huashen218/convxai-cia-dataset huggingface dataset:
Title: StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement
Authors: family: Zhang
given: Zheng; family: Xu
given: Ying; family: Wang
given: Yanhao; family: Yao
given: Bingsheng; family: Ritchie
given: Daniel; family: Wu
given: Tongshuang; family: Yu
given: Mo; family: Wang
given: Dakuo; family: Li
given: Toby Jia-Jun
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: interactive storytelling, dialogic reading, voice user interfaces, child-agent interactions, co-reading, human-AI collaboration

Abstract: Despite its benefits for children’s skill development and parent-child bonding, many parents do not often engage in interactive storytelling by having story-related dialogues with their child due to limited availability or challenges in coming up with appropriate questions. While recent advances made AI generation of questions from stories possible, the fully-automated approach excludes parent involvement, disregards educational goals, and underoptimizes for child engagement. Informed by need-finding interviews and participatory design (PD) results, we developed StoryBuddy, an AI-enabled system for parents to create interactive storytelling experiences. StoryBuddy’s design highlighted the need for accommodating dynamic user needs between the desire for parent involvement and parent-child bonding and the goal of minimizing parent intervention when busy. The PD revealed varied assessment and educational goals of parents, which StoryBuddy addressed by supporting configuring question types and tracking child progress. A user study validated StoryBuddy’s usability and suggested design insights for future parent-AI collaboration systems.
Title: Keep the VRhythm going: A musician-centred study investigating how Virtual Reality can support creative musical practice
Authors: family: Ppali
given: Sophia; family: Lalioti
given: Vali; family: Branch
given: Boyd; family: Ang
given: Chee Siang; family: Thomas
given: Andrew J.; family: Wohl
given: Bea S.; family: Covaci
given: Alexandra
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Virtual Reality, Musical practice, Creativity, Performing, Improvisation, Rehearsing, Music

Abstract: The acoustic and visual experiences of musicians in the spaces they perform in are complex and organic in nature, entailing a continuous interaction with the environment. With this project, we leverage the power of Virtual Reality (VR) to support musicians in their creative practice by transporting them to novel sonic and visual worlds. For this, we developed a musician-centred VR system, featuring various acoustic and visual virtual environments, VR Rehearse & Perform, based on design requirements gathered with musicians and performance experts. To investigate how VR can be designed to support music-makers in their creative musical practice, we performed iterative tests with 19 musicians followed by semi-structured interviews. Our findings suggest that VR has the potential to support different aspects of the creative musical practice, such as rehearsing, performing and improvising. Our research provides insights and inspirations toward designing musician-centred VR experiences for various musical activities.
Title: Super Size Me: Interface Size, Identity and Embodiment in Digital Musical Instrument Design
Authors: family: Mice
given: Lia; family: McPherson
given: Andrew P.
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: interface design, interaction, effort, digital musical instrument, size, entanglement, embodiment

Abstract: Digital interfaces are shrinking, driven by pressures of mass production and consumer culture, and often accompanied by a discourse of control, precision or convenience. Meanwhile, human bodies remain the same size, and the changing size of interfaces has implications for the formation of user identities. Drawing on embodied cognition, effort and entanglement theories of HCI, we explored the impact of interface size on the co-constitution of humans and technology. We designed an oversized digital musical instrument and invited musicians to use the instrument to create original performances. We found that both the performances and the musicians’ self-perception were influenced by the large size of the instrument, shining new light on the ways in which designing technology is designing humans and in turn culture.
Title: Exploring Interactive Sound Design for Auditory Websites
Authors: family: Zhang
given: Lotus; family: Shao
given: Jingyao; family: Liu
given: Augustina Ao; family: Jiang
given: Lucy; family: Stangl
given: Abigale; family: Fourney
given: Adam; family: Morris
given: Meredith Ringel; family: Findlater
given: Leah
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: voice interaction, interaction design, audio display

Abstract: Auditory interfaces increasingly support access to website content, through recent advances in voice interaction. Typically, however, these interfaces provide only limited audio styling, collapsing rich visual design into a static audio output style with a single synthesized voice. To explore the potential for more aesthetic and intuitive sound design for websites, we prompted 14 professional sound designers to create auditory website mockups and interviewed them about their designs and rationale. Our findings reveal their prioritized design considerations (aesthetics and emotion, user engagement, audio clarity, information dynamics, and interactivity), specific sound design ideas to support each consideration (e.g., replacing spoken labels with short, memorable audio expressions), and challenges with applying sound design practices to auditory websites. These findings provide promising direction for how to support designers in creating richer auditory website experiences.
Title: Dance Transitions: What Forms of Technology Best Support Professional Dancers as They Learn New Movement Styles?
Authors: family: Walton
given: Elizabeth; family: Mackay
given: Wendy E.
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Movement Support Tools, Transitions, Dance

