Three scenarios illustrate AI’s game-changing potential:
Scenario 1: Helping teachers
AI and teachers can work side-by-side to make teaching more effective. For instance, facial and voice recognition and emotional analysis can measure students’ engagement and emotions and determine their attention, understanding, and confidence. AI also enables teachers to access the best content available globally and personalize it to individual students in their local language.
Scenario 2: Personalizing the learning experience
AI-based tutoring and guided content that adapts according to student learning styles, needs, and engagement can help students learn at their own pace. For example, adaptive homework or learning aids can tailor assignments or content to align with a student’s understanding, moving away from “one size fits all” homework and providing better coaching and tutoring.
Scenario 3: Enhancing third-party learning content
Online adaptive learning platforms have made huge strides in the past few years. AI turbocharges such third party tools by personalizing the experience: understanding how a specific student is interacting with the platform and recommending the right content for each student to ensure the student is learning.
A tiered approach to adoption
AI applications in education will likely be introduced in a measured way, across three broad phases or levels of maturity.
Tier 1 is highly tactical. With insufficient collection of student data limiting machine learning and AI hardware costs still high, students will be restricted to using primitive adaptive learning tools. Teachers will be limited to sourcing content based mainly on their input, and very limited student data.
At Tier 2, digitally enriched classrooms build the foundation for broad scale AI applications. Advancements in data privacy policies and AI capabilities will foster more comprehensive collection of student data to improve education, and continually declining AI hardware costs will fuel an expanding use of AI. Classrooms will be fitted with video and audio capture equipment, handwriting recognition tools, and possibly integrate with available wearable technology to support analysis of student and teacher actions and interactions.
Tier 3 will be characterized by a connected educational platform, which will immensely transform the learning experience. A strong foundation of student-based data and AI, combined with supporting technological advancements, will further accelerate AI use.
With movement from each tier of adoption expected to take approximately six years, AI could completely transform education around the world by as early as 2036.
What is the value?
The potential economic and social benefits of AI taking a front seat in education create a case for action that’s difficult to ignore:
- Benefit 1: Better educational outcomes
- Benefit 2: Improved quality and scalability of teacher training
Making personalized education a reality
Three important considerations should be at the top of the agenda of any initiatives to make greater use of AI in the education system.
- The first and arguably the most important is personal privacy. For AI to flourish, school systems need to provide a clear and understandable value proposition to families; employ sophisticated tools and practices to maintain and protect student data; and operate with complete transparency.
- Second, both AI developers and educators must remain cognizant of bias. If the data on which the AI system is trained is geared toward a certain demographic (race, economic tier, or culture), the output will be biased.
- Finally, with schools increasingly collecting massive amounts of data to inform the education process, data storage becomes a major concern. The amount of additional storage capacity needed per year could skyrocket to 8.6 billion gigabytes (8.0 exabytes) by 2040.