Generative AI is increasingly used in learning environments, but most systems focus on generating responses rather than supporting interaction. This limitation is especially important for blind and visually impaired (BVI) learners, who rely on non-visual ways to navigate and understand programming tasks. We present findings from a co-design study with BVI high school students exploring expectations for AI assistants in expressive computer science learning. Participants described how AI could support accessible interaction, guide learning, and empower learner agency. We derive two design principles for inclusive AI assistants: (1) situated multimodal interaction and (2) scaffolded iterative interaction. These principles shift the focus from adapting outputs (e.g., audio) to designing interactions that support how learners navigate and engage in the CS learning context. Our work highlights the importance of interaction design in accessible AI and the value of involving BVI learners in the design of AI-powered educational technologies.

Ambient computational systems—increasingly present in installation art, traffic control systems, and smart homes—can evoke “awe” through their conceptual and physical vastness. While this awe can productively evoke inter-user connectedness and spark dramatic conceptual shifts, this effect has been understudied in Human-Computer Interaction. To investigate this phenomenon, we built Sound Clouds, an interactive art installation and ambient computational system designed to evoke awe. Deployed in a public art space and experienced by over 200 visitors, Sound Clouds transformed a warehouse-sized urban space into an immersive sound-reactive environment with large-scale neutrally-buoyant inflatables. An interview study (n=35) showed that though interactions with Sound Clouds provoked a range of uncertain mental models, it also spurred participants to shift their focus towards awe, play, sensory experience, and collaboration. This paper ends with design considerations for creators seeking to manage the intrinsic role of awe in ambient computational systems.

The rapid growth of generative AI in education has deepened the need for both responsible AI practices and AI literacy. However, these domains are often addressed separately, leaving a gap in guidance for educators, designers, developers, and researchers. This paper presents a conceptual framework that connects responsible AI principles with AI literacy and introduces its application through a practical checklist as a toolkit, with a hypothetical case example, which offers actionable prompts for responsible use of AI in educational and design contexts. Together, the TEACH-RAI framework and toolkit aim to provide both theoretical grounding and accessible resources to foster responsible engagement with AI in the educational context.

Museums play a critical role in promoting public understanding of emerging technologies like artificial intelligence (AI), but it is unclear what design features lead to learning about AI in museums. We contribute a design research exploration of how embodiment and creativity foster AI literacy in museum exhibits. We present design prototypes of three museum exhibits—DataBites, Knowledge Net, and LuminAIx—that aim to teach middle schoolers about AI. We present results from a qualitative analysis of an in-museum study in which we examined participants’ understanding of and interest in AI through interviews and video recordings. Our findings illuminate how creativity fosters interest in AI and how different forms of embodiment contribute to learning about AI. We recommend that AI museum exhibits utilize creative and personally relevant activities to engage middle schoolers, support hybrid conceptualizations of AI, and leverage tangible interaction to make AI concepts approachable.

Expressive computer science (CS) learning environments teach coding through the creation of an artifact, such as audio or video output.EarSketch is an expressive CS learning environment designed to teach computing through music production, mixing and arranging sounds using code.In this paper, we explore the accessibility challenges of using EarSketch for learners who are Blind and Visually Impaired (BVI).We present key findings from co-design studies with teachers and students at an institution specializing in BVI education, focused on gathering both groups' unique perspectives about EarSketch's ability to support teachers' curricula, students' workflows using the system with accessibility software, and challenges faced by users who are BVI.

This study conducts a novel approach to redesign EarSketch, an expressive computer science (CS) learning environment that integrates music composition into computing education, with a specific focus on inclusivity for blind and visually impaired (BVI) learners. This approach centers on the participation of teachers, students, and the community as co-designers, leveraging their insights and experiences to enhance the program’s accessibility and effectiveness. By actively involving the stakeholders in the development process, the study aims to address the unique educational challenges and needs of learners who are visually impaired more effectively. The participatory design approach is expected to not only maintain the intrinsic appeal of EarSketch but also to expand its accessibility, ensuring that it becomes a more inclusive tool in computer science education. The ultimate goal is to establish a more adaptable and inclusive educational paradigm within STEAM, particularly in computing education and music, that is responsive to the diverse needs of all students, including those with visual impairments. The contributions of this paper are design recommendations based on our data that can be applied to the design of EarSketch and other expressive CS environments for BVI learners.

This paper explores how different interaction modalities with AI agents affect human perception of the co-creative process. We utilize the Wizard of Oz methodology within Drawcto, a co-creative drawing system, to examine co-creativity across three scenarios: human-human, human-robot, and human-software interactions. Using a mixed-methods approach, we combined insights using the Observable Creative Sensemaking (OCSM) method with data from structured interviews. The study involved 20 participants engaging in a collaborative drawing task under each interaction scenario. Key findings reveal an average OCSM curve indicative of typical human-human interactions, varied themes in human-AI collaboration, and a notable influence of AI embodiment on participant perceptions, with the robot interface resembling human-human collaboration more closely than the software interface. Overall, this research offers valuable insights into how different interaction modalities influence the perceived role of AI in the co-creative process and provides design considerations for enhancing human-AI co-creative interactions.

LuminAI is an interactive art installation that allows participants to collaborate with an AI dance partner by improvising movements. During the interaction, the participant dances with an AI dance partner who learns from the participant’s movements in real-time and remixes them into new, unexpected forms of motion. LuminAI blurs the lines between the participant and AI agent, inviting the participant to improvise and engage with AI in a dance of creativity. Recently, we’ve redesigned LuminAI with the educational purpose of enhancing the public’s AI literacy. We separated LuminAI into three panels with AI-related educational goals for each panel and redesigned the user interaction. In this paper, we present the redesign of LuminAI and educational goals centering on enhancing the public’s AI literacy.

As generative AI rapidly enters everyday life, educational interventions for teaching about AI need to cater to how young people, in particular middle schoolers who are at a critical age for reasoning skills and identity formation, conceptualize and interact with AI. We conducted nine focus groups with 24 middle school students to elicit their interests, conceptions of, and approaches to a popular generative AI tool, ChatGPT. We highlight a) personally and culturally-relevant topics to this population, b) three distinct approaches in students’ open-ended interactions with ChatGPT: AI testing-oriented, AI socializing-oriented, and content exploring-oriented, and 3) an improved understanding of youths’ conceptions and misconceptions of generative AI. While misconceptions highlight gaps in understanding what generative AI is and how it works, most learners show interest in learning about what AI is and what it can do. We discuss the implications of these conceptions for designing AI literacy interventions in museums.

Generative Artificial Intelligence (AI) has witnessed unprecedented growth in text-to-image AI tools. Yet, much remains unknown about users’ prompt journey with such tools in the wild. In this paper, we posit that designing human-centered text-to-image AI tools requires a clear understanding of how individuals intuitively approach crafting prompts, and what challenges they may encounter. To address this, we conducted semi-structured interviews with 19 existing users of a text-to-image AI tool. Our findings (1) offer insights into users’ prompt journey including structures and processes for writing, evaluating, and refining prompts in text-to-image AI tools and (2) indicate that users must overcome barriers to aligning AI to their intents, and mastering prompt crafting knowledge. From the findings, we discuss the prompt journey as an individual yet a social experience and highlight opportunities for aligning text-to-image AI tools and users’ intents.

Fostering learners’ interest remains an important challenge in computer science (CS) education. In this paper, we explore how creative music-making, tangible interfaces, and embodiment can be used toward this end. The primary contribution of this paper is Xylocode, a novel exhibit that introduces middle school age learners to computing concepts and fosters interest in CS via a tangible playspace for making music using an embodied simulation. We additionally present an in-museum evaluation of Xylocode with 29 middle school age children. Our results indicate that the exhibit fosters situational interest in computer science and leads to recognition of certain computing concepts, including arrays and global variables. Future research is needed to assess whether the exhibit leads to longer-term learning and/or interest gains and to explore why other computing concepts were not recognized by as many learners. We identify several implications and directions for future work based on our findings.

Co-creation in embodied contexts is central to the human experience but is often lacking in our interactions with computers. We seek to develop a better understanding of embodied human co-creativity to inform the human-centered design of machines that can co-create with us. In this paper, we ask: What characterizes dancers’ experiences of embodied dyadic interaction in movement improvisation? To answer this, we ran focus groups with 24 university dance students and conducted a thematic analysis of their responses. We synthesize our findings in an Interconnected Model of Improvisational Dance Inputs, where movement choices are shaped by the interplay between in-the-moment influences between the self, partner, and the environment, a set of generative strategies, and heuristics for a successful collaboration. We present a set of design recommendations for LuminAI, a co-creative AI dance partner. Our contributions can inform the design of AI in embodied co-creative domains.

Fostering young learners’ literacy surrounding AI technologies is becoming increasingly important as AI is becoming integrated in many aspects of our lives and is having far-reaching impacts on society. We have developed Knowledge Net and Creature Features, two activity boxes for family groups to engage with in their homes that communicate AI literacy competencies such as understanding knowledge representations, the steps of machine learning, and AI ethics. Our current work is exploring how to transform these activity boxes into museum exhibits for middle-school age learners, focusing on three key considerations: centering learner interests, generating personally meaningful outputs, and incorporating embodiment and collaboration on a larger scale. Our demonstration will feature the existing Knowledge Net and Creature Features activity boxes alongside early-stage prototypes adapting these activities into larger-scale museum exhibits. This paper contributes an exploration into how to design AI literacy learning interventions for varied informal learning contexts.

This paper introduces a new method for quantifying open-ended collaborative embodied improvisation: Observable Creative Sense-Making (OCSM). This technique builds on previous work on Creative Sense-Making (CSM), examines its shortcomings, and addresses it by reformalizing and grounding CSM in current literature from embodied social cognition and an intersubjective perspective of creativity. We apply this method to empirical studies of human collaboration in dance improvisation with 16 advanced college dancers and establish the method’s validity. The OCSM method described in this paper includes a qualitative coding technique, a web-based tool for coding the interaction, and the cognitive theory behind its application.

Alternative game controllers — physical input mechanisms for interactive media that are distinct from traditional handheld controllers or computer inputs — are a continuing presence in commercial and academic games fields. Many of these works, presented at conferences, festivals, and public art outlets, forefront social interaction as a key component of the play they afford, supporting a variety of designs specifically aimed at collaborative play. However, despite a substantial body of work in this field, there is as of yet no unified framework for designing or conceptualizing collaborative games that use alternative controllers.

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.

Co-creative proccesses between people can be characterized by rich dialogue that carries each person's ideas into the collaborative space. When people co-create an artifact that is both technical and aesthetic, their dialogue reflects the interplay between these two dimensions. However, the dialogue mechanisms that express this interplay and the extent to which they are related to outcomes, such as peer satisfaction, are not well understood. This paper reports on a study of 68 high school learner dyads' textual dialogues as they create music by writing code together in a digital learning environment for musical remixing. We report on a novel dialogue taxonomy built to capture the technical and aesthetic dimensions of learners' collaborative dialogues. We identified dialogue act n-grams (sequences of length 1, 2, or 3) that are present within the corpus and discovered five significant n-gram predictors for whether a learner felt satisfied with their partner during the collaboration. The learner was more likely to report higher satisfaction with their partner when the learner frequently acknowledges their partner, exchanges positive feedback with their partner, and their partner proposes an idea and elaborates on the idea. In contrast, the learner is more likely to report lower satisfaction with their partner when the learner frequently accepts back-to-back proposals from their partner and when the partner responds to the learner's statements with positive feedback. This work advances understanding of collaborative dialogue within co-creative domains and suggests dialogue strategies that may be helpful to foster co-creativity as learners collaborate to produce a creative artifact. The findings also suggest important areas of focus for intelligent or adaptive systems that aim to support learners during the co-creative process.

This article presents Active Prolonged Engagement eXpanded (APEX), a framework and toolkit for informing evidence-based decisions about the iterative design of embodied, collaborative museum exhibits. We provide an overview of APEX, a framework that builds on both prior work and experimentally derived data to provide an understanding of how visitors' physical, social, emotional, and intellectual engagement transform during the course of their interaction with an exhibit. We present two case studies demonstrating how to apply APEX in practice, analyzing video recordings of participant interactions with different design iterations of TuneTable-an interactive exhibit for co-creative computational music-making-at both a macro- and micro-level. In the case studies, we explore how APEX reveals important features of participant interaction that suggest implications and directions for design. Finally, we present a toolkit of resources to aid researchers in operationalizing APEX as a framework for video analysis, in-situ observation, and iterative design and evaluation.

The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of six AI assignments from the 2021 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.

Action selection from many options with few constraints is crucial for improvisation and co-creativity. Our previous work proposed creative arc negotiation to solve this problem, i.e., selecting actions to follow an author-defined ‘creative arc’ or trajectory over estimates of novelty, unexpectedness, and quality for potential actions. The CARNIVAL agent architecture demonstrated this approach for playing the Props game from improv theatre in the Robot Improv Circus installation. This article evaluates the creative arc negotiation experience with CARNIVAL through two crowdsourced observer studies and one improviser laboratory study. The studies focus on subjects’ ability to identify creative arcs in performance and their preference for creative arc negotiation compared to a random selection baseline. Our results show empirically that observers successfully identified creative arcs in performances. Both groups also preferred creative arc negotiation in agent creativity and logical coherence, while observers enjoyed it more too.

Fostering public AI literacy (i.e. a high-level understanding of artificial intelligence (AI) that allows individuals to critically and effectively use AI technologies) is increasingly important as AI is integrated into individuals’ everyday lives and as concerns about AI grow. This paper investigates how to design collaborative, creative, and embodied interactions that foster AI learning and interest development. We designed three prototypes of collaborative, creative, and/or embodied learning experiences that aim to communicate AI literacy competencies. We present the design of these prototypes as well as the results from a user study that we conducted with 14 family groups (38 participants). Our data analysis explores how collaboration, creativity, and embodiment contributed to AI learning and interest development across the three prototypes. The main contributions of this paper are: 1) three designs of AI literacy learning activities and 2) insights into the role creativity, collaboration, and embodiment play in AI learning experiences.

desAIner is a creativity support tool able to assist a fashion designer in the ideation process of creating clothing through the use of a ”bad” Generative Adversarial Network (GAN). After training the GAN on a relatively small number of diverse high fashion images from popular designers’ clothing collections, the tool generates a latent space of surreal visual representations and combinations of these fashion images for designers to explore and generate fresh ideas. Using this tool, we conducted interviews with two fashion designers who used the tool and discussed how these ”bad” GANs can help them turn the creative task of designing novel clothing into a more effortless and efficient task by presenting surreal visual stimuli to incite inspiration.

Computer science educators often use multiple creative computing platforms to motivate and support students learning computer science. Arguably, we understand little about the complementary ways in which the various platforms build on students' prior experiences. This study compares two CS+music platforms used by middle school students in a summer camp to understand the unique affordances of each platform at activating and building upon prior music and computing experiences. We assess interest formation through pre and post student surveys and via interviews on the final day of the camp. The findings suggest that using different approaches to CS+music platform design may help engage students with different levels of prior music and coding experience.

AI is becoming increasingly integrated in common technologies, which suggests that learning experiences for audiences seeking a "casual" understanding of AI-i.e. understanding how a search engine works, not necessarily understanding how to program one-is an increasingly important design space. Informal learning spaces like museums are particularly well-suited for such public science communication efforts, but there is little research investigating how to design AI learning experiences for these spaces. This paper explores how to design museum experiences that communicate key concepts about AI, using collaboration, creativity, and embodiment as inspirations for design. We present the design of five low-fidelity AI literacy exhibit prototypes and results from a thematic analysis of participant interactions during a co-design workshop in which family groups interacted with the prototypes and designed exhibits of their own. Our findings suggest new topics and design considerations for AI-related exhibits and directions for future research.

Museum visitors often come into the museum space receptive to exploring new ideas, and this may encourage members of visitor groups to be supportive and cooperative when engaging together with exhibits. However, as participant groups explore the concepts of the exhibit, interruptions, conflicts, or disagreements may result. We collectively label this social tension as discord. This paper studies discord among family groups interacting with TuneTable, a museum exhibit designed to promote middle school students' interest in and learning of basic computing concepts (e.g. loops, conditionals) through music programming. We analyzed video recordings of each participant group and found that discord often appears alongside three markers of high engagement: a) complex physical manipulation of exhibit components; b) conversation demonstrating an in-depth understanding of how the exhibit works; and c) instances of collaboration between group members. Our findings suggest that certain types of discord could potentially be indicators of productive learning experiences at museum exhibits related to computing. In addition, when designing informal learning experiences for computing education, our findings suggest that discord is a potential trigger for deeper engagement that warrants further exploration.

Artificial intelligence (AI) is becoming increasingly integrated in user-facing technology, but public understanding of these technologies is often limited. There is a need for additional HCI research investigating a) what competencies users need in order to effectively interact with and critically evaluate AI and b) how to design learner-centered AI technologies that foster increased user understanding of AI. This paper takes a step towards realizing both of these goals by providing a concrete definition of AI literacy based on existing research. We synthesize a variety of interdisciplinary literature into a set of core competencies of AI literacy and suggest several design considerations to support AI developers and educators in creating learner-centered AI. These competencies and design considerations are organized in a conceptual framework thematically derived from the literature. This paper's contributions can be used to start a conversation about and guide future research on AI literacy within the HCI community.

Much work has been done on educational games, game-based learning, and gamification in recent years, exploring how games may benefit learning. However, the reverse relationship has yet to be fully explored—how can educational psychology and pedagogy influence our understanding of player experience and the design of games? A study was conducted to examine how various aspects of player experience are related to two commonly used motivational constructs in educational psychology: achievement goals and causal attributions. In the study, 165 participants were asked to play a game and fill out a questionnaire on their experiences. We found that players’ achievement goals and causal attributions were both significantly correlated to various components of player experience. Additionally, we found that achievement goals and causal attributions are significant predictors of psychological flow over and above feelings of challenge and immersion. While challenge and immersion are typical considerations when seeking to design flow experiences in games, this study suggests that game designers should also consider ways in which they may inspire particular achievement goals and causal attributions in their players. These findings highlight the connection between the learning sciences and the growing field of player experience, and we hope this paper serves as an example for future translational work.

Artificial intelligence (AI) is becoming increasingly pervasive in our everyday lives. There are consequently many common misconceptions about what AI is, what it is capable of, and how it works. Compounding the issue, opportunities to learn about AI are often limited to audiences who already have access to and knowledge about technology. Increasing access to AI in public spaces has the potential to broaden public AI literacy, and experiences involving co-creative (i.e. collaboratively creative) AI are particularly well-suited for engaging a broad range of participants. This paper explores how to design co-creative AI for public interaction spaces, drawing both on existing literature and our own experiences designing co-creative AI for public venues. It presents a set of design principles that can aid others in the development of co-creative AI for public spaces as well as guide future research agendas.

Co-creative (i.e. collaboratively creative) activities involving physical interaction are becoming more prevalent in museums as a way of promoting opportunities for exploratory learning-through-doing. However, there is still a need for new techniques for understanding how physical interaction relates to engagement and creative expression in order to both evaluate exhibits and iterate on their design. This article reports on a study of how family groups physically interact in a museum environment with a specific co-creative exhibit--TuneTable. We relate observable markers of physical interaction with stages of engagement/expression based in the literature and identify several different trajectories of participant engagement and creative expression as they navigate the exhibit. We explore what these trajectories tell us about the types of inquiry and experimentation that TuneTable supports and discuss design implications. This paper's main contribution is a deep study of how physical markers reveal trajectories of creative engagement within a specific co-creative installation.

Educators have long claimed that pedagogical content knowledge (PCK), ways of presenting a subject that make it comprehensible to others, is a critical element of student academic success. This paper presents an exploratory study finding that PCK significantly correlates with students' computer science (CS) content knowledge acquisition while teacher CS content knowledge does not. This study analyzes systemic factors comprising the theory of change for the EarSketch learning intervention including classroom- and student-level factors that contribute to shifts in students' attitudes toward computing and ultimately to students' intentions to persist in future computing endeavors and students' CS content knowledge. We present the results of a multi-level modeling analysis and offer an exploratory approach to measuring CS PCK along with recommendations to improve the sensitivity of the method.

Educators have long claimed that pedagogical content knowledge (PCK), ways of presenting a subject that make it comprehensible to others, is a critical element of student academic success. This poster presents findings from a preliminary study of Computer Science Principles teachers that demonstrate a significant correlation between teacher PCK and student content knowledge. The study describes the measures used to assess PCK, operationalizes the mechanisms for measuring teacher pedagogical content knowledge, shares the results from a multi-level modeling analysis, and identifies methodological improvements for follow-up research. The findings from this initial study show correlations of teacher PCK with student content knowledge while accounting for other teacher- and student-level variables across multiple schools.

