Artificial Intelligence (AI) has the potential to transform learning for K-12 students nationwide. Rather than receiving the same instruction and content as classmates with differing interests, ability levels, and capabilities, students can experience learning that is truly personalized and work at their own pace with needed instructional supports, engaging content in areas that pique their curiosity, automated scoring and instant feedback, messages of encouragement, and opportunities to take a break provided for them at just the right time. As the leading provider of virtual education for K-12 students, our company—K12—is executing on a multi-year roadmap to deliver this type of experience for our students.
The first, and I believe most important, role that AI can serve is to match students to instruction at their individual learner level, focused on the right skills, delivered in the right progression, and in the mode of instruction—video, interactive examples, guided practice, etc.—that is most effective for each student. Students learn differently, have distinct strengths and weaknesses, and progress at their own pace. Through AI, an instructional system can target a student’s needs more and more precisely as it gathers data on what works best for that student. We have introduced these capabilities into our system—providing adaptive, levelled instruction and practice, matching students to texts and their reading level, and providing on-demand AI-powered instructional help. And in the next few years, we will build on these capabilities to make our delivery of AI-powered instruction more pervasive and precise. We even plan to recommend different types of instructional delivery—independent, paired learning with one other student, small-group work, and whole-class instruction—based on what we learn about each student through data.
Through AI, an instructional system can also detect when students become frustrated, disengaged, or distracted and either alert teachers or intervene directly to re-engage the students. This capability can also be utilized in the delivery of virtual instruction in distance learning.
For the coming school year, we are launching a new video-based virtual learning system that leverages AI capabilities to alert teachers when a student is not paying attention. We are also planning to implement this capability in the coming years for independent learning, using a student’s mouse or cursor and the student’s movement through the course content to detect that the student is stuck or has lost interest. And we will explore various remedies—from an automated voice assistant that will inquire whether the student needs help and to direct the student to appropriate content or instruction through responses to questions, or to the automated presentation of different content to provide a break, re-engage the student, or offer needed remediation.
Another critical capability to drive truly personalized learning is automated scoring. The best way to assess students’ understanding and skill development is through written and spoken responses. Automated scoring capabilities continue to advance, enabling a digital instructional system to tutor students in writing and speaking, reducing the scoring burden on teachers, and providing instant, accurate assessments of students’ comprehension of instructional content and development of communication skills.
"AI can match students to content in areas of interest and continually learn as students’ interests evolve to create a learning environment that will keep all students engaged"
This year, we launched automated reading levelling scoring that assesses students’ oral fluency and comprehension of texts and is using the capability not only to help teachers track reading growth but also to match to texts at their individual reading levels. This capability has the potential to be used as an automated tutor to help students learn to read independently, beginning with basic phonics. In addition, spoken language assessment capabilities can be used to support the needs of English Language Learners and help students develop professional skills—speaking, collaboration, etc.—that they will ultimately need to succeed in the workplace.
At K12, we have ventured into Project Based Learning—having students work in small groups and assume different roles to complete and present a project—with a focus on preparing students for careers in a variety of areas. Implementing Project-Based Learning in a virtual environment is a challenge since students and their teachers are not located in the same place and have to use virtual collaboration tools. AI can be critical in not only helping the virtual collaboration be most effective but also in assisting teachers in monitoring and developing the skills students need for success in collaborative work and ultimately in careers.
Last year, we partnered with students from the Carnegie Mellon METALS (Masters of Educational Technology and Applied Learning Sciences) program to design and prototype such a system, measuring participation, the effectiveness of communication, collaboration capability and other essential skills; and we plan to build this capability into our system in coming years.
Matching Content to Student Interests
AI can match students to content in areas of interest and continually learn as students’ interests evolve to create a learning environment that will keep all students engaged. We have built this capability into a digital library that we offer, matching students to books in areas that will interest them, and we plan to continue building out the capability throughout our system to create learning unique interest-driven learning pathways for every student.
As we move into the future, new AI capabilities will continue to evolve. The potential ways in which these capabilities will transform learning are limitless.