As data science (DS) grows in importance across disciplines, its integration into K-12 education remains fragmented, especially when the high school curricula are already packed. Embedding DS within existing computer science (CS) courses offers a practical solution by leveraging overlapping skills and content. To make the case for DS in CS classrooms, an important step is to examine how DS fits into the landscape of CS education through educational standards. This study explores the extent to which core high school DS topics align with the Computer Science Teachers Association (CSTA) standards, a widely adopted framework guiding K-12 CS education in the U.S. We conducted a qualitative document analysis comparing the high school CSTA standards to 61 DS subtopics synthesized from leading DS curricula and frameworks. Two researchers independently coded each pair of CSTA standard and DS subtopic for explicit or implicit connections, resolving discrepancies through consensus. To visualize alignment patterns, we developed an interactive Sankey diagram that maps the connection between the two frameworks. Our findings show that 16 of 17 DS topics align with at least one CSTA standard, primarily within the ''Data & Analysis'' and ''Algorithms & Programming'' concept areas. However, alignment often relies on broad or open-ended standards that flatten distinctions between DS practices at various level. Meanwhile, critical DS areas such as machine learning remain unaddressed. This analysis reveals both the promise and limitations of embedding DS in CS classrooms, informing future efforts to integrate DS meaningfully in K–12 education through standards-based curriculum design.

The emergence of Generative Artificial Intelligence (GenAI) tools broadly, and Large Language Models (LLMs) specifically, are equipping introductory programming instructors with a whole new class of pedagogical tools. While GenAI certainly poses threats to time-honored instructional techniques, it also provides opportunities for new forms of instructional support. In this work, we introduce our strategy for configuring an LLM to serve as a ''rubber duck debugging'' coding assistant to help novice programmers when they encounter difficulties in programming assignments. The key contribution of this work is not in the idea of using LLMs for debugging itself (which has already been demonstrated elsewhere, e.g., [3]) but to demonstrate the ease, flexibility, and pedagogical potential of the strategy. In particular, through carefully crafted prompts and easily accessible platforms, rubber duck LLMs can assist learners with specific questions while also situating those questions alongside larger computer science concepts and computational thinking practices. This work contributes an easily replicated and model-agnostic instructional strategy that productively and responsibly leverages the power of LLMs to assist novice programmers in developing foundational programming skills.

Data science education has gained momentum in recent years. Along with the development of curricula to teach data science, the number and diversity of tools for introducing data science to learners are also multiplying. The tools used to teach data science play a central role in shaping the learning experience. Therefore, it is important to carefully choose which tools to use to introduce learners to data science. This article presents a systematic analysis of 30 data science tools that are, or designed to be, used in introductory data science education for K-12 students. The identified tools list includes spreadsheets, visual analysis tools, and scripting environments. For each tool, we examine facets of its capabilities, interactions, educational support, and accessibility. For block-based programming tools, we also examine the data science functionalities available in that tool’s blocks. This paper advances our understanding of the current state of introductory data science environments and highlights opportunities for creating new tools to better prepare learners to navigate the data-rich world surrounding them.

This paper presents a pilot study of an interest-driven data science curriculum for high school students. The curriculum uses authentic and meaningful data exploration activities to situate data science in students' lived experiences. The curriculum aims to lay the computational foundation of data science and equip students with the necessary skills and practices to become informed and active citizens in our data-driven world. The pilot study, conducted in two sections of a computer science class, demonstrates the curriculum's inquiry-based approach, which allows students to formulate questions based on their interests and answer them by manipulating publicly available datasets. The study illustrates how a block-based learning environment and API data retrieval can be harnessed to support data science learning activities that situate the topics in learners’ lived experiences and create an engaging learning experience. The study advances our understanding of ways to use novel technologies to introduce learners to data science, emphasizing the practical implications of using authentic data and the inquiry-based approach in curriculum design.

We live in an increasingly computational world where youth are impacted by computing technologies and algorithms whether they are using them directly or not. The omnipresence of technology and the impacts it has on society lead to Threats to Techquity, or the aspects of computing and technologies that cause or could cause inequity, especially inequity based on marginalized identities. We partnered with youth and teachers to co-design the Talking Techquity curriculum, a middle school curriculum introducing Threats to Techquity alongside computer science skills. After co-designing the curriculum, the teacher partners taught it to sixth grade students. This paper introduces the Talking Techquity curriculum and explores the successes and challenges of teaching it using data from teacher interviews. This work expands efforts to teach students about the social justice and equity impacts of computing and offers an example of how Threats to Techquity can be brought into the classroom.

students to learn in order to succeed in an increasingly data-driven world. Foundational data literacy skills currently live in a number of subjects across K-12 (e.g., data collection and analysis in science classes, statistical calculations in mathematics/statistics, data visualization and communication in civics/social studies), however, a growing number of schools and districts are introducing stand-alone data science (DS) courses. Given the centrality of computing and programming in the contemporary practice of DS, many of these courses include topics historically reserved for computer science (CS) classes. Further, many CS courses include dedicated time for DS topics (e.g., AP Computer Science Principles' unit on Data). In many ways, DS educators and CS educators are working towards the same ends in complementary ways. However, at other times, the two disciplines are in tension, especially given the scarcity of time in K-12 student schedules for non-core subjects. This panel will explore what DS education and CS education can learn from each other, how each can contribute and advance the goals of the other, and how these two intertwined disciplines can productively live alongside each other in K-12 settings.

The demand for computing talent is at an all-time high, but not everyone feels equally welcome or has equal access to pursue opportunities in technology fields. Women, non-binary, Black, Hispanic/Latino/a/x, and first-generation students are the least likely to have access to paid undergraduate internships that lead to job opportunities in technology companies. This experience report discusses two programs designed to address the lack of internships among historically excluded populations: a micro-internship program and a career program. We present data showing the role that each program played in creating professional pathways for racially diverse undergraduate women and non-binary students. Both programs prepare these undergraduates for professional environments by exposing them to tech careers and developing their social capital through professional networking. Quantitative and qualitative data were collected as well as summer employment plans to evaluate the effectiveness of the program. We present the short- and long-term impact of each program on students' career interests and sense of belonging in computing. A summary of lessons learned from implementing each program are also shared for stakeholders interested in designing similar programs.

