As large language models (LLMs) and chatbots become increasingly prevalent, there is an urgent need to create engaging, age-appropriate learning activities that foster foundational AI literacy with a focus on natural language processing (NLP). This paper presents the iterative design and implementation of three instructional activities that introduce middle school learners (ages 11--14) to NLP concepts through playful, hands-on experiences aligned with the AI4K12 Big Idea of Natural Interaction. These activities include: (1) an unplugged card game that develops students' understanding of embeddings and similarity, (2) an unplugged collaborative sentence-generation challenge that illustrates how language models work, and (3) a web-based educational game in which students design and interact with chatbots. Each activity was implemented and refined across multiple educational contexts, including teacher professional development workshops, summer camps, and classroom implementations. All activities are designed to be easy to set up, requiring only commonly available classroom technology (e.g., laptops) and a few inexpensive materials (e.g., decks of cards), and are supported with facilitation guides and reflection prompts. Early implementations revealed areas for refinement, leading to clearer scaffolding that helped students connect gameplay to underlying NLP concepts, and post-refinement surveys indicated that students found the activities both enjoyable and educational. Findings suggest that blending unplugged and digital formats enhances comprehension, and that tailoring content to students' local contexts supports engagement. By making these activities openly available, this work contributes to the growing ecosystem of K–12 AI education resources and offers practical guidance for integrating NLP concepts into classroom instruction.

AI-based chatbots have the potential to accelerate learning and teaching, but may also have counterproductive consequences without thoughtful design and scaffolding. To better understand teachers’ perspectives on large language model (LLM) based chatbots, we conducted a study with 11 teams of middle-school teachers using chatbots for a science and computational thinking activity within a block-based programming environment. Based on a qualitative analysis of audio transcripts and chatbot interactions, we propose three profiles: explorer, frustrated, and mixed that reflect diverse scaffolding needs. In their discussions, we found that teachers perceived chatbot benefits such as building prompting skills and self confidence alongside risks including potential declines in learning and critical thinking. Key design recommendations include scaffolding the introduction to chatbots, facilitating teacher control of chatbot features, and suggesting when and how chatbots should be used. Our contribution informs the design of chatbots to support teachers and learners in middle school coding activities.

As use of generative AI grows across industries, educators must adapt curricula to prepare students for AI-augmented workplaces. While prior research has documented AI adoption among software developers, less is known about how domain-specific engineers (e.g., mechanical, electrical, civil) use GenAI for coding-related work. This pilot study surveyed and interviewed professional engineers to examine employer expectations and current GenAI coding workflows. Our findings suggest that domain-specific engineers use GenAI less frequently than software developers due to safety-critical contexts and legacy systems. Participants emphasized verification and ownership as the most critical professional skills.

Students are most commonly introduced to computer science through high school classes focused on teaching coding from the basics. While formal classes focused on foundational programming are essential, early exposure to computer science foundations for students can be essential for a more successful understanding of the concepts, with a stronger foundation and an increased interest in computer science. This project specifically looks at integrating computer science lesson scaffolding (Parsons' problems and starter code) into school lessons, mainly focused but not limited to science topics, to create exposure to computer science while students learn other school subjects. This is aimed at ensuring that students are able to gain computer science concepts without having to have specialized computer science classes at the schools. In this research, a one-week middle school computer science camp, Ctrl+Alt+Explore, was held to test these various computing-infused lessons on 24 middle school students. Additionally, we aimed at understanding the impact of Parsons problem difficulty and student learning outcomes. In this study, we identified increased student coding knowledge through students creating their own coding projects, suggesting that coding scaffolding can lead to increased computer science learning outcomes.

Adoption of artificial intelligence (AI) is at an inflection point. With daily use of AI escalating due to widely available software tools, educators, researchers, and policymakers must adapt swiftly to changing educational needs. While think tanks and Big Tech companies often promote the notion that AI serves as a powerful tool for democratizing access to knowledge and opportunities, our work in rural communities underscores the disparity in access to AI education and related opportunities. In this paper, we report on our experience introducing foundational AI concepts to rural middle school students using an unplugged game-based learning activity. By providing engaging learning experiences to rural populations, we hope to broaden interest in and understanding of AI technologies. To this end, we conducted a classroom study in which two middle school teachers implemented our unplugged AI learning activity with their students. Analyzing survey data from 60 of the participating students, we explore the impact of the activity on their interest in AI, their conceptual understanding, and examine potential gender differences. Additionally, we share insights from the teachers who participated in our professional development sessions in preparation for the classroom implementations.

