Search

The video-game industry has recently grown from focused markets to mainstream. The advancements the industry has been enjoying motivated researches to propose techniques and tools to support the activities across the different phases of the game development lifecycle. Game testing is one of the crucial activities within the game development process. Due to the nature of game testing, many automated game testing techniques have been proposed in the literature. However, there is no framework that could be used to aid practitioners in selecting appropriate techniques suitable for their particular development efforts. In this paper we present an attribute-based framework to classify and compare these techniques and provide such aid to practitioners. The framework is also meant to guide researchers interested in proposing new game testing techniques. The paper discusses a number of prominent techniques against the framework. Analysis of the discussion reveals gaps and suggests open points for future research.

with the increase of mobile device usage around the globe, face-to-face communication has degraded and complete prohibition is not realistic. The degradation is not to be prevented as it happens as a side effect of technology. However, balancing usage of mobile device and quality of face-to-face communication is possible. Thus, by approaching users through developing a party genre mobile game, which is not famous as a mobile game at the time, with local multiplayer focus and introducing the given game to users, it is expected that face-to-face communication can be encouraged, thus resulting in mobile party game to become a media for the encouragement. Sample mini game that is a part of party game is developed with the help of Unity game engine as a testing object in which user response is collected. As application testing take place, and target user response is collected, face-toface encouragement is proven and user response is positive towards the game. Sample game testing has effectively reintroduced the existence of nowadays rare party game in mobile platform along with encouraging face-to-face communication, shown by the enthusiasm and enjoyment that audience testers have experienced. In the end, with mobile party game can help by being a media to encourage face-to-face communication and prevent degradation of such communication, future developments of a complete party game in mobile platform is highly encouraged as overall face-to-face communication quality enhancement may be required in the future in order to mitigate degradation.

In this article, we present a new methodology that employs tester agents to automate video game testing. We introduce two types of agents—synthetic and humanlike—and two distinct approaches to create them. Our agents are derived from Sarsa and Monte Carlo tree search (MCTS) but focus on finding defects, while traditional game-playing agents focus on maximizing game scores. The synthetic agent uses test goals generated from game scenarios, and these goals are further modified to examine the effects of unintended game transitions. The humanlike agent uses test goals extracted by our proposed multiple greedy-policy inverse reinforcement learning (MGP-IRL) algorithm from tester trajectories. MGP-IRL captures multiple policies executed by human testers. We use our agents to produce test sequences, and run the game with these sequences. At each run, we use an automated test oracle to check for bugs. We analyze the proposed method in two parts—we compare the success of humanlike and synthetic agents in bug finding, and we evaluate the similarity between humanlike agents and human testers. We collected 427 trajectories from human testers using the General Video Game Artificial Intelligence (GVG-AI) framework and created three games with 12 levels that contain 45 bugs. Our experiments reveal that humanlike and synthetic agents compete with human testers’ bug finding performances. Moreover, we show that MGP-IRL increases the humanlikeness of agents while improving the bug finding performance.

