論文アブストラクト： Videogames are complex stimuli, and selecting games that consistently induce a desired player experience (PX) in an experimental setting can be challenging. The number of relatively high-quality games being released each year continues to increase, which makes deriving a shortlist of plausible candidate games from this pool increasingly problematic. Despite this, guidance for structuring and reporting on the game selection process remains limited. This paper therefore proposes two approaches to game selection: the first leverages online videogame databases and existing PX research, and is structured with respect to widely-applicable videogame metadata. The second process applies established game design theory to serve researchers when insufficient connections between desired PX outcomes and recognisable game elements exist. Both methods are accompanied by example reports of their application. The present work aims to assist experimental researchers in selecting videogames likely to meet their needs, while encouraging more rigorous standards of reporting in the field.
論文アブストラクト： In distributed multiplayer games, it can be difficult to communicate strategic information for planning game moves and player interactions. Often, players spend extra time communicating, reducing their engagement in the game. Visual annotations in game maps and in the gameworld can address this problem and result in more efficient player communication. We studied the impact of real-time feedback on planning annotations, specifically two different annotation types, in a custom-built, third-person, multiplayer game and analyzed their effects on player performance, experience, workload, and annotation use. We found that annotations helped engage players in collaborative planning, which reduced frustration, and shortened goal completion times. Based on these findings, we discuss how annotating in virtual game spaces enables collaborative planning and improves team performance.
論文アブストラクト： Learning games now play a role in both formal and informal learning, including foundational skills such as literacy. While feedback is recognised as a key pedagogical dimension of these games, particularly in early learning, there has been no research on how commercial games available to schools and parents reify learning theory into feedback. Using a systematic content analysis, we examine how evidence-based feedback principles manifest in five widely-used learning games designed to foster young children's reading skills. Our findings highlight strengths in how games deliver feedback when players succeed. Many of the games, however, were inconsistent and not proactive when providing error feedback, often promoting trial and error strategies. Furthermore, there was a lack of support for learning the game mechanics and a preference for task-oriented rewards less deeply embedded in the gameplay. Our research provides a design and research agenda for the inclusion of feedback in early learning games.
論文アブストラクト： Streakiness refers to observed tendency towards consecutive appearances of particular patterns. In video games, streakiness is oftentimes inevitable, where a player keeps winning or losing for a short period. However, the phenomenon remains understudied in present online game research. How do players perceive streakiness? How does it impact player experience (PX)? How should streakiness be taken into consideration for the design of PX? In this paper, we address these questions through a qualitative study of player discussions about streakiness in League of Legends. We found that players developed various ways to describe a streak. Both winning and losing streaks negatively impacted PX. Players devised numerous strategies to manage streakiness, among which disengagement was a primary means. We analyze streakiness as a social construct through which players coped with complex game systems. We discuss design implications for managing streakiness in online games.
対戦ゲームなどにおいてよく見られる、連勝した後に何故か連敗が続くなどといった傾向に関する様々な疑問について、「League of Legends」のプレイヤー達が過去にフォーラムで行った議論や対策を収集・分析することで定性的に研究しています。