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Gamification of learning does not involve students in designing and creating their own games or in playing commercially produced video games, making it distinguishable from game-based learning, or using educational games to learn a concept. Within game-based learning initiatives, students might use Gamestar Mechanic or GameMaker to create their ...
Game-based learning (GBL) is a type of game play that has defined learning outcomes. Generally, game-based learning is designed to balance subject matter with gameplay and the ability of the player to retain, and apply said subject matter to the real world. [4] Children tend to spend hours playing hide and seek, learning the steps of digital ...
In his book What Video Games Have to Teach Us About Learning and Literacy, James Paul Gee talks about the application and principles of digital learning. Gee has focused on the learning principles in video games and how these learning principles can be applied to the K-12 classroom. Successful video games are good at challenging players.
The James Paul Gee Learning Games Awards were created in 2020 to apply Gee's theories to the identification and judging of learning game design. Gee's book is used in Kimon Keramidas' [9] argument explaining the learning processes of gamers. Some of the schema and elements that are used in game designing can be analogously used as "frameworks ...
Gamification techniques are intended to leverage people's evolved desires for socializing, learning, mastery, competition, achievement, status, self-expression, altruism, or closure, or simply their response to the framing of a situation as game or play. [32]
In 2014, an educational researcher concluded a multi-year study of adaptive learning for educational game design. The research developed and validated the ALGAE (Adaptive Learning GAme dEsign) model, a comprehensive adaptive learning model based on game design theories and practices, instructional strategies, and adaptive models.
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The most publicly known application of machine learning in games is likely the use of deep learning agents that compete with professional human players in complex strategy games. There has been a significant application of machine learning on games such as Atari/ALE, Doom, Minecraft, StarCraft, and car racing. [1]
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