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1. Investigating the Impact of Annotation Interfaces on Player Performance in Distributed Multiplayer Games

   https://doi.org/10.1145/3173574.3173888  

   Alharthi, Sultan A; Torres, Ruth C; Khalaf, Ahmed S; Toups_Dugas, Phoebe O; Dolgov, Igor; Nacke, Lennart E (April 2018, ACM)

   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. 

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2. The WearableLearning Platform: A Computational Thinking Tool Supporting Game Design and Active Play

   https://doi.org/10.1007/s10758-022-09601-1  

   Arroyo, Ivon; Closser, Avery Harrison; Castro, Francisco; Smith, Hannah; Ottmar, Erin; Micciolo, Matthew (August 2022, Technology, Knowledge and Learning)

   This emerging technology report introduces the WearableLearning (WL) platform as a tool to exercise computational thinking and STEM learning for 5-12th grade students through mobile technology-augmented active game play and game creation. Freely available at WearableLearning.org, it allows students and teachers to play, create, debug, and manage multiplayer, active games. To date, WearableLearning has been used in schools and afterschool programs by roughly 500 students and 25 teachers to create games covering STEM curricular content. WearableLearning enables the creation of physically active and social games, while offering possibilities for research on computational thinking, embodied cognition, collaborative learning, game-based learning, and practical applications of technology in STEM classrooms. 

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3. Multiplayer Physical and Virtual Reality Games for Team-based Manufacturing Simulation

   Aqlan, F. (June 2020, ASEE Annual Conference proceedings)

   Familiarity with manufacturing environments is an essential aspect for many engineering students. However, such environments in real world often contain expensive equipment making them difficult to recreate in an educational setting. For this reason, simulated physical environments where the process is approximated using scaled-down representations are usually used in education. However, such physical simulations alone may not capture all the details of a real environment. Virtual reality (VR) technology nowadays allows for the creation of fully immersive environments, bringing simulations to the next level. Using rapidly advancing gaming technology, this research paper explores the applicability of creating multiplayer serious games for manufacturing simulation. First, we create and validate a hands-on activity that engages groups of students in the design and assembly of toy cars. Then, a corresponding multiplayer VR game is developed, which allows for the collaboration of multiple VR users in the same virtual environment. With a VR headset and proper infrastructure, a user can participate in a simulation game from any location. This paper explores whether multiplayer VR simulations could be used as an alternative to physical simulations. 

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4. Multiplayer Physical and Virtual Reality Games for Team-based Manufacturing Simulation

   https://doi.org/10.18260/1-2--34989  

   Zhao, R.; Aqlan, F.; Elliott, L.; Baxter, E. (June 2020, ASEE Annual Conference proceedings)

   Familiarity with manufacturing environments is an essential aspect for many engineering students. However, such environments in real world often contain expensive equipment making them difficult to recreate in an educational setting. For this reason, simulated physical environments where the process is approximated using scaled-down representations are usually used in education. However, such physical simulations alone may not capture all the details of a real environment. Virtual reality (VR) technology nowadays allows for the creation of fully immersive environments, bringing simulations to the next level. Using rapidly advancing gaming technology, this research paper explores the applicability of creating multiplayer serious games for manufacturing simulation. First, we create and validate a hands-on activity that engages groups of students in the design and assembly of toy cars. Then, a corresponding multiplayer VR game is developed, which allows for the collaboration of multiple VR users in the same virtual environment. With a VR headset and proper infrastructure, a user can participate in a simulation game from any location. This paper explores whether multiplayer VR simulations could be used as an alternative to physical simulations. 

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5. Nonverbal Human Signals Can Help Autonomous Agents Infer Human Preferences for Their Behavior

   Candon, Kate; Chen, Jesse; Kim, Yoony; Tsoi, Nathan; Vázquez, Marynel (May 2023, ACM)

   An overarching goal of Artificial Intelligence (AI) is creating autonomous, social agents that help people. Two important challenges, though, are that different people prefer different assistance from agents and that preferences can change over time. Thus, helping behaviors should be tailored to how an individual feels during the interaction. We hypothesize that human nonverbal behavior can give clues about users' preferences for an agent's helping behaviors, augmenting an agent's ability to computationally predict such preferences with machine learning models. To investigate our hypothesis, we collected data from 194 participants via an online survey in which participants were recorded while playing a multiplayer game. We evaluated whether the inclusion of nonverbal human signals, as well as additional context (e.g., via game or personality information), led to improved prediction of user preferences between agent behaviors compared to explicitly provided survey responses. Our results suggest that nonverbal communication -- a common type of human implicit feedback -- can aid in understanding how people want computational agents to interact with them. 

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