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Benjamin Walsh

dblp:209/6094 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2023
0000-0003-0515-4626ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computing education · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computing education › ethics education
AI ethics education
0.712023
Literacy and STEM Teachers Adapt AI Ethics Curriculum · AAAI 2023
Computing education
teacher professional development
0.712023
Literacy and STEM Teachers Adapt AI Ethics Curriculum · AAAI 2023

Methods — techniques the papers use, named apart from their topics

qualitative case study · 0.7TPACK framework · 0.7
YearPublicationVenuePosition
2023 Literacy and STEM Teachers Adapt AI Ethics Curriculum
abstract
This article examines the ways secondary computer science and English Language Arts teachers in urban, suburban, and semi-rural schools adapted a project-based AI ethics curriculum to make it better fit their local contexts. AI ethics is an urgent topic with tangible consequences for youths’ current and future lives, but one that is rarely taught in schools. Few teachers have formal training in this area as it is an emerging field even at the university level. Exploring AI ethics involves examining biases related to race, gender, and social class, a challenging task for all teachers, and an unfamiliar one for most computer science teachers. It also requires teaching technical content which falls outside the comfort zone of most humanities teachers. Although none of our partner teachers had previously taught an AI ethics project, this study demonstrates that their expertise and experience in other domains played an essential role in providing high quality instruction. Teachers designed and redesigned tasks and incorporated texts and apps to ensure the AI ethics project would adhere to district and department level requirements; they led equity-focused inquiry in a way that both protected vulnerable students and accounted for local cultures and politics; and they adjusted technical content and developed hands-on computer science experiences to better challenge and engage their students. We use Mishra and Kohler’s TPACK framework to highlight the ways teachers leveraged their own expertise in some areas, while relying on materials and support from our research team in others, to create stronger learning experiences.
Benjamin Walsh, Bridget Dalton, Stacey Forsyth, Tom Yeh
AAAI1
2022 Making Art with and about Artificial Intelligence: Three Approaches to Teaching AI and AI Ethics to Middle and High School Students
abstract
In this hands-on workshop participants will experience the curricula from three NSF funded projects, which engage youth in creating art with and about AI technologies while exploring related ethical concerns.
Benjamin Walsh, Safinah Arshad Ali, Francisco Enrique Vicente Castro, Kayla DesPortes, Daniella DiPaola, Irene Lee, William Payne 0003, Scott Sieke, Helen Zhang
SIGCSE (2)1