The expansion of computer science into more classrooms invites researchers and evaluators to shift their focus from predominantly measuring student-level factors to measuring both student- and classroom-level variables. Research presented in this article uses multi-level modeling to study student-level factors within the larger context of classroom-level factors. Specifically, we analyze EarSketch, a collaborative and authentic learning tool, that introduces students to programming through music remixing, has previously been shown to increase student engagement, and increases learners' intentions to persist in computing. This article presents classroom implementation frameworks commonly used in math and science education but rarely, if ever, applied to computer science. The results from a multi-level modeling analysis show that classroom implementation correlates with students' intentions to persist in computing but may not be related to student attitudes toward computing or content knowledge acquisition. Further analysis reveals that one of the five classroom implementation factors, elaboration, emerges as the most salient. This article triangulates these results with qualitative findings from school administrators and teachers, and the article concludes by theorizing how classroom implementation frameworks may be adapted to meet the unique needs of computer science teachers, learners, researchers, evaluators, and curriculum developers.

Students who have positive attitudes towards computing are more likely to intend to persist in computing and ultimately persist in computing. Thus, this study describes the development and assessment of the Attitudes Towards Computing Scale, which was developed based on Williams et al. [20] Computer Science Attitude Survey. Assessment of the survey involved testing its reliability, dimensionality, and validity. Internal consistency reliability of the subscales and the total scale were strong. However, dimensionality tests using factor analysis did not support a five-factor structure; rather, the factor analyses suggested either using one item per subscale or mean composites of the subscales to form a total score of attitudes towards computing. This suggests there may not be meaningful differences among subscales. Tests of criterion validity show that the short-form of the scale, using a mean composite score of either one item per subscale or the composites of the subscales themselves, predict students' computing knowledge and intentions to persist just as well as using the subscales. Furthermore, an example is shown why using the subscales may be problematic due to multicollinearity issues. Recommendations for improving scales, such as not using reverse-coded items and having a sufficient number of items that differentiate between subscales, are provided. Ultimately, this study provides the computer science field with a scale of attitudes towards computing that demonstrates moderate validity and offers an example of how to assess other scales used in computer science education.

Play-in particular adult-child play---is an important component of child development. This article investigates how to design for adult-child play through Sound Happening, an interactive installation for musical play. We present a preliminary analysis of participant interactions with Sound Happening at The Children's Museum of Pittsburgh, where a total of 112 children and 53 adults interacted with the exhibit. The data from these interactions indicates that Sound Happening can facilitate both verbal parental engagement and partnered adult-child play. We highlight several features of Sound Happening that can be used as design principles for adult-child play environments. These include incorporating embodied interfaces, designing for multiple levels of engagement, and utilizing culturally recognizable interaction modalities.

This paper proposes a novel framework for real-time decisionmaking in open-ended improvised human-computer performances and a work in progress system for studying it within the Props game domain. The proposed work uses creative arcs (i.e. continuous trajectories through a dimensional space consisting of novelty, surprise and value) as a way to guide the exploration of generated candidate actions for the improvising agent to perform. This paper also describes the proposed agent's relationship to curious agents and several considerations for computationally evaluating creativity in this domain. It details the interactive installation housing the system and the architecture design (completed and planned) before concluding with a discussion of future work.

STEAM education is an approach to engage students in STEM topics by prioritizing personal expression, creativity, and aesthetics. EarSketch, a collaborative and authentic learning tool, introduces students to programming through music remixing, has previously been shown to increase student engagement, and increases learner's intentions to persist in computing. The goal of EarSketch is to broaden participation in computing through a thickly authentic learning environment that has personal and real world relevance in both computational and music domains. This article reports a quasi-experimental study suggesting that an authentic learning environment predicts increased intentions to persist via identity/belongingness and creativity. We ran a path analysis that exposed the creativity subscales, and this analysis reveals that "sharing" is the one creativity sub-construct that predicts increased intention to persist. This work makes a significant contribution to computer science education by revealing how an authentic STEAM curriculum affects student attitudes and knowledge, by presenting scales to measure authenticity and personal creativity, and by discussing how identity/belongingness may affect student success.

EarSketch is a curriculum and learning environment designed to engage diverse student populations in introductory computing courses through an approach that connects coding and computational thinking with the composition, production, and remixing of popular music. Prior studies at the high school level have shown significant impacts on student engagement and intention to persist in computing, especially for female students. This paper describes an adaptation of EarSketch for use in an introductory undergraduate-level programming course for non-majors at an open-access four-year college. The paper describes a quasi-experimental study comparing student engagement, content knowledge, and intention to persist between course sections using EarSketch and non-EarSketch flavors of the curriculum, along with a path analysis exploring factors related to student engagement and intention to persist. The findings suggest that STEAM learning interventions such as EarSketch can significantly impact gains in student content knowledge, engagement, and intention to persist across diverse undergraduate student populations.

Computational thinking skills will be important for the next generation of students. However, there is a disparity in the populations joining the field. Integrating computational thinking into artistic fields has shown to increase participation in computer science. In this paper, we present our initial design prototype for TunePad, a sound composition tablet application controlled by a block-based programming environment. TunePad is designed to introduce learners to computational thinking and to prepare them for text-based coding environments. From our preliminary testing, with children ages 7-14, we observed that our design actively engages learners and communicates how the programming blocks control the sounds being played. This testing is a prelude to more formal studies as we continue to improve the design and interface of TunePad. With this work, we intend to engage students in computational thinking who may not have otherwise been exposed, giving the opportunity to more people to enter the computer science field.

