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   Ma, Renkai ; Gui, Xinning ; Kou, Yubo ( November 2022 , Proceedings of the ACM on Human-Computer Interaction)

   Esports, like traditional sports, face governance challenges such as foul play and match fixing. The esports industry has seen various attempts at governance structure but is yet to form a consensus. In this study, we explore esports governance in League of Legends (LoL), a major esports title. Through a two-stage, mixed-methods analysis of rule enforcement that Riot Games, LoL's developer and publisher, has performed against esports participants such as professional players and teams, we qualitatively describe rule breaking behaviors and penalties in LoL esports, and quantitatively measure how contextual factors such as time, perpetrator identity, and region might influence governance outcomes. These findings about rule enforcement allow us to characterize the esports governance of LoL as top-down and paternalistic, and to reflect upon professional players' work and professionalization in the esports context. We conclude by discussing translatable implications for esports governance practice and research. 

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2. "A Time and Phase for Everything" - Towards A Self Regulated Learning Perspective on Computational Support for Esports

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   Kleinman, Erica ; Habibi, Reza ; Yao, Yichen ; Gayle, Christian ; Seif El-Nasr, Magy ( October 2022 , Proceedings of the ACM on Human-Computer Interaction)

   Computational support for learning in the domain of esports has seen a great deal of attention in recent years as an effective means of helping players learn and reap the benefits of play. However, previous work has not examined the tools from a learning theory perspective to assess if learning is prompted and supported in the right place and time. As a first step towards addressing this gap, this paper presents the results of two studies: a review of existing computational tools, and an online survey of esports' players' learning needs supplemented with qualitative interviews. Using Zimmerman's Cyclical Phase Model of Self-Regulated Learning as a lens, we identify patterns in the types of support offered by existing tools and players' support interests during different learning phases. We identify 11 opportunities for future research and development to better support self-regulated learning in esports.

    

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3. reVISit: Supporting Scalable Evaluation of Interactive Visualizations

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   Ding, Yiren ; Wilburn, Jack ; Shrestha, Hilson ; Ndlovu, Akim ; Gadhave, Kiran ; Nobre, Carolina ; Lex, Alexander ; Harrison, Lane ( October 2023 , Proceedings of IEEE VIS)

   reVISit is an open-source software toolkit and framework for creating, deploying, and monitoring empirical visualization studies. Running a quality empirical study in visualization can be demanding and resource-intensive, requiring substantial time, cost, and technical expertise from the research team. These challenges are amplified as research norms trend towards more complex and rigorous study methodologies, alongside a growing need to evaluate more complex interactive visualizations. reVISit aims to ameliorate these challenges by introducing a domain-specific language for study set-up, and a series of software components, such as UI elements, behavior provenance, and an experiment monitoring and management interface. Together with interactive or static stimuli provided by the experimenter, these are compiled to a ready-to-deploy web-based experiment. We demonstrate reVISit's functionality by re-implementing two studies --- a graphical perception task and a more complex, interactive study. reVISit is an open-source community project, available at https://revisit.dev/. 

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   null (Ed.)

   There is an increasing trend of Virtual-Reality (VR) applications found in education, entertainment, and industry. Many of them utilize real world tools, environments, and interactions as bases for creation. However, creating such applications is tedious, fragmented, and involves expertise in authoring VR using programming and 3D-modelling softwares. This hinders VR adoption by decoupling subject matter experts from the actual process of authoring while increasing cost and time. We present VRFromX, an in-situ Do-It-Yourself (DIY) platform for content creation in VR that allows users to create interactive virtual experiences. Using our system, users can select region(s) of interest (ROI) in scanned point cloud or sketch in mid-air using a brush tool to retrieve virtual models and then attach behavioral properties to them. We ran an exploratory study to evaluate usability of VRFromX and the results demonstrate feasibility of the framework as an authoring tool. Finally, we implemented three possible use-cases to showcase potential applications. 

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