An Evaluation of the K-12 Conversational AI Literacy Curriculum
"Teaching Tech to Talk: K-12 Conversational Artificial Intelligence Literacy Curriculum and Development Tools," authored by Jessica Van Brummelen, Tommy Heng, and Viktoriya Tabunshchyk, addresses a significant gap in K-12 education regarding AI literacy, notably concerning conversational AI agents. With increasing interaction between children and AI through devices like smart speakers and smartphones, this paper emphasizes educating young students on AI mechanisms and societal implications.
Study Overview
The authors developed an AI literacy curriculum utilizing MIT App Inventor’s Conversational Agent Interface. This curriculum was introduced in week-long workshops for students in grades 8-12, focusing on eight established AI competencies. These competencies ranged from understanding AI functionalities to critically evaluating the ethical dimensions of AI technology. Evaluations were conducted through direct feedback from teachers and students, with assessments targeting both AI and conversational AI understanding.
Curriculum Design and Methods
The curriculum spanned five days, each session lasting 2.5 hours, featuring hands-on tutorials, interactive activities, and a focus on AI competencies and ethics. It intentionally targeted students with little to no prior programming exposure, adapting educational approaches to accommodate various learning paces. The research addressed essential research questions regarding the impact of building conversational agents on students' AI understanding and identifying effective methods for AI educational workshops.
Key Findings
The paper found that most students had not previously engaged in creating conversational agents, with 90% acknowledging this was their initial experience. Post-workshop results demonstrated a significant understanding of AI principles and reinforcement of AI ethics, with students expressing positive engagement and interest throughout the program. The curriculum's interactive nature and hands-on activities, particularly in developing Alexa skills, were highlighted as factors contributing to high student engagement. However, areas requiring improved focus included ML concepts and AI ethical implications, as students displayed difficulty comprehending ML's generalization aspects.
Implications and Future Directions
This research contributes a well-rounded framework for integrating AI literacy into K-12 education, leveraging direct programming experience with conversational agents. Teacher feedback was crucial in refining the course, indicating the need for collaborative curriculum design to enhance practical application and student interest. By demonstrating practical implementation and direct engagement with AI technology, the paper points toward scalable solutions for expanding AI literacy across various educational settings.
Future research should explore broader implementation strategies, possibly expanding workshop integration with existing educational technologies to provide a more comprehensive understanding of AI's multifaceted implications. Developing methodologies that efficiently tackle the inherent challenges of teaching complex AI concepts, particularly those related to ML and ethical considerations, is essential for optimizing student proficiency in AI literacy.
Conclusion
The authors successfully illustrate the value of incorporating conversational AI programming within K-12 education, aligning educational practice with technological advancements in AI. The findings advocate for enhanced teacher collaboration and refined curriculum pacing to fully engage diverse student capabilities. This research presents a promising avenue for enriching AI literacy, equipping future generations with the necessary tools and understanding to navigate an evolving technological landscape.