Engaging middle school students in complex computational topics such as AI can pose unique challenges to educators, ranging from simplifying potentially difficult mathematical material to maintaining student interest in the subject. One approach to help address these challenges is to utilize hands-on, real-world examples. We conducted a week-long summer camp for 24 students, centering each day around activities aligned with one of the Five Big Ideas in AI. Students participated in exit ticket reflections following each activity. The pathfinding activities, which occurred on one of the days, incorporated real-world examples and digital simulations of three pathfinding algorithms (breadth-first search, depth-first search, and A*), including an activity modeled after the game Pac-Man. Thematic analysis of exit-ticket responses revealed four major themes regarding students' key takeaways from the activities: (1) pathfinding for character movement, notably in video games like Minecraft; (2) pathfinding as a means of efficient navigation; (3) theoretical reasoning regarding the speed of the A* algorithm compared to others, highlighting its intelligent search mechanism; and (4) empirical reasoning based on personal experience during activities, where some students noted A* consistently performed fastest. These findings indicate that students not only engaged with AI concepts but also demonstrated a nuanced understanding of algorithmic efficiency. We examine the implications of these findings on understanding student engagement with interactive pathfinding activities and highlight the potential for future work in this area.

Block-Based Programming (BBP) platforms, such as Snap!, have become increasingly prominent in $\mathrm{K}-12$ computer science education due to their ability to simplify programming concepts and foster computational thinking from an early age. While these platforms engage students through visual and gamified interfaces, teachers often face challenges in using them effectively and finding all the necessary features for classroom management. To address these challenges, we introduce SnapClass, a classroom management system integrated within the Snap! programming environment. SnapClass was iteratively developed drawing on established research about the pedagogical and logistical challenges teachers encounter in computing classrooms. Specifically, SnapClass allows educators to create and customize block-based coding assignments based on student skill levels, implement rubric-based auto-grading, and access student code history and recovery features. It also supports monitoring student engagement and idle time, and includes a help dashboard with a “raise hand” feature to assist students in real time. This paper describes the design and key features of SnapClass those are developed and those are under progress.

With the growing prevalence of AI, the need for K-12 AI education is becoming more crucial, which is prompting active research in developing engaging and age-appropriate AI learning activities. Efforts are underway, such as those by the AI4K12 initiative, to establish guidelines for organizing K- 12 AI education; however, effective instructional resources are needed by educators. In this paper, we describe our work to design, develop, and implement an unplugged activity centered on facial recognition technology for middle school students. Facial recognition is integrated into a wide range of applications throughout daily life, which makes it a familiar and engaging tool for students and an effective medium for conveying AI concepts. Our unplugged activity, “Guess Whose Face,” is designed as a board game that focuses on Representation and Reasoning from AI4K12’s 5 Big Ideas in AI. The game is crafted to enable students to develop AI competencies naturally through physical interaction. In the game, one student uses tracing paper to extract facial features from a familiar face shown on a card, such as a cartoon character or celebrity, and then other students try to guess the identity of the hidden face. We discuss details of the game, its iterative refinement, and initial findings from piloting the activity during a summer camp for rural middle school students.

Background and Context. The importance of CS to 21st-century life and work has made it important to find ways to integrate learning CS and programming into the regular school day. However, learning CS is difficult, so teachers integrating programming need effective strategies to scaffold the learning. In this study, we analyze students’ log data and apply a novel technique to compare Parsons Problems with from-scratch programming in a middle school science class. Objectives. Our research questions aimed to investigate whether, how, and when Parsons Problems improve learning efficiency for a programming exercise within science, utilizing log data analysis and an automated progress detector (SPD). Method. We conducted a study on 199 students in a 6th-grade science course, divided into two groups: one engaged with Parsons problems, and the other, a control group, worked on the same programming task without scaffolding. Then, we analyzed differences in performance and coding characteristics between the groups. We also adopted an innovative application of SPD to gain a better understanding of how and when Parsons problems helped students make more progress on the coding task, with an objective measure of final student grades. Findings. The experimental group, with scaffolding through Parsons Problems, achieved significantly higher grades, spent significantly less time programming, and toggled less between block category tabs. Interestingly, they ran their code more frequently compared to the control group. The SPD analysis revealed that the experimental group made significantly higher progress in all four quartiles of their coding time. Implications. Our findings suggest that Parsons problems can improve learning efficiency by enhancing novices’ learning experience without negatively impacting their performance or grades, which is especially important when programming is integrated into K12 courses.

