How Can AI Help Students Reduce Cognitive Load at School?
Cognitive load?is a term that refers to the amount of working memory resources that are required to process information and perform a task. Cognitive load theory (CLT) suggests that there are?three types of cognitive load: intrinsic, extraneous, and germane. Intrinsic load is determined by the complexity and difficulty of the task itself, extraneous load is caused by the design and presentation of the instruction, and germane load is related to the cognitive processes that facilitate learning and understanding.
According to CLT, learning is most effective when the total cognitive load does not exceed the capacity of working memory, which is limited in both time and space. Therefore, instructional designers and educators should aim to optimize the cognitive load by reducing extraneous load, managing intrinsic load, and enhancing germane load.
One way to achieve this goal is to use artificial intelligence (AI) as a tool to support learning and instruction. AI is a branch of computer science that aims to create systems and machines that can perform tasks that normally require human intelligence, such as reasoning, problem-solving, decision-making, natural language processing, and so on. AI has many applications in education, such as adaptive learning systems, intelligent tutoring systems, chatbots, educational games, and data analytics.
In this blog entry, I will explore how AI can help students reduce cognitive load at school by providing some examples.
AI can help reduce extraneous load by providing personalized and adaptive feedback and guidance. For example, an AI-enriched digital biology textbook can integrate a knowledge base and algorithms that allow students to ask questions and receive answers while learning about complex biological concepts. This can help students reduce their cognitive load by providing them with relevant information and explanations that match their prior knowledge and learning needs.
AI can also help manage intrinsic load by adjusting the level of difficulty and complexity of the tasks according to the students’ abilities and progress. For example, an AI-based system can use data from students’ performance and behavior to dynamically select and sequence problems that are appropriate for their current level of competence and challenge. This can help students avoid frustration and boredom while maintaining an optimal level of cognitive load for learning.
AI can also help enhance germane load by facilitating cognitive processes that promote deep learning and understanding. For example, an AI-based system can use scaffolding techniques such as prompts, hints, examples, analogies, and metacognitive questions to support students’ self-regulation, reflection, elaboration, and transfer of knowledge. This can help students increase their cognitive load by engaging in meaningful learning activities that require higher-order thinking skills.
AI can be a powerful ally for students who want to reduce their cognitive load at school. By using AI as a tool to support learning and instruction, students can optimize their cognitive load by reducing extraneous load, managing intrinsic load, and enhancing germane load. This can lead to better learning outcomes and more enjoyable learning experiences.
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Loveless, B. (2022, March 10).?Cognitive Load theory – the definitive guide. Education Corner.?https://www.educationcorner.com/cognitive-load-theory/
MindTools. (n.d.). Mindtools.com. Retrieved May 10, 2023, from?https://www.mindtools.com/aqxwcpa/cognitive-load-theory
Shibli, D., & West, R. (2018, February 22).?Cognitive Load Theory and its application in the classroom. My College; The Chartered College of Teaching.?https://my.chartered.college/impact_article/cognitive-load-theory-and-its-application-in-the-classroom/
The importance of cognitive load theory. (n.d.). Et-foundation.co.uk. Retrieved May 10, 2023, from?https://set.et-foundation.co.uk/resources/the-importance-of-cognitive-load-theory
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Impact Wales- I7 research-informed strategies to avoid cognitive overload for your pupils.
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Founder @ Node | AI Strategy, Training, Policy and Tools for the Future of Education
1 年Thank you Barbara. This is food for thought. Although I can’t help but think that you could have gone a little deeper here and given more practical examples as to me this all seems quite theoretical at present and I’m not sure how any of your ideas could be practically applied. For example what do you mean by ‘an AI-enriched digital biology textbook? Would be great for you to explain in a following post. The foundations of this are fascinating.
Human-centred Leader #L&D #WorkplaceStrategy #FutureOfLearning #AIethics
1 年Great post, Barbara Anna Zielonka aI presents as many opportunities as it dies challenges
Education Technology Consultant | Expert in Enhancing Learning through AV & Digital Tools | Mentor & Speaker in EdTech
1 年I just finished reading your article on how AI can help students reduce cognitive load in school, and I have to say, it was a fantastic read! As someone who is passionate about education, it's exciting to see how technology is changing the way we learn. Your insights into how AI can provide personalized learning experiences and real-time feedback are especially noteworthy. It's great to think that students can receive the right level of support they need to succeed and overcome their cognitive limitations. I also appreciate your emphasis on the importance of ethical considerations and teacher involvement when using AI in education. It's crucial to ensure that these technologies are being used in a way that aligns with educational goals and benefits students. Overall, great article, and thanks for sharing your expertise on this important topic! Looking forward to reading more from you in the future.
Digital Engagement Architect, Innovation Catalyst and Online Safety Advocate APL Lead (South Africa) | Education Technology Expert
1 年Thanks for sharing this valuable post.