The recent developments in Artificial Intelligence (AI) technologies challenge educators and educational institutions to respond with curriculum and resources that prepare students of all ages with the foundational knowledge and skills for success in the AI workplace. Research on AI Literacy could lead to an effective and practical platform for developing these skills. We propose and advocate for a pathway for developing AI Literacy as a pragmatic and useful tool for AI education. Such a discipline requires moving beyond a conceptual framework to a multi-level competency model with associated competency assessments. This approach to an AI Literacy could guide future development of instructional content as we prepare a range of groups (i.e., consumers, co-workers, collaborators, and creators). We propose here a research matrix as an initial step in the development of a roadmap for AI Literacy research, which requires a systematic and coordinated effort with the support of publication outlets and research funding, to expand the areas of competency and assessments.
We recently presented on AI Literacy at the 2021 AI4EDU conference: paper | video
If you, or your colleagues/students, are interested in doing foundational research that will support the collaborative development of a competency-based AI literacy framework, please get in touch. The creation of a useful framework “requires a village” and should represent the the best ideas and evidence from AI researchers from around the world.
Contact us to learn more about how you can get involved.
Here are some ideas of the types of research we anticipate being useful to development of a research-based competency model approach:
|AI literacy competency framework||AI literacy assessments||AI literacy education||AI literacy policy|
|Quasi–Experimental||External validation to determine of AI ethics competency actually changes behavior in the workplace||Comparison of alternative assessment strategies among groups of consumers and co-workers||Effectiveness of an e-learning curriculum for achieving collaborator level literacy skills||Difference-in-difference assessment of two more school district policies for AI literacy instruction|
|Meta Analysis||Systematic review of data literacy frameworks and their application in non-STEM majors||Systematic review of competency assessments across literacy initiatives||Systematic review of the effectiveness of MOOC programs teaching AI literacy skills||Systematic review of government policies regarding the application of low AI systems in education settings|
|Case Study/ Ethnography||Case study of an HR department using an AI literacy framework to create job descriptions||Case study of an organization HR department using an AI literacy competency model for recruiting||Case study of a AI literacy curriculum used for first year students at a community college||Case study of a state government attempt to pass regulations for AI use in medicine|
|Technology development and evaluation||Development and evaluation of program that HR departments to score resumes based on AI literacy skills identified||Development and evaluation of an App that allows students to self-assess their AI literacy skills||Development and evaluation of an AI literacy spaced repetition e-learning tool for high school students||Development and evaluation of NLP tool to analyze policy documents for AI literacy implications|