Software testing is a crucial development technique to capture defects and slow code. When testing 3D graphics, it is hard to create automatic tests that detect errors or slow performance. Finding performance issues in game maps is a complex task that requires much manual work. Gaming companies such as EA DICE could benefit from automating the process of finding these performance issues in their game maps. This thesis tries to solve the problem by creating automatic tests where the camera is placed in a top-down perspective and flies over the in-game map, recording the time it takes to create render and client simulation frames for each map segment. The resulting trace is then visualised as a heatmap, where the mean frame creation times are rendered with pseudo colouring techniques to help pinpoint possible issues for the test engineers. The key findings of this thesis are that a heatmap visualisation of frame creation times saves much time for the developers trying to find these issues; it also lowers the amount of knowledge needed to find performance issues. This tool automates a process that formerly needed considerable manual work to get the same result. Now, artists with low coding experience can find performance issues without the technical knowledge of a Quality Assurance engineer. The thesis also highlights the drawbacks of a top-down perspective of camera trace since this is not how EA DICE games are usually rendered for the player in runtime. With this thesis as a base, other tests could be made with other ways of moving the camera and visualising the trace. Mjukvarutestning är en viktig programvaruutvecklings teknik för att fånga felaktig eller långsam kod. Det är svårt att skapa automatiska tester för 3D grafik som hittar fel eller dålig prestanda i koden. Att hitta prestandaproblem i spelkartor är en komplex uppgift som kräver mycket manuellt arbete. Spelföretag såsom EA DICE skulle dra fördel av att automatisera processen att hitta dessa prestandaproblem i spelkartor. Denna uppsats försöker lösa detta genom att skapa automatiska tester där kameran placeras i ett uppifrån-och-ned-perspektiv och sedan flyger genom banan i spelet samtidigt som den samlar in data på hur lång tid det tar för renderings-bildrutor och klient-simulerings-bildrutor att skapas för varje ban-segment. Den resulterande datan är därefter visualiserade som ett färgdiagram, där medelvärdet på tiden för att skapa varje bildruta ritas upp med en psuedofärgningsteknik för att markera möjliga problemområden för testingenjörerna. Nyckelupptäckter för denna uppsats är att färgdiagramsvisualiseringen av bildruta-skapande-tider sparar mycket tid för utvecklare som försöker hitta prestandaproblem. Det minskar också kunskapströskeln som behövs för att lokalisera prestandaproblem. Detta verktyg automatiserar en process som tidigare krävde omfattande manuellt arbete för att få samma resultat. Numera kan game artists med låg koderfarenhet hitta dessa prestandaproblem utan den tekniska kunskapen hos en kvalitetskontroll-ingenjör. Den här uppsatsen visar också nackdelar med ett uppifrån-och-ned-perspektiv för kameran då det inte är så EA DICE spel normalt renderas för spelarna. Den här uppsatsen kan användas som utgångspunkt för andra som vill utveckla testverktyg och med fördel ta i beaktning de utvecklingspunkter denna uppsats belyser.

Artificially intelligent (AI) game software incorporates different algorithms to generate intelligent human-like responses to the users playing them. Testing AI game software poses great difficulty because of the complex possibilities that can result at a given point and analysis of said possibilities is a tedious task. Also during software development there are resource constraints due to which testing targets specific parts of the software. An AI game of Chess takes into consideration a large amount of possible outcomes at any given point before deciding a move. Therefore, testing it in its entirety is impractical. In this paper we propose a metamorphic testing approach for testing an AI Chess game i.e. a Chess engine’s algorithm of determining and pruning out possible outcomes and ultimately deciding on a final outcome. For validating our approach, we have done error seeding on an open source Chess engine and tested it through our approach. The results for our proposed approach for testing an AI Chess game through metamorphic relations show that it is successful in revealing 71% of the total seeded faults. On comparison of our proposed approach with the existing technique of testing Chess engine i.e., perft function, we have come across situations in which our proposed approach reveals errors overlooked by the existing technique. In the future we aim to extend our approach towards other AI game software.

The exponential increase in the speed of the mobile industry has led to a decreasing quality in many associated mobile apps. Besides, the number of distinct Android devices reached thousands. This challenged the development of universally accepted test applications that can run on all devices. This paper focuses on the development of a new mobile game testing framework, referred to, MAuto. MAuto records the user actions in the game and replays the tests on any Android device. MAuto uses image recognition, through AKAZE features, to record the test cases and the Appium framework to replay the user actions automatically. The feasibility of the developed tool has been demonstrated through testing on the Clash of Clans mobile game.

Humans use generalized cognitive maps (GCM) for navigation in dynamic environments. Mechanisms of the generation of GCM in the brain are not well understood. Nevertheless, there is a mathematical model that allows their simulation. Here we propose a methodology for testing the GCM concept in behavioral experiments and comparing results with the model. We perform experiments with human subjects playing a specially design arcade computer game. The resulting trajectories of objects controlled by humans on a PC screen are then compared with those predicted by the GCM model. We show that human trajectories exhibit significant similarity with the model trajectories in dynamical scenes with objects moving at high speed. If the speed of the controlled object decreases, then men and experienced users maintain a similarity with the model predictions, while women and untrained subjects deviate significantly.

