research-article

Open access

AI Book Club: An Innovative Professional Development Model for AI Education

Authors:

Beatriz Perret,

Grace PuAuthors Info & Claims

SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 1

Pages 202 - 208

https://doi.org/10.1145/3478431.3499318

Published: 22 February 2022 Publication History

Abstract

This paper describes an AI Book Club as an innovative 20-hour professional development (PD) model designed to prepare teachers with AI content knowledge and an understanding of the ethical issues posed by bias in AI that are foundational to developing AI-literate citizens. The design of the intervention was motivated by a desire to manage the cognitive load of AI learning by spreading the PD program over several weeks and a desire to form and maintain a community of teachers interested in AI education during the COVID-19 pandemic. Each week participants spent an hour independently reading selections from an AI book, reviewing AI activities, and viewing videos of other educators teaching the activities, then met online for 1 hour to discuss the materials and brainstorm how they might adapt the materials for their classrooms. The participants in the AI Book Club were 37 middle school educators from 3 US school districts and 5 youth-serving organizations. The teachers are from STEM disciplines as well as Social Studies and Art. Eighty-nine percent were from underrepresented groups in STEM and CS. In this paper we describe the design of the AI Book Club, its implementation, and preliminary findings on teachers' impressions of the AI Book Club as a form of PD, thoughts about teaching AI in classrooms, and interest in continuing the book club model in the upcoming year. We conclude with recommendations for others interested in implementing a book club PD format for AI learning.

References

[1]

Barab, S. A., Barnett, M. G., & Squire, K. (2002). Building a community of teachers: Navigating the essential tensions in practice. The Journal of The Learning Sciences, 11(4), 489--542.

[2]

Costanza-Chock, S. (2020). Design Justice: Community-Led Practices to Build the Worlds We Need. MIT Press.

[3]

Developing AI Literacy (DAILy) curriculum. https://aieducation.mit.edu

[4]

DiPaola, D., Ali, S., Hong, J., Zhang, H., Breazeal, C., & Lee, I. (2020). Youth as Investigators of Bias in Artificial Intelligence. American Educational Research Association 2021.

[5]

Ethical and Societal Implications of Data and Artificial Intelligence: A roadmap for research. (2019). Nuffield Foundation. https://www.nuffieldfoundation.org/sites/default/files/files/Ethical-and-Societal-Implications-of-Data-and-AI-report-Nuffield-Foundat.pdf

[6]

Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.

[7]

Gardner-McCune, C., Touretzky, D., Martin, F., and Seehorn, D. (2019). AI for K-12: Making Room for AI in K-12 CS Curricula. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19). ACM, New York, NY, USA, 1244--1244.

Digital Library

[8]

Hakkarainen, K., Palonen, T., Paavola, S., & Lehtinen, E. (2004). Communities of networked expertise: Professional and educational perspectives. Elsevier Scientific Publ. Co.

[9]

Kalyuga, S. & Liu, T. C. (2015). Managing Cognitive Load in Technology-Based Learning Environments. Educational Technology & Society, 18 (4), 1--8.

[10]

Katz, S., Earl, L., Ben Jaafar, S., Elgie, S., Foster, L., Halbert, J., & Kaser, L. (2008). Learning networks of schools: The key enablers of successful knowledge communities. McGill Journal of Education/Revue des sciences de l'éducation de McGill, 43(2), 111--137.

[11]

Lee, I., Ali, S., Zhang, H., DiPaola, D., Breazeal, C. (2020). Developing Middle School Students' AI Literacy. In Proceedings of the 52nd ACM technical symposium on computer science education.

[12]

Long, D., and Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, 1--16.

Digital Library

[13]

Marques, L. S., Gresse Von Wangenheim, C., & Hauck, J. C. R. (2020). Teaching Machine Learning in School: A Systematic Mapping of the State of the Art. Informatics in Education, 283--321. https://doi.org/10.15388/infedu.2020.14

[14]

Mitchell, M. (2019). Artificial Intelligence: A Guide for Thinking Humans. Picador.

[15]

Select Committee on AI. (2018). AI in the UK: ready, willing and able. House of Lords Paper 100, 183. https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf

[16]

Sweller, J. (1988). "Cognitive Load During Problem Solving: Effects on Learning". Cognitive Science. 12 (2): 257--285.

[17]

Sweller, J., van Merrienboer, J. J. G., Paas, F. G. W. C. (1998). "Cognitive Architecture and Instructional Design". Educational Psychology Review. 10 (3): 251--296. S2CID 127506.

[18]

Tedre, M., Toivonen, T., Kaihila, J., Vartiainen, H., Valtonen, T., Jormanainen, I., & Pears, A. (2021). Teaching Machine Learning in K-12 Computing Education: Potential and Pitfalls. ArXiv:2106.11034 [Cs]. http://arxiv.org/abs/2106.11034

[19]

Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge University Press.

[20]

Zhang, H., Lee, I., Ali, S., DiPaola, D., Cheng, Y., & Breazeal, C. (2021). Integrating Ethics and Career Futures with Technical Learning to Promote AI Literacy for Middle School Students: An Exploratory Study. In publication, International Journal of AI Education.

