.