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.

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.

Science undergraduate students benefit from gaining computing skills due to the growing overlap between scientific discovery and computational methods. One approach is to encourage students majoring in science to pursue a computing minor; however, only a few seem to undertake this endeavor. Financially disadvantaged students face additional barriers that may further deter them from this pursuit. Unfortunately, there is limited research on the benefits, limitations, and barriers related to earning a computing minor. This study aims to explore the perspectives of undergraduate college students from the United States in a scholarship program designed to aid low-income science majors in completing an information science and technology (IS&T) minor. Using an exploratory qualitative research approach, semi-structured interviews were conducted with seven students in a scholarship program. Based on the findings, three main recommendations for program stakeholders are proposed. First, explicitly explain the unique advantages of gaining computing knowledge for science majors. Second, ensure students have a foundational understanding of computing and related study skills. Third, guide students in strategically planning their course sequence to optimize their time and workload.

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.

With the increasing prevalence of large language models (LLMs) such as ChatGPT, there is a growing need to integrate natural language processing (NLP) into K-12 education to better prepare young learners for the future AI landscape. NLP, a sub-field of AI that serves as the foundation of LLMs and many advanced AI applications, holds the potential to enrich learning in core subjects in K-12 classrooms. In this experience report, we present our efforts to integrate NLP into science classrooms with 98 middle school students across two US states, aiming to increase students' experience and engagement with NLP models through textual data analyses and visualizations. We designed learning activities, developed an NLP-based interactive visualization platform, and facilitated classroom learning in close collaboration with middle school science teachers. This experience report aims to contribute to the growing body of work on integrating NLP into K-12 education by providing insights and practical guidelines for practitioners, researchers, and curriculum designers.

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.

Multi-pronged programs that involve students in a combination of proven interventions (i.e., tutoring other students, building community, developing skills, etc.) constitute one pedagogical approach to increasing the number and diversity of computing professionals. In this manuscript, we evaluate the efficacy of one such multi-pronged program, the STARS Computing Corps, a Broadening Participation in Computing Alliance program funded by the National Science Foundation. These analyses improve upon previous efforts to assess the efficacy of STARS by examining dosage effects of the program, adding controls for students' initial intentions to pursue computing, and conducting these analyses at various points in a student's participation in STARS. We also conduct analyses to determine the efficacy of various STARS activities. Controlling for students' initial intentions to persist in computing, we find robust evidence that spending more time each week on STARS' activities positively predicts students' intentions to persist in a computing career, and that STARS has a heightened positive impact on Black and Hispanic students. We do not find evidence that the number of semesters a student spends in STARS is predictive of computing persistence, nor do we find differences in the efficacy of various STARS activities. In sum, these results suggest that STARS has a positive impact on students' intentions to persist in computing and that multi-pronged programs like STARS should focus on the intensity of participation (as opposed to the length of participation or a particular activity) to increase students' desire to persist in computing careers.

As artificial intelligence permeates our lives through various tools and services, there is an increasing need to consider how to teach young learners about AI in a relevant and engaging way. One way to do so is to leverage familiar and pervasive technologies such as conversational AIs. By learning about conversational AIs, learners are introduced to AI concepts such as computers’ perception of natural language, the need for training datasets, and the design of AI-human interactions. In this experience report, we describe a summer camp curriculum designed for middle school learners composed of general AI lessons, unplugged activities, conversational AI lessons, and project activities in which the campers develop their own conversational agents. The results show that this summer camp experience fostered significant increases in learners’ ability beliefs, willingness to share their learning experience, and intent to persist in AI learning. We conclude with a discussion of how conversational AI can be used as an entry point to K-12 AI education.

The ubiquity of AI-based conversational apps such as Siri, Alexa and Google Assistant means more young users are interacting with these apps. The increasing popularity of these conversational applications brings a potential opportunity to attract learners to AI, CS and STEM fields. CS Education researchers need to explore how to leverage this opportunity, in particular to serve learners who are underrepresented in CS and STEM. This experience report describes the design and iterative refinement of a series of two-week summer camps in which 62 predominantly Black students participated in hands-on AI-based learning experiences to design and develop their own conversational AI apps. We discuss the organization of this summer camp experience, including strategies for recruiting from and building trust within the target community, designing professional development for camp facilitators, structuring the camp activities, and encouraging projects that are personally and socially relevant. We share challenges and lessons learned from this AI summer camp in the hopes that they will inform other researchers and practitioners who are interested in designing and deploying similar experiences.

