Are AI Updates Overhyped? The Real Impact of Prompt Engineering

AI is making its way into classrooms, but are the tech updates really helping? A recent study put this to the test with two AI tools, Gemini and Coteach, focusing on their ability to classify the cognitive demand of math tasks. The findings? Not exactly a tech fairy tale.

Gemini and Coteach: A Tale of Two AIs

Gemini, a general-purpose AI, and Coteach, tailored for education, were the subjects of this study. Both initially showed decent results on benchmarks. But when it came to updates, the story took a turn. Gemini's accuracy stayed put at 58%. Coteach? It dropped from 75% to a shaky 50%. Clearly, updates didn't wave a magic wand over these tools.

Prompt Engineering to the Rescue?

Enter prompt engineering. By using exemplar tasks, researchers saw an improvement in both tools. Gemini's accuracy jumped to 67%, while Coteach clawed back to its original 75%. So what gives? It seems that tweaking how we ask questions does more than just slapping on a new version number.

What's the Real Lesson Here?

The takeaway is clear: relying solely on model updates is bullish on hopium. Instead, prompt engineering offers a more reliable boost in performance. This ends badly if educators bank on model updates alone to enhance learning tools. Are we too quick to trust version numbers without looking under the hood?

In a world of flashy AI updates, this study highlights a harsh truth. Sometimes, the simplest tweaks outperform the most touted upgrades. Educators and researchers should prioritize how AI tools are used rather than just the tools themselves. Everyone has a plan until liquidation hits, and in this case, the plan should involve smarter prompt strategies, not just new software versions.