This paper describes a new technique for quantifying interaction dynamics during open-ended co-creation, such as collaborative drawing or playing pretend. We present a cognitive framework called creative sense-making. This framework synthesizes existing cognitive science theories and empirical investigations into open-ended improvisation to develop a method of quantifying cognitive states and types of interactions through time. We apply this framework to empirical studies of human collaboration (in the domain of pretend play) and AI-based systems (in the domain of collaborative drawing) to establish its validity through cross-domain application and inter-rater reliability within each domain. The creative sense-making framework described includes a qualitative coding technique, interaction coding software, and the cognitive theory behind their application.

This paper reports on the design and evaluation of LuminAI, a socially interactive art installation in which participants can engage in collaborative movement improvisation with virtual agents and other humans. LuminAI was used as a technical probe to study social interaction within interactive art at a local art gala during which over 100 participants interacted with the system. Video and interview data was gathered during the event and analyzed using thematic analysis to develop a taxonomy to guide the design of socially interactive systems involving humans and artificial agents. This taxonomy helped us identify areas where LuminAI was successful, where it needs improvement, and conceptual spaces we have yet to explore.

STEAM education is a method for driving student engagement in STEM topics through personal expression, creativity and aesthetics. EarSketch, a collaborative and authentic learning tool which introduces students to programming through music remixing, has previously been shown to enhance student engagement and intent to persist in computing. The goal of EarSketch is to broaden participation in computing through a thickly authentic learning environment that has personal and real world relevance in both computational and music domains. This mixed methods study extends previous work by 1) using a newly- developed instrument to assess creativity and 2) testing a theory of change model that provides an explanatory framework for increasing student engagement in STEAM. The results suggest that students who used EarSketch express statistically significant gains in computing attitudes and creativity. Furthermore, a series of multiple regression analyses found that a creative learning environment, fueled by a meaningful and personally relevant EarSketch curriculum, drives improvements in students' attitudes and intent to persist in computing. This work makes a significant contribution to computer science education by establishing the effectiveness of an authentic STEAM curriculum and advancing our knowledge of the underlying mechanisms driving students' motivations to persist in STEM disciplines.

Participants of the session will discover EarSketch (https://earsketch.gatech.edu), a free, web-based learning environment that teaches introductory computer science through music. It aligns with Computer Science Principles and has been used in a variety of other educational contexts as well, ranging from late elementary through College. EarSketch provides an in-depth introduction to computer science and programming through composing, producing, and remixing music with Python and JavaScript code. No previous knowledge or experience in music, Python, or JavaScript is required to begin learning or teaching with EarSketch. Results from pilot studies show that EarSketch facilitates student learning about computation and improves student engagement in computing through parameters such as self-confidence, motivation, or intent to persist. This trend is particularly true for female and minority students, who are underrepresented today in US computer science classrooms. EarSketch comprises a curriculum, teacher materials, a coding environment, a DAW (Digital Audio Workstation), a sound database, and sharing tools. Fundamental computing concepts are introduced through curricular modules that teach how to place sounds, create rhythms, and manipulate effects, with a focus on popular genres such as hip hop and dubstep. The platform has over 77,000 users in computer science classrooms across the US and internationally. EarSketch receives funding from the National Science Foundation, the Scott Hudgens Family Foundation, the Arthur M. Blank Family Foundation, and the Google Inc. Fund of Tides Foundation.

In this paper we present a preliminary design and initial assessment of a computational musical tabletop exhibit for children and teenagers at the Museum of Design Atlanta (MODA). We explore how participatory workshops can promote hands-on learning of computational concepts through making music. We also use a hands-on approach to assess informal learning based on maker interviews. Maker interviews serve to subjectively capture impromptu reflections of the visitors' achievements from casual interactions with the exhibit. Findings from our workshops and preliminary assessment indicate that experiencing and taking ownership of tangible programming on a musical tabletop is related to: ownership of failure, ownership through collaboration, ownership of the design, and ownership of code. Overall, this work suggests how to better support ownership of computational concepts in tangible programming, which can inform how to design self-learning experiences at the museum, and future trajectories between the museum and the school or home.

This article describes a new technique for quantifying creative collaboration and applies it to the user study evaluation of a co-creative drawing agent. We present a cognitive framework called creative sense-making that provides a new method to visualize and quantify the interaction dynamics of creative collaboration, for example, the rhythm of interaction, style of turn taking, and the manner in which participants are mutually making sense of a situation. The creative sense-making framework includes a qualitative coding technique, interaction coding software, an analysis method, and the cognitive theory behind these applications. This framework and analysis method are applied to empirical studies of the Drawing Apprentice collaborative sketching system to compare human collaboration with a co-creative AI agent vs. a Wizard of Oz setup. The analysis demonstrates how the proposed technique can be used to analyze interaction data using continuous functions (e.g., integrations and moving averages) to measure and evaluate how collaborations unfold through time.

This paper reports on the design and evaluation of a co-creative drawing partner called the Drawing Apprentice, which was designed to improvise and collaborate on abstract sketches with users in real time. The system qualifies as a new genre of creative technologies termed "casual creators" that are meant to creatively engage users and provide enjoyable creative experiences rather than necessarily helping users make a higher quality creative product. We introduce the conceptual framework of participatory sense-making and describe how it can help model and understand open-ended collaboration. We report the results of a user study comparing human-human collaboration to human-computer collaboration using the Drawing Apprentice system. Based on insights from the user study, we present a set of design recommendations for co-creative agents.