Effective professional learning communities (PLCs) are important in supporting teacher learning. This study investigated computer science (CS) teacher leaders' perspectives on the lessons and the challenges in supporting CS teachers through local PLCs. We purposefully selected ten CSTA chapters and conducted focus group interviews with the chapter leaders between 2020 and 2022. Our findings indicated that these PLCs offered social-emotional support, continual networking opportunities, and rich professional learning resources. Also, they amplified teachers' voices and supported CS teachers' professional identity building. To engage CS teachers, the teacher leaders built trust, collaborated with other PLCs or organizations, and set an inclusive PLC culture. These PLCs had challenges in recruitment, leadership development and transition and building group identity.

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.

Motivation: Recent efforts to expand K-12 computer science education highlight the great need for well-prepared computer science (CS) teachers. Teacher identity theory offers a particular conceptual lens for us to understand computer science teacher preparation and professional development. The emerging literature suggests that teacher identity is central to sustaining motivation, efficacy, job satisfaction, and commitment, and these attributes are crucial in determining teacher retention. While the benefits associated with a strong sense of teacher identity are great, teachers face unique challenges and tensions in developing their professional identity for teaching computer science.

This paper reports a study of CSTA chapter leaders' percep-tions of their chapter's roles in supporting computer science (CS) teachers. Intent on understanding the impact of member-ship in a professional organization on the development of teacher professional identity, our research revealed that in the chapter leaders' perceptions local CSTA chapters had an im-portant role in supporting the development of their mem-bers' professional identity as a CS teacher.

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.

Current efforts to expand K-12 CS education highlight the great need of well-prepared CS teachers with a strong sense of professional identity. This study proposes the CS teacher identity scale, a quantitative instrument for measuring CS teachers' sense of professional identity. The survey was piloted through a national teacher survey and tested for its reliability, dimensionality, and validity. The analysis reveals a four-factor solution for the CS teacher identity scale.

A number of computing departments have adapted studio-based pedagogy for teaching Human-Computer Interaction (HCI) to help students develop creative design skills. These efforts have shown promise, however, some challenges that emerge when integrating studio-based pedagogy into computing programs have been neglected by researchers. This research focuses on these challenges in the implementation and evaluation of a studio-based approach integrated into three HCI-related courses. This study is based on 6 classes, 44 interviews with students, observations, and interviews with members of the teaching team. Findings supported many positive outcomes from previous studio-based implementations. Nevertheless, students felt the change in pedagogy frustrating and it may have hindered their creativity, motivation, and engagement. This paper highlights these conflicting narratives, comparing computing culture with studio-based pedagogy. We conclude with considerations for future implementations.

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.

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.

In an effort to evaluate computer science education using more modern, automated data science techniques, we consider Hattie's work in Visible Learning then define a comprehensive framework to provide the capability to automatically generate a quantitative meta-analysis using predefined moderators (e.g., age, grade, etc.) with data derived from multiple individual research studies. To define the initial criteria, we developed a list of critical questions that the framework must address, including what moderators are most important to include, how to address homogeneity across various studies, how to define categories of influencing factors, and how to compute summary effect size. This initial framework describes how the meta-analysis is derived from effect sizes that are calculated based on each mean and standard deviation reported in experimental and quasi-experimental studies. Since the goal of this foundational research is to create an auto-generated meta-analysis tool, we define a basic user experience that would allow users to select moderators and predefined levels of heterogeneity (such as "include only random control group studies" or "include studies reported in journal articles") for inclusion in the meta-analysis. We conducted a feasibility study of the framework using data (number of participants, mean, standard deviation) collected from 21 data samples curated from eight computer science education articles with a primary and secondary focus across ten venues (2012-2018). We consider what we learned conducting the study, including the need for full system transparency, issues related to data integrity, and issues related to defining and selecting appropriate formulas for differing sets of data.

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.

A growing body of evidence indicates that there is a deep effect of noncognitive factors on academic achievement and learning. In this study, we analyzed a set of 31 evaluation instruments designed to measure noncognitive constructs (e.g., self-efficacy, confidence, motivation) within computing education. Using the Lee and Shute framework, we assigned each of the 115 unique constructs found in the instruments into one of the four components (Student Engagement, Learning Strategies, School Climate, Social-familial Influences) and their subcomponents to determine which constructs are most frequently measured. We found that the majority of constructs were designed to measure Student Engagement (Affect and Cognition) and School Climate (Teacher Variables). Constructs measuring Learning Strategies and Social-Familial Influences (e.g., homework strategies, peer influences) occur the least. This study may enable further discussions of what noncognitive factors are/are not currently being measured within the computing education community.

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.