With the widespread adoption of smartphones in our daily life, mobile games experienced increasing demand over the past years. Meanwhile, the quality of mobile games has been continuously drawing more and more attention, which can greatly affect the player experience. For better quality assurance, general-purpose testing has been extensively studied for mobile apps. However, due to the unique characteristic of mobile games, existing mobile testing techniques may not be directly suitable and applicable. To better understand the challenges in mobile game testing, in this paper, we first initiate an early step to conduct an empirical study towards understanding the challenges and pain points of mobile game testing process at our industrial partner NetEase Games. Specifically, we first conduct a survey from the mobile test development team at NetEase Games via both scrum interviews and questionnaires. We found that accurate and effective GUI widget detection for mobile games could be the pillar to boost the automation of mobile game testing and other downstream analysis tasks in practice. We then continue to perform comparative studies to investigate the effectiveness of state-of-the-art general-purpose mobile app GUI widget detection methods in the context of mobile games. To this end, we also develop a technique to automatically collect GUI widgets region information of industrial mobile games, which is equipped with a heuristic-based data cleaning method for quality refinement of the labeling results. Our evaluation shows that: (1) Existing GUI widget detection methods for general-purpose mobile apps cannot perform well on industrial mobile games. (2) Mobile game exhibits obvious difference from other general-purpose mobile apps in the perspective GUI widgets. Our further in-depth analysis reveals high diversity and density characteristics of mobile game GUI widgets could be the major reasons that post the challenges for existing methods, which calls for new research methods and better industry practices. To enable further research along this line, we construct the very first GUI widget detection benchmark, specially designed for mobile games, incorporating both our collected dataset and the state-of-the-art widget detection methods for mobile apps, which could also be the basis for further study of many downstream quality assurance tasks (e.g., testing and analysis) for mobile games.

Graphically-rich applications such as games are ubiquitous with attractive visual effects of Graphical User Interface (GUI) that offers a bridge between software applications and end-users. However, various types of graphical glitches may arise from such GUI complexity and have become one of the main component of software compatibility issues. Our study on bug reports from game development teams in NetEase Inc. indicates that graphical glitches frequently occur during the GUI rendering and severely degrade the quality of graphically-rich applications such as video games. Existing automated testing techniques for such applications focus mainly on generating various GUI test sequences and check whether the test sequences can cause crashes. These techniques require constant human attention to captures non-crashing bugs such as bugs causing graphical glitches. In this paper, we present the first step in automating the test oracle for detecting non-crashing bugs in graphically-rich applications. Specifically, we propose \texttt{GLIB} based on a code-based data augmentation technique to detect game GUI glitches. We perform an evaluation of \texttt{GLIB} on 20 real-world game apps (with bug reports available) and the result shows that \texttt{GLIB} can achieve 100\% precision and 99.5\% recall in detecting non-crashing bugs such as game GUI glitches. Practical application of \texttt{GLIB} on another 14 real-world games (without bug reports) further demonstrates that \texttt{GLIB} can effectively uncover GUI glitches, with 48 of 53 bugs reported by \texttt{GLIB} having been confirmed and fixed so far., Comment: ESEC/FSE 2021

Facial emotional processing is one of the most important activities in effective calculations, engagement with people and computers, machine vision, video game testing, and consumer research. Facial expressions are a form of nonverbal communication, as they reveal a person's inner feelings and emotions. Extensive attention to Facial Expression Recognition (FER) has recently been received as facial expressions are considered. As the fastest communication medium of any kind of information. Facial expression recognition gives a better understanding of a person's thoughts or views and analyzes them with the currently trending deep learning methods. Accuracy rate sharply compared to traditional state-of-the-art systems. This article provides a brief overview of the different FER fields of application and publicly accessible databases used in FER and studies the latest and current reviews in FER using Convolution Neural Network (CNN) algorithms. Finally, it is observed that everyone reached good results, especially in terms of accuracy, with different rates, and using different data sets, which impacts the results.