Cited By

Elsakova RMarkus’ A(2024)Professional Development of University Educators in Artificial Intelligence: Current StateVysshee Obrazovanie v Rossii = Higher Education in Russia10.31992/0869-3617-2024-33-11-73-9433:11(73-94)Online publication date: 2-Dec-2024
https://doi.org/10.31992/0869-3617-2024-33-11-73-94
Quiroz PGutierrez FStephenson BStone JBattestilli LRebelsky SShoop L(2024)Scratch-NB: A Scratch Extension for Introducing K-12 Learners to Supervised Machine LearningProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630920(1077-1083)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3626252.3630920
Li HKim S(2024)Developing AI literacy in HRD: competencies, approaches, and implicationsHuman Resource Development International10.1080/13678868.2024.233796227:3(345-366)Online publication date: 5-Apr-2024
https://doi.org/10.1080/13678868.2024.2337962
Show More Cited By

Index Terms

AI Book Club: An Innovative Professional Development Model for AI Education
1. Computing methodologies
  1. Machine learning
2. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Adult education
      2. Model curricula

Recommendations

AI Literacy: Finding Common Threads between Education, Design, Policy, and Explainability
CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Fostering public AI literacy has been a growing area of interest at CHI for several years, and a substantial community is forming around issues such as teaching children how to build and program AI systems, designing learning experiences to broaden ...
ActiveAI: The Effectiveness of an Interactive Tutoring System in Developing K-12 AI Literacy
Technology Enhanced Learning for Inclusive and Equitable Quality Education
Abstract
As we witness groundbreaking advancements in Artificial Intelligence (AI), it is clear that the next generation must be equipped with AI literacy: the skill to interact, evaluate, and collaborate with AI systems. This study introduces ActiveAI, a ...
Improving Teachers' Self-Confidence in Learning Technology Skills and Math Education through Professional Development

Using technology tools in math instruction can help stimulate problem-solving skills and understanding of math concepts. However, teachers need to be confident in their abilities to use technology tools. This study investigated whether or not a four-...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 1

February 2022

1049 pages

ISBN:9781450390705

DOI:10.1145/3478431

General Chairs:
Larry Merkle
Air Force Institute of Technology, USA
,
Maureen Doyle
Northern Kentucky University, USA
,
Program Chairs:
Judithe Sheard
Monash University, Australia
,
Leen-Kiat Soh
University of Nebraska-Lincoln, USA
,
Brian Dorn
University of Nebraska at Omaha, USA

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License.

Sponsors

SIGCSE: ACM Special Interest Group on Computer Science Education

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 February 2022

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

National Science Foundation

Conference

SIGCSE 2022

Sponsor:

SIGCSE

SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education

March 3 - 5, 2022

RI, Providence, USA

Acceptance Rates

Overall Acceptance Rate 1,595 of 4,542 submissions, 35%

Upcoming Conference

SIGCSE TS 2025

Sponsor:
sigcse

The 56th ACM Technical Symposium on Computer Science Education

February 26 - March 1, 2025

Pittsburgh , PA , USA

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
1,423
Total Downloads

Downloads (Last 12 months)796
Downloads (Last 6 weeks)108

Reflects downloads up to 24 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Elsakova RMarkus’ A(2024)Professional Development of University Educators in Artificial Intelligence: Current StateVysshee Obrazovanie v Rossii = Higher Education in Russia10.31992/0869-3617-2024-33-11-73-9433:11(73-94)Online publication date: 2-Dec-2024
https://doi.org/10.31992/0869-3617-2024-33-11-73-94
Quiroz PGutierrez FStephenson BStone JBattestilli LRebelsky SShoop L(2024)Scratch-NB: A Scratch Extension for Introducing K-12 Learners to Supervised Machine LearningProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630920(1077-1083)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3626252.3630920
Li HKim S(2024)Developing AI literacy in HRD: competencies, approaches, and implicationsHuman Resource Development International10.1080/13678868.2024.233796227:3(345-366)Online publication date: 5-Apr-2024
https://doi.org/10.1080/13678868.2024.2337962
Huang LLiang MXiong YWu XLim C(2024)A Systematic Review of Technology-Enabled Teacher Professional Development During COVID -19 PandemicComputers & Education10.1016/j.compedu.2024.105168(105168)Online publication date: Sep-2024
https://doi.org/10.1016/j.compedu.2024.105168
Li LYu FZhang E(2024)A systematic review of learning task design for K-12 AI education: Trends, challenges, and opportunitiesComputers and Education: Artificial Intelligence10.1016/j.caeai.2024.1002176(100217)Online publication date: Jun-2024
https://doi.org/10.1016/j.caeai.2024.100217
Yeter IYang WSturgess J(2024)Global initiatives and challenges in integrating artificial intelligence literacy in elementary education: Mapping policies and empirical literatureFuture in Educational Research10.1002/fer3.59Online publication date: 18-Oct-2024
https://doi.org/10.1002/fer3.59
Domínguez Figaredo DStoyanovich J(2023)Responsible AI literacy: A stakeholder-first approachBig Data & Society10.1177/2053951723121995810:2Online publication date: 19-Dec-2023
https://doi.org/10.1177/20539517231219958
Allison J(2023)Classifying the Characteristics of Effective Continuing Professional Development (CPD) for Computer Science Teachers in the 16-18 SectorACM Transactions on Computing Education10.1145/358227523:2(1-30)Online publication date: 8-Jun-2023
https://dl.acm.org/doi/10.1145/3582275
DiPaola DMoore KAli SPerret BZhou XZhang HLee IDoyle MStephenson BDorn BSoh LBattestilli L(2023)Make-a-Thon for Middle School AI EducatorsProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569743(305-311)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569743

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents