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Video game analytics are widely adopted within academia and industrial development – yet, the player’s perspective is rarely considered as a driving factor, even though vast communities are interested in self-regulated learning, cross-comparisons and empirical trends or insights. In this work, we propose to empower the role of the player as the central impulse for analytics, collect requirements and data from the community of one of the most popular MMORPGs (Guild Wars 2), establish a tool over a 18-month period of participatory development and discuss the co-created features. With analytics for in-game logs from (n=175,099) unique players and atomic game actions of over 2 million hours played, we contribute a large-scale, long-term iterative implementation and evaluation of a player-driven instrument to quantify popularity, viability and hierarchical inspection between classes or individual performances. This tool found frequent usage among the actual game community, delivering game data science to the very player.
This paper explores \textit{redirection of activity} as an intervention strategy for self-regulation online. We conducted an explorative study ($N$ = 19) of the browser extension \textit{Aiki}, which redirects a user from a self-defined `time-wasting' website to an online platform for learning programming (Sololearn, Codecademy, or Udemy). Based on quantitative measures alone, using Aiki decreased the participants' time spent on time-wasting websites on average, and increased programming knowledge. However, several users ended up avoiding\enlargethispage{20pt} their time-wasting websites entirely when Aiki was active, or they discontinued the use of the extension after `the novelty wore off'. Based on these effects, we qualitatively explored the user experiences and identified four challenges and four opportunities for using redirection of activity as an intervention strategy for self-regulation of time management in a browser. Our results suggest that this intervention strategy is promising, but careful design is necessary to strike an optimal balance between independence and regulation.
While it is widely assumed that games can engage patients in therapy through their inherent 'motivational pull', relatively little attention has been paid to what HCI games research can learn from strategies employed by therapists. We address this gap by leveraging Self-Determination Theory (SDT) and its mini-theories Basic Psychological Needs Theory and Organismic Integration Theory as a theoretical lens on physical therapy for children and adolescents. Results from in-depth interviews with twelve therapists show that they carefully adjust sessions to allow patients to experience competence, making more comprehensive adjustments than currently offered by games. Additionally, we highlight how therapists leverage their relationship with patients to support motivation, but struggle to reconcile meaningful experiences of autonomy with therapeutic goals. On this basis, we reflect on implications for researchers and designers who create games for physical therapy, and the potential of SDT to provide a foundation for game design and therapeutic practice.
Research on Extended Reality (XR) and Artificial Intelligence (AI) is booming, which has led to an emerging body of literature in their intersection. However, the main topics in this intersection are unclear, as are the benefits of combining XR and AI. This paper presents a scoping review that highlights how XR is applied in AI research and vice versa. We screened 2619 publications from 203 international venues published between 2017 and 2021, followed by an in-depth review of 311 papers. Based on our review, we identify five main topics at the intersection of XR and AI, showing how research at the intersection can benefit each other. Furthermore, we present a list of commonly used datasets, software, libraries, and models to help researchers interested in this intersection. Finally, we present 13 research opportunities and recommendations for future work in XR and AI research.
Technology embeddedness in HCI textiles has great potential for enabling novel interactions and enriched experiences, but unless carefully designed, could inadvertently worsen HCI’s sustainability problem. In an attempt to bridge sustainable debates and practical material-driven scholarship in HCI, we propose Multimorphic Textile-forms (MMTF), as a design approach developed through a lens of multiplicity and extended life cycles, that facilitate change in both design/production and use-time via the simultaneous thinking of the qualities and behaviour of material and form. We provide a number of cases, textile-form methods and vocabulary to enable exploration in this emerging design space. MMTF grants insights into textiles as complex material systems whose behaviour can be tuned across material, interaction and ecological scales for conformal, seamless, and sustainable outcomes.
Studying mental models has recently received more attention, aiming to understand the cognitive aspects of human-computer interaction. However, there is not enough research on the elicitation of mental models in complex dynamic systems. We present Thought Bubbles as an approach for eliciting mental models and an avenue for understanding players' mental model development in interactive virtual environments. We demonstrate the use of Thought Bubbles in two experimental studies involving 250 participants playing a supply chain game. In our analyses, we rely on Situation Awareness (SA) levels, including perception, comprehension, and projection, and show how experimental manipulations such as disruptions and information sharing shape players' mental models and drive their decisions depending on their behavioral profile. Our results provide evidence for the use of thought bubbles in uncovering cognitive aspects of behavior by indicating how disruption location and availability of information affect people's mental model development and influence their decisions.