Abstract: Most current dance support technologies focus on dancers, teachers or choreographers who are engaged in a single activity. We are interested in creating tools that support professional dancers over longer periods of time, as their careers and personal practices evolve. We interviewed 12 professional and pre-professional dancers about a critical moment in their careers: the transition to a new dance style due to shifting interests, ageing or injury. We identify three key challenges—overcoming habits, learning new forms of movement, transitioning over time—and their strategies for addressing them. We argue that successful tools must help dancers change their mentality about new movement styles, rather than focusing solely on movement mechanics. We suggest three possible implications for design: develop “movement substrates” that handle multiple movement representations; integrate learning and reflection in a single session; and create movement definitions through movement. We conclude with a discussion of directions for future research.
Title: Embodied Geometric Reasoning with a Robot: The Impact of Robot Gestures on Student Reasoning about Geometrical Conjectures
Authors: family: Michaelis
given: Joseph E; family: Di Canio
given: Daniela
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: gesture, human-robot interaction, embodied cognition, mathematics learning

Abstract: In this paper, we explore how the physically embodied nature of robots can influence learning through non-verbal communication, such as gesturing. We take an embodied cognition perspective to examine student interactions with a NAO robot that uses gestures while reasoning about geometry conjectures. College aged students (N = 30) were randomly assigned to either a dynamic condition, where the robot uses dynamic gestures that represent and manipulate geometric shapes in the conjectures, or control condition, where the robot uses beat gestures that match the rhythm of speech. Students in the dynamic condition: (1) use more gestures when they reason about geometry conjectures, (2) look more at the robot as it speaks, (3) feel the robot is a better study partner and uses effective gestures, but (4) were not more successful in correctly reasoning about geometry conjectures. We discuss implications for socially supported and embodied learning with a physically present robot.
Title: Family as a Third Space for AI Literacies: How do children and parents learn about AI together?
Authors: family: Druga
given: Stefania; family: Christoph
given: Fee Lia; family: Ko
given: Amy J
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Abstract: Many families engage daily with artificial intelligence (AI) applications, from conversations with a voice assistant to mobile navigation searches. While there are known ways for youth to learn about AI, we do not yet understand how to engage parents in this process. To explore parents’ roles in helping their children develop AI literacies, we designed 11 learning activities organized into four topics: image classification, object recognition, interaction with voice assistants, and unplugged AI co-design. We conducted a 5-week online in-home study with 18 children (5 to 11 years old) and 16 parents. We identify parents’ most common roles in supporting their children and consider the benefits of parent-child partnerships when learning AI literacies. Finally, we discuss how our different activities supported parents’ roles and present design recommendations for future family-centered AI literacies resources.
Title: Family Learning Talk in AI Literacy Learning Activities
Authors: family: Long
given: Duri; family: Teachey
given: Anthony; family: Magerko
given: Brian
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: embodied, collaborative, learning talk, informal learning, family learning, AI literacy, AI education

Abstract: The unique role that AI plays in making decisions that affect human lives creates a need to foster improved public understanding of AI systems. Informal learning spaces are particularly important contexts for fostering AI literacy, as they have the potential to reach a broader audience and provide spaces for children and parents to learn together. This paper explores 1) what types of dialogue family groups engage in when learning about AI in an at-home learning environment in order to inform our understanding of 2) how to design AI literacy activities for informal learning contexts. We present an analysis of family group dialogue surrounding three different AI education activities and use our findings to reflect on, update, and add to existing principles for designing AI literacy educational interventions.
Title: Adaptive Empathy Learning Support in Peer Review Scenarios
Authors: family: Wambsganss
given: Thiemo; family: Soellner
given: Matthias; family: Koedinger
given: Kenneth R; family: Leimeister
given: Jan Marco
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Automated Feedback, Writing Support Systems, Empathy Learning, Educational Applications

