min read

How LLMs Will Revitalize the Classroom

In the next few years, we’re confident that we’ll see an even greater change in how educators approach learning engagement and motivation using AI. Learning’s going to become more personal, more focused, and, as a result, more effective.
Written by
Coleman Numbers
Published on
July 7, 2023

Like many full-time students, I've been reveling in the Edenic, reflexive, utterly non-reflective pleasures of a classless summer. And, as is perhaps the case with many students you know, the fall semester hangs over me like a pumpkin-spice scented, sweater-wearing, book-laden revenant. I know I can't escape this spectre whose voice is the sound of crunchy leaves, whose eyes glower like projector lenses. But I'll try.

Which brings me to a curious question in relation to our weekly blog: how will AI affect learners' involvement in the classroom?

LLMs like ChatGPT (but there are myriad others, and there’s a case to be made that OpenAI’s hegemony is to be short-lived) models can understand, generate, and respond to human language, facilitating interactive and responsive learning experiences. With this capacity, they address these two crucial elements of successful learning: engagement and motivation.


Standardized education models often fail to sustain learners' attention. Since these AI systems really came on board, a major selling point of theirs in learning has been the ability to tailor learning experiences to individual needs, making education more interactive and relevant. For instance, students can converse with AI tutors, which can adapt explanations to a learner's understanding level, making content digestible and engaging.

AI can provide immediate responses to questions and answers, allowing students to see their progress and areas for improvement in real time. With interaction that closely resembles human-to-human conversation, learning becomes an engaging dialogue rather than a one-way flow of information.

This has always been the ideal, and its appeal is manifest in the market for private tutors. But natural language tech makes this offering scalable and affordable for the economically disadvantaged.


Personalization is a powerful motivator. When learning is adapted to individual interests and capabilities, it becomes more meaningful and captivating. AI models can analyze learner behavior and preferences to deliver personalized content, kindling interest and motivation.

The ability to facilitate self-paced learning is another motivation booster. Learners can progress at their own speed without feeling rushed or held back, fostering a sense of ownership and self-efficacy in the process.

Transforming the Everyday Learning Experience

As LLMs like ChatGPT become commonplace, the challenges of impersonalized, rote learning could diminish. And as these AI companions reason and problem-solve alongside learners, they create a dynamic learning environment that continuously adapts to a learner's needs.

LLM tools will also enable to students to take on more constructive assignments. Instead of addressing narrow, one-answer problems like "What were the economic consequences of the New Deal?", students could take on an assignment posed like this: "Use ChatGPT and plugins of your choice to sort through primary sources from the time of the Roosevelt administration; use these sources to build a picture of how various people from different backgrounds responded to this historic policy moment."

The effect of LLMs isn’t constrained to a student and their course material, either. AI models could take on the rote tasks of pedagogy, like lesson planning and standardized grading, which will free teachers to focus on fostering creativity and critical thinking.

Models could also assist in fostering collaboration between learners, who could team up to play against sophisticated synthetic opponents in learning games, or work together to solve problems posed by a shrewd artificial tutor.

The result of all these new methods? A more innovation-driven learning culture.

Challenges and Opportunities

Challenges and ethical considerations should be weighed as AI's presence in learning expands. To create an efficient and ethical learning environment, we need to address issues like data privacy and LLM hallucination, alignment, and bias, among others. In our industry, we also face a more specific worry: that we implement AI tools too well, trapping learners in ecosystems of artificial tutors that alienate humans from social bonds that are also integral to meaningful learning.

If we can solve these concerns, though, we unlock the future of AI we all want: fostering a learning process that people are personally invested in. And we're starting to see the fruits of that effort. Gamification, AI mentoring, and AI-driven collaborative learning are gaining traction. Plugins for ChatGPT and various LLM APIs afford the tools more power to collate scholarly work and data into useful, real-time insights.

In the next few years, we’re confident that we’ll see an even greater change in how educators approach learning engagement and motivation using AI. Learning’s going to become more personal, more focused, and, as a result, more effective.

We’re committed to delivering those improvements at Mindsmith, whether in the classroom or the boardroom. You can discover how we’re doing that by demoing our GPT-driven lesson generator and editor now.

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