Modern computer games typically have a huge interaction spaces and non-deterministic environments. Automation in testing can provide a vital boost in development and it further improves the overall software's reliability and efficiency. Moreover, layout and game logic may regularly change during development or consecutive releases which makes it difficult to test because the usage of the system continuously changes. To deal with the latter, tests also need to be robust. Unfortunately, existing game testing approaches are not capable of maintaining test robustness. To address these challenges, this paper presents an agent-based approach for robust automated testing based on the reasoning type of AI.

Video-game projects are notorious for having day- one bugs, no matter how big their budget or team size. The quality of a game is essential for its success. This quality could be assessed and ensured through testing. However, to the best of our knowledge, little is known about video-game testing. In this paper, we want to understand how game developers perform game testing. We investigate, through a survey, the academic and gray literature to identify and report on existing testing processes and how they could automate them. We found that game developers rely, almost exclusively, upon manual play-testing and the testers' intrinsic knowledge. We conclude that current testing processes fall short because of their lack of automation, which seems to be the natural next step to improve the quality of games while maintaining costs. However, the current game-testing techniques may not generalize to different types of games.

You have come this far. Only the final chapter remains after this. You may think that the hard part is over. In that case, we ask you to look into some recent big titles you have played. The common and expected style right now is to use the last chapter to either give some sort of closure to the player or throw in some hints regarding the sequel. The final boss fights are usually put in just before that. Hence, the chapter before the last one is usually... tricky. Okay now, don’t be scared. This is more like a manual, rather than a game. We won’t drop a bombshell on you suddenly. But trust us when we say that game testing and publishing is one of the biggest concerns you should have in mind. So far, we have covered the part of the development journey. Testing and publishing are integral parts of it. So, in this chapter, you will discover these parts of the map.

Game design and development without a doubt have a real potential to become a tool to support the experiencing of cultural heritage context by the large public in a fun and interactive ways. This research aims to enrich the Malaysian cultural and folklore learning experience of traditional game Wau and Toyol through a mobile game design and development. The productions then analyzed based on the relations between game play, game narration, game challenges, game technological solutions, game mechanics and the effectiveness of learning. This paper highlights the overall process involved in the game development by using agile methodology. Game testing have been conducted, the results obtained shown that a connection to the cultural heritage and folklore context of Wau and Toyol can be achieved and can be identified as a significant platform to engage interactive learning experiences.

To enable automated software testing, the ability to automatically navigate to a state of interest and to explore all, or at least sufficient number of, instances of such a state is fundamental. When test- ing a computer game the problem has an extra dimension, namely the virtual world where the game is played on. This world often plays a dominant role in constraining which logical states are reach- able, and how to reach them. So, any automated testing algorithm for computer games will inevitably need a layer that deals with navigation on a virtual world. Unlike e.g. navigating through the GUI of a typical web-based application, navigating over a virtual world is much more challenging. This paper discusses how concepts from geometry and graph-based path finding can be applied in the context of game testing to solve the problem of automated navigation and exploration. As a proof of concept, the paper also briefly discusses the implementation of the proposed approach.

The mobile casual game application lifespan is getting shorter. A company has to shorten the game testing procedure to avoid being squeezed out of the game market share. There is no sufficient testing indicator to objectively evaluate the operability of different game designs. Many automated testing methodologies are proposed, but they adopt rule-based approaches and cannot provide quantitative analysis to statistically evaluate gameplay experience. This study suggests applying &ldquo, Learning Time&rdquo, as a testing indicator and using the learning curve to identify the operability of different game designs. This study also proposes a Long/Short-Term Memory based automated testing model (called LSTM-Testing) to statistically testing game experience through end-to-end functionality (Input: game image, Output: game action) without any manual intervention. The experiment results demonstrate LSTM-Testing can provide quantitative testing data by using learning time as the control variable, game design as the independent variable, and time to complete game as the dependent variable. This study also demonstrates how LSTM-Testing evaluates the effectiveness of different gameplay learning strategies, e.g., reviewing the newest decisions, reviewing the correct decision, or reviewing the wrong decisions. The contributions of LSTM-Testing are (1) providing an objective and quantitative analytical game-testing framework, (2) reducing the labor cost of inefficient and subjective manual game testing, and (3) allowing game company boosts software development by focusing on game intellectual property and leaves game testing to artificial intelligence (AI).

