AI Integration in Schools: The Missed Opportunity

The lack of preparedness of US K-12 schools to incorporate Generative AI into their educational plans is a pressing issue that requires immediate attention by the current administration.

Prompt engineering and data science has become pervasive across all industries, signifying a broad shift in how companies operate, innovate, and compete. This widespread adoption is driven by the recognition that data and AI are not just tools for enhancing existing processes but foundational to creating new value propositions and business models.

Prompt engineering, the art of crafting inputs to generate desired outputs from AI systems, is now crucial for businesses seeking to leverage natural language processing (NLP) technologies for customer service, content creation, and strategic decision-making. With these AI applications, companies can automate complex tasks, provide personalized customer experiences, and glean insights from unstructured data like customer feedback or social media conversations.

Data science is equally transformative outside the tech industry. It can extract meaningful insights from large volumes of data. Retailers use it for inventory forecasting and customer behavior analysis, while healthcare providers use it to predict patient outcomes and improve care. Even traditional sectors like manufacturing and agriculture rely on data science for operational efficiency and to predict market demand.

Our economy is evolving towards a more data-driven economy, where success increasingly depends on the ability to interpret data and interact intelligently with technology. As such, prompt engineering and data science are not just technical skills but strategic assets reshaping the competitive landscape across all industries.

The Current State of AI Integration in Schools

One area where the incorporation of Generative AI lags is the US K-12 education system. This gap in preparedness poses significant challenges and missed opportunities for educators and students alike, highlighting a need for systemic changes to embrace the future of learning.?

Our current paradigm for applying Generative AI and data science is to use these tools to improve the curriculum and pedagogical models. This approach will not get us where we need to be. The Biden Administration's 2025 education budget proposal makes incremental investments in this area, but its dependence on the teacher's unions for political support constrains its approach.

What is needed? If you ask the leadership in Washington, they will tell you that the digital divide remains a stark reality, with disparities in access to high-speed internet and modern computing devices making it difficult for some students to engage with AI-based learning tools. This is patently false. USAFacts, referencing Federal Communications Commission (FCC) benchmarks, noted that more than 97% of people had access to high-speed internet in 2021, although it's important to differentiate between having access to high-speed internet and subscribing to a broadband service. Other credible sources estimate that 90% of US households have broadband access.?

Another critical challenge often cited is the need for more professional development opportunities for educators in AI. Without proper training, teachers may feel ill-equipped to navigate the complexities of Generative AI tools or to integrate them effectively into their teaching practices. This is the wrong approach, as teachers do not need to "integrate" AI tools into their teaching practices. We need to use AI tools to define a new model of delivering education that addresses the needs of our children and our economy.?

The Path Forward

Change The Structure

Class attendance is plummeting, According to a recent report, the proportion of students attending schools with high or extreme rates of chronic absenteeism?more than doubled—from 26% during the 2017-2018 school year to 66% during the 2021-2022 school year. The Everyone Graduates Center at Johns Hopkins University and Attendance Works analyzed federal data.?

Between the fall of 2010 and the fall of 2021, public charter school enrollment more than doubled, from 1.8 million to 3.7 million students — for an overall increase of 1.9 million. By contrast, the number of students attending traditional public schools decreased by 4%, or 2.0 million students, over the same period (from 47.4 million to 45.4 million students. The trends are clear.

Educating our children in "batches" by age (what critics call the factory model of education) has worked well in the past, but there has been a secular change in how students want to consume education. We must move to a system where students can use digital tools and resources to learn outside of school. This requires more than teachers posting homework assignments online. It requires moving away from delivering education according to the student's age and moving to a system that focuses on learning achievement - personalized learning. AI tools can make that possible.

The Role of The Teacher

Teachers are the most critical asset in our education system. We need to ensure that they allocate all of their available time to teaching. Only 40% of teachers' time is spent on classroom instruction, with the balance spread across other activities. Grading and lesson prep account for 22% of the time each week, areas that AI tools can easily facilitate. You have just added 50% more resources to classroom instruction. Let our teachers teach.

Measuring Educational Achievement?

Our approach to assessment needs to evolve to a model that requires a minimum measure of competency in specific subjects. Advancement should not be related to days in the classroom but to performance against a standard. You pass, or you fail. You advance to the next course or level when you demonstrate mastery of the course content.?

Between 2010 and 2022, the National Assessment of Educational Progress (the "Nation's Report Card") recorded steady declines in?reading ,?math , and?US history achievement . However, student GPAs climbed steadily higher. In 2022, more than 89% of high schoolers received an A or a B in math, English, social studies, and science. Yet the percentage who can demonstrate proficiency is at an all-time low if one looks at state proficiency exams. Only?42%?of students in California met or exceeded state standards in English language arts in 2023. Math scores were even lower, with 29.6% meeting or exceeding state standards.?

We see the same trends at the university level. Universities have raised their grades to artificially distinguish their graduates, as the bachelor's degree has become the new high-school diploma. Harvard has a 3.8 average grade point average, up from 2.7 in 1963. While this grade inflation may boost job placement statistics in the short term, it's an intellectual race to the bottom.?

Curriculum Integration

The goal of adding data science and prompt engineering as required courses of study should be to prepare students not to consume AI technology but to create and think critically in a world where AI plays an increasingly significant role. This requires equipping students with a foundational understanding of AI and its applications, fostering skills essential for the future workforce. All students from 5th grade onwards should have prompt engineering as part of the formal curriculum.

The lack of preparedness of US K-12 schools to incorporate Generative AI into their educational plans is a pressing issue that requires immediate attention. The goal should be transformative—embracing Generative AI in education should not be about keeping pace with technological advancements but about reshaping our system to address the needs of our "consumers." Clearly, there is room for improvement.?