Okay, let’s talk about AI
If you are interested in the latest developments of AI in education and how it can transform the way we teach and learn, you might want to read this blog post. I will summarize some of the trends and tools that use adaptive learning systems for elementary school settings, and how AI can make them better.
Adaptive learning is a form of personalized learning that adjusts the content, pace and difficulty of instruction to match each student's needs and preferences. Adaptive learning systems use data and algorithms to monitor students' progress, identify their strengths and weaknesses, and provide them with feedback and guidance. Adaptive learning can help students learn at their own pace, improve their engagement and motivation, and close the achievement gap. In short, they allow educators to differentiate instruction and experiences for students better so that their learning and success are optimized.
There are many Edtech tools that use adaptive learning systems for elementary school settings such as Century, Amplify, Moby Max, and Dreambox. All of these tools or platforms use Big data analytics to drive decisions around what the student should experience next and how. These tools can be a great helper for the educator to orchestrate learning opportunities for each student that is better tailored to each student's needs.
However, as a teacher who has seen and heard the defeated moans of students on Dreambox many times. Big data and analytics are still quite limited in their ability to continue to adapt to the emotional and cognitive states of each student along with their very varied lived experiences and personalities. Eventually, the machine fails to help them grow by either bombarding them with challenges that are discouraging or boring them to death (as many students have very vividly expressed to me).
Here’s where AI can enhance these tools and make them more effective and efficient:
AI can provide more accurate and timely feedback to students and teachers, based on real-time data analysis and natural language processing. Imagine a natural coach in a Math puzzle helping a student talk out their ideas or even cracking a joke to help them calm down.
AI can generate even more diverse and engaging content for students, such as interactive simulations, videos, quizzes and games. The data analytical processing quality can increase to a point of providing highly tailored experiences for each student. Even tailored to incorporate non-curricular interests and experiences to explain concepts.
AI can create even more personalized and flexible learning paths for students, based on their goals, preferences, emotions and learning styles. The order of magnitude of pathways can continue to grow and expand as AI learns more about the student.
AI has the potential to revolutionize education by making it more accessible, personalized and engaging for all learners. However, there are also challenges and risks involved in using AI in education, such as ethical issues, privacy concerns, bias and inequality. Therefore, it is important to ensure that AI is used in a responsible and human-centred way, guided by ethical principles and standards.
I hope you enjoyed this blog post and learned something new about AI in education. If you have any questions or comments, please feel free to share them below. Thank you for reading!