Emília Pietriková

Open access peer-reviewed chapter

A peer-reviewed journal of applied informatics that covers a broad range of topics, especially dealing with the social and business aspects of informatics.

Open access peer-reviewed chapter

This chapter explores the essential role of game and graphics rendering engines in creating computer games and their applications in education. Starting with a brief discussion on the importance of visualization in game development, we analyze popular game engines, including CryEngine, Irrlicht, Unreal Engine, Unity, and Godot, and graphics rendering engines (cores), including OpenSceneGraph (OSG) and Object-Oriented Graphics Rendering Engine (OGRE). Each engines unique features and pedagogical potentials are discussed, with emphasis on Unity, Godot, and Unreal Engines interactive and step-by-step tutorials. This analysis reflects the adaptability of game engines to different teaching styles and provides insights into their effectiveness as tools for teaching game development and computer science. The chapter aims to highlight game engines role in game creation and education by exploring these topics.

The following chapter presents an experience with academic education in computer games design and development based on game theory, emphasizing iterative development, rapid (paper) prototyping, and game testing. We demonstrate and comment on various educational activities focused on game testing, describing them in steps and including benefits and motivation. Iteration of card game rules, design of a board game, design of a computer game with a paper prototype, and testing of early-access games are supplemented with students’ practical outputs in both text and graphical form. The results include feedback in the testing forms: Focus Groups, Playtesting, Usability Testing, and Quality Assurance.

Computer games and, of course, the development associated with them have been in the spotlight for many years; recently, also with technologies, such as virtual reality or extended reality. The main part of this chapter presents the classification of collaborative XR systems, the concept of the major application architectures and the consistency models of shared virtual game environments. The next subchapter briefly deals with the sharing of property ownership. The mentioned concepts and examples used in the chapter are implemented in many works and projects using a collaborative environment (also in gamified form) developed in the laboratory LIRKIS, the home laboratory of the authors. The knowledge presented in this chapter may provide tips and inspiration for some other game projects, and practical and useful notes on the advantages or disadvantages of some systems will be interesting and useful.

In the following study, we deal with data-driven support for novice programmers – students, working in large groups. We introduce a virtual assistant, which aims to simplify communication and feedback, sending reports and advice during the programming course. We experiment with 134 students during one semester period, and we try to understand how the virtual assistant affects novices – students. In the introduction, we state 3 hypotheses, focusing on performance, behavior, and motivation. The experiment evaluation relies on data collected throughout the semester. The results reveal the impact of the virtual assistant on novice programmers in 2 of the studied aspects – performance and motivation. This can be perceived as potential towards efficient support in programming education, especially in large groups. We also believe the study is contributional to the areas of learning analytics and program comprehension.

Following up on the issue of programmer knowledge profiles, the present article deals with the generation of profiles for C language programmers. The main idea is based on static analysis of source codes, assembling the most significant data about their author. Such a profile can point out some abilities and habits of the programmer. The process of static analysis applies methods and techniques of size metrics, complexity metrics, and clone detection. We also present an experiment focused on novice programmers. The results show that knowledge profiles provide an easy way of novice programmers’ progress tracking. The main contribution is believed to be in the area of program comprehension.