Back to Search
Start Over
ML-Quest: a game for introducing machine learning concepts to K-12 students.
- Source :
-
Interactive Learning Environments . Feb2024, Vol. 32 Issue 1, p229-244. 16p. - Publication Year :
- 2024
-
Abstract
- Owing to the predominant role of Machine Learning(ML) across domains, it is being introduced at multiple levels of education, including K-12. Researchers have leveraged games, augmented reality and other ways to make learning ML concepts interesting. However, most of the existing games to teach ML concepts either focus on use-cases and applications of ML instead of core concepts or directly introduce ML terminologies, which might be overwhelming to school students. Hence, in this paper, we propose ML-Quest, a game to incrementally present a conceptual overview of three ML concepts: Supervised Learning, Gradient Descent and K-Nearest Neighbor (KNN) Classification. The game has been evaluated through a controlled experiment, for its usefulness and player experience using the TAM model, with 41 higher-secondary school students. Results show that students in the experimental group perform better in the test than students in the control group, with 5% of students in the experimental group scoring full marks. However, none of the students in the control group could score full marks. The survey results indicate that around 77% of the participants who played the game either agree or strongly agree that ML-Quest has made their learning interactive and is helpful in introducing them to ML concepts. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10494820
- Volume :
- 32
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Interactive Learning Environments
- Publication Type :
- Academic Journal
- Accession number :
- 175722366
- Full Text :
- https://doi.org/10.1080/10494820.2022.2084115