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http://dx.doi.org/10.9717/kmms.2020.24.4.593

FlappyBird Competition System: A Competition-Based Assessment System for AI Course  

Sohn, Eisung (University College, Yonsei University)
Kim, Jaekyung (University College, Yonsei University)
Publication Information
Journal of Korea Multimedia Society / v.24, no.4, 2021 , pp. 593-600 More about this Journal
Abstract
In this paper, we present the FlappyBird Competition System (FCS) implementation, a competition-based automated assessment system used in an entry-level artificial intelligence (AI) course at a university. The proposed system provides an evaluation method suitable for AI courses while taking advantage of automated assessment methods. Students are to design a neural network structure, train the weights, and tune hyperparameters using the given reinforcement learning code to improve the overall performance of game AI. Students participate using the resulting trained model during the competition, and the system automatically calculates the final score based on the ranking. The user evaluation conducted after the semester ends shows that our competition-based automated assessment system promotes active participation and inspires students to be interested and motivated to learn AI. Using FCS, the instructor significantly reduces the amount of time required for assessment.
Keywords
Online Judge; Competition-Based Learning; Gamification; AI Education; Automated assessment;
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