C. Putnam, Melisa Puthenmadom, Marjorie Ann M. Cuerdo, Wanshu Wang, Nathaniel Paul
{"title":"Adaptation of the System Usability Scale for User Testing with Children","authors":"C. Putnam, Melisa Puthenmadom, Marjorie Ann M. Cuerdo, Wanshu Wang, Nathaniel Paul","doi":"10.1145/3334480.3382840","DOIUrl":"https://doi.org/10.1145/3334480.3382840","url":null,"abstract":"In this paper, we describe a pilot study in which we adapted and tested the System Usability Scales (SUS) for children between ages of 7-11. We began the study with interviews with four elementary school teachers in which we asked their help with modifying the SUS usability statements for children. We then tested those questionnaire statements with 30 children after they completed puzzles in mobile apps; we assessed the statements' understandability, dimensionality, construct validity and reliability. Our adapted SUS statements were mostly understandable. A Principal Component Analysis resulted in a four-Component model; two of those components were established as reliable. However, we were only able to support construct validity for four questionnaire statements (and none of the four Components). This pilot study contributes to the knowledgebase of user testing with children.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127955133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Towards Improving Emotion Self-report Collection using Self-reflection","authors":"Surjya Ghosh, Bivas Mitra, Pradipta De","doi":"10.1145/3334480.3383019","DOIUrl":"https://doi.org/10.1145/3334480.3383019","url":null,"abstract":"In an Experience Sampling Method (ESM) based emotion self-report collection study, engaging participants for a long period is challenging due to the repetitiveness of answering self-report probes. This often impacts the self-report collection as participants dropout in between or respond with arbitrary responses. Self-reflection (or commonly known as analyzing past activities to operate more efficiently in the future) has been effectively used to engage participants in logging physical, behavioral, or psychological data for Quantified Self (QS) studies. This motivates us to apply self-reflection to improve the emotion self-report collection procedure. We design, develop, and deploy a self-reflection interface and augment it with a smartphone keyboard-based emotion self-report collection application. The interface provides feedback to the users regarding the relation between typing behavior and self-reported emotions. We validate the proposed approach using a between-subject study, where one group (control group) is not exposed to the self-reflection interface and the other group (study group) is exposed to it. Our initial results demonstrate that using self-reflection it is possible to engage the participants in the long-term and collect more self-reports.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133834247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Family Group Chat: Family Needs to Manage Contact and Conflict","authors":"Alireza Mogharrab, Carman Neustaedter","doi":"10.1145/3334480.3382872","DOIUrl":"https://doi.org/10.1145/3334480.3382872","url":null,"abstract":"Many instant messaging applications offer group chat feature where members can share messages and make voice or video calls with a group of social contacts. We conducted a study to understand how families use group chat and what challenges they face. We found family members develop certain habits in using their family group chat, and their behavior changes when they are separated by distance or during a specific situation such as a conflict. Family members might have challenges to construct meaning from a pile of messages, find a specific message from the past and catch up with the new messages posted in the group. They need more control over when they wish to deliver a message and better ways to share their experiences.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131576416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Antle, J. Hourcade, Paulo Blikstein, J. A. Fails, F. Garzotto, O. Iversen, P. Markopoulos, G. Revelle
{"title":"Child-Computer Interaction SIG: Looking Forward After 18 Years","authors":"A. Antle, J. Hourcade, Paulo Blikstein, J. A. Fails, F. Garzotto, O. Iversen, P. Markopoulos, G. Revelle","doi":"10.1145/3334480.3381060","DOIUrl":"https://doi.org/10.1145/3334480.3381060","url":null,"abstract":"This SIG will provide child-computer interaction researchers and practitioners an opportunity to discuss future directions for the field after 18 years of Interaction Design and Children conferences. Topics for discussion include interdisciplinarity, theory and rigor, impact, emerging areas of research, and ethics.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129398936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maximilian Altmeyer, Marc Schubhan, Pascal Lessel, Linda Muller, A. Krüger
{"title":"Using Hexad User Types to Select Suitable Gamification Elements to Encourage Healthy Eating","authors":"Maximilian Altmeyer, Marc Schubhan, Pascal Lessel, Linda Muller, A. Krüger","doi":"10.1145/3334480.3383011","DOIUrl":"https://doi.org/10.1145/3334480.3383011","url":null,"abstract":"Given that an increasing number of people cultivate poor eating habits, encouraging people to eat healthy is important. One way to motivate people eating healthy is using gamification, i.e. using game elements in a non-game context. Often, a static set of gamification elements is used. However, research suggests that the motivational impact of gamification elements differs substantially across users, demanding personalized approaches. In this paper, we contribute to this by investigating the perception of frequently used gamification elements in the healthy eating domain and correlations to Hexad user types in an online study (N=237). To do so, we created storyboards illustrating these gamification elements and show their comprehensibility in a lab study (N=8). Our results validate and extend previous research in the healthy eating domain, underline the need for personalization and could be used to inform the design of gamified systems for healthy eating.