The past decade has seen a growing number of culturally relevant K-8 computer science curricula. However, as teachers are the experts on their own classrooms, empowering them to customize instructional materials that draw on the cultural identities and personal experiences of their students can be a powerful strategy. Unfortunately, this process can be challenging and time-consuming.

Data is increasingly shaping the way people interact with each other and the world more broadly. For youth growing up in an increasingly data-driven society, it is critical they have foundational data literacy skills. A central component of data literacy is the ability to collect, analyze, visualize, and make meaning from data. All of these activities are mediated and shaped by the tools that youth use to carry out these data practices. Given the essential role tools play in enabling and supporting youth in engaging with and interpreting data, understanding what tools are used and how they are used in educational contexts will help us understand how youth are being prepared to be data-literate citizens. In this paper, we present the analysis of the data collection and analysis tools used in 4 widely adopted high school data science curricula. The analysis attends to both what tools are used as well as what datasets they are used to analyze. This work contributes to our understanding of the way youth are being introduced to concepts and practices from the field of data science and the role the tools play in shaping those experiences.

AI code generators like OpenAI Codex have the potential to assist novice programmers by generating code from natural language descriptions, however, over-reliance might negatively impact learning and retention. To explore the implications that AI code generators have on introductory programming, we conducted a controlled experiment with 69 novices (ages 10-17). Learners worked on 45 Python code-authoring tasks, for which half of the learners had access to Codex, each followed by a code-modification task. Our results show that using Codex significantly increased code-authoring performance (1.15x increased completion rate and 1.8x higher scores) while not decreasing performance on manual code-modification tasks. Additionally, learners with access to Codex during the training phase performed slightly better on the evaluation post-tests conducted one week later, although this difference did not reach statistical significance. Of interest, learners with higher Scratch pre-test scores performed significantly better on retention post-tests, if they had prior access to Codex.

In traditional scientific publishing, studies are designed, conducted and written-up, then submitted to a conference or journal for peer review. This means that any feedback from reviewers on the design of the study is too late to be acted upon. It also means that reviewers cannot detect questionable practices such as bending of the written-up study aims to match the found data, or modification of the analysis to produce a statistically significant result. Registered Reports are a new kind of scientific publication process where the study design is written-up and peer reviewed before the study is conducted. This way, changes to data collection or procedure can still be made in response to reviewer comments, and the analysis has been stated on the record. The accept/reject decision is also made in principle at this stage, which avoids the decision being based on whether results are significant and can increase researcher confidence that the work will be published. At the time of writing, Registered Reports are available at the Computer Science Education journal and are being added at ACM Transactions on Computer Education. If not publishing at these venues, preregistration is a voluntary alternative where the design is published at a trusted third-party site like the Open Science Foundation (with an embargo), but without the peer review and early accept/reject. This birds of a feather session will bring together researchers with an interest in registering their study, reviewing such studies, or who have questions or interest in this new process.

Transitioning from block-based programming environments to text-based programming environments can be challenging as it requires students to learn new programming language concepts. In this paper, we identify and classify the issues encountered when transitioning from block-based to text-based programming. In particular, we investigate differences that emerge in learners when using a structured editor compared to an unstructured editor. We followed 26 high school students (ages 12-16; M=14 years) as they transitioned from Scratch to Python in three phases: (i) learning Scratch, (ii) transitioning from Scratch to Python using either a structured or unstructured editor, and (iii) evaluating Python coding skills using an unstructured editor. We identify 27 distinct types of issues and show that learners who used a structured editor during the transition phase had 4.6x less syntax issues and 1.9x less data-type issues compared to those who did not. When these learners switched to an unstructured editor for evaluation, they kept a lower rate on data-type issues but faced 4x more syntax errors.

As society increasingly relies on computers to drive social, economic, and political decisions, the computing workforce must reflect the racial and gender diversity of the larger population. This experience report presents CompSciConnect (CSC), a multi-year program designed to broaden participation in computing for middle school aged students from historically excluded populations (girls and/or Black, Latina/o/e/x, and Native American [BLNA] students). Each cohort of CSC participants span three years with participants meeting for 2 weeks in the summer and one weekend a month during the school year. Students progress through three levels of the program: Yellow (beginner), Red (intermediate), and Terp (advanced). Quantitative and qualitative data guided the growth and implementation of CSC. CSC began in 2012 with just 14 students and now has reached over 532 students. Additionally, CSC alumni cite their experiences in CSC as contributing to their decisions to major in a computing field. Various design factors-such as community-centered student recruitment strategies, the long-term structure of the program, and the scaffolded curriculum-contributed to CSC's growth and its positive impact on CSC participants. In this paper, we present CSC, elaborate on the design factors that led to CSC's success, and highlight the challenges and lessons learned throughout CSC's development.

Switch mode is a novel block-based programming feature that allows learners to author one or more lines of text-based code inside of a block-based program. The design of Switch mode seeks to support novices in authoring text-based code while keeping the scaffolds of block-based programming present. Switch mode blocks can be used like any other block but instead of specifying a specific behavior. Switch blocks have a text-based programming editor embedded with it to type in commands. In Switch mode, users can convert conventional blocks to Switch blocks or start from blank Switch blocks to immediately begin typing Python commands. Predefined Switch blocks support single line commands, multi-line programs, variables, nested structures, and function headers. This demo introduces the switch mode approach and will provide a hands-on tutorial on how to author switch mode programs. The session will also share a case study showcasing the potential of switch mode using data from in a 9th grade classroom study. This demo session will introduce attendees to a new and novel approach for helping novices transition from block-based to text-based programming and provide opportunities for hands-on exploration of the tool alongside discussions of how it might be used in classrooms.

