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Artificial Intelligence in the Classroom: What Educators Need to Know

Artificial Intelligence in the Classroom: What Educators Need to Know

Artificial intelligence and education—totally unrelated, right? In fact, the connections and applications between the two might surprise you. But first, it’s important to understand what artificial intelligence (AI) actually is.

There are very few people who have not heard of AI. The media and industry have touted the technology as the next industrial revolution, the destroyer and creator of millions and millions of jobs. The reality is much more centered and less dramatic. The simple truth is that we are nowhere near Artificial General Intelligence, where a system of algorithms—sets of rules followed by computers for complex problem-solving operations—is self-learning and requires no human intervention, but we have successfully developed complex and powerful systems that are narrow and focused. Simply put, today's AI is a combination of sophisticated machine learning algorithms and massive amounts of data that do an amazing job of solving very specific problems that they were trained on.

The absolute key to any successful AI is data. With an experienced data scientist well-trained in machine learning and a deep understanding of the domain they are working in, there is really nothing that cannot be modeled. The single limiting factor to success is the lack of data. If you want your organization—including districts, schools, and classrooms—to succeed with AI, you need to understand the data you have, the gaps in the data, and devise a plan to acquire any data that is missing or limited.

Challenges educators face today and how AI can help

Over the past 20 years, education technology has become a ubiquitous part of the classroom experience. Educators and students use devices and online programs for everything from tracking student grades and attendance to completing hands-on project-based learning. Edtech has expanded student and educator options, and overall improved engagement, increased knowledge retention, encouraged individual learning, and promoted collaboration. It’s also provided educators with huge amounts of valuable student data.

However, advances in edtech have not been able to overcome the consistent strains on educators’ workloads and time, and it certainly has not replaced their critical roles. Time and again, students have been shown to thrive in environments where they have strong relationships and personalized instruction. Teachers simply don't have enough time to dedicate to cultivating these relationships while needing so much time to prepare lessons for each day, grade the previous day's work, and perform every other administrative function that is required of them. This is where all that student data and the artificial intelligence it can power shines.

AI or machine learning driven applications can take all of that (sometimes overwhelming) data on student progress and outcomes and use it to automate repetitive tasks and proactively recommending content, lessons, and other teaching materials that are truly personalized based on statistical rigor. In the process, it can hand back those critical hours to educators and free them up to focus on building one-on-one relationships and providing truly personalized instruction for each student.

Edmentum driving innovation with AI

At Edmentum, we’re excited about these new doors that AI is opening up in education. We’re rapidly developing multiple AI-driven application features that will address a number of challenges educators face today. The foundation for all of these features will start with a Conversational AI platform to allow intelligent back-and-forth conversation between the educator and Edmentum programs. The first feature within the conversational AI will be a recommender system that suggests to the educator a sequence of items and content related to what they are teaching that day, week, month, or school year.

The recommendations will be driven by what set of items and content are statistically likely to maximize student performance within the application based on student performance profiles within the class, school, and across the country. The recommender system will also quickly setup educators within the application at the start of the school year, providing support and increasing efficiency for brand-new through highly experienced users.

Ultimately, our current research & development efforts are targeted towards proactively recommending items, content, and learning paths for both students and educators to anticipate needs to drive growth in student outcomes, reduce time spent on preparing and administrative tasks, and increase overall satisfaction with the learning journey. The student data is there, and with artificial intelligence, we believe that it can really be put to use for educators and students in ways that are innovative, safe, and meaningful.

 

Interested in learning more about cutting edge approaches for leveraging edtech to save time? Check out this blog on The Importance of Automating your Program

ben.post's picture

Ben leads data science, data engineering, business intelligence, and cloud computing. He is currently working on a comprehensive Artificial Intelligence strategy for all Edmentum products, as well as building a system of machine learning algorithms to predict customer behavior with prescriptive recommendations for intervention. Prior to joining Edmentum, Ben led Artificial Intelligence strategy and capability for Travelers Insurance. Before that, he spent several years in consulting and product development leading data science  and analytic organizations. Ben earned his BS in Economics & Statistics from the University of Minnesota and his MS in Econometrics and Mathematical Statistics from the University of Rome – Tor Vergata.

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