AI in Education Specialization (AI-Ed)

Learning Goals

• Understand AI fundamentals in education such as foundational AI concepts (e.g., machine learning, natural language processing, and data-driven decision-making), especially as they relate to teaching and learning.

• Design AI-enhanced learning experiences, applying principles of user-centered design to create AI-powered educational tools and experiences tailored to diverse learner needs and contexts, leveraging affordances of AI (e.g. adaptive learning, personalized educational content, assessment , creativity, etc)

• Evaluate AI tools for education by critically evaluating  existing AI-driven educational tools for efficacy, ethical use, and accessibility within various learning contexts and age groups (k-12, higher ed, informal learning, workplace learning, etc).

• Foster AI literacy and responsible AI use by understanding AI’s potential impacts on the future of learning and society, along with ethical concerns and biases in AI. Engage in research methods specific to studying AI’s impact on learning and cognitive development. Understand ethical and responsible frameworks  (e.g., fairness, accountability, transparency) in the design and use of AI and analytics tools for educational contexts.

AI-Ed Career paths:

Students specializing in AI & Education within an Educational Technology program can pursue careers that blend AI, data science, and educational expertise, addressing the growing demand for technology-driven solutions in learning environments. 

These roles are typically available in edtech companies, research institutions, K-12 and higher education, government agencies, and nonprofit organizations focused on technology’s impact on learning.
Examples of careers that include AI-Ed:

• AI focused EdTech Product Manager

• Learning Experience Designer or Instructional Technologist with AI Focus

• Data Scientist in Education

• Ethics and Policy Advisor in AI Education

• AI Literacy Educator/Trainer