31 citations · 61 across the 15 of their papers we have counts for
15 papers
Understanding teens' self-beliefs when learning to construct and deconstruct AI/ML systems: Developing a survey instrument
Luis Morales-Navarro, Deborah Fields, Michael T. Giang +3
Despite growing calls to foster AI literacy, there are few available survey instruments designed for children and youth that study computational empowerment alongside construction…
Building to Understand: Examining Teens' Technical and Socio-Ethical Pieces of Understandings in the Construction of Small Generative Language Models
Luis Morales-Navarro, Daniel J. Noh, Lucianne Servat +3
The rising adoption of generative AI/ML technologies increases the need to support teens in developing AI/ML literacies. Child-computer interaction research argues that constructio…
Rapid Testing, Duck Lips, and Tilted Cameras: Youth Everyday Algorithm Auditing Practices with Generative AI Filters
Lauren Vogelstein, Vedya Konda, Deborah Fields +3
Today's youth have extensive experience interacting with artificial intelligence and machine learning applications on popular social media platforms, putting youth in a unique posi…
CreateAI Insights from an NSF Workshop on K12 Students, Teachers, and Families as Designers of Artificial Intelligence and Machine Learning Applications
Yasmin Kafai, José Ramón Lizárraga, R. Benjamin Shapiro
In response to the exponential growth in the use of artificial intelligence and machine learning applications, educators, researchers and policymakers have taken steps to integrate…
Expanding the Scope of Computational Thinking in Artificial Intelligence for K-12 Education
Yasmin Kafai, Shuchi Grover
The introduction of generative artificial intelligence applications to the public has led to heated discussions about its potential impacts and risks for K-12 education. One partic…
Learning AI Auditing: A Case Study of Teenagers Auditing a Generative AI Model
Luis Morales-Navarro, Michelle Gan, Evelyn Yu +3
This study investigates how high school-aged youth engage in algorithm auditing to identify and understand biases in artificial intelligence and machine learning (AI/ML) tools they…
Building babyGPTs: Youth Engaging in Data Practices and Ethical Considerations through the Construction of Generative Language Models
Luis Morales-Navarro, Daniel J. Noh, Yasmin B. Kafai
As generative language models (GLMs) have gained popularity, youth are increasingly using them in their everyday lives. As such, most research has centered on supporting youth as u…
What Can Youth Learn About Artificial Intelligence and Machine Learning in One Hour? Examining How Hour of Code Activities Address the Five Big Ideas of AI
Luis Morales-Navarro, Yasmin B. Kafai, Eric Yang +1
The prominence of artificial intelligence and machine learning in everyday life has led to efforts to foster AI literacy for all K-12 students. In this paper, we review how Hour of…
Learning About Algorithm Auditing in Five Steps: Scaffolding How High School Youth Can Systematically and Critically Evaluate Machine Learning Applications
Luis Morales-Navarro, Yasmin B. Kafai, Lauren Vogelstein +2
While there is widespread interest in supporting young people to critically evaluate machine learning-powered systems, there is little research on how we can support them in inquir…
Unpacking Approaches to Learning and Teaching Machine Learning in K-12 Education: Transparency, Ethics, and Design Activities
Luis Morales-Navarro, Yasmin B. Kafai
In this conceptual paper, we review existing literature on artificial intelligence/machine learning (AI/ML) education to identify three approaches to how learning and teaching ML c…
Learning about Data, Algorithms, and Algorithmic Justice on TikTok in Personally Meaningful Ways
Luis Morales-Navarro, Yasmin B. Kafai, Ha Nguyen +11
TikTok, a popular short video sharing application, emerged as the dominant social media platform for young people, with a pronounced influence on how young women and people of colo…
Youth as Peer Auditors: Engaging Teenagers with Algorithm Auditing of Machine Learning Applications
Luis Morales-Navarro, Yasmin B. Kafai, Vedya Konda +1
As artificial intelligence/machine learning (AI/ML) applications become more pervasive in youth lives, supporting them to interact, design, and evaluate applications is crucial. Th…
Investigating Youths' Everyday Understanding of Machine Learning Applications: a Knowledge-in-Pieces Perspective
Luis Morales-Navarro, Yasmin B. Kafai
Despite recent calls for including artificial intelligence (AI) literacy in K-12 education, not enough attention has been paid to studying youths' everyday knowledge about machine…
Twenty Constructionist Things to Do with Artificial Intelligence and Machine Learning
Yasmin Kafai, Luis Morales-Navarro
In this paper, we build on the 1971 memo "Twenty Things to Do With a Computer" by Seymour Papert and Cynthia Solomon and propose twenty constructionist things to do with artificial…
Not Just Training, Also Testing: High School Youths' Perspective-Taking through Peer Testing Machine Learning-Powered Applications
L. Morales-Navarro, M. Shah, Y. B. Kafai
Most attention in K-12 artificial intelligence and machine learning (AI/ML) education has been given to having youths train models, with much less attention to the equally importan…