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.

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 poster presents the development and implementation of a 10-day remix-based summer camp curriculum designed to introduce high school students, particularly a multinational cohort of young women, to programming through creative coding. The curriculum integrates music composition using EarSketch and web development with HTML and CSS. The camp aims to inspire participants to gain self-efficacy in programming and motivate them to explore STEM/computing careers. Preliminary results from surveys and interviews indicate increased confidence in programming skills. This ongoing research explores the impact of remixing as a gateway for transitioning into more general-purpose computing domains such as web development.

To engage diverse populations of students who may not self-select into computing courses, a curriculum for a middle school music technology + computer science course that addresses learning standards for both subjects was developed and deployed. Students who engage with the curriculum learn modern music production techniques and computational thinking concepts. This is through a mix of traditional approaches to music technology education (digital audio workstations) and computational approaches via a culturally relevant learning platform that introduces students to coding through music production and remixing. This poster reflects on the last two years of curriculum design and deployment, teacher training, and student and educator engagement and feedback to provide insight into the teaching (and learning) of computational thinking in the music technology classroom.

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.

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.

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.

This paper explores some of the challenges posed by automated grading of programming assignments in a STEAM (Science, Technology, Engineering, Art, and Math) based curriculum, as well as how these challenges are addressed in the automatic grading processes used in EarSketch, a music-based educational programming environment developed at Georgia Tech. This work-in-progress paper reviews common strategies for grading programming assignments at scale and discusses how they are combined in EarSketch to evaluate open ended STEAM-focused assignments.

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.

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 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.

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 statement describes LOLC, a text-based collaborative music improvisation environment for laptop ensemble developed at Georgia Tech and presented in performance by the authors at the Creativity and Cognition conference.

This paper discusses LOLC, a text-based collaborative music improvisation system for laptop ensemble developed by the authors. The paper evaluates LOLC in the context of a recent performance by professional classical musicians with minimal computer experience. Using qualitative data from interviews with the performers and quantitative data from server logs, the paper considers the degree to which LOLC facilitated collaborative improvisation among the musicians and the degree to which LOLC was accessible to non-programmers to learn and perform.

Graph Theory links the creative music-making activities of web site visitors to the dynamic generation of an instrumental score for solo violin. Participants use a web-based interface to navigate among short, looping musical fragments to create their own unique path through the open-form composition. Before each concert performance, the violinist prints out a new copy of the score that orders the fragments based on the decisions made by web visitors.

N.A.G. (Network Auralization for Gnutella) is interactive software art designed to actively involve a lay public without musical training in a creative musical experience. Users enter search keywords, and the software looks for matching music files on the Gnutella peer-to-peer file-sharing network. As it downloads music, it plays an audio collage whose structure is based on the relative download rates of the files.

Auracle is a networked sound instrument controlled by the voice. Users jam together over the Internet using only a microphone. Throughout the development process, the authors experimented with different approaches to interpreting vocal input and facilitating user interaction. This paper outlines some of the tools used to implement and evaluate those ideas, simulate the wide range of activities of Auracle users, and facilitate the development process.