Existing research has primarily delved into the realm of computer science outreach aimed at K-12 students, with a focus on both informal and non-formal approaches. However, a noticeable research gap exists when it comes to cybersecurity outreach tailored specifically for underserved secondary school students. This article addresses this void by presenting an iterative pilot of a cybersecurity curriculum. This innovative curriculum integrates a one-week summer camp and a series of 1.5-hour workshops designed to provide students with a comprehensive understanding of cybersecurity.

As the presence of artificial intelligence (AI) technologies increases throughout everyday life, so does the need to engage rural communities in AI learning experiences, as these communities often have limited access to such educational opportunities. This work presents three game-based learning activities rooted in core AI concepts: natural language processing, search, and reinforcement learning. These activities were implemented in a summer camp with middle grades students in a rural area of the USA. We share an overview of the activities, as well as key observations and takeaways from student responses in post-activity surveys.

With the growing prevalence of AI, the need for K-12 AI education is becoming more crucial, which is prompting active research in developing engaging AI learning activities. In this paper, we present our work on a game construction toolkit for middle school students and educators that enables them to tailor an AI-focused unplugged card game activity. In our prior work, we designed, developed, and piloted an unplugged card game activity where players predict the identity of a person based on hand-drawn features extracted from a set of facial cards. The activity aims to teach AI concepts aligned with one of the big ideas in AI utilizing techniques from facial recognition. During our pilot testing of the activity, we discovered that creating face cards that capture students' interest is a crucial factor in promoting student engagement. As a result, we designed a card game construction toolkit that allows students and educators to craft their own face card decks using photos that are personally interesting to them, looking to foster engagement and improve replayability of the activity. The toolkit's design is focused on ensuring easy accessibility and features a simple web-based interface that allows users to download and print their customized cards. We expect this toolkit will enhance the usability and educational effectiveness of our unplugged K-12 AI education activity.

In computing classrooms, building an open-ended programming project engages students in the process of designing and implementing an idea of their own choice. An explicit planning process has been shown to help students build more complex and ambitious open-ended projects. However, novices encounter difficulties in exploring and creatively expressing ideas during planning. We present Idea Builder, a storyboarding-based planning system to help novices visually express their ideas. Idea Builder includes three features: 1) storyboards to help students express a variety of ideas that map easily to programming code, 2) animated example mechanics with example actors to help students explore the space of possible ideas supported by the programming environments, and 3) synthesized starter code to help students easily transition from planning to programming. Through two studies with high school coding workshops, we found that students self-reported as feeling creative and feeling easy to communicate ideas; having access to animated example mechanics of an actor help students to build those actors in their plans and projects; and that most students perceived the synthesized starter code from Idea Builder as helpful and time-saving.

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.

The ever pervasive nature of artificial intelligence (AI) in our world necessitates a focus on fostering an AI literate society. Young children, those aged 11 to 14, are at a critical point in developing their dispositions toward and perceptions of science, technology, engineering, and mathematics (STEM), which influences their future education and career interests. Youth in rural areas are in particular need of access to AI learning opportunities to prepare them for the future workforce; digital games may be one way to attract young, rural students to STEM education and careers. In this paper, we explore how to introduce rural middle grades students to foundational AI concepts through digital game design activities. To inform our efforts and to establish an understanding of what these student populations as well as their teachers know about AI and games, we conducted a set of interviews and focus groups. In brief, students’ awareness and understanding of AI varied significantly, whereas teachers had limited knowledge of AI. Moreover, students shared great interest in playing and designing games. In support of our findings, we are developing a set of game design activities around five core AI concepts and ensuring the activities are of interest to our rural students.

Motivation. We have created a modular project-based learning curriculum, Computer Science Frontiers (CSF) [1, 8], for secondary students in attempts to increase the persistence of computer science (CS) students in higher education. The CSF course is divided into four different modules (Distributed Computing, Internet of Things, Artificial Intelligence, and Software Engineering), each centered around a topic typically introduced to students only in higher education. Using the block-based programming environment NetsBlox [4], students are able to access various Application Programming Interfaces related to their interests [2, 3]. The goal of this course is to increase student interest in CS during high school - when first career choices occur [7] - in hopes they will persist in CS during their undergraduate studies.

Background and Context: Open-ended programming projects encourage novice students to choose and pursue projects based on their own ideas and interests, and are widely used in many introductory programming courses. However, novice programmers encounter challenges exploring and discovering new ideas, implementing their ideas, and applying unfamiliar programming concepts and APIs. Code examples are one of the primary resources students use to apply code usage patterns and learn API knowledge, but little work has investigated the effect of having access to examples on students’ open-ended programming experience.

