## 2 Related Work
### The Role of Serious Games in Teaching Algorithms
SQL Island, a web-based text adventure game for learning the Structured-Query Language (SQL), was utilized in the context of a programming assignment for an undergraduate Web Programming course [9]. Fifty-six students submitted the assignment based on SQL Island and evaluated the game using the MEEGA+ model. Students evaluated positively the player experience and perceived short-term learning, while their performance in the assignment was very good. The authors concluded that a game that is used in the context of programming assignments can have better results if the following features are supported [9]: good examples of new programming constructs; tasks connected to the story of the game; ability to register and save progress; usage of learning analytics for automatic assessment and reporting of class statistics. Although numerous serious games for programming have been designed, we were able to find only three games for AI concepts and algorithms, namely Obsolescence [27], Maestro [28] and Sokoban Solver [29]. The small number of games for AI and the rather limited research investigating if and how serious games can support students in comprehending AI concepts/algorithms motivated the authors in designing SpAI War. In the paragraphs that follow, the aforementioned AI games are briefly described, while a comparative analysis of the aforementioned games and SpAI War is presented in Table 1.  
Obsolescence [27] is a digital board game designed to educate military decision-makers on dealing with the threats imposed by disruptive AI technologies. In the context of the game, the players participate in competing militaries that build and move forces and interact with AI-based technology cards in order to gain influence points. Obsolescence was evaluated by 48 participants recruited from the United States Air Force and Department of Defense. The evaluation utilized a pre-post survey with questions related to the five learning objectives (LOs) of the game and aimed at evaluating short-term learning. The study showed that the game achieved its LOs, while there was a strong correlation between actual learning and perceived learning. Maestro is an open-source game-based platform under development ([[https://maestro-ai.github.io/](https://maestro-ai.github.io/)]([https://maestro-ai.github.io/](https://maestro-ai.github.io/))) (accessed on 1 May 2023) that aims to introduce higher education students to robust AI, which refers to countermeasures and the prevention of AI vulnerabilities [28]. Maestro utilizes goal-based scenarios and a competitive programming environment. In this environment, students are assigned the roles of the attacker or the defender and work either alone or in teams for devising their attack or defense according to their role. The solutions provided are evaluated for their quality, and students are ranked in a leaderboard. Maestro was positively evaluated by undergraduate students in two offerings of an AI course though a survey. Object-oriented Sokoban solver [29] is a game project that can be utilized for teaching both object-oriented analysis and design and AI. When it comes to AI, the Sokoban solver can be used as a case study for: implementing and experimenting on different path-finding algorithms in order to move one or more boxes on a grid with or without obstacles; teaching heuristics in the context of estimating the distance between the player and the goal state. Although this is an interesting approach, no application and/or evaluation results are available. Based on the comparative analysis of serious games on AI, it turns out that the available games have different goals: Obsolescence aims at educating military decision-makers on dealing with the threats imposed by disruptive AI technologies; Maestro aims at educating future AI workforce on dealing with AI vulnerabilities; and Sokoban solver aims at supporting students experiment with AI algorithms in the context of a Sokoban puzzle game by diving into its code.