Regression testing aims to check the functionality consistency during software evolution. Although general regression testing has been extensively studied, regression testing in the context of video games, especially Massively Multiplayer Online Role-Playing Games (MMORPGs), is largely untouched so far. One big challenge is that game testing requires a certain level of intelligence in generating suitable action sequences among the huge search space, to accomplish complex tasks in the MMORPG. Existing game testing mainly relies on either the manual playing or manual scripting, which are labor-intensive and time-consuming. Even worse, it is often unable to satisfy the frequent industrial game evolution. The recent process in machine learning brings new opportunities for automatic game playing and testing. In this paper, we propose a reinforcement learning-based regression testing technique that explores differential behaviors between multiple versions of an MMORPGs such that the potential regression bugs could be detected. The preliminary evaluation on real industrial MMORPGs demonstrates the promising of our technique.

General game testing relies on the use of human play testers, play test scripting, and prior knowledge of areas of interest to produce relevant test data. Using deep reinforcement learning (DRL), we introduce a self-learning mechanism to the game testing framework. With DRL, the framework is capable of exploring and/or exploiting the game mechanics based on a user-defined, reinforcing reward signal. As a result, test coverage is increased and unintended game play mechanics, exploits and bugs are discovered in a multitude of game types. In this paper, we show that DRL can be used to increase test coverage, find exploits, test map difficulty, and to detect common problems that arise in the testing of first-person shooter (FPS) games., 4 pages, 6 figures, 2020 IEEE Conference on Games (CoG), 600-603

Game testing is a necessary but challenging task for gaming platforms. Current game testing practice requires significant manual effort. In this paper, we proposed an automated game testing framework combining adversarial inverse reinforcement learning algorithm with evolutionary multi-objective optimization. This framework aims to help gaming platform to assure market-wide game qualities as the framework is suitable to test different games with minimum manual customization for each game.

Facial emotion analysis is one of the most important tasks in affective computing, human-computer interaction, computer vision, video game testing and market research. Facial expressions are a kind of non-verbal communication because it shows the internal feelings and emotional states of a person. Emotions are a kind of feedback through which what customers want and need can be identified. In this paper, the human group facial sentiment recognition system is proposed using a deep learning approach. The proposed framework uses the Haar filter to detect and extract face features. Then the convolutional neural network (CNN) is developed to recognize facial expressions and classify them into five basic emotion states namely happy, sad, anger, surprise and neutral. Finally, the predicted group emotions are fed into an audio synthesizer to get audio output. The proposed model achieves a final accuracy of 65% for Facial Expression Recognition (FER)-2013 and 60% for custom datasets.

The article deals with the peculiarities of the project technology use, its positive effect and drawbacks. It has been found that project technology became popular and widespread due to the rational combination of the theoretical knowledge and their practical application for the problem solution in common educational activity of students. It has been defined that the forms of conducting classes on project technology may vary, but have to contain three components that include cognitive-mental and search-creative activity: a clear mechanism for determining functional and role interests of the class members; algorithm of project development proposed by students; mechanism of expert evaluation or game testing of a project. Five different types of project technology in the professional training of future physical education teachers are analyzed: research, search, creative, prognostic and analytical.The positive effect of various project technology implementation was analyzed: it forms skills of joint activity, teaches cooperation, develops the aim of competence; develops the sense of not only collective but also individual responsibility; project work helps students to develop an analytical, prognostic, research and creative potential; during the process of projects defense presentation skills and abilities develop as well, together with communicative and interactive competence.The drawbacks of the project technology are also identified: members do not find consensus or have different views on project development; prefer individual responsibility to collective one, trigger special attention to their own project; project work requires a lot of time and groups do not always adhere to time limits, which lowers motivation and leads to disappointment; presentation does not always allow to prove the pluses of the project due to the underdeveloped communicative culture and weak presentation skills, thus, the members of a lesson may be frustrated with the final result.