The ubiquity of artificial intelligence (AI) in everyday life suggests the need to ensure young students know about AI, its uses and limitations, and its benefits and risks, while enabling them to develop expertise in using AI-driven technologies. To support rural middle grades students and educators in learning and teaching AI concepts, we are designing AI-focused learning activities centered around the creation of digital gameplay experiences. To inform our designs, we conducted educator interviews and student focus groups to gain insights into their understanding of AI, their computer science background, and their knowledge and interest in gaming. Building on findings from these interviews and focus groups, we have designed a set of hands-on activities to elicit deeper feedback from students and educators on their preferences, points of confusion, and interests. In this work, we present our initial AI-infused game design activities.

Many students rely on examples when learning to program, but they often face barriers when incorporating these examples into their own code and learning the concepts they present. As a step towards designing effective example interfaces that can support student learning, we investigate novices' needs and strategies when using examples to write code. We conducted a study with 12 pairs of high school students working on open-ended game design projects, using a system that allows students to browse examples based on their functionality, and to view and copy the example code. We analyzed interviews, screen recordings, and log data, identifying 5 moments when novices request examples, and 4 strategies that arise when students use examples. We synthesize these findings into principles that can inform the design of future example systems to better support students.

The demand is growing for a populace that is literate in Artificial Intelligence (AI); such literacy centers on enabling individuals to evaluate, collaborate with, and effectively use AI. Because the middle school years are a critical time for developing youths' perceptions and dispositions toward STEM, creating engaging AI learning experiences for middle grades students (ages 11 to 14) is paramount. The need for providing enhanced access to AI learning opportunities is especially pronounced in rural areas, which are typically underserved and underresourced. Inspired by prior research that game design holds significant potential for cultivating student interest and knowledge in computer science, we are designing, developing, and iteratively refining an AI-centered development environment that infuses AI learning into game design activities. In this work, we review design principles for game design interventions focused on middle grades computer science education and explore how to introduce AI learning experiences into interactive game design activities. We also discuss results from our initial co-design sessions with middle grades students and teachers in rural communities.

As computer science is increasingly taught in secondary schools, tools need to integrate block-based environments into learning platforms. This way, teachers can more effectively lead lessons, help students, and assess students' programs in their classrooms. We conducted a participatory design process with three K-12 computing teachers to understand their struggle and needs for block coding within their classrooms. The teachers identified 14 needs that were not already addressed by our tool, SnapClass. SnapClass, a new web-based learning platform for Snap!, integrates assignments with starter code, executable student submissions, rubric-based assessment, and a gradebook into one platform. The teachers designed prototypes for three features important to their classrooms: assignment differentiation, help-requests, and peer and self-assessment. This paper begins by introducing SnapClass and the motivation for its development. Then through thematic analysis of the session transcripts, we identify the common struggles teachers face while instructing programming and summarize how they would address those struggles through the design of SnapClass.

Historically, female students have shown low interest in the field of computer science. Previous computer science curricula have failed to address the lack of female-centered computer science activities, such as socially relevant and real-life applications. Our new summer camp curriculum introduces the topics of artificial intelligence (AI), machine learning (ML) and other real-world subjects to engage high school girls in computing by connecting lessons to relevant and cutting edge technologies. Topics range from social media bots, sentiment of natural language in different media, and the role of AI in criminal justice, and focus on programming activities in the NetsBlox and Python programming languages. Summer camp teachers were prepared in a week-long pedagogy and peer-teaching centered professional development program where they concurrently learned and practiced teaching the curriculum to one another. Then, pairs of teachers led students in learning through hands-on AI and ML activities in a half-day, two-week summer camp. In this paper, we discuss the curriculum development and implementation, as well as survey feedback from both teachers and students.

Our researchers seek to support students in building block-based programming projects that are motivating and engaging as well as valuable practice in learning to code. A difficult part of the programming process is planning. In this research, we explore how novice programmers used a custom-built planning tool, PlanIT, contrasted against how they used storyboarding when planning games. In a three-part study, we engaged novices in planning and programming three games: a maze game, a break-out game, and a mashup of the two. In a set of five case studies, we show how five pairs of students approached the planning and programming of these three games, illustrating that students felt more creative when storyboarding rather than using PlanIT. We end with a discussion on the implications of this work for designing supports for novices to plan open-ended projects.