Ensuring that computer science curricula connect to learners' home culture, interests, and lived experiences is one approach to making the field more equitable. A central feature of the Scratch Encore Curriculum is to provide many opportunities for learners to plan and implement open-ended programming projects that invite them to draw on their prior knowledge, experiences, and cultural resources. To date, relatively little research has been done to analyze how learners respond to such curricular invitations, specifically with respect to what aspects of themselves and their interests they choose to express in their resulting projects.

This paper introduces the VEX 123 Coder and Coder cards, a novel approach for supporting novices programming a small robotic device. The VEX 123 Coder is a plastic device, similar in size and shape to a smartphone, that connects to the VEX 123 Robot via Bluetooth, and allows young users to define robot instructions by sliding predefined Coder cards into slots on the Coder. This approach blends features of tangible programming with key conceptual underpinnings and interaction patterns used in block-based programming and beyond. In this paper, we present key design and technical features of the Coder and Coder cards, and the results of elementary classroom testing sessions showing how the Coder and Coder cards can support youth in authoring programs. This work contributes a new programming approach to the literature on how to introduce youth to the practice of programming.

This paper introduces VEX 123, a robot that can be programmed via four distinct methods designed to support users at all levels of programming ability, ranging from young users who cannot yet read to professional programmers. The VEX 123 can be programmed by: (1) directly pressing buttons on its exterior; (2) using a tangible programming approach based on a physical Coder and Coder Cards; (3) defining instructions with a block-based programming language; and (4) using the Python programming language. In providing a range of programming approaches, the VEX 123 can meet the user at their current level of ability and comfort while also providing mechanisms to help them move from basic to more sophisticated and powerful programming approaches. In supporting four distinct programing approaches that span physical and virtual contexts, the VEX 123 contributes a novel addition to the growing ecosystem of tools designed to introduce novices to the practice of programming.

Abstract Newly released robot programming tools have made it feasible for end‐users to program industrial robots by combining block‐based languages and lead‐through programming. To use these systems effectively, end‐users, who usually have limited or no programming experience, require training. To train users, tutoring systems are often used for block‐based programming—some even for lead‐through programming—but no tutorial system combines these two types of programming. We present CoBlox Interactive Tutorials (CITs), a novel tutoring approach that teaches how to use both the hardware and software components that comprise a typical end‐user robot programming environment. As users switch between the two programming styles, CITs provide them with extensive scaffolding, give users immediate feedback on missteps, and provide guidance on next steps. To evaluate CITs, we conducted a study with 79 industrial end‐users using a programming environment released by ABB Robotics that compares our approach to training with training videos, the most commonly used training in industry. This study, one of the largest to date on training professional end‐users, found that CIT‐trained users authored more correct programs in less time than video‐trained users. This shows that a tight integration of hardware and software concepts is crucial to training end‐users to program industrial robots.

Transitioning from block-based programming environments to conventional text-based programming languages is a challenge faced by many learners as they progress in their computer science education. In this paper, we introduce CodeStruct, a new intermediary programming environment for novices designed to support children who have prior experience with block-based programming to ease the eventual transition to text-based programming. We describe the development of CodeStruct and its key design features. We then present the results from a two-week long programming class with 26 high school students (ages 12-16; M=14 years) investigating how CodeStruct supported learners in transitioning from Scratch to Python. Our findings reveal how learners used the scaffolds designed into CodeStruct to support their transition from blocks to text, and that transitioning to CodeStruct reduced completion time (1.98x) and help requests (4.63x) when compared to transitioning directly to Python. Finally, learners that used CodeStruct, performed equally well (and slightly better in 10/16 programming activities) in their final transition to fully text-based Python programming.

Open-ended tasks can be both beneficial and challenging to students learning to program. Such tasks allow students to be more creative and feel ownership over their work, but some students struggle with unstructured tasks and, without proper scaffolds, this can lead to negative learning experiences. Scratch is a widely used coding platform to teach computer science in classrooms and is designed to support learner creativity and expression. With its open-ended nature, Scratch can be used in various ways in the classroom to meet the needs of schools and districts. One challenge of using Scratch in classrooms is supporting learners in exploring their interests and fostering creativity while still meeting the instructional goals of a lesson and ensuring all students are engaged with, and understand, focal concepts and practices.

In 2020, the world confronted an unprecedented event affecting education globally: COVID-19. Events that disrupt education are not new; Homelessness or trauma negatively impact education at an individual level, whereas war stops education completely. This event is unique in that it caused the cessation of in-person instruction for all but with a rapid transition to remote instruction.

Given the increasing interest and need to teach students computer science in formal education settings, it is imperative to understand how to do so effectively and equitably. An important step of learning to program is being able to define the objective of a program and then plan out how to implement a program to produce the desired outcome. This step is particularly important in younger learners who may have little experience with programming or trying to create their own technological artifacts. In this paper, we explore how to scaffold young programmers in planning their open-ended programs as part of an intermediate Scratch curriculum for middle grade students. We analyze 203 paper and virtual planning documents from 103 5th-8th grade students. Our results reveal that the students often completed a majority of the document, which was consistent across grade levels. However, we found differences in student completion based on teacher and between physical and virtual documents. This work advances our understanding of how to support novice, young programmers in planning programs.

