đź“– Tutoring In The Palm Of Your Hands
AI-driven Intelligent Tutoring Systems enhance personalized learning through knowledge representation, adaptive content generation, and real-time analytics, fueling a growing education market.
Today's Highlights
- How AI is enabling intelligent tutoring
- This Week On BuzzBelow - a recap on this week's topics
- In Other News - a few interesting developments we're tracking
Artifical Intelligence (AI) is disrupting the education landscape in a big way. Among the various applications of AI in education, Intelligent Tutoring Systems (ITS) stand out as a revolutionary stride towards personalized learning. These systems utilize AI to offer a tailored educational experience, adapting to the individual needs and capabilities of each student. Let's explore some ways AI is enabling intelligent tutoring:
Knowledge Representation & Reasoning
Knowledge graphs and ontologies are used to represent and organize educational content systematically. Inference engines and reasoning algorithms enable ITS to deduce students' understanding and misconceptions, based on their interactions with the system.
Incorporating a cutting-edge AI assistant into the educational repertoire, Khan Academy recently introduced "Khanmigo," a pioneering tool aimed at enhancing the learning and teaching experience on their platform. Knowledge graphs and ontologies are instrumental in systematically organizing and representing educational content, establishing a structured foundation for intelligent tutoring systems.
Adaptive Content Generation
Advanced ITS leverages Generative Adversarial Networks (GANs) and other generative models to create new instructional material tailored to individual learners. Adaptive content generation can help in keeping the instructional material updated and aligned with learners' current needs. Powered by proprietary artificial intelligence technology, OBRIZUM's platform enables organizations in high-skill areas to automatically create, deliver, and monitor adaptive online learning and development materials.
Real-time Analytics & Feedback Systems
Real-time analytics are crucial for monitoring students' progress and providing immediate feedback. Bayesian networks, Markov Decision Processes (MDPs), and other probabilistic models are employed to estimate students' knowledge state and to decide on the optimal instructional strategies. Pearson’s Aida demonstrates problem-solving techniques to students and explains the practical applications of calculus. Students can either take a picture of their handwritten work or put in an equation. Aida analyzes student work and offers feedback on each line of a handwritten or typewritten problem using breakthroughs in deep learning.
The market for AI in education, of which ITS is a significant part, has been on a growth trajectory. In 2021, the global AI in education market was valued at USD 1.82 billion, and it is anticipated to expand at a Compound Annual Growth Rate (CAGR) of 36.0% from 2022 to 2030. By understanding and addressing the challenges inherent in this technology, the education sector can harness the full potential of AI to foster a conducive learning environment.
This Week on BuzzBelow
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Sukanya Ganesh
In Other News
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