In this paper, we study the effects of several Monte Carlo Tree Search (MCTS) modifications for video game testing. Although MCTS modifications are highly studied in game playing, their impacts on finding bugs are blank. We focused on bug finding in our previous study where we introduced synthetic and human-like test goals and we used these test goals in Sarsa and MCTS agents to find bugs. In this study, we extend the MCTS agent with several modifications for game testing purposes. Furthermore, we present a novel tree reuse strategy. We experiment with these modifications by testing them on three testbed games, four levels each, that contain 45 bugs in total. We use the General Video Game Artificial Intelligence (GVG-AI) framework to create the testbed games and collect 427 human tester trajectories using the GVG-AI framework. We analyze the proposed modifications in three parts: we evaluate their effects on bug finding performances of agents, we measure their success under two different computational budgets, and we assess their effects on human-likeness of the human-like agent. Our results show that MCTS modifications improve the bug finding performance of the agents.

Worldwide, every year 525 000 children under the age of five die from diarrhoea. The simple act of washing hands with soap and water can prevent more than one-third of diarrhoeal disease cases. In the densely populated urban areas of the developing world, handwashing wastewater is commonly discharged to the environment without any treatment, creating unhygienic situations and breeding places for different vectors and wasting a valuable resource. However, this relatively clean wastewater can be treated and reused using simple technological solutions. The objective of our water innovation is, therefore, twofold: improving children’s health through stimulating handwashing at schools while at the same time demonstrating the feasibility of water conservation through low-tech, nature-based treatment and safe reuse of handwashing wastewater for irrigation and toilet flushing. To enhance the intrinsic motivation of children and school staff to adopt this innovation, four educational games were developed drawing on theories used in gamification of learning, such as social learning theory and engagement theories. This paper provides an overview of the games and the main results of the game testing. For promoting hygiene among school children, a board and a card game were developed based on the F-diagram – commonly used by water and sanitation practitioners to illustrate the main routes for pathogen transmissions from faeces. In addition, the system linking handwashing wastewater collection, treatment and reuse for irrigation and toilet flushing was simulated by the development of two board games which targeted school children, school staff and the operators of the treatment system. The prototypes and final versions were tested in two schools in the Oromia region in Ethiopia – while the treatment system (constructed wetland) for handwashing wastewater is located in one school. Children that play-tested the games were generally enthusiastic and eager to play repeatedly, which demonstrated that board and card games are appropriate tools to engage with this young target group. We conclude that there is a large potential for development, use, and upscaling of educational games for more sustainable WaSH interventions.

Game testing has been long recognized as a notoriously challenging task, which mainly relies on manual playing and scripting based testing in game industry. Even until recently, automated game testing still remains to be largely untouched niche. A key challenge is that game testing often requires to play the game as a sequential decision process. A bug may only be triggered until completing certain difficult intermediate tasks, which requires a certain level of intelligence. The recent success of deep reinforcement learning (DRL) sheds light on advancing automated game testing, without human competitive intelligent support. However, the existing DRLs mostly focus on winning the game rather than game testing. To bridge the gap, in this paper, we first perform an in-depth analysis of 1349 real bugs from four real-world commercial game products. Based on this, we propose four oracles to support automated game testing, and further propose Wuji, an on-the-fly game testing framework, which leverages evolutionary algorithms, DRL and multi-objective optimization to perform automatic game testing. Wuji balances between winning the game and exploring the space of the game. Winning the game allows the agent to make progress in the game, while space exploration increases the possibility of discovering bugs. We conduct a large-scale evaluation on a simple game and two popular commercial games. The results demonstrate the effectiveness of Wuji in exploring space and detecting bugs. Moreover, Wuji found 3 previously unknown bugs1, which have been confirmed by the developers, in the commercial games.

