Game-based learning in architecture education: Consolidating visual design principles in freshmen

Abstract

Using games to teach people concepts has always been an attention-catching topic in the area of education. That is the main premise of game-based learning. Providing the players with manipulation tools such as the ability to change scale etc. to change the game environment by giving them more flexible options further facilitates their learning through trial and error, and encourages more involvement. With this aim, it was decided to create an artificial intelligence (AI) evaluated free creation video game aimed to consolidate visual design principle (VDP) knowledge in freshmen architecture students. VDPs are the underlying patterns that are present in designs people usually find appealing. The artificial intelligence that was used in the game was trained to detect some of these principles. There are more than only three main elements, however the artificial intelligence is trained on 3 main principles and their derivatives, which end up making up 9 sub VDPs. These VDPs are emphasis (color, isolation, shape), balance (symmetric, asymmetric, crystallographic), rhythm (regular, progressive, flowing). Artificial intelligence was decided to be used in the game because it can detect the trained VDP with success, as well as create a reliable checkpoint before students present their ideas to their instructors, which is time-consuming and might induce stress on some students. The usage of AI aims to eliminate some of that stress and the gaming nature of game-based learning is expected to motivate students further. The game welcomed the players with a menu screen in which they could choose to learn about VDPs with several example pictures and explanations. Following that, they could play a quiz mini-game where they were asked to choose a picture out of three pictures that held the VDP that was asked from them. All 9 sub VDPs, derived out of 3 main design principles, the artificial intelligence can detect were asked in order. Once they were done with the quiz, the game moved on to the "creation" section where the players were given an objective to create a composition with an emphasis on a specific VDP. The composition was managed by placing and manipulating design elements (basic shapes such as square, triangle, hexagon etc. or object textures) on a canvas with a grid. The design elements could snap onto the grid so that it would be easier to create more calculated compositions. When the players were happy with their composition, they submitted their compositions to the application in the background where artificial intelligence resides and that artificial intelligence evaluated that composition, giving a score to the player. The score showed the top 3 VDPs the composition had and the percentages of how much they governed the composition. Once players were done playing and creating their compositions, they were asked to fill out a questionnaire. Players' experiences about the game were obtained via the questionnaire, which based its scientific validity on the research named "Assessing the Core Elements of Gaming Experience (CEGE)". The questionnaire consisted of 24 statements in which students were asked to grade their level of agreement to using a 5-point Likert scale. 43 students participated in the questionnaire and all 43 of them answered every question. There was only one group and no control group. Following the questionnaire, a follow-up survey was given to 10 students. The follow-up survey consisted of 7 open-ended questions aimed to further understand what elements of the game were liked or disliked. According to the results gathered through that questionnaire, the majority of players stated that playing the game helped them consolidate their VDP knowledge, that they would want to see the game used in VDP education, and that they would want serious games to be used in education more. In addition, the results of the follow-up survey were helpful to see what was done right in the serious game, and what else could have been added to improve the game. This result points to the need for further research on game-based learning in architecture and shows some students' wish for more game-based learning in architecture education.