Innovation or disruption? The role of LLMs in shaping education

Ivan Yamshchikov
by
Image

Subscribe to Toloka News

Subscribe to Toloka News

As a new school year kicks off, parents, educators, and students alike are inundated with both excitement and apprehension. In the realm of education technology, much of this apprehension stems from the debate surrounding Artificial Intelligence. While the societal conversation often skews toward AI alarmism—warnings about job losses, ethical quandaries, and dystopian futures—it's worth pausing to explore the flip side. I am an AI enthusiast and an educator and I hear too much about which methods can reliably detect if a student generated their essay, and too little about exciting educational opportunities that large language models (LLMs) bring to the classroom.

Empower your GenAI development

Get your expert data for Fine-tuning, RLHF and Evaluation. High-quality, for any domain, at scale.
Talk to us
Image

Engaging Students Through Conversations

Imagine it’s a Physics class. Students could engage in a virtual dialogue with a simulated Sir Isaac Newton, thanks to LLMs. They can ask “Sir Isaac” about his contribution to physics and learn about foundational concepts such as inertia, force, and momentum first-hand. The LLM can generate quizzes to test students' understanding, fostering collaboration and critical thinking. For example, “Sir Isaac” might offer different questions to different students. The students, in return, could discuss the questions and the right answers with one another and then double check the answers with the teacher. Thus we can fosters independent thinking, effective collaboration and active learning—outcomes that are often hard to achieve in traditional lecture settings.

A Hands-On Approach to Algorithms

Let’s say we want to teach students sorting algorithms as a part of our computer science curriculum. An LLM could generate computer science puzzles that require students to apply sorting algorithms in real-world situations. It's one thing to learn how different algorithms work in theory; it's another to compare and debate solutions testing multiple ones on the flight. This dynamic approach transforms a potentially monotonous class into an engaging, hands-on experience where a student can learn by doing.

Broader perspectives

LLMs could be used to help students structure the creative process. If a student asks the LLM to generate several ideas for their school biology project, they will definitely get some suggestions that hold water. However, these results could be an order of magnitude better. Imagine the students ask the LLM to simulate Jennifer Doudna, a pioneer in CRISPR technology, and brainstorm on the project together. The students can give some ideas that they came up with, ask the model to come up with more options, then give feedback on the ideas that they found exciting. With a few iterations, they might stumble upon something truly genius. Learning can go far beyond acquiring facts; with these tools at their disposal, students have to thinking critically by design.

Towards a Future of Responsible AI Integration in Education

While there are legitimate concerns about the misuse of AI in educational settings, we shouldn't lose sight of the myriad ways it can enrich learning experiences. From facilitating deeper engagement in physics to gamifying computer science education, LLMs offer a versatile range of applications. Nevertheless, it's important to temper this enthusiasm with ongoing dialogues around data privacy, accessibility, and ethical considerations.

By adopting a balanced approach that recognizes both the potential and the pitfalls of AI, we open the door for a more engaging, personalized, and multidimensional educational experience. In doing so, we move one step closer to realizing a future where AI serves as a valuable collaborator in the educational journey.

Article written by:
Ivan Yamshchikov
Updated: 

Recent articles

Have a data labeling project?

Take advantage of Toloka technologies. Chat with our expert to learn how to get reliable training data for machine learning at any scale.
Fractal

More about Toloka

  • Our mission is to empower businesses with high quality data to develop AI products that are safe, responsible and trustworthy.
  • Toloka is a European company. Our global headquarters is located in Amsterdam. In addition to the Netherlands, Toloka has offices in the US, Israel, Switzerland, and Serbia. We provide data for Generative AI development.
  • We are the trusted data partner for all stages of AI development–from training to evaluation. Toloka has over a decade of experience supporting clients with its unique methodology and optimal combination of machine learning technology and human expertise. Toloka offers high quality expert data for training models at scale.
  • The Toloka team has supported clients with high-quality data and exceptional service for over 10 years.
  • Toloka ensures the quality and accuracy of collected data through rigorous quality assurance measures–including multiple checks and verifications–to provide our clients with data that is reliable and accurate. Our unique quality control methodology includes built-in post-verification, dynamic overlaps, cross-validation, and golden sets.
  • Toloka has developed a state-of-the-art technology platform for data labeling and has over 10 years of managing human efforts, ensuring operational excellence at scale. Now, Toloka collaborates with data workers from 100+ countries speaking 40+ languages across 20+ knowledge domains and 120+ subdomains.
  • Toloka provides high-quality data for each stage of large language model (LLM) and generative AI (GenAI) development as a managed service. We offer data for fine-tuning, RLHF, and evaluation. Toloka handles a diverse range of projects and tasks of any data type—text, image, audio, and video—showcasing our versatility and ability to cater to various client needs.
  • Toloka addresses ML training data production needs for companies of various sizes and industries– from big tech giants to startups. Our experts cover over 20 knowledge domains and 120 subdomains, enabling us to serve every industry, including complex fields such as medicine and law. Many successful projects have demonstrated Toloka's expertise in delivering high-quality data to clients. Learn more about the use cases we feature on our customer case studies page.