From Demo to Design in Teaching Machine Learning

TY - GEN

T1 - From Demo to Design in Teaching Machine Learning

AU - Bilstrup, Karl Emi Kjær

AU - Kaspersen, Magnus Høholt

AU - Assent, Ira

AU - Enni, Simon

AU - Petersen, Marianne Graves

N1 - Publisher Copyright: © 2022 ACM.

PY - 2022/6

Y1 - 2022/6

N2 - The prevalence of artificial intelligence (AI) and machine learning (ML) technologies in digital ecosystems has led to a push for AI literacy, giving everybody, including K-12 students, the necessary knowledge and abilities to engage critically with these new technologies. While there is an increasing focus on designing tools and activities for teaching machine learning, most tools sidestep engaging with the complexity and trade-offs inherent in the design of ML models in favor of demonstrating the power and functionality of the technology. In this paper, we investigate how a design perspective can inform the design of educational tools and activities for teaching machine learning. Through a literature review, we identify 34 tools and activities for teaching ML, and using a design perspective on ML system development, we examine strengths and limitations in how they engage students in the complex design considerations linked to the different components of machine learners. Based on this work, we suggest directions for furthering AI literacy through adopting a design approach in teaching ML.

AB - The prevalence of artificial intelligence (AI) and machine learning (ML) technologies in digital ecosystems has led to a push for AI literacy, giving everybody, including K-12 students, the necessary knowledge and abilities to engage critically with these new technologies. While there is an increasing focus on designing tools and activities for teaching machine learning, most tools sidestep engaging with the complexity and trade-offs inherent in the design of ML models in favor of demonstrating the power and functionality of the technology. In this paper, we investigate how a design perspective can inform the design of educational tools and activities for teaching machine learning. Through a literature review, we identify 34 tools and activities for teaching ML, and using a design perspective on ML system development, we examine strengths and limitations in how they engage students in the complex design considerations linked to the different components of machine learners. Based on this work, we suggest directions for furthering AI literacy through adopting a design approach in teaching ML.

KW - AI literacy

KW - Design

KW - CCTD

KW - CEED

UR - https://www.scopus.com/pages/publications/85132999699

U2 - 10.1145/3531146.3534634

DO - 10.1145/3531146.3534634

M3 - Article in proceedings

AN - SCOPUS:85132999699

SP - 2168

EP - 2178

BT - Proceedings of the 5th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2022

PB - Association for Computing Machinery

T2 - 5th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2022

Y2 - 21 June 2022 through 24 June 2022

ER -