Understanding AI

Guidance that support districts and charters in understanding and implementing instructional AI tools

The advent of Artificial Intelligence (AI) within the educational sphere marks a pivotal shift towards integrating technology that complements human intelligence and enriches the humanitarian essence of learning.

The burgeoning influence demands a discerning approach to adopting and implementing technological solutions. The educational community must engage in an informed evaluation of AI- driven products, focusing on the mechanics of their operation, the nature of data collection, and the origins of their informational content. This strategy ensures the alignment of technological adoption with core educational values of integrity, safety, and instructional efficacy. One helpful glossary on AI for education is the CIRCLS Glossary of Artificial Intelligence Terms for Educators.

Defining AI

AI is not a singular technology but rather a collection of technologies and methodologies to simulate human cognitive processes. These include machine learning, natural language processing (NLP), robotics, and computer vision. AI systems can analyze large volumes of data, learn from experiences, and perform tasks with varying degrees of autonomy. We have provided the following graphic to provide a common language of terms and themes of AI in the K-12 classroom (Regona et al., 2022).

What is Artificial Intelligence? What is it Not?

Artificial Intelligence encompasses a broad range of computer science disciplines aimed at creating machines capable of performing tasks that typically require human intelligence. These tasks include learning, problem-solving, pattern recognition, and language understanding.

While AI augments human capabilities, it does not replicate empathy, creativity, or ethical judgment. Its learning is limited by the data it’s trained on, emphasizing the need for critical thinking about its use and limitations.

Predictive AI analyzes past behaviors to identify patterns and forecast future actions or preferences, such as recommending products or movies. In education, these tools predict student outcomes by analyzing data patterns, but their predictions are informed guesses rather than certainties. Educators should use human discretion to assess potential biases or inaccuracies. Predictive AI is also used in personalized tutoring and administrative tasks like scheduling.

Generative AI creates new content, such as text, images, videos, or music, based on patterns learned from training data. It can assist with tasks like grading papers, drafting lesson plans, generating educational content, and providing personalized learning experiences. Essentially, Generative AI acts like a skilled artist, producing original works from its extensive learning. For teachers, it can learn from various sources, such as textbooks and scientific journals, to generate new material that aligns with the patterns and structures of the learned content.

While Generative AI often makes valuable suggestions and is designed to predict what is right, users must know that results can be inaccurate, misleading, or incomplete (Gianinni, 2023).

This guidance document focuses on Generative AI in K-12 educational settings. Generative AI offers transformative opportunities in education by fostering creativity, critical thinking, and engagement. It can generate creative writing prompts, solve math problems, and illustrate scientific concepts, enhancing K-12 learning. However, these technologies also present challenges that need careful management. Educators can better integrate generative AI by understanding its capabilities and limitations and fostering a culture of critical thinking and continuous learning among students. This prepares students for a future where AI plays a significant role.