Efforts to improve and promote CS education characterized by greater participation of underrepresented groups have taken off sharply in the six years since the Expanding Computing Education Pathways (ECEP) NSF alliance was first funded. Though many of these initiatives are occurring at the student and teacher level, ECEP and other national-level organizations have demonstrated the importance of focusing on change at the state level, as this can have important, long-term implications on policy and infrastructure. This poster describes ECEP's emergent design as a backbone organization helping state-level teams achieve educational change around CS. It also highlights key lessons learned through the alliance about how to foster CS education change at the state level. Four key lessons stand out. 1) The importance of understanding that engaging states requires appreciating the commonality of a framework around key areas to change (such as state standards, teacher certification and graduation requirements) but also respecting the uniqueness of state circumstances in these change areas. 2) The shared value created through a collective impact model to build a community that can support rich discussion and sharing of ideas. 3) The utility of an empirically derived a 4-stage model of state change used by ECEP that emphasized defining leaders, understanding the CS education landscape and finding allies to support efforts. and 4) The role of state team structures that can facilitate change when they are guided by identifying and engaging key stakeholders within a state and giving them a voice in driving the strategies and plans.

Over the last few years, a number of repositories of information relevant to the computing education community have come online, each with different content and purpose. In this special session, we present an overview of these repositories and the content that each provides. Demonstrations of the functionality of the repositories will be shown and attendees are encouraged to come with their questions and suggestions for improvement if they are currently users of the repositories.

Rise Up 4 CS was created at Georgia Tech in the spring of 2013 to help African American students succeed in their Advanced Placement (AP) Computer Science A (CSA) high school course and on the exam. The AP CSA course is intended to be equivalent to a college level CS1 course. In the fall of 2014, Sisters Rise Up 4 CS was also created to help female students succeed. Rise Up (RU) and Sisters Rise Up (SRU) both offer remote and in-person help sessions led by undergraduate students, who serve as near-peer role models. The long-term goal of these projects is to attract more underrepresented students to computing careers by increasing their self-efficacy. Self-efficacy is the belief that one can succeed in a particular task or field. Thanks to generous support from Google, RU and SRU have been offered at several other colleges and universities as well. This paper summarizes the results from spring 2013 to summer 2016, reports on an alumni survey answered by 68 (32%) of the 211 alumni, and includes excerpts from five semi-structured interviews. The majority (63%) of the alumni survey respondents, who are in college, are majoring in computing. A similar percentage of the alumni who are still in high school intend to major in computing (62%). When asked about the programs' impact on their career choices and interest in computing, 61% of respondents indicated that the program increased their interest in computer science and 24% indicated that it changed their career plans to computing.

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.

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.

Educational Robotics for Absolute Beginners is a MOOC designed to introduce K-12 teachers with no prior computer science or robotics experience to the basics of LEGO NXT Robot programming. The course was developed following several successful in-person workshops on the same topic. This paper introduces some of the issues that arose as we transitioned the material to a MOOC, describes some of the unique challenges we faced by incorporating specialized hardware into a MOOC, and presents some preliminary data evaluating the success of our approach.

This paper describes Project Rise Up 4 CS, an attempt to increase the number of Black students in Georgia that pass the Advanced Placement (AP) Computer Science (CS) A exam. In 2012 Black students had the lowest pass rates on the AP CS A exam both in Georgia and nationally. Project Rise Up 4 CS provided Black students with role models, hands-on learning, competitions, a financial incentive, and webinars on AP CS A content. The first cohort started in January of 2013 and finished in May 2013. Of the 27 students who enrolled in the first cohort, 14 met all of the completion requirements, and 9 (69%) of the 13 who took the exam passed. For comparison, in 2012 only 22 (16%) of 137 Black students passed the exam in Georgia. In 2013, 28 (22%) of 129 Black students passed the exam in Georgia. This was the highest number of Black students to pass the AP CS A exam ever in Georgia and a 27% increase from 2012. In addition, students who met the completion requirements for Project Rise Up 4 CS exhibited statistically significant changes in attitudes towards computing and also demonstrated significant learning gains. This paper discusses the motivation for the project, provides project details, presents the evaluation results, and future plans.

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.

Few question the need to offer excellent programs in computer science at the Bachelors and Graduate Levels. But computer science is not just for computer scientists! An understanding of key computer science concepts is essential to comprehending the underpinnings of what drives much of the culture and environment that students will encounter upon graduation. Unfortunately, in the United States most state, regional, and national K-12 standards do not include computer science among the core competencies required of all students. However, careful study reveals many opportunities to satisfy mandatory non-computer-science standards while simultaneously teaching important concepts in computer science. This paper begins with an overview of these standards and suggests that educational robotics could be incorporated into K-12 curricula to satisfy these standards.

