extended-abstract

Classy Trash Monster: An Educational Game for Teaching Machine Learning to Non-major Students

Authors:

Young Yim DohAuthors Info & Claims

CHI EA '22: CHI Conference on Human Factors in Computing Systems Extended Abstracts

Article No.: 479, Pages 1 - 7

https://doi.org/10.1145/3491101.3516487

Published: 28 April 2022 Publication History

Abstract

As machine learning (ML) became more relevant to our lives, ML education for college students without technical background arose important. However, not many educational games designed to suit challenges they experience exist. We introduce an educational game Classy Trash Monster (CTM), designed to better educate ML and data dependency to non-major students who learn ML for the first time. The player can easily learn to train a classification model and solve tasks by engaging in simple game activities designed according to an ML pipeline. Simple controls, positive rewards, and clear audiovisual feedback makes game easy to play even for novice players. The playtest result showed that players were able to learn basic ML concepts and how data can impact model results, and that the game made ML feel less difficult and more relevant. However, proper debriefing session seems crucial to prevent misinterpretations that may occur in the learning process.

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Cited By

Yuan JLieberman HSmith DXin Y(2025)Learner’s Permit: Accessible Artificial Intelligence Through an Educational GameArtificial Intelligence in Education Technologies: New Development and Innovative Practices10.1007/978-981-97-9255-9_32(462-477)Online publication date: 1-Jan-2025
https://doi.org/10.1007/978-981-97-9255-9_32

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Published In

cover image ACM Conferences

CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems

April 2022

3066 pages

ISBN:9781450391566

DOI:10.1145/3491101

Editors:
Simone Barbosa
PUC-Rio, Brazil
,
Cliff Lampe
University of Michigan, USA
,
Caroline Appert
Université Paris-Saclay, France
,
David A. Shamma
Toyota Research Institute, USA

Copyright © 2022 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 28 April 2022

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CHI '22: CHI Conference on Human Factors in Computing Systems

April 29 - May 5, 2022

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Cited By

Yuan JLieberman HSmith DXin Y(2025)Learner’s Permit: Accessible Artificial Intelligence Through an Educational GameArtificial Intelligence in Education Technologies: New Development and Innovative Practices10.1007/978-981-97-9255-9_32(462-477)Online publication date: 1-Jan-2025
https://doi.org/10.1007/978-981-97-9255-9_32

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