Abstract: Advances in Natural Language Processing offer techniques to detect the empathy level in texts. To test if individual feedback on certain students’ empathy level in their peer review writing process will help them to write more empathic reviews, we developed ELEA, an adaptive writing support system that provides students with feedback on the cognitive and emotional empathy structures. We compared ELEA to a proven empathy support tool in a peer review setting with 119 students. We found students using ELEA wrote more empathic peer reviews with a higher level of emotional empathy compared to the control group. The high perceived skill learning, the technology acceptance, and the level of enjoyment provide promising results to use such an approach as a feedback application in traditional learning settings. Our results indicate that learning applications based on NLP are able to foster empathic writing skills of students in peer review scenarios.
Title: How Interest-Driven Content Creation Shapes Opportunities for Informal Learning in Scratch: A Case Study on Novices’ Use of Data Structures
Authors: family: Cheng
given: Ruijia; family: Dasgupta
given: Sayamindu; family: Hill
given: Benjamin Mako
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: connected learning, computational participation, computers and children, learning to code, Scratch, informal learning, creativity support tools, online communities, forums, social computing and social navigation

Abstract: Through a mixed-method analysis of data from Scratch, we examine how novices learn to program with simple data structures by using community-produced learning resources. First, we present a qualitative study that describes how community-produced learning resources create archetypes that shape exploration and may disadvantage some with less common interests. In a second quantitative study, we find broad support for this dynamic in several hypothesis tests. Our findings identify a social feedback loop that we argue could limit sources of inspiration, pose barriers to broadening participation, and confine learners’ understanding of general concepts. We conclude by suggesting several approaches that may mitigate these dynamics.
Title: AlgoSolve: Supporting Subgoal Learning in Algorithmic Problem-Solving with Learnersourced Microtasks
Authors: family: Choi
given: Kabdo; family: Shin
given: Hyungyu; family: Xia
given: Meng; family: Kim
given: Juho
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Subgoal learning, Algorithmic problem-solving, Learnersourcing

Abstract: Designing solution plans before writing code is critical for successful algorithmic problem-solving. Novices, however, often plan on-the-fly during implementation, resulting in unsuccessful problem-solving due to lack of mental organization of the solution. Research shows that subgoal learning helps learners develop more complete solution plans by enhancing their understanding of the high-level solution structure. However, expert-created materials such as subgoal labels are necessary to provide learning benefits from subgoal learning, which are a scarce resource in self-learning due to limited availability and high cost. We propose a learnersourcing workflow that collects high-quality subgoal labels from learners by helping them improve their label quality. We implemented the workflow into AlgoSolve, a prototype interface that supports subgoal learning for algorithmic problems. A between-subjects study with 63 problem-solving novices revealed that AlgoSolve helped learners create higher-quality labels and more complete solution plans, compared to a baseline method known to be effective in subgoal learning.
Title: TunePad Playbooks: Designing Computational Notebooks for Creative Music Coding
Authors: family: Horn
given: Mike; family: Banerjee
given: Amartya; family: Brucker
given: Matthew
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: design, computational notebooks, playbooks, Computational literacy, music

Abstract: This paper describes the design of an online learning platform that empowers musical creation and performance with Python code. For this platform we have developed an innovative computational notebook paradigm that we call TunePad playbooks. While playbooks borrow ideas from popular computational notebooks like Jupyter, we have designed them from the ground up to support creative musical expression including live performances. After discussing our design principles and features, we share findings from a series of artifact-centered interviews conducted with experienced TunePad users. Our results show how systems like ours might flexibly support a variety of creative workflows, while suggesting opportunities for future work in this area.
Title: Assisting Teaching Assistants with Automatic Code Corrections
Authors: family: Malysheva
given: Yana; family: Kelleher
given: Caitlin
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Abstract: Undergraduate Teaching Assistants(TAs) in Computer Science courses are often the first and only point of contact when a student gets stuck on a programming problem. But these TAs are often relative beginners themselves, both in programming and in teaching. In this paper, we examine the impact of availability of corrected code on TAs’ ability to find, fix, and address bugs in student code. We found that seeing a corrected version of the student code helps TAs debug code 29% faster, and write more accurate and complete student-facing explanations of the bugs (30% more likely to correctly address a given bug). We also observed that TAs do not generally struggle with the conceptual understanding of the underlying material. Rather, their difficulties seem more related to issues with working memory, attention, and overall high cognitive load.
Title: Understanding People’s Experience for Physical Activity Planning and Exploring the Impact of Historical Records on Plan Creation and Execution
Authors: family: Xu
given: Kefan; family: Yan
given: Xinghui; family: Newman
given: Mark W
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Planning, Qualitative Research, Personal Informatics, Physical Activity, Mobile Health, Self-reflection

