PENGENALAN POLA DAN TINGKATAN MOTIVASI PLAYER DALAM PENGGUNAAN GHOST TRADITIONAL GAME BERDASARKAN ANALISIS LOG DATA

Dalam bermain sebuah game, faktor motivasi dalam bermain game sangat memiliki peran penting terhadap keberlangsungan dari misi game tersebut untuk diselesaikan. Penelitian ini bertujuan untuk melaporkan hasil pengenalan pola player dan tingkatan motivasi player pada game yang telah dibangun bernama Ghost Traditional Game. Game tersebut menanamkan unsur Artificial Intelligence (AI) dengan jenis Decision Tree dan Finite State Machine berbasis desktop, terdiri dari sepuluh level dengan kategori kemudahan dan kesulitan yang telah diatur sedemikian rupa pada tahapan Game Design. Metode yang digunakan adalah matching player pattern detection yang direkam melalui log data dan motivation questionnaire technique. Sejumlah 30 orang player mengujicoba game ini, dengan tingkat usia yang berbeda-beda antara 12-22 tahun. Hasilnya adalah untuk pengenalan pola player terhadap iterasi masing-masing level yang digunakan pada saat game testing cenderung lebih cocok sama dengan prediksi pola pada game design, untuk motivasi player dalam menyelesaikan misi game dengan kategori sangat setuju, dan rata-rata waktu yang dibutuhkan oleh player untuk menyelesaikan misi game adalah 60 menit.Dalam bermain sebuah game, faktor motivasi dalam bermain game sangat memiliki peran penting terhadap keberlangsungan dari misi game tersebut untuk diselesaikan. Penelitian ini bertujuan untuk melaporkan hasil pengenalan pola player dan tingkatan motivasi player pada game yang telah dibangun bernama Ghost Traditional Game. Game tersebut menanamkan unsur Artificial Intelligence (AI) dengan jenis Decision Tree dan Finite State Machine berbasis desktop, terdiri dari sepuluh level dengan kategori kemudahan dan kesulitan yang telah diatur sedemikian rupa pada tahapan game design. Metode yang digunakan adalah matching player pattern detection yang direkam melalui log data dan motivation questionnaire technique. Sejumlah 30 orang player menguji coba game ini, dengan tingkat usia yang berbeda-beda antara 12-22 tahun. Hasilnya adalah untuk pengenalan pola player terhadap iterasi masing-masing level yang digunakan pada saat game testing cenderung lebih cocok sama dengan prediksi pola pada game design, untuk motivasi player dalam menyelesaikan misi game dengan kategori sangat setuju, dan rata-rata waktu yang dibutuhkan oleh player untuk menyelesaikan misi game adalah 60 meni

Multiplayer mechanism design for soil tillage serious game

The primary goal of Serious Games is not only for fun but also for lesson. In learning the first stage of soil tillage which using the mouldboard plow, a proper understanding is needed so that the soil tillage process will follow the needs of plant growth. The use of serious games as a study instrument for soil tillage is under the concept of digital game-based learning (DGBL). The problem of players when playing serious games is less motivated to play because the serious game system and scenario are less challenging. That challenges accelerate the shape of knowledge and experience when playing the games (user experience). By referring to the Learning Mechanics Gaming Mechanics (LM-GM) model, which is based on multiplayer in serious games, hopefully the learning process of land management using the mouldboard plow can be optimized. This process can increase learning motivation and elevate the user experience. This research results a design concept of a learning mechanism and a game mechanism for a serious multiplayer game of soil tillage with a mouldboard plow. There are three types of learning mechanisms in conceptual and concrete components, also six types of game mechanisms that can be used as a reference for the formation of multiplayer serious games and the increase player motivation

Measuring the Impact of Factors Affecting Game Development in Distributed Software Development

A software game is an application that is not only applicable for entertainment purposes but also used in domains like business, education and health care. Software game development is a multidisciplinary process that involves art, sound, artificial intelligence (AI), control systems and human factors which makes it different from traditional software development practice.  Distributed software development (DSD) facilitates decentralized zones for the availability of multidisciplinary human resources at less cost. Past studies explored many influencing factors for game development, however, how these factors majorly affect the game development in Distributed Software Development (DSD) environment yet not been studied as per our knowledge. In this research, we not only identified the most influencing factors for game development in DSD but also gauge a relationship matrix between these factors with games’ technical requirements. In our evaluation, we took twenty-nine top-rated animated games to establish a mapping of these factors present in these games. To calculate the variation in a given project budget, we execute Monte-Carlo simulations between the independent variable (influencing factors) and dependent variable (overall cost) that forecast the valuation of each variable impact on the overall nominal cost of the project. Empirical results of our research conclude that among all identified factors, ‘Physical Resources’ and ‘Freelancers’ have a significant impact on the overall project cost. Our research findings quantitatively assist the software project managers to estimate the cost deviations due to influencing factors in Distributed Software Development (DSD) environment.   &nbsp

Beam Me 'Round, Scotty! II: Reflections on Transforming Research Goals into Gameplay Mechanics

© {Owner/Author | ACM} 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts, http://dx.doi.org/10.1145/3270316.3273039.We reflect on the design, implementation, and testing of the experimental testbed game Beam Me 'Round, Scotty! II and the numerous design lessons learned in transitioning theoretical research questions about social presence and connectedness into concrete gameplay mechanics contrasting asymmetric and symmetric cooperative play. We discuss the unanticipated challenges that can emerge from seemingly unrelated design choices and the importance of grounding experimental conclusions and design recommendations in specific gameplay contexts.Funder 1, NSERC Discovery Grant 2016-04422 || Funder 2, NSERC Discovery Accelerator Grant 492970-2016 || Funder 3, NSERC CREATE Saskatchewan-Waterloo Games User Research (SWaGUR) Grant 479724-2016 || Funder 4, Ontario Early Researcher Award ER15-11-18

It Takes Two to Negotiate: Modeling Social Exchange in Online Multiplayer Games

Online games are dynamic environments where players interact with each other, which offers a rich setting for understanding how players negotiate their way through the game to an ultimate victory. This work studies online player interactions during the turn-based strategy game, Diplomacy. We annotated a dataset of over 10,000 chat messages for different negotiation strategies and empirically examined their importance in predicting long- and short-term game outcomes. Although negotiation strategies can be predicted reasonably accurately through the linguistic modeling of the chat messages, more is needed for predicting short-term outcomes such as trustworthiness. On the other hand, they are essential in graph-aware reinforcement learning approaches to predict long-term outcomes, such as a player's success, based on their prior negotiation history. We close with a discussion of the implications and impact of our work. The dataset is available at https://github.com/kj2013/claff-diplomacy.Comment: 28 pages, 11 figures. Accepted to CSCW '24 and forthcoming the Proceedings of ACM HCI '2