The new wave of educational technology

Young boy sitting on grass using a tablet computer

The Children’s Machine: Rethinking School in the Age of the Computer, is one of the first books to examine the use of computers in the classroom. In it, author Seymour Papert writes, “Information technologies, from television to computers and all of their combinations, open unprecedented opportunities for action in improving the quality of the learning environment.” Since the book was first published in the 90s, advancements in computing and networking have helped digital learning multiply exponentially. From the growth of artificial intelligence and the creation of more and more complex algorithms, we are poised to see another wave of educational technology advancements become a reality. To discuss these advancements, I spoke with Luis Oros, who is part of Pearson’s Advanced Computing & Data Science Lab. Recently, Luis wrote about the death of education and the birth of learning, which looks at the current state of change in education. In this interview we look to the future.  

 

Q. How does computing today compare to yesterday?

Oros: Everyday educators make lots of decisions for their courses and their students. Often the time spent assessing situations, managing tasks, and other administrative roles takes instructors away from the valuable time they could spend teaching. Understanding this reality, we brought together teams of people who are united by the fundamental mission of unleashing the untapped potential of advanced computing and data science to create innovative software capabilities and processes with the goal of giving back time educators can use to build relationships with students.

To understand what we mean by advanced computing, let’s look at two illustrations. You have yesterday’s computing, and today’s computing. Yesterday’s computing is when engineers code the rules, and specific information into the computer. Any type of output — say reports or analytics — requires people to monitor reports and determine how to improve effectiveness. This model depends upon people making decisions.

Today’s computing is evolving with engineers telling the computer where to find information or data to update the rules. Engineers are not updating the rules, they tell the computer where to look, and it updates it on its own. The more the system is used, the more data it gathers, which improves the system and begins to automate it. This model allows the computer to make decisions.

So we can see a difference in the complexity of computing in these two examples. We have simple computing when we create algorithms to work with structured data, such as test scores. We get advanced computing when we consider anything as data, and we create systems that learn how to interpret any kind of data to make decisions.

Q. Let’s explore the practical application of advanced computing. How is it being used to improve learning?

Oros: Remember, we believe we can help decrease the number of decisions, minimize drudgery and administrative tasks, and help instructors get back to the roots of what they love, which is teaching. So to get at the heart of helping instructors focus where they need to, we need to go far deeper than just creating new features within existing programs. Thus, our teams of people are looking at core problems and trying to solve the overall issues.

One of the issues we are pursuing is creating models that can determine what the learner can and cannot do. It is predicting future student performance. For example, if we can understand Johnny’s current skill level of writing, we can start to create models on the likelihood of what he will be able to do in the future. That information starts to inform digital learning aid interventions and helps students as they need it, when they need it. Offloading that burden from the instructor.

A second issue we are examining is personalizing instruction and educational technology materials. So let’s say you have identified that Johnny has not mastered a learning objective. The question then becomes, “What do we need to do to help?” That is the first step in automating personalized learning instruction. Creating systems that independently and automatically create personalized curriculum, interventions, and learning aids is a huge step forward. It means that rather than one teacher creating one curriculum for all of her students, we are looking at creating algorithms where every student can have their own custom curriculum.

A third piece we are really excited about is called complex performance, or unstructured data. Structured data is what most people are familiar with. It contains clean yes or no items, clearly labeled and tagged columns, rows, etc. Unstructured data is what the human brain works with, which is raw audio information, images, video, or text that doesn’t have any perceivable pattern. Creating systems that can perceive, comprehend, reason, and make decisions is the foundation to advanced computing.

Q. How do you decide what to pursue?

Oros: What we are trying to do is get really good at solving fundamental human problems. The place where we start is to identify the most painful problems our customers face. Once we find it then we ask, “Where can we apply advanced computing and data science in a way no one has thought about before that could significantly alleviate or solve the problem?” This is where we rely upon our data scientists, and they start thinking about it holistically and in new ways. We don’t just want to be features builders; we want to focus on solving fundamental education challenges.

Q. How can this help people land jobs?

Oros: We know that employability is a growing concern for students taking on large financial burdens to get an education. We also know that 21st century skills are important for tomorrow’s workforce. If you talk to a lot of employers they will tell you that critical thinking, creativity, collaboration, and communication are important to the workforce, yet many graduates lack those key skills. On the other hand, if you talk to professors many will tell you that critical thinking is a core pillar of their actual course and what students are getting out of it. There is a disconnect here, a mismatch if you will.

We think there is a great opportunity in actually measuring and developing 21st century skills like critical thinking. But there’s a problem, how do you do that? This is a problem we are working on. If we can develop those underlying capabilities, then the potential exists to help our learners realize their reasons for pursuing an education in the first place, which for many is to get a good paying job in an in-demand field to support their family.