How 2021 in Ed Tech: AI, Data Analytics Were Top Priorities

Growing interest in artificial intelligence tools and data analytics were among the dominant trends in education technology in both K-12 and higher education this year, according to industry leaders. The last 12 months were a time of experimentation for both K-12 and higher education institutions. Flush with new federal funding but straining against disruptions such as COVID-19 and rampant cyber threats, schools adapted with help from ed-tech companies, nonprofits and other industry partners to meet a growing demand for flexible online learning options, as well as to improve student performance and tackle learning loss that resulted from last year's school closures. For school districts, colleges and universities, often this work included efforts to close the digital divide and distribute tablets and laptops; start coding boot camps and other training programs to prepare the future workforce for new technologies; and make cybersecurity investments and study programs to create a bulwark of infrastructure and skills against cyber criminals. For ed-tech companies and industry leaders helping schools through this, much of the focus was on student data and AI-driven programs designed to assist with lesson planning, student feedback and educational content. Google Cloud Head of Education Steven Butschi told Government Technology that instructors across grade levels have grown more interested in using AI-driven ed-tech tools to close achievement gaps made worse by shifting to and from remote learning. Citing a study this year from Google and Boston Consulting Group, he said 90 percent of college-level educators expressed a need for enhanced technology to meet the growing demand for flexible tutoring. Along those lines, Google announced the creation of an AI tutor last month to provide students with personalized feedback on assignments, academic coaching and course advisement. It was as an expansion of Google’s Student Success Services, a software suite released in 2020, which includes virtual assistant functions, analytics, enrollment algorithms and other higher ed applications. “They all are thinking about how we can make learning more personalized, aligning it to when you need it for access 24/7, and using data more effectively to engage students,” Butschi said. “As you think about that, it starts to tee up to why we’re seeing data analytics, artificial intelligence and machine learning to personalize and gauge learning starting to pop up more and more. Now we’re starting to see this is opening up, where we’re having asynchronous and synchronous learning. We’re having hybrid learning,” he continued. “The AI tutors are complementing in-person and professor-led learning.” According to a recent report from Market Research Engine, the global market for artificial intelligence in education technology will reach $5.80 billion by 2025, with a compound annual growth rate of 45 percent. Neil Heffernan, a computer science professor at Worcester Polytechnic Institute and lead developer of the AI-based student feedback program ASSISTments, said this projected growth is partly to do with AI’s potential to identify and address areas in need of improvement and help close achievement gaps. He said ASSISTment’s AI feature Quick-Comments won an $8 million grant last week from the U.S. Department of Education's Education Innovation and Research program to improve its machine-learning tutoring functions. “What we want to do is find out which human tutors are doing a good job, look at what they’re doing, and put that back into the computer so that when no humans are around, we can have the program doing that,” he said. “When we have the computer doing that, we can measure how they do on the next problem.” While AI is helping schools with tutoring and curricula, new data management systems are streamlining the collection and storage of student performance data to identify and address areas where improvement is needed. The aim is to make the data more readable and enable data systems to integrate with learning management systems (LMS) like Google Classroom and Canvas that have only become more commonplace in K-12 during COVID-19. Over the past year, K-12 districts and state education officials have worked with organizations such as the analytics nonprofit Ed-Fi Alliance and adopted tools like the Apigee API platform from Google Cloud to standardize data systems and make them interoperable. Trenton Goble, VP of K-12 Strategy at Instructure, said schools need student performance data that can "flow into a data warehouse environment with clear and easy-to-use reporting" and gauge the impact of remote learning. “As schools went back to a face-to-face environment this fall, we saw a lot of interest in assessments,” he said. "Assessmen