ActiveAI: Introducing AI Literacy for Middle School Learners with Goal-based Scenario Learning
Project Overview
The document discusses the ActiveAI project, which aims to improve AI literacy among middle school students in grades 7-9 by providing interactive and engaging learning experiences grounded in the AI4K12 framework and learning science principles. By incorporating goal-based scenarios and immediate feedback, ActiveAI addresses prevalent challenges in AI education, such as the limited exposure to and complexity of AI concepts, through hands-on projects and the use of intelligent agents that simplify understanding. Currently in the implementation phase, the project emphasizes the importance of practical engagement in learning about AI, and it includes ongoing evaluations to measure its effectiveness in enhancing students' comprehension and skills in this critical area of study.
Key Applications
ActiveAI
Context: Middle school learners in grades 7-9
Implementation: Utilizes goal-based scenarios, immediate feedback, project-based learning, and intelligent agents in an app format.
Outcomes: Fosters understanding of AI concepts, engages students, enhances AI literacy skills, and encourages critical thinking.
Challenges: Complexity of AI concepts, maintaining student engagement, ensuring ethical interactions, and addressing biases in datasets.
Implementation Barriers
Educational Barrier
Limited exposure to AI concepts in traditional curricula, necessitating a stronger emphasis on AI literacy.
Proposed Solutions: Implementing specialized programs like ActiveAI that focus on AI literacy and hands-on experiences.
Complexity Barrier
The complexity of AI concepts requiring necessary mathematical and computational understanding.
Proposed Solutions: Using intelligent agents to simplify concepts and providing immediate feedback to enhance understanding.
Engagement Barrier
Challenges in maintaining student engagement and motivation.
Proposed Solutions: Incorporating interactive and goal-based learning scenarios that relate to real-world challenges.
Ethical Barrier
Ensuring students develop AI literacy responsibly and critically, while addressing ethical concerns.
Proposed Solutions: Encouraging critical thinking in evaluating AI-generated output and discussing ethical implications.
Bias Barrier
Potential biases that can emerge from unbalanced datasets, highlighting the importance of dataset management.
Proposed Solutions: Educating students about dataset management and the importance of balanced datasets.
Project Team
Ying Jui Tseng
Researcher
Gautam Yadav
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Ying Jui Tseng, Gautam Yadav
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