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From the Jetsons to Doc Brown to Neo’s showdown with Agent Smith to the chilling debauchery of Westworld, storytellers have long foretold a world where technology evolves to the point of near sentience. That world may be closer than we think.
Artificial intelligence, or AI, has catapulted from the pages of science fiction to the forefront of real-world innovation. Whether you’re talking about business optimization using machine learning, chatbots standing at the ready to answer your questions, or the proliferation of smart technology’s role in our day-to-day lives, AI is no longer a far-fetched dream. It’s a reality.
The possible applications of AI in a wide variety of fields are as boundless as they are profound. This is especially true of education, with AI presenting both opportunities and challenges. On the one hand, it could fuel customized learning experiences, optimization of classroom management, and more productive partnerships with parents. On the other hand, it could also enable cheating by tech-savvy students, make personal data vulnerable to digital hijackers, and create significant learning curves for already ill-supported educators.
But AI in education is big money. Its total market value surged to $1.82 billion in 2021, and research suggests that number will grow by an average of 36% annually between 2022 and 2030.
What Exactly Is AI?
Ask a dozen people what qualifies as “artificial intelligence,” and you’ll probably get a dozen different answers. This is partly because our understanding of where AI began, where it is now, and where it could be tomorrow has evolved with every leap in innovation.
You can trace the origins of AI in education to the development of Bayesian inference or Ada Lovelace’s 1837 contributions as the world’s first programmer. While we might not associate those milestones with AI today, they felt like near magic in their day. They weren’t. They were the product of pioneers in the educational space.
But what does that tell us about AI today? Scholarly research offers numerous definitions, all of which boil down to the concept of rules-based systems capable of organizing and communicating information in a human-like way. Even that interpretation, though, casts a fuzzy light on the field of research.
The average consumer might best relate to the interpretation by mathematician and computer scientist Alan Turing. In 1950 he argued that if a machine can fool someone into thinking it’s human, it qualifies as intelligent.
The truth is that today’s most appropriate definition of AI may not fit tomorrow’s. When we consider its role in education, this reality underscores a historic symbiotic relationship between the two. It is education that shapes the meaning of the term, and it’s the field in which we can most clearly see its application.
How Is AI Being Used in the Classroom?
At one point, calculators were considered a groundbreaking form of AI. The application of AI in education today, of course, is far more complex.
Much of AI innovation in education has been rooted in online learning. Though far from new, its significance was elevated in the wake of COVID-19. With students out of the classroom, teachers and administrators needed to find solutions that would keep students engaged and the lines of communication open.
Aware that the term artificial intelligence has left a sour taste in the mouths of some teachers, education companies tend to frame their AI offerings as educational technology, or EdTech.
The resulting AI education solutions can be divided into three categories.
Operational Support
The average teacher works more than 54 hours a week, with more than half of that work being completed outside of school. Tasks like lesson planning and grading put a significant burden on educators already overwhelmed by larger class sizes and fewer resources.
AI offers automation opportunities that lessen that workload. Though online testing has been around for years, advances in technology now allow teachers to automate some of that work, all while organizing information to keep students and parents aware of the progress being made.
AI can also centralize communication and notes regarding individual students, all of which can be backed by analytic data on student technology use. This makes it easier for teachers to identify problems, track interactions with parents, and use available data to improve progress.
Customized Instruction
The idea that different students learn in different ways is not new. From Aristotle to Dr. Maria Montessori, from scholarly research in the 1960s and beyond, educators and researchers alike have debated the concept of learning styles and their relevance in the classroom.
Though some research suggests that learning styles are more fact than fiction, AI has the power to put theory into practice by adapting lessons to student performance using a “branching” model of instruction. This provides extra support to students on the topics where they’re struggling, while empowering higher-performing students with more engaging, complicated subject matter.
Though a conclusive finding regarding the impact of AI on student grade outcomes is likely years away, studies so far indicate that satisfaction levels are markedly higher with AI-enabled learning. Both students and teachers benefit from the flexibility, transparency, and communication ease AI systems offer.
Student Tools
Beyond the sphere of EdTech, AI research has yielded a litany of tools that not only support students in their coursework but teach skills that transfer to the real world.
This is especially true with writing assignments. Services offered by companies like Grammarly, Hemingway, and more will flag errors and make suggestions, allowing students to fix mistakes before submitting their work. More important, they explain why the mistakes were flagged in the first place, reinforcing essential lessons from the classroom.
Other tools relate to knowledge building. Programs such as Explain Like I’m Five, for instance, can simplify complex ideas in a way that empowers students to explore discussions on topics in an informed manner. Scholarcy is another solution, generating summaries of complicated research to guide students through technical analyses that might otherwise seem over their heads.
What Comes Next for AI in Education?
The future of AI in education is bright, due in no small part to the fact that education is where its most significant breakthroughs are being created in the first place. As our understanding of the technology and its possible application expands, the sky is truly the limit.
That doesn’t mean there aren’t concerns about the ethics and logistics involved. Topics like information security, enablement of cheating, and diminishing opportunities for learning social skills are frequent flashpoints in debates about AI in education. Teachers wary of unforeseen consequences are not reassured by insinuations that AI might be about to replace them.
Many, however, have realized that progress is unlikely to slow down. Instead, they’re betting that students and teachers can use AI to improve outcomes for everyone. It’s the smart play. After all, it was the ingenuity of students and educators that got us this far. If anyone can address application concerns while accelerating and enriching the learning experience, our money is on them.
