Teaching the Foundations of Machine Learning with Candy

Daniela Huppenkothen, Gwendolyn Eadie
Proceedings of the First Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 141:29-35, 2021.

Abstract

Machine learning is ubiquitous in decision-making processes across society. The presence and development of ML drives a need for improved education in key concepts at the secondary and tertiary levels that not only trains people to become informed citizens but also trains future researchers to be both principled and ethical practitioners. In this vein, we present a structured classroom activity that simultaneously teaches both supervised classification and critically thinking about ML applications and ethics. We use an active, object-based learning approach to teach supervised classification using a variety of candies, and a problem-based scenario to encourage critical questions about ethics in ML applications.

Cite this Paper

BibTeX
@InProceedings{pmlr-v141-huppenkothen21a, title = {Teaching the Foundations of Machine Learning with Candy}, author = {Huppenkothen, Daniela and Eadie, Gwendolyn}, booktitle = {Proceedings of the First Teaching Machine Learning and Artificial Intelligence Workshop}, pages = {29--35}, year = {2021}, editor = {Bischl, Bernd and Guhr, Oliver and Seibold, Heidi and Steinbach, Peter}, volume = {141}, series = {Proceedings of Machine Learning Research}, month = {14 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v141/huppenkothen21a/huppenkothen21a.pdf}, url = {https://proceedings.mlr.press/v141/huppenkothen21a.html}, abstract = {Machine learning is ubiquitous in decision-making processes across society. The presence and development of ML drives a need for improved education in key concepts at the secondary and tertiary levels that not only trains people to become informed citizens but also trains future researchers to be both principled and ethical practitioners. In this vein, we present a structured classroom activity that simultaneously teaches both supervised classification and critically thinking about ML applications and ethics. We use an active, object-based learning approach to teach supervised classification using a variety of candies, and a problem-based scenario to encourage critical questions about ethics in ML applications.} }
Endnote
%0 Conference Paper %T Teaching the Foundations of Machine Learning with Candy %A Daniela Huppenkothen %A Gwendolyn Eadie %B Proceedings of the First Teaching Machine Learning and Artificial Intelligence Workshop %C Proceedings of Machine Learning Research %D 2021 %E Bernd Bischl %E Oliver Guhr %E Heidi Seibold %E Peter Steinbach %F pmlr-v141-huppenkothen21a %I PMLR %P 29--35 %U https://proceedings.mlr.press/v141/huppenkothen21a.html %V 141 %X Machine learning is ubiquitous in decision-making processes across society. The presence and development of ML drives a need for improved education in key concepts at the secondary and tertiary levels that not only trains people to become informed citizens but also trains future researchers to be both principled and ethical practitioners. In this vein, we present a structured classroom activity that simultaneously teaches both supervised classification and critically thinking about ML applications and ethics. We use an active, object-based learning approach to teach supervised classification using a variety of candies, and a problem-based scenario to encourage critical questions about ethics in ML applications.
APA
Huppenkothen, D. & Eadie, G.. (2021). Teaching the Foundations of Machine Learning with Candy. Proceedings of the First Teaching Machine Learning and Artificial Intelligence Workshop, in Proceedings of Machine Learning Research 141:29-35 Available from https://proceedings.mlr.press/v141/huppenkothen21a.html.

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