![]() The participants felt empowered by the significant gains in their literacy and conceptual understanding of AI. ![]() The results of their pre- and post-course conceptual tests, surveys and self-reflective writing tasks indicated that the courses successfully equipped the participants with a conceptual understanding of AI. Eighty-two volunteers completed two AI literacy courses comprising 7 h of machine learning and 9 h of deep learning. This study fills the knowledge gap by evaluating AI literacy courses that aim to build conceptual understanding among university students from diverse study backgrounds. There is a research gap in refocussing AI literacy courses from combining conceptual learning with mathematical formulae and programming codes to emphasising conceptual building from the beginning. The innovative teaching experience carried out during two years meant a great motivation, an improvement of the learning capacity and a continuous recycling of knowledge to which Computer Engineers are faced to.Īrtificial intelligence (AI) applications have become prevalent in all walks of life, but efforts to promote AI literacy to educated citizens from diverse study backgrounds are limited. The main objective of this work is to gamify the classroom with the idea of providing students with valuable hands-on experience by means of addressing a real problem, as well as the possibility to cooperate and compete simultaneously to acquire ML competences. In this context, communities offering platforms for open competitions such as Kaggle can be used as a motivating element. Developing the necessary competences in this field is not a trivial task, and applying innovative methodologies such as gamification can smooth the initial learning curve. It falls under the umbrella of Data Science and is usually developed by Computer Engineers becoming what is known as Data Scientists. The strength of the AI opponent can be varied, there is a save game feature and the game keeps track of the moves played and has the option to print these.Machine learning (ML) is the field of science that combines knowledge from artificial intelligence, statistics and mathematics intending to give computers the ability to learn from data without being explicitly programmed to do so. The games play in a small window, are mouse controlled, have optional music and sound effects plus an internet play option. This implementation gives the player the options to play Five Men's Morris, Six Men's Morris, Nine Men's Morris, and Twelve Men's Morris, the Five and Six men variants are played on the same board but the Nine and Twelve man variants each use a different board. A player wins when their opponent is reduced to two men, because then they can no longer make a line of three, or when an opponent has no more legal moves to make. When all pieces have been placed the second phase begins, here players move their pieces around the board and once again, whenever a player completes a line of three men they can remove one of their opponent's men. Whenever a player completes a 'mill', or line of three pieces they can remove one of their opponent's pieces. It starts with players placing their pieces/men at intersections of lines and corners of the squares. The is played on a board with concentric squares marked on it, these are connected by lines. Nine Men's Morris is a player vs computer, mouse controlled, implementation of a strategy board game that dates back to the Roman Empire.
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