Generative AI lessons from the classroom offer insights into effective teaching and learning strategies.
Copyright: forbes.com – “8 Generative AI Lessons From The Classroom”
Offering courses that effectively prepare students today for collaborative work with generative AI in the future is a challenge that few instructors have mastered well. Several key lessons have emerged from the Neeley School of Business, Texas Christian University classrooms, where I teach, that might be helpful to effectively harness the generative AI tools in other educational contexts.
1. Continuous Adaptation
The ever-evolving nature of Generative AI technology compels educators to perpetually adapt their teaching materials. New AI platforms are created daily (There Is an AI For That) and existing AI platforms are refined sometimes week to week, becoming more capable, but requiring instructors to update their AI-related curricula to align with the new capabilities.
Particularly, the Large Language Model (LLM) frameworks are regularly updated to improve their efficacy, e.g., the recent introduction of Custom Instructions in ChatGPT. These updates call for a corresponding revision in teaching materials presented to students. Sending regular generative AI email briefs to faculty interested in adopting the technology might help instructors stay current with the AI platform changes.
2. Effective Prompting
Investing time and thought into creating prompts is instrumental in eliciting meaningful interactions with Generative AI systems. Quality prompts are the product of iterative refinement, significantly affecting the quality of the AI-generated output. This so-called ‘prompt engineering’ serves as a critical intermediary that connects ambiguous inquiries to insightful, nuanced answers.
For example, assignments involving generative AI must be thoroughly tested beyond simple copying and pasting of the project’s content into AI platforms. Educators should provide a comprehensive context in the prompts, which will significantly improve the generated responses’ relevance and accuracy.[…]
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