The Emerging Achievement Gap in Education
AI Lessons from My Game Design Classroom
Last week, while watching a YouTube video by Jason Hamilton, a.k.a. "The Nerdy Novelist", about AI's role in writing, something clicked. In the video Jason emphasized the importance of "working harder and smarter" with AI, not just working smarter. This simple yet profound insight perfectly captured what I've been observing in my graduate-level game design classroom, where the impact of AI tools has created the largest achievement gap I've ever seen in my teaching career.
When AI Meets the Classroom: A Teaching Experiment
Last term, I had decided to run an experiment in my introductory game design course for graduate Digital Media students. Instead of discouraging the use of or even banning AI tools – as many educators have chosen to do – I actively encouraged their use. To assist the students, I created video tutorials showing how to integrate AI throughout the game development process.
Here's a practical example from my class: In previous terms, creating a playable 3D game character would take my students several weeks. The process involved character design, 3D modeling, rigging (creating a skeleton for animation), and implementing animations. This term, students could use a chain of AI tools – MidJourney for character design, 3DAIStudio for 3D modeling, Adobe Mixamo for rigging and animation, and Spline for web implementation – to complete the same task in under an hour.
The results? They weren't quite as polished as traditionally crafted characters, but they were more than serviceable for learning game design principles. More importantly, this efficiency allowed students to focus on other aspects of game design they might never have had time to explore.
The Tale of Four Students
To understand what happened next, let me introduce you to four types of students I observed in my class. Similar to how Jason Hamilton described the phenomenon in his video, I am representing them with four fictional characters:
Larry - Puts in minimal effort and refuses to use AI tools
Angie - Puts in minimal effort but embraces AI tools
Harry - Works hard but refuses to use AI tools
Sarah - Works hard and embraces AI tools
It is obvious that different students will perform differently in every class. However, in previous terms, the quality gap between my highest and lowest performing students was not all that dramatic. This term? The difference was staggering. It was like comparing middle school projects to professional game development work. What I witnessed in my classroom this term was an achievement gap I had not seen before.
The Unprecedented Achievement Gap
Many educators are primarily concerned about students like Angie who use AI with minimal effort to match the output of traditionally hardworking students like Harry. But in doing so they're missing something far more significant: the enormous divide that's emerging between students who combine minimal effort with AI resistance or unfamiliarity and those students who embrace both hard work as well as new technologies.
The contrast between Larry and Sarah's work was nothing short of stunning. Larry, putting in minimal effort and refusing to engage with AI tools, produced work that barely met basic requirements. Sarah, on the other hand, combined her strong work ethic with AI's capabilities to create projects that wouldn't look out of place in a professional portfolio. She used the time saved by AI tools to push boundaries, experiment with advanced concepts, and refine her work to a level I've never seen before in an introductory course.
This gap isn't just larger than usual – it's fundamentally different in nature. While educators worry about AI tools letting less motivated students take shortcuts, we're overlooking how these same tools, when combined with dedication and hard work, are enabling our most committed students to soar to new heights. The distance between Larry and Sarah's work isn't just a matter of degree; it's a complete paradigm shift in what students can achieve.
Why This Matters Beyond the Classroom
It is important to note that this isn't just about grades or classroom performance. We're witnessing the emergence of a new kind of performance divide – one that's not based on traditional measures of academic ability or effort alone, but on students' willingness and ability to effectively leverage AI tools.
And let’s not forget that in the professional world, the ability to work with AI isn't just an advantage anymore – it's becoming a necessity. By preventing students from learning how to use AI tools in educational settings, we might think we're maintaining equity and fairness, but we're actually doing them a disservice. We're denying them the opportunity to develop crucial productivity skills they'll need in their careers.
Looking Forward: The New Educational Challenge
I strongly believe that as educators, we need to shift our focus. Instead of debating whether to allow AI tools in our classrooms, we should be asking ourselves:
How do we help students like Larry not only embrace new technologies, but also discover how these tools can motivate them to work harder?
How do we ensure students like Angie develop and maintain strong fundamental skills while leveraging AI?
How do we show hardworking students like Harry that AI tools can amplify their efforts rather than replace them?
And perhaps most importantly, how do we create learning environments that encourage more students to become like Sarah?
The achievement gap I witnessed in my game design class isn't just a warning sign – it's a glimpse into the future of education. Our challenge isn't to prevent students from using AI tools; it's to ensure all students can use these tools effectively while maintaining their drive to excel.
The future belongs to those who can work both harder and smarter. As educators, it's our responsibility to prepare all our students for that future, not just the ones who figure it out on their own.