What are artificial intelligence literacy and competency? A comprehensive framework to support them
Artificial intelligence (AI) education in K–12 schools is a global initiative, yet planning and executing AI education is challenging. The major frameworks are focused on identifying content and technical knowledge (AI literacy). Most of the current definitions of AI literacy for a non-technical aud...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , |
| Format: | article |
| Published: |
2024
|
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1016/j.caeo.2024.100171 https://www.sciencedirect.com/science/article/pii/S2666557324000120 http://hdl.handle.net/10576/55957 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1857415085214924800 |
|---|---|
| author | Thomas K.F., Chiu |
| author2 | Ahmad, Zubair Ismailov, Murod Sanusi, Ismaila Temitayo |
| author2_role | author author author |
| author_facet | Thomas K.F., Chiu Ahmad, Zubair Ismailov, Murod Sanusi, Ismaila Temitayo |
| author_role | author |
| dc.creator.none.fl_str_mv | Thomas K.F., Chiu Ahmad, Zubair Ismailov, Murod Sanusi, Ismaila Temitayo |
| dc.date.none.fl_str_mv | 2024-06-10T04:11:47Z 2024-06-30 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://dx.doi.org/10.1016/j.caeo.2024.100171 26665573 https://www.sciencedirect.com/science/article/pii/S2666557324000120 http://hdl.handle.net/10576/55957 6 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Elsevier |
| dc.rights.none.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | AI literacy AI competency K-12 education Machine learning Data literacy Generative AI |
| dc.title.none.fl_str_mv | What are artificial intelligence literacy and competency? A comprehensive framework to support them |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Artificial intelligence (AI) education in K–12 schools is a global initiative, yet planning and executing AI education is challenging. The major frameworks are focused on identifying content and technical knowledge (AI literacy). Most of the current definitions of AI literacy for a non-technical audience are developed from an engineering perspective and may not be appropriate for K–12 education. Teacher perspectives are essential to making sense of this initiative. Literacy is about knowing (knowledge, what skills); competency is about applying the knowledge in a beneficial way (confidence, how well). They are strongly related. This study goes beyond knowledge (AI literacy), and its two main goals are to (i) define AI literacy and competency by adding the aspects of confidence and self-reflective mindsets, and (ii) propose a more comprehensive framework for K–12 AI education. These definitions are needed for this emerging and disruptive technology (e.g., ChatGPT and Sora, generative AI). We used the definitions and the basic curriculum design approaches as the analytical framework and teacher perspectives. Participants included 30 experienced AI teachers from 15 middle schools. We employed an iterative co-design cycle to discuss and revise the framework throughout four cycles. The definition of AI competency has five abilities that take confidence into account, and the proposed framework comprises five key components: technology, impact, ethics, collaboration, and self-reflection. We also identify five effective learning experiences to foster abilities and confidences, and suggest five future research directions: prompt engineering, data literacy, algorithmic literacy, self-reflective mindset, and empirical research. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | qu_a37e75c51b775c708e6a8eca027c0450 |
| identifier_str_mv | 26665573 6 |
| language_invalid_str_mv | en |
| network_acronym_str | qu |
| network_name_str | Qatar University repository |
| oai_identifier_str | oai:qspace.qu.edu.qa:10576/55957 |
| publishDate | 2024 |
| publisher.none.fl_str_mv | Elsevier |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| spelling | What are artificial intelligence literacy and competency? A comprehensive framework to support themThomas K.F., ChiuAhmad, ZubairIsmailov, MurodSanusi, Ismaila TemitayoAI literacyAI competencyK-12 educationMachine learningData literacyGenerative AIArtificial intelligence (AI) education in K–12 schools is a global initiative, yet planning and executing AI education is challenging. The major frameworks are focused on identifying content and technical knowledge (AI literacy). Most of the current definitions of AI literacy for a non-technical audience are developed from an engineering perspective and may not be appropriate for K–12 education. Teacher perspectives are essential to making sense of this initiative. Literacy is about knowing (knowledge, what skills); competency is about applying the knowledge in a beneficial way (confidence, how well). They are strongly related. This study goes beyond knowledge (AI literacy), and its two main goals are to (i) define AI literacy and competency by adding the aspects of confidence and self-reflective mindsets, and (ii) propose a more comprehensive framework for K–12 AI education. These definitions are needed for this emerging and disruptive technology (e.g., ChatGPT and Sora, generative AI). We used the definitions and the basic curriculum design approaches as the analytical framework and teacher perspectives. Participants included 30 experienced AI teachers from 15 middle schools. We employed an iterative co-design cycle to discuss and revise the framework throughout four cycles. The definition of AI competency has five abilities that take confidence into account, and the proposed framework comprises five key components: technology, impact, ethics, collaboration, and self-reflection. We also identify five effective learning experiences to foster abilities and confidences, and suggest five future research directions: prompt engineering, data literacy, algorithmic literacy, self-reflective mindset, and empirical research.This is supported by General Research Fund (project code: 14610522), Research Grant Council, Hong Kong, SAR.Elsevier2024-06-10T04:11:47Z2024-06-30Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://dx.doi.org/10.1016/j.caeo.2024.10017126665573https://www.sciencedirect.com/science/article/pii/S2666557324000120http://hdl.handle.net/10576/559576enhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:qspace.qu.edu.qa:10576/559572024-07-23T15:53:57Z |
| spellingShingle | What are artificial intelligence literacy and competency? A comprehensive framework to support them Thomas K.F., Chiu AI literacy AI competency K-12 education Machine learning Data literacy Generative AI |
| status_str | publishedVersion |
| title | What are artificial intelligence literacy and competency? A comprehensive framework to support them |
| title_full | What are artificial intelligence literacy and competency? A comprehensive framework to support them |
| title_fullStr | What are artificial intelligence literacy and competency? A comprehensive framework to support them |
| title_full_unstemmed | What are artificial intelligence literacy and competency? A comprehensive framework to support them |
| title_short | What are artificial intelligence literacy and competency? A comprehensive framework to support them |
| title_sort | What are artificial intelligence literacy and competency? A comprehensive framework to support them |
| topic | AI literacy AI competency K-12 education Machine learning Data literacy Generative AI |
| url | http://dx.doi.org/10.1016/j.caeo.2024.100171 https://www.sciencedirect.com/science/article/pii/S2666557324000120 http://hdl.handle.net/10576/55957 |