ML-Quest: a game for introducing machine learning concepts to K-12 students

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.

KEYWORDS:

• Machine learning
• games
• learning
• K-12 education
• teaching

Acknowledgments

We would like to thank all the participants for their valuable time and honest feedback. Shruti Priya and Shubhankar Bhadra have contributed to the design and development of the game and its deployment. Sridhar Chimalakonda and Akhila Sri Manasa Venigalla have contributed more towards the idea, providing inputs and suggestions during the design, deployment and evaluation of the game. The authors declare that ethics statement is not applicable for this work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The game is made available for play online at https://i.simmer.io/@shobhi1310/ml-game.

Notes

1 https://unity.com/solutions/console-and-pc-games.

2 https://assetstore.unity.com/publishers/7659.

3 https://assetstore.unity.com/packages/3d/environments/landscapes/lowpoly-environment-pack-99479.

4 https://assetstore.unity.com/packages/3d/environments/house-pack-35346.

5 https://assetstore.unity.com/publishers/17283.

6 https://assetstore.unity.com/publishers/20529.

7 https://assetstore.unity.com/packages/tools/ai/easy-population-102334.

8 https://assetstore.unity.com/packages/3d/props/feline-gargoyle-27106.

9 https://assetstore.unity.com/packages/3d/props/weapons/free-medieval-weapons-72541.

10 https://assetstore.unity.com/packages/tools/gui/textmesh-pro-effect-156234.

11 https://developer.mozilla.org/en-US/docs/Web/API/WebGL_API.

12 https://simmer.io.

13 https://luden.io/wtl/.

Additional information

Notes on contributors

Shruti Priya

Shruti Priya is a BTech student in the Department of Computer Science & Engineering at IIT Tirupati, India. She is interested in the area of Software development dealing with Human Computer Interaction, Data Analysis and Machine Learning. Mostly, her projects deal with finding solutions to improve quality of education and code quality analysis to help novice programmers.

Shubhankar Bhadra

Shubhankar Bhadra is a BTech student in the Department of Computer Science and Engineering at IIT Tirupati, India. He is interested in the area of web and application development along with interest in optimization of algorithms. His projects mostly deal with developing solutions and products to solve various problems with a smart approach.

Sridhar Chimalakonda

Sridhar Chimalakonda is an Assistant Professor in the Department of Computer Science & Engineering at IIT Tirupati, India. He received his PhD and MS in Research in Computer Science & Engineering from the International Institute of Information Technology – Hyderabad, India. He leads the Research in Intelligent Software and Human Analytics (RISHA) Lab which primarily works in the area of Software Engineering, and specifically towards empirically and qualitatively assessing quality, reuse, architecture and evolution of a broad range of software systems (such as mobile, web, games and so on). He is passionate about the massive potential of technology for improving the quality of education and automation in educational technologies.

Akhila Sri Manasa Venigalla

Akhila Sri Manasa Venigalla is a PhD Scholar in the Department of Computer Science and Engineering, pursuing her thesis in the areas of Software Engineering and Software Documentation, at the Indian Institute of Technology Tirupati, Tirupati, India. She is interested in the areas of End User Software Engineering. More specifically, her work examines research aspects in finding ways to support novice programmers and end user software engineers.