There is an increasing need for knowledgeable K-12 computer science (CS) teachers. It is necessary to inform teachers how to debug and help their students debug programs. Research has shown that debugging is difficult for novices because the process requires different skills from creating programs and instructing students how to debug can help them acquire these skills. To this end, we developed a CS professional development for middle grade teachers (grades 5th-8th/ages 10-13) that includes lessons on debugging. The teachers completed debugging activities that involved finding bugs in Scratch programs and explaining how they would help their students in debugging. We qualitatively analyzed their responses and found that teachers successfully identified the problem but they struggled to locate it in the code. In considering how they would help students who had such a bug, the teachers often focused on helping the student find a solution for the bug rather than on identifying the problem or its source. Finally, teachers' ability to identify bugs and the pedagogical strategies to engage students in this process differed based on CS teaching experience and prior CS knowledge. This work contributes to our understanding of teachers' debugging abilities and advances our knowledge on how to support teachers in teaching their students how to debug their programs.

INFACT aims to provide differentiable teaching and learning activities in Computational Thinking (CT) that are inclusive for neurodiverse learners in grades 3-8. Neurodiversity refers to learners with autism, ADHD, dyslexia, and other related cognitive differences. Underlying many neurodiverse conditions is differences with executive function (EF). In previous research on game-based learning, neurodiverse students became class leaders in CT activities [1]. Special education teachers noted that CT practices align with strategies they use to support problem-solving practices. Leveraging these affordances of CT, INFACT activities are designed with embedded EF scaffolds to support neurodiverse learners.

The session will present an overview of findings of a recently funded NSF workshop that set out to examine the pressing issues for computing education research for the next 15 years. Based on dialogs for scholars working in this area, the workshop participants developed a series of themes and topics that they felt should become the focus of computing education research efforts for the next 15 years. Main themes that emerged and will be discussed in this session include: diversity, equity, inclusion, ethics, broadening participation, teaching, learning, K-12, research to practice, computing's connection to other fields, and computing education research disciplinary issues. The session will focus on interesting research questions from each of these areas that are ripe to be explored as well as enablers and blockers to the progress of this work.

The expansion of computer science (CS) into K-12 contexts has resulted in a diverse ecosystem of curricula designed for various grade levels, teaching a variety of concepts, and using a wide array of different programming languages and environments. Many students will learn more than one programming language over the course of their studies. There is a growing need for computer science assessment that can measure student learning over time, but the multilingual learning pathways create two challenges for assessment in computer science. First, there are not validated assessments for all of the programming languages used in CS classrooms. Second, it is difficult to measure growth in student understanding over time when students move between programming languages as they progress in their CS education. In this position paper, we argue that the field of computing education research needs to develop methods and tools to better measure students' learning over time and across the different programming languages they learn along the way. In presenting this position, we share data that shows students approach assessment problems differently depending on the programming language, even when the problems are conceptually isomorphic, and discuss some approaches for developing multilingual assessments of student learning over time.

There is a need for more K-12 computer science (CS) teachers. The need to scale teacher professional development (PD) points the CS education community towards virtual learning, and prior work shows that in-person PD with a diffuse schedule is more successful than condensed schedules. There is currently little research about virtual K-12 CS PD with a diffuse schedule. The pandemic served as a forced opportunity to explore the design and implementation of a diffuse-scheduled virtual PD for two small, equally-sized cohorts of middle school (grades 5-8) teachers; one from a metropolitan school district and another from across the United States.

There is a national shortage of certified computer science (CS) teachers. While significant effort and resources have been put towards addressing this shortage, the number of newly certified CS teachers entering the profession each year remains low. In this position paper, we argue that Colleges of Information Studies (iSchools) can serve as fertile grounds for recruiting future K-12 CS teachers. The motivation for looking to iSchools as venues for expanding the K-12 CS teacher pipeline is threefold: (1) the content taught in undergraduate iSchool programs closely aligns with K-12 CS content, (2) undergraduate programs in iSchools are experiencing rapid growth in enrollment and have a diverse student body, and (3) iSchools focus on social aspects of computing and thus attract students well-suited for K-12 teaching as a profession. To develop these arguments, we review the content of top iSchool undergraduate programs, showing the alignment between iSchool undergraduate coursework and K-12 CS. Further, using the University of Maryland's Bachelor of Science in Information Sciences as a case study, we show how iSchools can serve as contexts for preparing future K-12 CS teachers. Collectively, this work seeks to expand how we think about recruiting future CS teachers, explicating arguing for iSchools as venues for expanding the K-12 CS teacher pipeline.

The 1980s and 1990s saw a robust connection between computer science education and cognitive psychology as researchers worked to understand how students learn to program. More recently, academic disciplines such as science and engineering have begun drawing on cognitive psychology research and theories of learning to create instructional materials and teacher professional development materials based on theories of learning, to some success. In this paper, we follow a similar approach by highlighting common areas of interest between computer science education and cognitive psychology–specifically theories of analogical transfer–and discuss how cross-pollination of theoretical constructs between disciplines can support research on the teaching and learning of multiple programming languages. We will also discuss areas where computing education research can adapt the existing theories from cognitive psychology to develop domain-specific theories of knowledge transfer in computing and feed back into cognitive psychology research to inform larger debates about the nature of cognition and learning.

Computing is rapidly becoming a critical literacy for succeeding in an increasingly technological world. While the proliferation of programs dedicated to broadening participation in computing increases access, computing education research can benefit from more directly drawing on current interest development theory to improve interventions that increase the desire to participate and persist in computing. In this article, we present an overview of current interest development theory and provide guidance to computing education researchers on ways to ground their conceptualization and measurement of interest in contemporary theory and inform ways of interweaving interest theory throughout intervention or curriculum design. The central contribution of this work is presenting the Integrated Interest Development for Computing Education Framework. This framework is organized around three central dimensions of interest: value, knowledge, and belonging. For each of these dimensions, the framework presents key factors that link the dimension to strategies that can be employed in computing education contexts to help develop interest. The article also describes methods of measuring interest in computing that are consistent with interest development theory, and provides examples and resources for validated measures of interest. We conclude with a discussion of the implications and potential for improving the conceptualization and measurement of interest development in computing education and future work needed to advance an understanding of how interest in computing develops that can lead to improving the design of computing educational programs to support interest development.