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132819741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Privacy-Preserving Framework for Collecting Demographic Information","authors":"A. Mashhadi","doi":"10.1145/3334480.3382800","DOIUrl":"https://doi.org/10.1145/3334480.3382800","url":null,"abstract":"Currently one of the biggest challenges regarding demographic detection in images and social media is the lack of labelled demographic data. A big part of the challenge is that no suitable mechanism exists to replace traditional intercept surveys in a way that ensures fairness and inclusion. The lack of labelled data has also impacted the training of AI algorithms. That is the lack of labels relevant to the target domains has made it hard to estimate the accuracy of the AI algorithms when they are applied to real world situations. In this paper, we propose a framework for collecting in-the-wild images and demographic labels from ordinary people (e.g., park visitors) that ensures that privacy is integrated at every stage of the data collection process from storage to processing and sharing.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114516095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gabriele Prato, Federico Sallemi, P. Cremonesi, M. Scriminaci, S. Gudmundsson, Silvio Palumbo
{"title":"Outfit Completion and Clothes Recommendation","authors":"Gabriele Prato, Federico Sallemi, P. Cremonesi, M. Scriminaci, S. Gudmundsson, Silvio Palumbo","doi":"10.1145/3334480.3383076","DOIUrl":"https://doi.org/10.1145/3334480.3383076","url":null,"abstract":"Recommending fashion outfits requires learning a concept of style and fashionability that is typically human. There has been an increasing research effort into creating Machine Learning models able to learn such concepts, in order to distinguish between compatible and incompatible clothes and to select an item that would complete an outfit. However, most of the work done in literature tackles this problem from a pure Machine Learning point of view, disregarding real-case scenarios and the human interaction with systems able to generate outfits. This work tries to move the problem of generating outfits to the Recommender Systems domain by presenting as its main contribution a novel algorithm for a fashion-specific Recommender System that generates fashionable outfits, able to scale its inference time to be useful in real use case scenarios, and applies such algorithm on public and industrial datasets. In addition to this, this work shows preliminary results on how this algorithm can be employed in a real scenario and reports as preliminary results the evaluations provided by three professional stylists on the outfits generated by such algorithms.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116382165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Eating Computers Considered Harmful","authors":"Kieran Browne, Ben Swift, Terhi Nurmikko-Fuller","doi":"10.1145/3334480.3381810","DOIUrl":"https://doi.org/10.1145/3334480.3381810","url":null,"abstract":"Contemporary computing devices contain a concoction of numerous hazardous materials. Though users are more or less protected from these substances, recycling and landfilling reintroduce them to the biosphere where they may be ingested by people. This paper calls on HCI researchers to consider these corporal interactions with computers and critiques HCI's existing responses to the e-waste problem. We propose that whether one would consider eating a particular electronic component offers a surprisingly useful heuristic for whether we ought to be producing it on mass with vanishingly short lifespans. We hypothesize that the adoption of this heuristic might affect user behaviour and present a diet plan for users who wish to take responsibility for their own e-waste by eating it. Finally we propose an alternative direction for HCI researchers to design and advocate for those affected by the material properties of e-waste.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116469188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eduardo Gomez Ruiz, S. Mitra, Shaun Lind, Shyna Khurana, Rafael Conte, Adam Williams
{"title":"Building a Program that Rewards and Gives back to Drivers","authors":"Eduardo Gomez Ruiz, S. Mitra, Shaun Lind, Shyna Khurana, Rafael Conte, Adam Williams","doi":"10.1145/3334480.3375210","DOIUrl":"https://doi.org/10.1145/3334480.3375210","url":null,"abstract":"This paper will introduce Uber's cross-disciplinary insights driven process behind building Uber Pro, a global loyalty program for drivers. Uber Pro's global rollout was preceded by extensive, original research, design and implementation. In this paper, we will cover the discovery phase lightly and go more in depth into the actual user and business decisions that needed to be taken by UX Research in collaboration with Product, Operations and Data Science to ensure we rolled out the right set of benefits in our key markets in a short time and enabled local teams to own the benefits platform to customize further, in an ongoing fashion. As Uber Pro grows to be a record-setting global rewards program, we are committed to developing close ties to customers around the world, via research and analytics that put users first.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123474169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Living Jiagu: Enabling Constructive Etymology for Chinese Learning","authors":"Yong Cheng, Sijia Ma, Jun Chen, Wenhui Guo, Yingying Zhao, Yaolin Chen, Jingtao Wang, Yushi Jing, Wenli Zhu","doi":"10.1145/3334480.3383167","DOIUrl":"https://doi.org/10.1145/3334480.3383167","url":null,"abstract":"Living Jiagu is an interactive, wall-sized exhibition for the engaging learning of Chinese writing. Living Jiagu leverages state-of-the-art machine learning technologies to facilitate the recognition and recall of Chinese characters via constructive etymology in context - i.e., learning the writing and meaning of pictographic characters by designing them from image prompts similar to the creators of Oracle Bone Script (OBS) 3000 years ago and experiencing how these characters function and interact in natural scenes. An installation of Living Jiagu received positive feedback from over one thousand users.","PeriodicalId":118996,"journal":{"name":"Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123481131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}