Abstract: Making and executing physical activity plans can help people improve their physical activity levels. However, little is known about how people make physical activity plans in everyday settings and how people can be assisted in creating more successful plans. In this paper, we developed and deployed a mobile app as a probe to investigate the in-the-wild physical activity planning experience for 28 days with 17 participants. Additionally, we explored the impact of presenting successful and unsuccessful planning records on participants’ planning behaviors. Based on interviews before, during, and after the deployment, we offer a description of what factors participants considered to fit their exercise plans into their existing routines, as well as factors leading to plan failures and dissatisfaction with planned physical activity. With access to historical records, participants derived insights to improve their plans, including trends in successes and failures. Based on those findings, we discuss the implications for better supporting people to make and execute physical activity plans, including suggestions for incorporating historical records into planning tools.
Title: The TAC Toolkit: Supporting Design for User Acceptance of Health Technologies from a Macro-Temporal Perspective
Authors: family: Nadal
given: Camille; family: McCully
given: Shane; family: Doherty
given: Kevin; family: Sas
given: Corina; family: Doherty
given: Gavin
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: technology acceptance, user-centered design, design cards, technology acceptance lifecycle, macro-temporal perspective

Abstract: User acceptance is key for the successful uptake and use of health technologies, but also impacted by numerous factors not always easily accessible nor operationalised by designers in practice. This work seeks to facilitate the application of acceptance theory in design practice through the Technology Acceptance (TAC) toolkit: a novel theory-based design tool and method comprising 16 cards, 3 personas, 3 scenarios, a virtual think-space, and a website, which we evaluated through workshops conducted with 21 designers of health technologies. Findings showed that the toolkit revised and extended designers’ knowledge of technology acceptance, fostered their appreciation, empathy and ethical values while designing for acceptance, and contributed towards shaping their future design practice. We discuss implications for considering user acceptance a dynamic, multi-stage process in design practice, and better supporting designers in imagining distant acceptance challenges. Finally, we examine the generative value of the TAC toolkit and its possible future evolution.
Title: More than Bedtime and the Bedroom: Sleep Management as a Collaborative Work for the Family
Authors: family: Shin
given: Ji Youn; family: Peng
given: Wei; family: Lee
given: Hee Rin
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Abstract: Sleep is a vital health issue. Continued sleep deficiency can increase the chance of stroke, cardiovascular disease, obesity, and diabetes. Previous studies have investigated sleep as an individual activity performed within bedrooms at night. In this study with twenty parents of young children, we identify sleep as a complex experience entangled with social dynamics between family members. For example, children's sleep means not just time for children to rest, but time for self-care for parents. This paper's contributions are twofold. First, we show how the boundaries that define sleep in terms of time (at night), space (in bedrooms), and unit of analysis (individual-focused) limit designers' opportunities to tackle the deeper sleep issues of families. Second, we suggest "division of labor" as an important but rarely discussed design concept to enhance family sleep, and as a design theme for home technologies that address issues emerging from social dynamics between householders.
Title: At-Home Pupillometry using Smartphone Facial Identification Cameras
Authors: family: Barry
given: Colin; family: de Souza
given: Jessica; family: Xuan
given: Yinan; family: Holden
given: Jason; family: Granholm
given: Eric; family: Wang
given: Edward Jay
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Abstract: With recent developments in medical and psychiatric research surrounding pupillary response, cheap and accessible pupillometers could enable medical benefits from early neurological disease detection to measurements of cognitive load. In this paper, we introduce a novel smartphone-based pupillometer to allow for future development in clinical research surrounding at-home pupil measurements. Our solution utilizes a NIR front-facing camera for facial recognition paired with the RGB selfie camera to perform tracking of absolute pupil dilation with sub-millimeter accuracy. In comparison to a gold standard pupillometer during a pupillary light reflex test, the smartphone-based system achieves a median MAE of 0.27mm for absolute pupil dilation tracking and a median error of 3.52% for pupil dilation change tracking. Additionally, we remotely deployed the system to older adults as part of a usability study that demonstrates promise for future smartphone deployments to remotely collect data in older, inexperienced adult users operating the system themselves.