Technology is expanding worldwide and, in conjunction, so are opportunities for creative computing to aid communities and the need for an expanded workforce. Yet, there is a global disparity in where youth are learning programming, with the majority of computing instruction occurring in developed countries and urban areas, if it occurs at all in developing countries. In this work, we sought to counteract this trend by bringing computing, specifically physical computing in the form of robotics, to youth and young adults in rural El Salvador. In this paper, we present the robotics activities completed with youth in a small, Salvadoran community. Based on field notes of the activities and interviews with the youth who participated, we present both the successes and difficulties we faced carrying out this educational outreach program. We further explore the challenges faced due to this unique environment and lessons learned that can help inform the expansion of computing opportunities in developing nations.

Given the importance of broadening participation in the field of computing, goals of supporting personal expression and developing a sense of belonging must live alongside the goals of conceptual knowledge and developing disciplinary expertise. Integrating opportunities for students to be creative in how they enact computing ideas plays an important role when designing curricula. We examine how student creativity, as expressed through theme and the use of costumes, backdrops, and narrative in Scratch projects, is affected by using a themed starter project. Starter projects are Scratch projects that include a set of sprites and backdrops aligned to a theme (e.g. baseball), but no code. Using within-group and between-group comparisons, we establish a baseline of what students do when they are given a starter project and explore how their projects differ in the absence of a starter project. This work contributes to our understanding of the impacts of structured elements within open-ended learning tasks and how we can design computer science learning experiences for students that promote opportunities for self-expression while engaging them in computing.

As computer science instruction gets offered to more young learners, transitioning from elective to requirement, it is important to explore the relationship between pedagogical approach and student behavior. While different pedagogical approaches have particular motivations and intended goals, little is known about to what degree they satisfy those goals.

While several introductory computer science curricula exist for children in K-8, there are few options that go beyond sequence, loops, and basic conditionals. The goal of this project is to not only fill this gap with a high-quality curriculum supported by complete instructional materials, but to also do so with an equity-balanced curriculum. That is, a curriculum that values advancing equity equally with student learning outcomes. In this paper, we introduce barriers to equity in public school classrooms, pedagogical approaches to culturally-relevant curricula, and how our Scratch Encore curriculum is designed to support equity-balanced learning. Finally, we present results of our pilot year, including early evidence of students taking advantage of the culturally-relevant design aspects.

As part of the national Computer Science for All initiative, there is a growing presence of computer science (CS) in K-8 classrooms. This poster presents findings from a survey of 130 K-8 teachers from Chicago Public Schools (CPS) about the state of computer science in their schools and their experiences teaching it. Results from the survey highlight the plurality of ways CS is being implemented in the classroom. The survey also reveals challenges instructors face in teaching CS. Finally, the survey reports on teachers' own experiences in the classroom, finding that teachers enjoy teaching CS and think their students also enjoy CS.

In response to the growing call to bring the powerful ideas of computer science to all learners, education decision makers, including teachers and administrators, are tasked with making consequential decisions on what curricula to use. Often, these decision makers have not been trained in computer science and are unfamiliar with the concepts taught and tools used. This is especially true in K–12 contexts where computer science expertise is less prevalent. To aid in the decision-making process around computing curricula, this article introduces the TEC Rubric. The TEC Rubric is composed of three main categories: Teacher Accessibility, Equity, and Content designed to support educational decision makers and designers when it comes to computing instruction. Along with presenting the full rubric and the process used in its creation, this article describes two examples of the rubric in action. First, the TEC Rubric is used to evaluate two widespread computer science curricula to demonstrate its evaluative capacity highlighting differences between the two curricula. Second, we show how the TEC Rubric can be used to help inform the design of new K–12 computing curricula. Overall, the TEC Rubric is designed to serve as a useful resource in the ongoing quest to bring effective, equitable, and engaging computing instruction into schools around the world.

As physical computing devices proliferate, researchers and educators push to make them more engaging to learners. One approach is to make the act of programming them more interactive and responsive via live programming so that program edits are immediately reflected in the behavior of the physical device. To understand the impact of live programming on interactions with physical computing devices, we conducted a comparative study where children ages 11-15 programmed a BBC micro:bit device using either the MicroBlocks live programming environment or MakeCode, the micro:bit default environment. Results show that MicroBlocks users spent more time interacting directly with the physical device while showing different patterns of interaction compared to MakeCode users. We also found variations in the differences between environments related to activity structures. This paper contributes to the growing body of literature on how the design of interfaces---like programming environments---for physical computing devices shapes emerging interaction patterns.

Participatory design is an essential design strategy for creating artifacts and experiences that reflect the voices of the population being designed for and with. The participatory design process can serve not only to research resulting artifacts but also as an empowering activity for those who participate. This paper explores how participatory design can serve as a context for young participants to enact and voice their emerging identities and reveals how different participatory design activities have unique affordances for supporting this identity enactment. Focusing on a group of 12 and 13-year-old African American girls, this paper presents a case study showing how participatory design activities served as venues for the girls to reflect characteristics of their current identities, project future identities, and apply aspects of their identities to shape materials for others. In doing so, we contribute a case study showing how participatory design allows participants to enact their identities, helping researchers gain insight into characteristics of those they are designing with and for. This paper advances our understanding of participatory design as a design approach for youth, especially as it relates to issues of broadening participation, identity, and equity.

The underrepresentation of women and minorities in the field of computer science is well documented. Due to this lack of representation, efforts to broaden participation in computing abound. One manner with which to do this is through the development of culturally relevant curricula. Education literature encourages the use of culturally relevant techniques and topics to teach school content through the knowledge of diverse groups as well as teach about culturally diverse populations. In addition, partnering with the students who will learn with the curriculum is encouraged in order to co-develop ideas and learn more about students' interests and experiences. This poster describes the outcomes from a series of participatory design sessions with a diverse group of stakeholders (students, teachers, parents, and administrators) to design an intermediate computing curriculum for 5th - 7th grade students. Specifically, we examine the topics developed by the participants that are being utilized as themes for curricular units. Preliminary analysis shows that participants of all ages brainstormed and utilized themes related to both cultural heritage and contemporary culture, but more focus was placed on youth culture and pop culture topics. The poster will describe the design methods used during the participatory design sessions as well as the themes developed and an overall analysis of the categories from which the themes are drawn.

