Gamifying & play

Paper session

会議の名前
CHI 2020
Pac-Euglena: A Living Cellular Pac-Man Meets Virtual Ghosts
要旨

The advancement of biotechnology enabled the development of "biotic video games", where human players manipulate real biological samples for fun and educational human-biology interactions. However, new design principles are needed to both leverage and mitigate biological properties (e.g., variability and stochasticity), and create unique play experiences that transcend traditional video games. This paper describes the implementation of Pac-Euglena, a biotic Pac-Man analog, where players guide live microscopic Euglena cells with light stimuli through a physical microfluidic maze. Through use of multi-modal stimuli, a mixed biology-digital-human reality is achieved, enabling cell interactions with virtual ghosts and collectibles. Through an iterative design process, we illustrate challenges and strategies for designing games with living organisms. A user study (n=18, conducted at a university event) showed that Pac-Euglena was fun, stimulated curiosity, and taught users about Euglena. We conclude with five general guidelines for the design and development of biotic games and HBI interfaces.

キーワード
Biological user interfaces
biotic games
Euglena gracilis
augmented reality
mixed reality
human-biology interaction (HBI)
著者
Amy T. Lam
Stanford University & University of Arizona, Stanford & Tucson, CA, USA
Jonathan Griffin
Stanford University, Stanford, CA, USA
Matthew Austin Loeun
Stanford University, Stanford, CA, USA
Nate J. Cira
Stanford University & Harvard University, Cambridge, MA, USA
Seung Ah Lee
Stanford University & Yonsei University, Seoul, Republic of Korea
Ingmar H. Riedel-Kruse
University of Arizona & Stanford University, Tucson, AZ, USA
DOI

10.1145/3313831.3376378

論文URL

https://doi.org/10.1145/3313831.3376378

動画
Designing IoT Resources to Support Outdoor Play for Children
要旨

We describe a Research-through-Design (RtD) project that explores the Internet of Things (IoT) as a resource for children's free play outdoors. Based on initial insights from a design ethnography, we developed four RtD prototypes for social play in different scenarios of use outdoors, including congregating on a street or in a park to play physical games with IoT. We observed these prototypes in use by children in their free play in two community settings, and report on the qualitative analysis of our fieldwork. Our findings highlight the designs' material qualities that encouraged social and physical play under certain conditions, suggesting social affordances that are central to the success of IoT designs for free play outdoors. We provide directions for future research that addresses the challenges faced when deploying IoT with children, contributing new considerations for interaction design with children in outdoor settings and free play contexts.

キーワード
Digital playing out
children
outdoor play
free play, pervasive play
Internet of Things
著者
Thomas Dylan
Northumbria University, Newcastle upon Tyne, United Kingdom
Gavin Wood
Northumbria University, Newcastle upon Tyne, United Kingdom
Abigail C. Durrant
Northumbria University, Newcastle upon Tyne, United Kingdom
John Vines
Northumbria University, Newcastle upon Tyne, United Kingdom
Pablo E. Torres
University College London, London, United Kingdom
Philip I. N. Ulrich
Canterbury Christ Church University, Canterbury, United Kingdom
Mutlu Cukurova
University College London, London, United Kingdom
Amanda Carr
Canterbury Christ Church University, Canterbury, United Kingdom
Sena Çerçi
Northumbria University, Newcastle Upon Tyne, United Kingdom
Shaun Lawson
Northumbria University, Newcastle upon Tyne, United Kingdom
DOI

10.1145/3313831.3376302

論文URL

https://doi.org/10.1145/3313831.3376302

Investigating User-Created Gamification in an Image Tagging Task
要旨

Commonly, gamification is designed by developers and not by end-users. In this paper we investigate an approach where users take control of this process. Firstly, users were asked to describe their own gamification concepts which would motivate them to put more effort into an image tagging task. We selected this task as gamification has already been shown to be effective here in previous work. Based on these descriptions, an implementation was made for each concept and given to the creator. In a between-subjects study (n=71), our approach was compared to a no-gamification condition and two conditions with fixed gamification settings. We found that providing participants with an implementation of their own concept significantly increased the amount of generated tags compared to the other conditions. Although the quality of tags was lower, the number of usable tags remained significantly higher in comparison, suggesting the usefulness of this approach.

キーワード
Customization
user-driven game design
bottom-up
motivation
replication
著者
Marc Schubhan
German Research Center for Artificial Intelligence (DFKI), Saarland Informatics Campus, Saarbrücken, Germany
Maximilian Altmeyer
German Research Center for Artificial Intelligence (DFKI), Saarland Informatics Campus, Saarbrücken, Germany
Dominic Buchheit
Saarland University, Saarland Informatics Campus, Saarbrücken, Germany
Pascal Lessel
German Research Center for Artificial Intelligence (DFKI), Saarland Informatics Campus, Saarbrücken, Germany
DOI

10.1145/3313831.3376360

論文URL

https://doi.org/10.1145/3313831.3376360

動画
Recognizing Affiliation: Using Behavioural Traces to Predict the Quality of Social Interactions in Online Games
要旨

Online social interactions in multiplayer games can be supportive and positive or toxic and harmful; however, few methods can easily assess interpersonal interaction quality in games. We use behavioural traces to predict affiliation between dyadic strangers, facilitated through their social interactions in an online gaming setting. We collected audio, video, in-game, and self-report data from 23 dyads, extracted 75 features, trained Random Forest and Support Vector Machine models, and evaluated their performance predicting binary (high/low) as well as continuous affiliation toward a partner. The models can predict both binary and continuous affiliation with up to 79.1% accuracy (F1) and 20.1% explained variance (R2) on unseen data, with features based on verbal communication demonstrating the highest potential. Our findings can inform the design of multiplayer games and game communities, and guide the development of systems for matchmaking and mitigating toxic behaviour in online games.

キーワード
affiliation
social interaction
evaluation
prediction
recognition
cooperative games
machine learning
bonding
著者
Julian Frommel
Ulm University & University of Saskatchewan, Ulm, Germany
Valentin Sagl
University of Saskatchewan, Saskatoon, SK, Canada
Ansgar E. Depping
University of Saskatchewan, Saskatoon, SK, Canada
Colby Johanson
University of Saskatchewan, Saskatoon, SK, Canada
Matthew K. Miller
University of Saskatchewan, Saskatoon, SK, Canada
Regan L. Mandryk
University of Saskatchewan, Saskatoon, SK, Canada
DOI

10.1145/3313831.3376446

論文URL

https://doi.org/10.1145/3313831.3376446