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1. VIRD: Immersive Match Video Analysis for High-Performance Badminton Coaching

   Lin, T.; Aouididi, A.; Chen, Z.; Beyer, J.; Pfister, H.; Wang, J. (January 2023, IEEE transactions on visualization and computer graphics)

   Badminton is a fast-paced sport that requires a strategic combination of spatial, temporal, and technical tactics. To gain a competitive edge at high-level competitions, badminton professionals frequently analyze match videos to gain insights and develop game strategies. However, the current process for analyzing matches is time-consuming and relies heavily on manual note-taking, due to the lack of automatic data collection and appropriate visualization tools. As a result, there is a gap in effectively analyzing matches and communicating insights among badminton coaches and players. This work proposes an end-to-end immersive match analysis pipeline designed in close collaboration with badminton professionals, including Olympic and national coaches and players. We present VIRD, a VR Bird (i.e., shuttle) immersive analysis tool, that supports interactive badminton game analysis in an immersive environment based on 3D reconstructed game views of the match video. We propose a top-down analytic workflow that allows users to seamlessly move from a high-level match overview to a detailed game view of individual rallies and shots, using situated 3D visualizations and video. We collect 3D spatial and dynamic shot data and player poses with computer vision models and visualize them in VR. Through immersive visualizations, coaches can interactively analyze situated spatial data (player positions, poses, and shot trajectories) with flexible viewpoints while navigating between shots and rallies effectively with embodied interaction. We evaluated the usefulness of VIRD with Olympic and national-level coaches and players in real matches. Results show that immersive analytics supports effective badminton match analysis with reduced context-switching costs and enhances spatial understanding with a high sense of presence. 

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2. Playing to Wait: A Taxonomy of Idle Games

   https://doi.org/10.1145/3173574.3174195  

   Alharthi, Sultan A.; Alsaedi, Olaa; Toups Dugas, Phoebe O.; Tanenbaum, Theresa Jean; Hammer, Jessica (January 2018, Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems)

   Idle games are a recent minimalist gaming phenomenon in which the game is left running with little player interaction. We deepen understanding of idle games and their characteristics by developing a taxonomy and identifying game features. This paper examines 66 idle games using a grounded theory approach to analyze play, game mechanics, rewards, interactivity, progress rate, and user interface. To establish a clearly bounded definition of idle games, we analyzed 10 non-idle games with the same approach. We discuss how idle games move players from playing to planning, how they question dominant assumptions about gameplay, and their unusual use of resources such as player attention and computer cycles. Our work illuminates opportunities for the design of idle games, suggests design implications, and provides a framework for researchers to clearly articulate questions about this genre. 

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3. A Taxonomy of Minecraft Activities for STEM

   Lane, H. Chad; Yi, Sherry; Guerrero, Brian; Comins, Neil F. (December 2017, 25th International Conference on Computers in Education Proceedings)

   This paper addresses the relationship between one of the most popular video games in history (Minecraft) and STEM education. It describes a taxonomy of STEM-relevant Minecraft activities (e.g., designing and building automated farms) and their relationship to a wide range of STEM disciplines as defined by Classification of Instructional Programs (CIP; a product of the US Department of Education). Based on interviews with expert Minecraft players, academic research that analyzes Minecraft's educational uses, existing game documentation, and feedback from STEM experts, the taxonomy provides the foundation for better understanding how playing the game may inform the development of STEM interest, and how educators may best leverage those connections. 

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4. POI Recommendation: A Temporal Matching between POI Popularity and User Regularity

   https://doi.org/10.1109/ICDM.2016.0066  

   Yao, Zijun; Fu, Yanjie; Liu, Bin; Liu, Yanchi; Xiong, Hui (December 2016, 2016 IEEE 16th International Conference on Data Mining)

   Point of interest (POI) recommendation, which provides personalized recommendation of places to mobile users, is an important task in location-based social networks (LBSNs). However, quite different from traditional interest-oriented merchandise recommendation, POI recommendation is more complex due to the timing effects: we need to examine whether the POI fits a user’s availability. While there are some prior studies which included the temporal effect into POI recommendations, they overlooked the compatibility between time-varying popularity of POIs and regular availability of users, which we believe has a non-negligible impact on user decision-making. To this end, in this paper, we present a novel method which incorporates the degree of temporal matching between users and POIs into personalized POI recommendations. Specifically, we first profile the temporal popularity of POIs to show when a POI is popular for visit by mining the spatio-temporal human mobility and POI category data. Secondly, we propose latent user regularities to characterize when a user is regularly available for exploring POIs, which is learned with a user-POI temporal matching function. Finally, results of extensive experiments with real-world POI check-in and human mobility data demonstrate that our proposed user-POI temporal matching method delivers substantial advantages over baseline models for POI recommendation tasks. 

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5. Keeping People Playing: The Effects of Domain News Presentation on Player Engagement in Educational Prediction Games

   https://doi.org/10.1145/3372923.3404813  

   Dzodom, Gabriel; Kulkarni, Akshay; Marshall, Catherine C.; Shipman, Frank M. (July 2020, HT '20: Proceedings of the 31st ACM Conference on Hypertext and Social Media)

   Educational prediction games use the popularity and engagement of fantasy sports as a success model to promote learning in other domains. Fantasy sports motivate players to stay up-to-date with relevant news and explore large statistical data sets, thereby deepening their domain understanding while potentially honing their data analysis skills. We conducted a study of fantasy sports players, and discovered that while some participants performed sophisticated data analysis to support their gameplay, far more relied on news and published commentary. We used results from this study to design a prototype prediction game, Fantasy Climate, which helps players move from intuitions and advice to consuming news and analyzing data by supporting a variety of activities essential to gameplay. Because news is a key component of Fantasy Climate, we evaluated two link-based interfaces to domain-related news, one geospatial and the other organized as a list. The evaluation revealed that news presentation has a strong effect on players' engagement and performance: players using the geospatial interface not only were more engaged in the game; they also made better predictions than players who used the list-based presentation. 

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