Computational thinking (CT) is increasingly becoming a part of the K-12 educational landscape. While high schools with computer science teachers or technology coaches on staff are well positioned to help teachers integrate computational thinking into instruction, early childhood through middle schools (grades p-8) are often less well equipped. Further, the concept of CT is often poorly defined, especially as it relates to younger learners. Despite these challenges, teachers are being asked to integrate CT into other content lessons. To understand if and how this is happening, we conducted a statewide survey of primary (early childhood through middle school) Maryland teachers. The survey asked the teachers about their conceptualization of CT, CT resources they rely on, and their comfort levels to provide effective CT instruction for their students. The results of our survey demonstrate that teachers hold diverse views of the concept of CT and use a varied set of instructional resources in their classrooms. The contribution of this work is in helping advance our understanding of the current state of CT in primary classrooms.

The introduction of the Advanced Placement (AP) Computer Science Principles course changed the high school computer science (CS) landscape in the United States. For the first time an AP course was designed to broaden participation in computing and attract all students as opposed to being designed to challenge the highest performing students. The goal was to design a rigorous and comprehensive CS high school course that highlighted the breadth of the field of CS beyond just programming. With the course first offered for AP credit in the 2016-2017 school year, this study explores how this -introductory advanced" CS course impacted high school CS class offerings. Using data from a state-wide survey and the Maryland Longitudinal Data System Center (MLDSC), we found inconsistent impacts with the AP Computer Science Principles introduction. Some schools increased the number of CS courses while other schools decreased CS course offerings. This was counter to our expectation of an increase in CS classes at the high school level across the state. Responses from a teacher survey yielded insight into this unexpected outcome and informed explanations for these changes.

The success of block-based programming environments like Scratch and Alice has resulted in a growing presence of the block-based modality in classrooms. For example, in the United States, a new, nationally-administered computer science exam is evaluating students' understanding of programming concepts using both block-based and text-based presentations of short programs written in a custom pseudocode. The presence of the block-based modality on a written exam in an unimplemented pseudocode is a far cry from the informal, creative, and live coding contexts where block-based programming initially gained popularity. Further, the design of the block-based pseudocode used on the exam includes few of the features cited in the research as contributing to positive learner experiences. In this paper, we seek to understand the implications of the inclusion of an unimplemented block-based pseudocode on a written exam. To do so, we analyze responses from over 5,000 students to a 20 item assessment that included both block-based and text-based questions written in the same pseudocode as the national exam. Our analysis shows students performing better on questions presented in the block-based form compared to text-based questions. Further analysis shows that this difference is consistent across conceptual categories. This paper contributes to our understanding of the affordances of block-based programming and if and how the modality can help learners succeed in early computer science learning experiences.

The discipline of professional archivists is rapidly changing. Most contemporary records are created, stored, maintained, used and preserved in digital form. Most graduate programs and continuing education programs in Archival Studies address this challenge by introducing students to information technology as it relates to digital records. We propose an approach to addressing this challenge based on introducing computational thinking into the graduate archival studies curriculum.

A new wave of collaborative robots designed to work alongside humans is bringing the automation historically seen in large-scale industrial settings to new, diverse contexts. However, the ability to program these machines often requires years of training, making them inaccessible or impractical for many. This paper rethinks what robot programming interfaces could be in order to make them accessible and intuitive for adult novice programmers. We created a block-based interface for programming a one-armed industrial robot and conducted a study with 67 adult novices comparing it to two programming approaches in widespread use in industry. The results show participants using the block-based interface successfully implemented robot programs faster with no loss in accuracy while reporting higher scores for usability, learnability, and overall satisfaction. The contribution of this work is showing the potential for using block-based programming to make powerful technologies accessible to a wider audience.

Visual block-based programming environments (VBBPEs) such as Scratch and Alice are increasingly being used in introductory computer science lessons across elementary school grades. These environments, and the curricula that accompany them, are designed to be developmentally-appropriate and engaging for younger learners but may introduce challenges for future computer science educators. Using the final projects of 4th, 5th, and 6th grade students who completed an introductory curriculum using a VBBPE, this paper focuses on patterns that show success within the context of VBBPEs but could pose potential challenges for teachers of follow-up computer science instruction. This paper focuses on three specific strategies observed in learners' projects: (1) wait blocks being used to manage program execution, (2) the use of event-based programming strategies to produce parallel outcomes, and (3) the coupling of taught concepts to curricular presentation. For each of these outcomes, we present data on how the course materials supported them, what learners achieved while enacting them, and the implications the strategy poses for future educators. We then discuss possible design and pedagogical responses. The contribution of this work is that it identifies early computer science learning strategies, contextualizes them within developmentally-appropriate environments, and discusses their implications with respect to future pedagogy. This paper advances our understanding of the role of VBBPEs in introductory computing and their place within the larger K-12 computer science trajectory.

Many robotic tasks in small manufacturing sites are quite simple. For example, a pick and place task requires only a few common commands. Unfortunately, the standard languages and programming environments for industrial robots are complex, making even these simple tasks nearly impossible for novices. To enable novices to program simple tasks we created a block-based programming language and environment focused on usability, learnability, and understandability and embedded its programming environment in a state-of-the-art robot simulator. By using this high-fidelity prototype over the course of a year in a case study, a user study, and for countless demonstrations we have gained many concrete insights. In this paper we discuss the details of the language, the design of its programming environment, and concrete insights gained via longitudinal usage.

