Key Takeaways
- The introduction of Generative AI (GenAI) and large language models (LLMs) is having a significant impact on education, but educators are not responding effectively.
- The Thayer method, a student-centred teaching approach, has been resilient to earlier technologies, but LLMs are different due to their ability to engage in dialogue and conversation.
- Educators need to re-evaluate their teaching methods and consider how to harness the power of AI for the benefit of students.
- The ability of LLMs to infer, collaborate, and create with humans in a conversation raises questions about the role of educators and the meaning of education.
Introduction to Generative AI and Education
Generative AI, particularly large language models (LLMs), has had a profound impact on education, but the response from educators and educational institutions has been lukewarm. Many educators seem to be either not responding at all or making only superficial changes to their teaching methods. This lack of response may be due to the fact that previous technologies, such as calculators, computers, and search engines, initially seemed to revolutionize education but ultimately had little lasting impact on classroom interactions. Even the shift to online learning during the Covid-19 pandemic had a limited effect on accelerating the delivery of courses online.
The Thayer Method: A Student-Centred Approach
The Thayer method is a student-centred teaching approach that has been resilient to earlier technologies. Developed at the U.S. Military Academy at West Point, this method shifts the responsibility for learning factual information to the student. Students are expected to study new material before class, come prepared with questions, and engage in collaborative problem-solving, active learning, and discussion led by both teachers and students. The Thayer method has elements of problem-based learning, the flipped classroom, and maker spaces. The author, who earned their undergraduate degree at West Point, recalls the interactive and engaging nature of classes, where students would work on problems individually and then present their solutions to the class, with minimal lectures and maximum discussion.
The Impact of Earlier Technologies on the Thayer Method
Earlier technologies, such as calculators, computers, and search engines, had little effect on the Thayer method, other than making it easier for students to access information and prepare for class. The Thayer method’s focus on dialogue, discussion, and collaborative problem-solving made it resistant to the impact of these technologies. However, large language models (LLMs) are different, as they have the ability to engage in conversation and dialogue, which is a uniquely human form of information exchange.
The Disruptive Nature of Large Language Models
LLMs are a subset of generative AI that are trained on vast amounts of data, allowing them to respond to human queries in a conversational manner. They have moved information access from documents to dialogue and from retrieval to reasoning. This conversational aspect of LLMs is especially disruptive to even resilient teaching methods, such as the Thayer method. LLMs can question responses, evaluate statements, review formulas, and engage in discussion as a collaborative partner, making them a game-changer in education.
Rethinking Education in the Age of AI
The advent of LLMs raises important questions for educators, such as "What does educating mean when technologies no longer just retrieve but infer, collaborate, and create with humans in a conversation?" Educators must re-evaluate their teaching methods and consider how to harness the power of AI for the benefit of students. This requires a fundamental shift in thinking about the role of educators and the meaning of education in the age of AI. By understanding the implications of LLMs and other AI technologies, educators can begin to develop new approaches to teaching and learning that take advantage of the unique capabilities of these technologies.
Conclusion
In conclusion, the introduction of Generative AI and large language models is having a significant impact on education, and educators must respond by re-evaluating their teaching methods and considering how to harness the power of AI for the benefit of students. The Thayer method, a student-centred teaching approach, has been resilient to earlier technologies, but LLMs are different due to their ability to engage in dialogue and conversation. By understanding the implications of LLMs and other AI technologies, educators can begin to develop new approaches to teaching and learning that take advantage of the unique capabilities of these technologies and prepare students for the challenges of the 21st century.
