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Games alone will not make schools more efficient, cannot replace teachers or serve as an educational resource that can reach an infinite number of students. The extent of the roles games will play in learning remains to be seen. More research in this area is needed to determine impact of games and learning.
Additional studies regarding typical errors made by instructors and the effects of the errors on acquisition of skills by learners are needed. In addition, prompting procedures have been primarily used to teach specific responses rather than response classes (e.g., conversational skills, social play skills). The relative effectiveness of ...
Today's games are more social, with most teens playing games with others at least some of the time and can incorporate many aspects of civic and political life. [12] In classrooms, social game-based learning platforms are increasing in popularity, as they purport to enable students to reinforce knowledge and develop social and leadership skills.
The development of these skills provides them with the tools to navigate the social context of a kindergarten classroom. These developments become obvious during children's social interactions that transform from playing alongside of their peers, to more complex and coordinated play amongst peers. [1] This transformation in social abilities ...
Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist in a shared environment. [ 1 ] Each agent is motivated by its own rewards, and does actions to advance its own interests; in some environments these interests are opposed to the ...
Social learning theory is a theory of social behavior that proposes that new behaviors can be acquired by observing and imitating others. It states that learning is a cognitive process that takes place in a social context and can occur purely through observation or direct instruction, even in the absence of motor reproduction or direct reinforcement. [1]
Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. Reinforcement learning is a behavioral learning ...
It was designed to play human opponents in games of noughts and crosses (tic-tac-toe) by returning a move for any given state of play and to refine its strategy through reinforcement learning. This was one of the first types of artificial intelligence.