A comprehensive AI literacy framework for K-12 education requires balancing technological understanding with socio-cultural awareness, incorporating diverse expert perspectives that emphasize both critical evaluation and practical engagement with AI technologies.

Objective: The main goal of this study was to frame AI literacy for K-12 education based on the perspectives of international and multidisciplinary stakeholders, identifying key competencies that students should acquire to critically evaluate AI, communicate with AI systems, and use AI effectively across various contexts.

Methods: The researchers conducted a qualitative analysis of responses from 33 international experts representing various disciplines and roles related to AI and education. Data was collected through an online survey with open-ended questions focusing on three aspects of AI literacy: understanding and critically evaluating the role of AI in everyday life, recognizing and using AI in daily contexts, and describing and developing AI solutions to everyday problems. The responses were analyzed using inductive content analysis to identify emerging themes and categories. Additionally, the researchers conducted a deductive content analysis to examine individual response profiles, specifically looking at how respondents balanced technological and socio-cultural perspectives.

Key Findings:

• The analysis resulted in four main categories of AI literacy competencies:
  1. Conceptual understanding and knowledge (including technical understanding, systems thinking, and human-machine interaction)
  2. Ethical and societal considerations (covering sustainability issues, responsible use, and societal impact)
  3. Critical thinking and reflection (focusing on mindful use, human vs. AI agency, and reflection)
  4. Design and development (encompassing specification, design, refinement, creation, and practices)
• Experts emphasized varying levels of technical knowledge requirements, from basic IT skills to deeper understanding of algorithms and neural networks
• Most respondents placed greater emphasis on socio-cultural aspects of AI literacy compared to purely technical aspects
• While all respondents acknowledged the importance of understanding how AI functions, they also recognized the challenge of fully comprehending AI systems that operate as "black boxes"
• There was disagreement about whether K-12 students should learn to create AI solutions, with only about half of the respondents considering design and development skills important
• Critical perspectives were seen as essential prerequisites for mindful use of AI, with experts stressing the importance of teaching students to recognize signs of AI in daily life

Implications: The findings contribute significantly to the field of AI in education by:

• Providing a framework for AI literacy that integrates multiple perspectives from diverse stakeholders
• Highlighting the essential interplay between technological understanding and socio-cultural awareness
• Emphasizing that some level of technical understanding is a prerequisite for both critically consuming and producing AI
• Offering insights that can inform the design and implementation of AI literacy curricula worldwide
• Suggesting that curricula should be tailored to address various aspects of AI literacy, ensuring students gain skills necessary to critically, responsibly, and creatively engage with AI technologies
• Aligning with recent influential frameworks while contributing unique nuances based on diverse stakeholder input

Limitations:

• The contextual nature of AI literacy necessitates multiple perspectives, and despite efforts to include diverse stakeholders, additional disciplines not represented in the study could provide further insights
• The framing of the three survey questions may have influenced the direction of responses
• The qualitative data analysis process involves subjective interpretation, though measures were taken to ensure consistency
• The study does not resolve the question of what constitutes a sufficient level of technical understanding for K-12 students
• The research does not provide detailed grade-level recommendations for when specific AI literacy components should be taught

Future Directions:

• Further research is needed to determine the appropriate level of technical understanding required for AI literacy at different grade levels
• Investigating the relationship between conceptual understanding and systems thinking, and how these can be supported, presents an interesting avenue for future study
• Additional research should explore how to effectively incorporate systems thinking into AI education
• Future studies could focus on developing and validating assessment methods for AI literacy
• Research is needed on effective pedagogical approaches for teaching AI literacy at the K-12 level

Title and Authors: "Framing AI Literacy for K-12 Education: Insights from Multi-Perspective and International Stakeholders" by Linda Mannila, Jonas Hallström, Charlotta Nordlöf, Fredrik Heintz, Katarina Sperling, and Linnéa Stenliden.

Published On: February 12-13, 2025

Published By: 27th Australasian Computing Education Conference (ACE 2025), ACM

This research makes a valuable contribution to the emerging field of AI literacy by providing a multifaceted framework based on diverse expert perspectives. The findings underscore the need for a balanced approach to AI literacy that integrates both technological and socio-cultural dimensions. The researchers highlight that students need not only to understand how AI works but also to develop critical thinking skills that allow them to evaluate AI's role in society.

The study reveals interesting tensions between different perspectives on what constitutes essential AI literacy. While some experts emphasized technological understanding, others placed greater importance on socio-ethical considerations. This diversity of viewpoints reinforces the researchers' argument for incorporating multiple perspectives when designing AI literacy frameworks and curricula.

The four-category framework developed through this research provides a structured approach to conceptualizing AI literacy that could serve as a foundation for curriculum development. By addressing conceptual understanding, ethical considerations, critical thinking, and design capabilities, this framework offers a comprehensive view of the competencies students need to navigate an increasingly AI-driven world.