Launching a successful video game is crucial for any video game developer given a competitive nature of a video game industry. A successful video game can guarantee the continuity of some companies, and their plans in the industry. On the other hand, a video game that does not generate enough sales may bring the business down. An extensive review of the literature on video game and the published frameworks was performed. The results show that existing frameworks only considered limited aspects of game development. Therefore, this paper proposes a holistic framework that covers every aspect of video game development. The framework discusses the pre-launch processes such as concept design, development budget, game engines and the post-launch aspects of marketing, multiplayer, and downloadable content. It also looks at the external forces and how they affect the internal pre and post launch processes. Finally, the proposed framework is applied to Duke Nukem Forever, a video game that was released in 2011 after fifteen years of development.

Este artigo propõe um jogo de tabuleiro para apoiar o ensino dos princípios da pesquisa científica. A metodologia envolve revisão de literatura, avaliação de jogos e design de games. Seu objetivo é definir boas práticas para a produção e utilização de jogos de tabuleiro (analógicos ou digitais) na disciplina Metodologia Científica. A revisão de literatura identificou alguns jogos de tabuleiro desenvolvidos com esse objetivo: Snakes and Ladders, Defense of Hidgeon, The Game of Research e Cheats and Geeks. Esses jogos foram avaliados a partir de diversas categorias de design de games e design educacional, como: narrativa, usabilidade/interface, mecânica, gameplay, arte/estética, aprendizagem, som, balanceamento entre entretenimento/educação e tempo para jogar. A partir dessa avaliação, o artigo sugere boas práticas para o design de jogos de tabuleiro educacionais e apresenta a proposta de um jogo de tabuleiro, O Jogo do Método, para o ensino de metodologia científica.

This study presents that the computer game using brain information as healthcare design outcomes is being philosophized as an object of thoughts. In order to define the philosophy of computer game with BCI (Brain-Computer Interaction), my paper examines Racing Car Game using EEG (electroencephalography) as healthcare information design outcomes and reconsiders the rule and use of BCI game in the conflict between the game and the narrative. It proposes that the BCI game using brain waves as bio-information originated from healthcare design reframes traditional philosophical discourses in knowledge game and contributes to the ecology of networked knowledge enabling new forms of collaborations between sciences, engineering, arts, and design.

Language and culture is an applied been possessed by every man since born. Language is a in the form of communication with each other. In daily life, communicate with the family, friend, even work also need good ability. Therefore a use of language that well and properly should be owned individuals[1]. Nihon-Goo! Is a Game made from computer for the purpose as a medium and facilitate the process increase knowledge and understanding basic vocabulary and culture in japan. After 5 times playing of one each day, game testing was conducted to 40 people and fill the questionnaire. Post-test data result shows that the game makes the player having difficulty answering the questions, but still want to play it again and again. So even though they failed to try it, they still tried again and again.

Human’s ignorance is the most threatening factor to natural water sources on the system. The habit of littering and poor waste management often occurs in developing countries, especially Indonesia. Through an educational game this message could be delivered easier. This paper is intended to find ways for people to be more concerned with water pollution. The questionnaire and interview methods are used to search for pre-test and post-test data. From the pre-test data, “Save The Sea” mobile game is created which can help educate the public about the dangers of water pollution. After 5 times playing of once each day, game testing was conducted to 39 people and fill the questionnaire. Post test data result shows that the game succeeded in creating conditions where people were more concerned about water pollution.

Mobile app markets have faced huge expansion during the last decade. Among different apps, games represent a large portion with a wide range of game categories having consumers in all age groups. To make a mobile game suitable for different age categories, it is necessary to adjust difficulty levels in such a way to keep the game challenging for different players with different playing skills. The mobile app puzzle game Wonderful Animals has been developed consisting of puzzles, find pairs and find differences game (available on the Google Play Store). The game testing was conducted on a group of 40 players by recording game level completion time and conducting a survey of their subjective evaluation of completed level difficulty. The study aimed to find a mechanism to adjust game level difficulty to the individual player taking into account the player’s achievements on previously played games. A pseudo-algorithm for self-learning mechanism is presented, enabling level difficulty adaptation to the player. Furthermore, player classification into three classes using neural networks is suggested in order to offer a user-specific playing environment. The experimental results show that the average recognition rate of the player class was 96.1%.

