A Competency Framework for AI Literacy: Variations by Different Learner Groups and an Implied Learning Pathway

IF 8.1 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

British Journal of Educational Technology Pub Date : 2024-12-27 DOI:10.1111/bjet.13556

Hyunkyung Chee, Solmoe Ahn, Jihyun Lee

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引用次数: 0

Abstract

This study aims to develop a comprehensive competency framework for artificial intelligence (AI) literacy, delineating essential competencies and sub-competencies. This framework and its potential variations, tailored to different learner groups (by educational level and discipline), can serve as a crucial reference for designing and implementing AI curricula. However, the research on AI literacy by target learners is still in its infancy, and the findings of several existing studies provide inconsistent guidelines for educational practices. Following the 2020 PRISMA guidelines, we searched the Web of Science, Scopus, and ScienceDirect databases to identify relevant studies published between January 2012 and October 2024. The quality of the included studies was evaluated using QualSyst. A total of 29 studies were identified, and their research findings were synthesized. Results show that at the K-12 level, the required competencies include basic AI knowledge, device usage, and AI ethics. For higher education, the focus shifts to understanding data and algorithms, problem-solving, and career-related competencies. For general workforce, emphasis is placed on the interpretation and utilization of data and AI tools for specific careers, along with error detection and AI-based decision-making. This study connects the progression of specific learning objectives, which should be intensively addressed at each stage, to propose an AI literacy education pathway. We discuss the findings, potentials, and limitations of the derived competency framework for AI literacy, including its theoretical and practical implications and future research suggestions.

Practitioner notes

What is already known about this topic

AI literacy is becoming increasingly important as AI technologies are integrated into various aspects of life and work.
Research on AI literacy competencies across diverse learner groups and disciplines remains fragmented and inconsistent to guide educational practices.
Studies providing a coherent pathway for AI literacy development throughout educational and working life are lacking.

What this paper adds

A comprehensive AI literacy competency framework consisting of 8 competencies and 18 sub-competencies.
Variations in AI literacy competencies with tailored configuration and prioritization across different learner groups by school levels and disciplines.
A proposed pathway for developing AI literacy from K-12 to higher education and workforce levels.

Implications for practice and policy

The framework can guide the design and implementation of AI curricula tailored to different learner characteristics and needs.
Education should shift focus from teaching how to use AI to fostering competencies for critical, strategic, responsible and ethical integration of AI.
Policies are needed to support a systematic pathway for lifelong AI literacy development from K-12 education to workforce training.

Abstract Image

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人工智能素养的能力框架：不同学习者群体的差异和隐含的学习途径

本研究旨在为人工智能（AI）素养建立一个全面的能力框架，描述基本能力和子能力。这个框架及其潜在的变化，针对不同的学习者群体（按教育水平和学科）量身定制，可以作为设计和实施人工智能课程的重要参考。然而，对目标学习者的人工智能素养的研究仍处于起步阶段，现有的一些研究结果为教育实践提供了不一致的指导。根据2020年PRISMA指南，我们检索了Web of Science、Scopus和ScienceDirect数据库，以确定2012年1月至2024年10月期间发表的相关研究。使用QualSyst评估纳入研究的质量。共确定了29项研究，并对其研究成果进行了综合。结果表明，在K-12级别，所需的能力包括基本的人工智能知识、设备使用和人工智能伦理。对于高等教育来说，重点转移到理解数据和算法、解决问题以及与职业相关的能力。对于一般劳动力，重点放在解释和利用特定职业的数据和人工智能工具，以及错误检测和基于人工智能的决策。本研究将具体学习目标的进展联系起来，在每个阶段都应该集中解决，提出了人工智能素养教育的途径。我们讨论了人工智能素养衍生能力框架的发现、潜力和局限性，包括其理论和实践意义以及未来的研究建议。随着人工智能技术融入生活和工作的各个方面，我们对这个话题的了解正变得越来越重要。对不同学习者群体和学科的人工智能读写能力的研究在指导教育实践方面仍然是碎片化和不一致的。在整个教育和工作生活中，缺乏为人工智能素养发展提供连贯途径的研究。一个由8个能力和18个子能力组成的全面的人工智能素养能力框架。人工智能读写能力的变化，根据学校水平和学科对不同的学习者群体进行量身定制的配置和优先级排序。从K-12到高等教育和劳动力水平发展人工智能素养的建议途径。该框架可以指导针对不同学习者特征和需求量身定制的人工智能课程的设计和实施。教育应将重点从教授如何使用人工智能转向培养对人工智能进行批判性、战略性、负责任和道德整合的能力。需要制定政策，支持从K-12教育到劳动力培训的终身人工智能素养发展的系统途径。

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来源期刊

British Journal of Educational Technology EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

15.60

自引率

4.50%

发文量

111

期刊介绍： BJET is a primary source for academics and professionals in the fields of digital educational and training technology throughout the world. The Journal is published by Wiley on behalf of The British Educational Research Association (BERA). It publishes theoretical perspectives, methodological developments and high quality empirical research that demonstrate whether and how applications of instructional/educational technology systems, networks, tools and resources lead to improvements in formal and non-formal education at all levels, from early years through to higher, technical and vocational education, professional development and corporate training.