The Computer Science Frontiers (CSF) project introduces teachers to the topics of artificial intelligence and distributed computing to engage their female students in computing by connecting lessons to relevant cutting edge technologies. Application topics include social media and news articles, as well as climate change, the arts (movies, music, and museum collections), and public health/medicine. CSF educators are prepared in a pedagogy and peer-teaching centered professional development program where they simultaneously learn and teach distributed computing, artificial intelligence, and internet of things lessons to each other. These professional developments allow educators to hone in on their teaching skills of these new topics and gain confidence in their ability to teach new computer science materials before running several activities with their students in the academic year classroom. In this workshop, teachers participating in the CS Frontiers professional development will give testimonials discussing their experiences teaching these topics in a two week summer camp. Attendees will then try out three computing activities, one from each Computer Science Frontiers module. Finally, there will be a question and answer session.

By age 15 girls start to lose interest in STEM, and less than 50% consider a STEM-related career. Providing hands-on internship opportunities has been one of the leading ways to help connect students with exploring computing careers; however, these opportunities are limited in high school. We propose a framework for a university-led high school internship initiative that focuses on service learning, co-design, and the propagation of engaging computing curricula for younger audiences. We piloted this model virtually in summer 2021, with high school students and teachers as interns mentored by university role models. Teams led the development and implementation of computing-infused curricula for a virtual summer coding camp. In this article, we share our framework and review the importance of service-learning for recruiting diverse participants and the use of co-design as a way to broker relationships between developers and community stakeholders. Additionally, we provide preliminary outcomes of our internship model on student and teacher participants gathered from qualitative data including end-of-summer presentations and post-program interviews.

Academic computing departments are seeking ways to broaden participation in computing (BPC), and many are encouraging individual faculty, staff, and students to attend diversity-oriented conferences, like the Tapia and STARS Celebrations of Diversity in Computing and Grace Hopper Celebration of Women in Computing. The purpose of the STARS Ignite Workshop is to provide faculty and staff with a framework including the tools and knowledge needed to make such conference attendance beneficial both to the students attending the conference and to the sponsoring faculty and their department. In this workshop, participants will learn to recruit and lead a BPC purpose-driven student conference cohort and the implementation of a BPC event or program. Participants will be provided with opportunities to adapt sample materials (recruitment emails, applications, etc.) to their own needs, assess the BPC needs at their institutions, and learn how to determine if their BPC efforts are successful. A laptop and Google account are required for this event. Interested attendees should be willing to commit to leading a student conference cohort to a diversity-oriented computing conference and then implementing a BPC event or program with these students.

This article examines the grading process and profiles of secondary computer science teachers as they assess block-based student programming submissions. Through an iterative design process, we have created a new tool, Gradesnap, which streamlines how teachers can open, review, and evaluate student submissions within the same interface. Our study compares teachers’ grading processes using the different assessment formats, so that we can understand how their grading processes can be augmented or supported to reduce ’pain points’ and to enable teachers to provide more constructive and formative feedback for students. We use a case study approach to examine the experiences and outcomes of four secondary computer science teachers with varied teaching and assessment experience, when grading as usual, grading with a rubric, and grading with GradeSnap. Our study shows that when participants use GradeSnap, they are able to give supportive comments to lower performing and borderline students who need critical feedback to better understand misconceptions. We also discovered that the different grading processes provided a vehicle for reflection for some teachers in understanding their grading goals and how they enact them. This research is the first to examine teacher grading processes for computer science, and highlights the need for teacher preparation and support for providing programming feedback and assessment.

We compare subject area block-based programming lessons made by two participant groups new to creating K-12 computing curricula. The first group consists of 29 high school interns with prior programming experience but not formal pedagogical training. The second group consists of 86 teachers who attended an infusing computing professional development, with formal pedagogical training but no background in programming. We examine a total of 113 lessons for their use of scaffolding, teacher accessibility, equity, and computing and subject area content. Our analysis extends prior work showing novice-student creator strength in conveying content knowledge and difficulty in incorporating equity into coding lessons. Compared to lessons created by the teacher group (less coding, more pedagogical experience), our results show that teachers also struggle with including equitable practices and opportunity for culturally responsive and identify affirming activities. However, they were much stronger in including assessment focused items. Furthermore, teachers were able to provide adequate support for coding and content knowledge. Our exploration of scaffolding included in these lessons shows that scaffolding included differs by creator and that projects involving worked examples were more often correlated to more evidence of equitable practices. Through this research, we gain insight into what additional knowledge and training are needed to help creators make higher quality and more accessible computing lessons for non-computer science courses.