Purpose This paper aims to identify successful game strategies that are used in digital video games and match those strategies to practices that may be incorporated in instructional design to gamify the learning experience. Design/methodology/approach The identification of successful strategies is based on literature explaining gamification and game strategies. Examples and suggestions of gamification are included from scholars, business leaders and actual practices. Findings The successful game strategies identified can be transferred into the learning environment without the inclusion of video games. Strategies identified support learner competence, relatedness and autonomy and encourage instructional designers or instructors to examine game play, realize how play can be used to provide more meaningful experiences to learners and rethink assessments. Originality/value The identified game elements are supported by motivation theory. These identifications offer instructional designers a list of game elements from which they may refer when designing in the future.

The dynamics of the market pose a challenge for the digital game industry. Game development firms must develop innovative games to satisfy game players’ ever-changing needs and sustain a suitable p...

A computer game is one of the most efficient instructional media for improving learners’ programming skills. Implementing a game development platform or a game engine as an instruction tool provides benefits to learners. This paper observes progress in the learning process, and measures how long learners take to find solutions. The participants in the experiment were divided into two groups. The first group used traditional instructional media, such as lecturing, studying class materials, and solving assigned programming assignments. On the other hand, the second group attended the lectures, similar to the first group, and used a game development platform as instructional media to solve assigned programming assignments. The results showed that the progressive skills of the Game Development Platform learners were higher, and the problem-solving time they spent was lower.

Purpose This paper aims to describe a successful outreach to transfer students through an interactive information literacy game. While the main purpose of the game is to introduce students to research and university library resources, it also allows for an analysis of incoming students’ information literacy skills. Design/methodology/approach This case study outlines the evolution of the game from a test-like tutorial administered through the Blackboard course management system to an interactive game in two iterations, describing the game in relation to game design and best practices and discussing how the artwork for the game was created. An analysis of data from student answers to the game questions over time shows what librarians have learned about the information literacy skills of incoming transfer students. Finally, student feedback about the game collected through a survey is presented along with ideas for future modifications. Findings This paper provides insights into the design and creation process of an interactive information literacy game and a model for how similar games can help librarians assess students’ information literacy skills. Practical implications Transfer students are hard to reach as a group at many institutions. An interactive game targeted to transfers during the admissions process is a potentially effective way to reach out to them. Originality/value This paper brings together two important issues in the library literature: how to reach out to transfer students and educational library games. Librarians involved with these issues will benefit from the paper’s insights and practical advice.

This article describes how game developers successfully ‘pull off’ game development, collaborating in the absence of consensus and working with recalcitrant and wilful technologies, shedding light on the games we play and those that make them, but also how we can be forced to work together by the platforms we choose to use. The concept of ‘boundary objects’ is exported from Science and Technology Studies (STS) to highlight the vital coordinating role of game development software. Rather than a mutely obedient tool, game software such as Unity 3D is depicted by developers as exhibiting magical, even agential, properties. It becomes ‘voodoo software’. This software acts as a boundary object, aligning game developers at points of technical breakdown. Voodoo software is tidied away in later accounts of game development, emphasizing how ethnographies of software development provide an anchor from which to investigate cultural production and co-creative practice.

Purpose–This study presented the results of each stage of the analysis, design, development, implementation, and evaluation (ADDIE) of a game designed to inform users on environmental issues.The game was named “Juan’s Kart” that aimed to teach players about waste segregation. Method–The analysis phase involved the conceptualization of a game and the determination of its design dimension. The design phase entailed development of game design guidelines, identification of hardware and software requirements specifications, and actual development of the game. The developed game was uploaded in Google Play. Four hundred respondents evaluated the game. Results–The game received favorable ratings from the respondents. Contributions–Thus, the game was successfully developed. It may be utilized as a training tool and its effectiveness may be investigated. Research Implications–Recommendations to improve the game were also presented