This paper proposes a new formal approach for negotiating shared mental models between humans and computational improvisational agents (improv agents) based on our sociocognitive studies of human improvisers. Negotiation of shared mental models serves as a core mechanism for improv agents to co-create stories with each other and with human interactors. The model aims to narrow the gap between human and machine intelligence by providing AI agents that, in the presence of incomplete knowledge about an improv scene, can use procedural representations not only to understand human parties but also to negotiate their mental models with them. The described approach allows flexible modeling of ambiguous, non-Boolean knowledge through the use of fuzzy logic and situation calculus that allows reasoning under uncertainty in a dynamic improvisational setting.

This article presents EarSketch, a learning environment that combines computer programming with sample-based music production to create a computational remixing environment for learning introductory computing concepts. EarSketch has been employed in both formal and informal settings, yielding significant positive results in student content knowledge and attitudes toward computing as a discipline, especially in ethnic and gender populations that are currently underrepresented in computing fields. This article describes the rationale and components of EarSketch, the evaluation design, and lessons learned to apply to future environment design and development.

This paper presents the result of an empirical study of 32 adult dyads (i.e. groups of two people) engaged in pretend play. Our analysis indicates that participatory sense-making plays a key role in the success of pretend play sessions. We use the cognitive science theory of enaction as a theoretical lens to analyze the empirical data given its robust conceptual framework for describing participatory sense-making. We present here five enactive characteristics of pretend play that appear to be necessary and sufficient for the emergence and maintenance of successful pretend play -- mental preparation, meaning building, narrative enaction, narrative deepening, and flow maintenance. This enactive formalization is used to propose a computational model of pretend play that can be used to design an agent capable of playing in real time with human users.

This paper describes a co-creative web-based drawing application called the Drawing Apprentice. This system collaborates with users in real time abstract drawing. We describe the theory, interaction design, and user experience of the Drawing Apprentice system. We evaluate the system with formative user studies and expert evaluations from a juried art competition in which a Drawing Apprentice submission won the code-based art category.

The Viewpoints AI installation attempts to create an interactive movement-based art experience that has minimal predefined instantial content. As opposed to focusing on designer-created content that reflects their specific view of an interactive experience, we have instead created a movement-based play space where interactors can freely dance with a virtual AI-based character named VAI, teaching it as they interact. VAI analyses interactor movements through procedural representations of the Viewpoints movement theory (from theatre and dance) and improvises responses as an equal collaborator from its past experience with people. VAI uses this procedurally and experientially realized content to present an engaging movement-based experience that any audience member can walk up to and immediately begin dancing with. The Viewpoints AI installation uses shadow theatre as inspiration for creating a liminal space for the projected AI character and an interactor's shadow to co-exist within a real / virtual space. Interactors step in front of a spotlight that projects their shadow onto a large muslin screen. VAI is also projected onto that same space. Viewpoints AI, thus builds on ancient and new media forms, creating an experience that is a playful - but coherent - expression between both the interactor and VAI.

EarSketch (http://earsketch.gatech.edu) is a free integrated curriculum, software toolset, audio loop library, and social sharing site that teaches computing principles through digital music composition and remixing. EarSketch students write code in either Python or JavaScript to make music, with a focus on popular genres such as hip hop and dubstep, while learning computing concepts such as variables, iteration, conditionals, strings, lists, functions, and recursion. Attendees to this demonstration session will be introduced to a new web-based version of EarSketch that integrates a code editor, digital audio workstation (DAW) music production interface, curriculum browser, and sharing service into a single integrated browser-based learning environment. This demo is of interest to secondary and early post secondary CS educators and to computing education researchers interested in STEAM and/or broadening participation. No prior musical knowledge or experience is expected and no prior programming experience with Python or JavaScript is required.

EarSketch (http://earsketch.gatech.edu) is an integrated curriculum, software toolset, audio loop library, and social sharing site that teaches computing principles through digital music composition and remixing. Attendees will learn to code in Python and/or JavaScript to place audio clips, create rhythms, and add and control effects within a multi-track digital audio workstation (DAW) environment while learning computing concepts such as variables, iteration, conditionals, strings, lists, functions, and recursion. Participants write code to make music, with a focus on popular genres such as hip hop. The agenda outlines the pedagogy of connecting musical expression to computation to broaden participation and engagement in computing; the underlying concept of thickly authentic STEAM that drives this approach; the alignment of the curriculum and learning environment with CS Principles; and basic musical concepts underlying EarSketch. The intended audience for this workshop is secondary and early post secondary CS educators. The course is of particular relevance to CS Principles teachers but also applicable to any introductory programming or computing course. No prior musical knowledge or experience is expected and no prior programming experience with Python or JavaScript is required.

In this paper, we describe a pilot study of EarSketch, a computational remixing approach to introductory computer science, in a formal academic computing course at the high school level. The EarSketch project provides an integrated curriculum, Python API, digital audio workstation (DAW), audio loop library, and social sharing site. The goal for EarSketch is to broaden participation in computing, particularly by traditionally underrepresented groups, through a thickly authentic learning environment that has personal and industry relevance in both computational and artistic domains. The pilot results show statistically significant gains in computing attitudes across multiple constructs, with particularly strong results for female and minority participants.