The last ten years have seen a proliferation of introductory programming environments designed for learners across the K-12 spectrum. These environments include visual block-based tools, text-based languages designed for novices, and, increasingly, hybrid environments that blend features of block-based and text-based programming. This paper presents results from a quasi-experimental study investigating the affordances of a hybrid block/text programming environment relative to comparable block-based and textual versions in an introductory high school computer science class. The analysis reveals the hybrid environment demonstrates characteristics of both ancestors while outperforming the block-based and text-based versions in certain dimensions. This paper contributes to our understanding of the design of introductory programming environments and the design challenge of creating and evaluating novel representations for learning.

As more elementary schools commit to integrating computer science instruction into their curricula, they seek guidance on what concepts are appropriate for students at different grade levels. Currently, little is known about how best to sequence computer science learning across elementary grades. In this paper, we present an analysis of 123 students' (age 9-12, grades 4-6) activities in a curriculum implemented in a visual block-based programming language. The goal of this work is to better understand the developmental appropriateness of foundational computer science ideas. All 4th, 5th, and 6th grade students in a single school completed the first module of a curriculum during the same school year with the same instructor. We analyzed each task students attempted and found that for simple concepts, there was little difference in performance between grade levels. However, differences were found for more complex topics, such as whether they completed initialization tasks and the way in which they solved 2-d navigation tasks. A closer look revealed that students understood the basic concepts, but were challenged by deeper applications of the basic concepts and influenced by non-computer science skills. This work serves as an empirically grounded investigation of elementary computer science learning and contributes to our understanding of computer science learning trajectories and concept sequencing in the late elementary grades.

Blocks-based, graphical programming environments are increasingly becoming the way that novices are being introduced to the practice of programming and the field of computer science more broadly. An open question surrounding the use of such tools is how well they prepare learners for using more conventional text-based programming languages. In an effort to address this transition, new programming environments are providing support for both blocks-based and text-based programming. In this paper, we present findings from a study investigating how learners use a dual-modality environment where they can choose to work in either a blocks-based or text-based interface, moving between them as they choose. Our analysis investigates what modality learners choose to work in, and if and why they move from one representation to the other within a single project. We conclude with a discussion of design implications and future directions for this work. This work contributes to our understanding of the affordances of blocks-based programming environments and advances our knowledge on how best to utilize them.

The number of students taking high school computer science classes is growing. Increasingly, these students are learning with graphical, block-based programming environments either in place of or prior to traditional text-based programming languages. Despite their growing use in formal settings, relatively little empirical work has been done to understand the impacts of using block-based programming environments in high school classrooms. In this article, we present the results of a 5-week, quasi-experimental study comparing isomorphic block-based and text-based programming environments in an introductory high school programming class. The findings from this study show students in both conditions improved their scores between pre- and postassessments; however, students in the blocks condition showed greater learning gains and a higher level of interest in future computing courses. Students in the text condition viewed their programming experience as more similar to what professional programmers do and as more effective at improving their programming ability. No difference was found between students in the two conditions with respect to confidence or enjoyment. The implications of these findings with respect to pedagogy and design are discussed, along with directions for future work.

Blocks-based programming is becoming the way that learners are being introduced to programming and computer science. Led by the popularity of tools like Scratch, Alice, and Code.org's Hour of Code activities, many new programming environments and initiatives are employing the blocks-based modality. This trend can be seen in the growing number of classroom computer science curricula incorporating blocksbased environments into their materials. Despite this rise in use, many open questions remain surrounding blocks-based programming. In this panel, we discuss the current state of blocks-based programming environments, review what we know about learning with blocks-based tools, and look to the future, discussing what form next-generation blocks-based, or blocks-inspired, programming environments might take. Research looking at blocks-based programming is revealing that modality matters: that the representations used to present programming concepts affect learners' conceptual understanding [6], programming practices [3], and perceptions of programming and computer science [5]. This panel brings together leading designers and researchers looking to advance graphical, blocks-based programming through new, innovate designs. The panel will open with a review of current research literature on learning with blocks-based programming and then continue with presentations of three recently designed blocks-based programming environments (Greenfoot 3, GP, Pencil Code), each of which look to push the boundaries of the approach in diffierent directions. These short presentations will frame the discussion of pertinent questions facing designers and educators who use blocksbased programming environments.

Blocks-based programming tools are becoming increasingly common in high-school introductory computer science classes. Such contexts are quite different than the younger audience and informal settings where these tools are more often used. This paper reports findings from a study looking at how high school students view blocks-based programming tools, what they identify as contributing to the perceived ease-of-use of such tools, and what they see as the most salient differences between blocks-based and text-based programming. Students report that numerous factors contribute to making blocks-based programming easy, including the natural language description of blocks, the drag-and-drop composition interaction, and the ease of browsing the language. Students also identify drawbacks to blocks-based programming compared to the conventional text-based approach, including a perceived lack of authenticity and being less powerful. These findings, along with the identified differences between blocks-based and text-based programming, contribute to our understanding of the suitability of using such tools in formal high school settings and can be used to inform the design of new, and revision of existing, introductory programming tools.

This dissertation investigates the comparative affordances and drawbacks of blocks-based, text-based, and hybrid blocks/text introductory programming tools. Blocks-based programming environments are growing in popularity and are increasingly being used in formal introductory programming contexts. To date, much of the work evaluating such tools has focused on their effectiveness in out-of-school contexts and emphasized engagement and attitudinal measures over content mastery. Given their growing presence in classrooms, it is important to understand the benefits and limitations of the use of the blocks-based programming approach in formal learning contexts relative to text-based or hybrid blocks/text alternatives. This dissertation will carry out a quasi-experimental study in high school computer science classrooms to answer questions related to the impact of blocks-based, text-based, and hybrid blocks/text introductory tools, assess the suitability of such tools for preparing students for future computer science learning opportunities, and explore the design space between blocks-based and text-based programming. The goal of this work is to better understand the tools we are using to introduce today's learners to computer science and lay the foundation for creating the tools of tomorrow.

