DIGITAL LIBRARY
GAMIFICA - CONTINUOUS LEARNING THROUGH GAMIFICATION MECHANISMS FOR MACHINE LEARNING
Universidad Politécnica de Madrid (SPAIN)
About this paper:
Appears in: EDULEARN23 Proceedings
Publication year: 2023
Pages: 4148-4154
ISBN: 978-84-09-52151-7
ISSN: 2340-1117
doi: 10.21125/edulearn.2023.1108
Conference name: 15th International Conference on Education and New Learning Technologies
Dates: 3-5 July, 2023
Location: Palma, Spain
Abstract:
GAMIFICA is an educational innovation project that aims to enhance the learning experience and motivation of students by incorporating gamification elements into the teaching of machine learning subject at Higher Education Area (HEA).

Machine learning is an area belonging to artificial intelligence and is multidisciplinary in nature as it requires mathematical, statistical, and programming knowledge. It studies algorithms that improve automatically through experience (Mitchell, 1997). These algorithms build mathematical models based on a set of data, called "training data" to make predictions or decisions without being explicitly programmed. This paper presents the design of a learning framework that can be integrated into the curriculum to make the learning process more interactive and dynamic in a supervised machine learning task. This is achieved through the creation of public leaderboards (Emily, 2015) that measure the skills of students performing a task and, synchronous and asynchronous activities to help students understand and apply the key concepts of supervised machine learning. A set of Likert-scale questions to explore students’ achievements is employed to assess the impact of gamification. Furthermore, two hypotheses are tested: (1) is the interest and motivation of the student related to the obtained ranking?; and, (2) is the perceived knowledge acquisition related to the obtained ranking? Additionally, the project addresses the development of an online platform that supports continuous learning by providing students with personalized feedback. The same platform includes forms that help educators to design more engaging and effective learning experiences for their students.

References:
[1] (Mitchell, 1997) T. Mitchell, “Machine Learning”. McGraw Hill, 1997
[2] (Emily 2015) E. Sun, Brooke Jones, Stefano Traca, and Maarten W. Bos. 2015. Leaderboard Position Psychology: Counterfactual Thinking. In ACM Conference on Human Factors in Computing Systems. 1217–1222.
Keywords:
Machine learning education, gamification, active learning.