Georgia Computes! ( GaComputes ) was a six-year (2006--2012) project to improve computing education across the state of Georgia in the United States, funded by the National Science Foundation. The goal of GaComputes was to broaden participation in computing and especially to engage more members of underrepresented groups which includes women, African Americans, and Hispanics. GaComputes’ interventions were multi-faceted and broad: summer camps and after-school/weekend programs for 4th--12th grade students, professional development for secondary teachers, and professional development for post-secondary instructors faculty. All of the efforts were carefully evaluated by an external team (led by the third and fourth authors), which provides us with an unusually detailed view into a computing education intervention across a region (about 59K square miles, about 9.9 million residents). Our dataset includes evaluations from over 2,000 students who attended after-school or weekend workshops, over 500 secondary school teachers who attended professional development, 120 post-secondary teachers who attended professional development, and over 2,000 students who attended a summer day (non-residential) camp. GaComputes evaluations provide insight into details of interventions and into influences on student motivation and learning. In this article, we describe the results of these evaluations and describe how GaComputes broadened participation in computing in Georgia through both direct interventions and indirect support of other projects.

We report on the implementation and evaluation of a three-year program to increase interest in studying computer science (CS) among African American male high school students. Over the course of 3 years, the Glitch Game Tester (Glitch) program employed 25 African American male high school students. These students tested pre-release digital games, full-time in the summer and part-time in the school year, with an hour of each day dedicated to learning introductory CS. Initially, only 20% of our participants expressed interest in pursing computing as a career. After Glitch, 65% have pursued some form of post-secondary computing studies. These outcomes, and the participants' enthusiasm for engaging in computing, are in sharp contrast to the crisis in African American male education and learning motivation. The research presented in this report discusses lessons learned through implementation of the Glitch program and higher education outcomes after graduation from the program.

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.

In computing education, we have only just started developing methods for accurately measuring a student's understanding of introductory computing, let alone characterizing a whole classroom, school, or university system. As part of evaluating the impact of "Georgia Computes!" we sought an understanding the factors influencing undergraduate enrollment in introductory computing for an entire state in the United States of America. We gathered surveys from over 1400 undergraduate students in introductory computing classes from 19 higher-education institutions in a single state. The analysis provided insight into the impact of "Georgia Computes!", into the connections between stages of the computing education pathways, and how factors that influence students' pursuit of computing differ between genders and majority/minority group students.

universities. But, it is not enough to offer computing summer camps and hope that students like them. The camps should be effective by some measure, such as broadening participation by underrepresented groups and/or increasing learning. Summer camps should also be financially sustainable, so that institutions can continue to offer them regularly. The summer camps at Georgia Tech have become effective and financially sustainable. This paper presents the rationale for our camps, the evaluation results that demonstrate positive attitude changes and increases in learning, and the business model that makes them financially sustainable. It also reports on the evaluation results from seven other colleges and universities in Georgia that offered computing summer camps during the summer of 2011 with assistance from Georgia Tech.

The National Center for Women & Information Technology (NCWIT) Extension Services for Undergraduate Programs (ES-UP) has created a large group of trained consultants (ESCs) and clients who are passionate about women's participation in computing. This panel will describe how our ESCs and clients have worked together to effect change and will show outcomes from our activities over the past three years.

Many young African American males have a passion for video games, but they don't often translate that passion into learning about computing. Part of the problem is that they do not identify with computing as a social norm within their peer group. This disidentification with computing can negatively impact academic performance and limit opportunities for upward mobility. We developed a job training program called Glitch Game Testers in which young African American men are trained to 'Sbreak open the black box' of their game consoles to learn about computing. Perceptions of peers' technical competency were measured before and after the summer 2010 program. Results showed that participants were more likely to view their peers as technical resources and their overall access to technical resources increased. Broader implications for motivating technology adoption in HCI are discussed.

This paper presents the findings of an exploratory, qualitative study revealing computing instructors' experience in adopting curriculum innovations. We interviewed eight instructors a year after they attended workshops on several innovative introductory Computer Science (intro CS) courses at undergraduate level. The interview was designed to elicit the extent to which instructors had adopted or adapted what they learned from the workshops, and what drove or prevented their efforts to make curriculum change. The results of this study reveal that the adoption and adaptation of computing curriculum innovations in new situations may involve systemic change affecting instructors, departments and institutions as a whole. The findings of this study suggest a list of questions that a computing instructor might ask before committing to a new innovation. We also consider implications of this study for disseminating computing education innovations.

Computing education suffers from low enrollment and a lack of diversity. Both of these problems require changes across the entire computing education pipeline. The "Georgia Computes!" alliance, funded by the National Science Foundation's Broadening Participation in Computing program, seeks to improve the computing education pipeline in Georgia. "Georgia Computes!" is having a measurable effect at each stage of the pipeline, but has not yet shown an impact across the whole pipeline.