What experiences should young children have with AI?

An illustration of children learning in a technology-enabled learning environment.

AI-based educational technologies have profound implications for young children’s language development, cognition, sensory perception, and future learning trajectories, but they are seldom developed with childrens' needs in mind.

Project description

Artificial intelligence (AI) is rapidly transforming our society, with growing recognition among educators and researchers of the need to prepare K-12 students for an AI-driven future. Unfortunately, little attention has gone to AI in early childhood education despite its profound implications for young children’s language development, cognition, sensory perception, and future learning trajectories. Responding to this need, our NSF-sponsored project will bring together global experts in three fields: AI, early childhood education, and child-computer interaction. Our goal is to achieve consensus, or at least to understand disciplinary disagreements, of three questions: (1) What are the most appropriate AI learning goals and content for young children? (2) What developmental advantages/constraints and equity concerns must be considered for AI learning? and (3) How can we introduce AI effectively and equitably? We are interested in recruiting one or two undergraduate research assistants to help with the project's core work of synthesizing and analyzing group interviews with experts in AI, child-computer interaction, and early childhood education.

Project outcome

The project outcome is a framework of early childhood AI learning, which will be shared in multiple conference presentations and journal articles.

Project details

Timing, eligibility and other details
Length of commitment About a semester, 3-5 months
Start time Fall (Aug/Sep), Winter (Dec)
In-person, remote, or hybrid? Hybrid Project
Level of collaboration Individual student project
Benefits Experience
Who is eligible All undergraduate students with Interest in computer science and/or AI. Interest in social science constructs. Experience with qualitative coding is a plus.

Core partners

  • Dr. X. Christine Wang, Professor of Education and director of UB's Early Childhood Research Center. 
  • Dr. Chris Proctor, Assistant professor of learning sciences and leader of UB's Computational Literacies Lab.

Project mentor

Chris Proctor

Assistant professor of Learning Sciences

Learning and Instruction

Phone: (323) 230 0313

Email: chrisp@buffalo.edu

Start the project

  1. Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
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Preparation activities

Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. Please reference this when you get to Step 2 of the Preparation Phase. 

Preparation consists of an introductory reading list of related to the project's theoretical framework and methods. Please contact the PI's if interested.

Keywords

AI, children, education, learning, artificial intelligence