Our work has focused on how to create a learning experience that is highly personally motivating for students, has a low barrier of entry for creation an artistic computational artifact, and is scalable for use in formal and informal education settings at the national level. We have created a learning environment called EarSketch that addresses student engagement through a STEAM learning experience that provides authentic learning in both the technical (i.e. computing) and artistic domains (i.e. music remixing). EarSketch is an integrated curriculum, software toolset, audio loop library, and social sharing site that teaches computing principles through digital music composition and remixing. Attendees will use Python to place audio clips, create rhythms, and add and control effects to a multi-track digital audio workstation (DAW) while learning computing concepts such as variables, iteration, conditionals, strings, lists, and functions. Participants write code to make music, with a focus on popular genres such as hip hop. The agenda outlines the pedagogy of connecting musical expression to computation. EarSketch has been used in introductory computing summer camps, secondary school classes, and is currently working towards integration with CS Principles pilot programs. All participants will need a laptop for running the EarSketch software. EarSketch will run on OSX and Windows laptops. Participants will also need headphones for listening to projects created using EarSketch. It is highly suggested that participants download the EarSketch installer at http://earsketch.gatech.edu/downloads and install the software prior to the workshop.

In this paper, we describe EarSketch, an integrated curriculum, software toolset, and social media website, grounded in constructionist principles, that targets introductory high school computing education. We hypothesize that the use of collaborative computational music composition and remixing may avoid some of the engagement and culture-specific issues that other approaches, both in music and other media, have had. We discuss the design of EarSketch, its use in a pilot summer camp, and the evaluation results from that pilot.

This article presents our currents findings from an empirical study of the cognition employed by performers in improvisational theatre. Improvised theatrical performance is an activity in which one or more individuals create a dramatic or comedic performance in real-time and is an interesting example of creative, real-time, collaborative problem solving. Unlike other forms of creative problem solving, improvisers are constrained from explicitly coordinating with the other improvisers on stage or revising their decisions after the fact. This article focuses on the means by which a group of improvisers converge on a shared understanding (i.e. a shared mental model) of what a scene is about and how it should proceed. We present our findings on how improvisers build shared mental models during a performance and discuss our applications of these findings to the design and development of improvisational intelligent agents.

We address the problem of building computational agents that are capable of play. Existing research has examined the forms, characteristics, and processes involved in various kinds of play at a high level. However, this research does not provide a unified framework at a level of detail sufficient for building computational agents that can play. As a step toward addressing this gap we synthesize diverse research on pretend play to recognize important components of pretend play agents. We also develop a formal model of one key component of pretend play, pretend object play, and present a computational implementation of this model. Our work provides initial criteria for the content and processes necessary for pretend play agents.

This paper presents an educational system that models global climate change research in a problem-based learning (PBL) framework. Paleoclimate Clues is a web-based application that will engage high school science teachers in generating and analyzing climate data from coral fossils. The design of Paleoclimate Clues aims to engage learners not only in NASA-related climate change data, but in the process of how that data is collected, analyzed, used to make conclusions about changing climate, and with what level of uncertainty, all embedded in a PBL educational framework.

People are ready to change themselves to adopt more eco-friendly habits such as conserving electricity when they are aware of the possible problems of their lifestyle. In this sense, ambient display, which users experience occasionally without its interfering with their primary tasks, is well suited to provide the feedback of their personal activities in a more subtle manner than direct information presentation. We present the results of user studies with two ambient displays in different visualization styles. Participants showed diverse usage behaviors of ambient displays according to their motivational level of sustainable lifestyle. In addition, iconic metaphor of eco-visualization can trigger more emotional attachment while indexical representation helps retrospective functions. Finally, we suggest design requirements for ambient displays that support different stages of persuasion from raising awareness to motivating to change behaviors and to maintaining desired habits.

For decades designers have used theatre metaphors to describe design methodologies and have used performance techniques to enhance the design process, two of which are improvisational acting and role-playing. Unfortunately, most design literature does not differentiate between these two practices even while using them in combination with various design methods. This paper discusses how improvisation and role-playing have been employed during the design process and why they are distinct from one another. The authors draw upon their current research involving improvisational acting and compare it with other role-playing research which examines role-playing from both a serious and entertainment angle. They conclude through this comparison that both performance techniques have their place in the design process and that more informed definitions of each technique can aid designers in deciding which technique's properties will benefit them the most.

This paper presents preliminary findings from our empirical study of the cognition employed by performers in improvisational theatre. Our study has been conducted in a laboratory setting with local improvisers. Participants performed predesigned improv "games", which were videotaped and shown to each individual participant for a retrospective protocol collection. The participants were then shown the video again as a group to elicit data on group dynamics, misunderstandings, etc. This paper presents our initial findings that we have built based on our initial analysis of the data and highlights details of interest.

Believable agents usually depend upon explicit, model-based simulations of human emotions. This work appeals instead to the sensibilities of dramatic acting to create agents that are believable. The chosen task is that of comedy improvisation as it provides a solid demonstration of the agents' believability in the context of a high-level deliberative goal. Furthermore, this work employs physical robots as the actors, employing the real-time sensor values from the robots as inputs into the acting process. This paper describes the dramatic approach to acting that we used and describes the Java-based implementation on two Nomad Scout robots. Actual, improvised scripts created by the robots are included and analyzed.