ActiveAI: Enabling K-12 AI Literacy Education & Analytics at Scale
Project Overview
The document outlines the creation of a K-12 AI literacy learning platform designed to deliver accessible educational materials and assessments related to artificial intelligence in schools. This platform facilitates large-scale data collection and analysis, which is crucial for improving AI literacy education. Preliminary findings demonstrate that students experience learning gains, underscoring the significance of cognitive engagement in achieving positive educational outcomes. The initiative seeks to advance the field of AI literacy by providing open access to data and practical resources for educators, ultimately aiming to enhance understanding and implementation of AI concepts in the classroom, thereby fostering a more informed and skilled student population in the realm of artificial intelligence.
Key Applications
K-12 AI Literacy Learning Platform
Context: K-12 education, targeting secondary school students and teachers
Implementation: Developed as a web application using Next.js and OpenAI APIs, featuring AI literacy modules and assessments. Engaged 1,000 users from 12 secondary schools.
Outcomes: Reported learning gains in AI literacy, identification of gender differences in assessment scores, and provision of data for secondary analysis.
Challenges: Limited large-scale learning datasets and varying educational contexts affecting the implementation.
Implementation Barriers
Data Scarcity
Large-scale learning data remains scarce despite efforts to develop learning materials. Collecting diverse data from various educational contexts can enrich the dataset and improve understanding of effective teaching strategies.
Proposed Solutions: Creating an online learning platform to collect data from multiple schools and making the dataset open access for research.
Variability in Educational Contexts
Differences in how schools implement AI literacy programs, with some schools integrating materials into regular subjects while others offer standalone courses.
Proposed Solutions: Collecting diverse data from various educational contexts to enrich the dataset and improve understanding of effective teaching strategies.
Project Team
Ruiwei Xiao
Researcher
Ying-Jui Tseng
Researcher
Hanqi Li
Researcher
Hsuan Nieu
Researcher
Guanze Liao
Researcher
John Stamper
Researcher
Kenneth Koedinger
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Ruiwei Xiao, Ying-Jui Tseng, Hanqi Li, Hsuan Nieu, Guanze Liao, John Stamper, Kenneth Koedinger
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai