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The Future of AI Can Be Kind: Strategies for Embedded Ethics in AI Education
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Yim Register – ProQuest LLC, 2024
The field of Data Science has seen rapid growth over the past two decades, with a high demand for people with skills in data analytics, programming, statistics, and ability to visualize, predict from, and otherwise make sense of data. Alongside the rise of various artificial intelligence (AI) and machine learning (ML) applications, we have also…
Descriptors: Artificial Intelligence, Ethics, Algorithms, Data Science
What Is Common to Transportation and Health in Machine Learning Education? The Domain Neglect Bias
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Mike, Koby; Hazzan, Orit – IEEE Transactions on Education, 2023
Contribution: This article presents evidence that electrical engineering, computer science, and data science students, participating in introduction to machine learning (ML) courses, fail to interpret the performance of ML algorithms correctly, since they fail to consider the application domain. This phenomenon is referred to as the domain neglect…
Descriptors: Engineering Education, Computer Science Education, Data Science, Introductory Courses
Explainable AI (XAI): Improving At-Risk Student Prediction with Theory-Guided Data Science, K-Means Classification, and Genetic Programming
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Bui, Ngoc Van P. – ProQuest LLC, 2022
This research explores the use of eXplainable Artificial Intelligence (XAI) in Educational Data Mining (EDM) to improve the performance and explainability of artificial intelligence (AI) and machine learning (ML) models predicting at-risk students. Explainable predictions provide students and educators with more insight into at-risk indicators and…
Descriptors: Artificial Intelligence, At Risk Students, Prediction, Data Science
AI MyData: Fostering Middle School Students' Engagement with Machine Learning through an Ethics-Infused AI Curriculum
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Ismaila Temitayo Sanusi; Fred Martin; Ruizhe Ma; Joseph E. Gonzales; Vaishali Mahipal; Solomon Sunday Oyelere; Jarkko Suhonen; Markku Tukiainen – ACM Transactions on Computing Education, 2024
As initiatives on AI education in K-12 learning contexts continues to evolve, researchers have developed curricula among other resources to promote AI across grade levels. Yet, there is a need for more effort regarding curriculum, tools, and pedagogy, as well as assessment techniques to popularize AI at the middle school level. Drawing on prior…
Descriptors: Artificial Intelligence, Middle School Students, Learner Engagement, Technology Uses in Education
Exploring a Digital Educational Escape Room Game to Support Artificial Intelligence Literacy and Team Building in an Online Environment
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Susie Gronseth; Amani Itani; Kathryn Seastrand; Bettina Beech; Marino Bruce; Thamar Solorio; Ioannis Kakadiaris – Journal of Interactive Learning Research, 2025
This study examines the design, implementation, and evaluation of a Digital Educational Escape Room (DEER) titled "Escape from the Doctor's Office," developed to enhance artificial intelligence/machine learning (AI/ML) literacy. Grounded in constructivist pedagogy and behaviorist principles, the DEER was designed using the ADDIE…
Descriptors: Educational Games, Artificial Intelligence, Technological Literacy, Teamwork
Teacher Alchemy? The Potential for Combining Digital and Social Methodologies in Supporting Learners in the Humanities and Social Sciences
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Sandra Leaton Gray; Mutlu Cukurova – Cogent Education, 2024
Debates surrounding the use of data science in educational AI are frequently rather entrenched, revolving around commercial models and talk of teacher replacement. This article explores the potential for digital textual analysis within humanities and social science education, advocating for a sociologically-driven approach that complements, rather…
Descriptors: Humanities, Social Sciences, Social Science Research, Research Methodology
Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines. Postdigital Science and Education
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Dora Kourkoulou, Editor; Anastasia-Olga Tzirides, Editor; Bill Cope, Editor; Mary Kalantzis, Editor – Springer, 2024
"Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines" is a resource for researchers and practitioners in a field where the mainstreaming of AI technologies, and their increased capacities for deception, have produced confusion and fear. Identifying theoretical frameworks and practices in teaching…
Descriptors: Trust (Psychology), Inclusion, Artificial Intelligence, Technology Uses in Education