Blocks-based programming environments are becoming increasingly common in introductory programming courses, but to date, little comparative work has been done to understand if and how this approach affects students' emerging understanding of fundamental programming concepts. In an effort to understand how tools like Scratch and Blockly differ from more conventional text-based introductory programming languages with respect to conceptual understanding, we developed a set of "commutative" assessments. Each multiple-choice question on the assessment includes a short program that can be displayed in either a blocks- based or text-based form. The set of potential answers for each question includes the correct answer along with choices informed by prior research on novice programming misconceptions. In this paper we introduce the Commutative Assessment, discuss the theoretical and practical motivations for the assessment, and present findings from a study that used the assessment. The study had 90 high school students take the assessment at three points over the course of the first ten weeks of an introduction to programming course, alternating the modality (blocks vs. text) for each question over the course of the three administrations of the assessment. Our analysis reveals differences on performance between blocks-based and text-based questions as well as differences in the frequency of misconceptions based on the modality. Future work, potential implications, and limitations of these findings are also discussed.

Graphical blocks-based programming environments, such as Scratch and Snap!, are becoming increasingly popular tools for introducing learners to programming in formal educational settings. However, a growing body of research is finding that students struggle when transitioning from these tools to more conventional, text-based programming languages. To better understand students' difficulties and begin to explore potential solutions to facilitate this transition, a 10-week, quasi-experimental study was conducted with 80 students across three high-school introductory programming classes. Each class spent five weeks working with different version of a blocks-based programming tool, each of which integrated text-based programming in a different way. After working in the introductory environments, students transitioned to Java for the remainder of the study. The goal of this project is to understand the affects of blocks-based programming on students' emerging understandings, document challenges students face in transitioning from blocks-based to text-based programming, and investigate potential ways to bridge these two modalities. To answer these questions, a mixed-method approach was taken that included cognitive interviews with learners, automated collection of student authored programs, and pre/mid/post attitudinal and content assessments.

This poster presents an environment and set of pedagogical strategies designed to explore how best to use blocks-based programming tools to prepare learners for future, text-based programming languages. Starting with the snap! programming environment, we added the capability to view the JavaScript equivalent of any blocks-based script authored inside the environment. Additionally, when students define behaviors for new blocks, they do so in JavaScript. This makes it possible to compose blocks-based scripts alongside text-based JavaScript programs and have the two run side-by-side. This environment was used during the first 5-weeks of an introductory programming class at the high school level as part of a quasi-experimental study investigating the relationship between programming modality and emerging student understanding. Teachers of the course used the blocks/text hybrid features in various ways to support learners developing an understanding of programming concepts and laying the foundation for future text-based instruction. These strategies included having students compose programs with graphical blocks then view the equivalent JavaScript, prompting class discussion on similarities and differences between the two modalities; having students write pseudocode for their blocks-based programs before comparing the pseudocode to the JavaScript; and finally, having students implement their algorithm directly in JavaScript, using blocks as a resource to reference proper syntax.

The pilot study gave us the opportunity to test out a number of components of the study design, including our attitudinal and content assessments and our curricular materials, interview protocols, and data collection strategies. While the pilot study yielded numerous useful insights, the choice of environment (Snap!) and the lack of a full text-based condition limited our ability to answer our stated research questions. In the next iteration of the study we will be using a customized version of Pencil Code (Fig. 1), which will give us isomorphic blocks, text, and hybrid interfaces. Our expectation is that the second iteration of the study will provide that data necessary to answer the questions at the heart of this dissertation; namely the relationship between programming modality and understanding in introductory high school programing classrooms, and insight into the design of introductory programming tools that can provide guidance on the creation of the next generation of computer science learning environments. In doing so, we hope to contribute to the development of tools and curricula that will prepare today's students for the computational futures that await them.

In this paper we present a novel approach to the design of game-based learning environments in which the content to be taught is embodied by the opponents the learners compete against as they play. By providing the player with the resources to make sense of the concepts exemplified by their opponents, as well as the tools needed to incorporate the concepts into their own gameplay strategy, players are challenged to learn from their opponents in order to advance in the game. This paper introduces RoboBuilder, a blocks-based, program-to-play game that uses this design strategy to introduce programming novices to core computer science concepts. Along with more fully developing this design principle, we provide evidence from a preliminary study conducted with RoboBuilder of players learning from their opponents to create winning strategies that use the concepts designed into the opponents they are facing.

This workshop, intended for CS educators from middle school through undergrad, will introduce participants to NetLogo. NetLogo is an easy-to-learn multi-agent language and integrated modeling environment in widespread use in classrooms (and research labs) globally. This hands-on tutorial will highlight computational modeling in the natural and social sciences, tie in core computer science concepts, and discuss how to promote student thinking about decentralized systems. The workshop will draw on the presenters' own experiences teaching courses on computational science, computational art, theory of computation, and educational outreach events. Participants will learn first-hand how NetLogo can enrich a variety of computing courses. NetLogo runs on Mac/Linux/Windows. Laptop required.

RoboBuilder is a blocks-based, program-to-play game designed to introduce students to core aspects of computational thinking in a fun and engaging environment. The game employs a constructionist design to challenge players to invent and implement strategies to control an on-screen robot using a specially designed visual programming language. During the game, players' robots compete against a series of progressively more challenging opponents in one-on-one battles. Through playing the game, players construct working programs, providing learners with the experience of reifying their own ideas using a computational medium, a practice central to our notion of computational thinking. This poster presents the design rationale for RoboBuilder and discusses key aspects of the game that contribute to giving learners a positive, hands-on introduction to core computational thinking skills including computationally expressing ideas, algorithmic thinking, and debugging.