Computational modeling provides an excellent vehicle for raising scientific awareness of emergent and topical phenomena such as COVID-19. Now more than ever, it is crucial to provide students with factual information about how diseases spread and how their own actions can impact that spread. In order to both encourage computational thinking skills and build scientific knowledge of the COVID-19 pandemic, we have created a series of programming activities through which students construct their own computational models based on the emerging scientific consensus around COVID-19. Students are able to model everyday situations such as being in a crowded area or going to stores while unknowingly infected, and immediately see the consequences of those actions. By including accurate scientific variables such as the reproductive number of the virus, incubation period, and period of communicability, students are able to create their own epi-curves that demonstrate the severity of the disease and provide students with visual representation of how quickly COVID-19 spreads. We also use the scientific model and associated modeling activities to reinforce best practices at home and in the community. Finally, this curriculum development effort demonstrates how block-based computational modeling activities lend themselves to agile curricular re-design around emerging and topics of local interest

Academic computing departments are seeking ways to broaden participation, and many are encouraging individual faculty, staff, and students to attend diversity-oriented conferences, like the Tapia and STARS Celebrations of Diversity in Computing and Grace Hopper Celebration of Women in Computing. Such conferences present opportunities to meet a broader community of people for professional development and networking, to be inspired by leaders in computing, and to celebrate diversity. However, while many institutions sponsor these conferences and support individual student attendance, students may not know how to leverage these opportunities effectively. We argue that leading a cohort of faculty/staff and students who attend a conference with the shared goal of broadening participation can provide lasting benefits for computing departments. This workshop will prepare faculty and staff to recruit and lead a team of students and leverage conference attendance to ignite broadening participation efforts. Through a hands-on collaborative process, the workshop provides the knowledge and tools needed to successfully lead a cohort, and helps attendees tailor the provided tools to their local strengths and needs to broaden participation in computing.

In 2018 and 2019, Infusing Computing offered face-to-face summer PD workshops to support middle and high school teachers in integrating computational thinking into their classrooms through week-long summer PD workshops and academic-year support. Due to COVID-19, 151 teachers attended the Summer 2020 PD workshops in a week-long virtual conference format. In this paper, we describe Virtual Pivot: Infusing Computing, which employed emerging technology tools, pre-PD training, synchronous and asynchronous sessions, Snap! pair programming, live support, and live networking. Drawing on findings from participant interviews and post-PD surveys, we argue that three categories of changes (digital tools, formats, and supports for teacher engagement and collaboration) were effective in increasing participants' self-efficacy in teaching CT, supporting collaboration, and enabling participants to design CT-infused content-area lessons. We conclude by discussing how elements of this virtual PD can be replicated to increase teacher and student access to CT practices in middle and high school classrooms

The AP Computer Science Principles (CSP) high school course introduces students to computer science and programming. What should motivated students study after successful completion of AP CSP? The AP CSA class teaches Java programming and it has traditionally not attracted students from underrepresented groups. We are working on an alternative, projects-based course that will teach cutting edge CS concepts, such as distributed computing, computer networking, cybersecurity, the internet of things and machine learning, in a hands-on, accessible manner. Such an approach enables students to work on problems that interest them making computing more relevant and the curriculum more engaging. We utilize NetsBlox, a collaborative, block-based programming environment that extends Snap! with a few carefully selected abstractions that open up the vast array of resources freely available on the internet for student programs. Moreover, the tool enables students to work together on the same project remotely similarly to how Google Docs operate. This demonstration will introduce the environment and highlight its utility in creating distributed applications such as a shared whiteboard app and projects that access public domain scientific data sources and visualize them in various ways using online services such as Google Maps or charting. More information is available at https://netsblox.org.

Project-based learning can encourage and motivate students to learn through exploring their own interests, but introduces special challenges for novice programmers. Recent research has shown that novice students perceive themselves to be "bad at programming, especially when they do not know how to start writing a program, or need to create a plan before getting started. In this paper, we present PlanIT, a guided planning tool integrated with the Snap! programming environment designed to help novices plan and program their open-ended projects. Within PlanIT, students can add a description for their project, use a to do list to help break down the steps of implementation, plan important elements of their program including actors, variables, and events, and view related example projects. We report findings from a pilot study of high school students using PlanIT, showing that students who used the tool learned to make more specific and actionable plans. Results from student interviews show they appreciate the guidance that PlanIT provides, as well as the affordances it offers to more quickly create program elements.

We have established a research-practice partnership (RPP) to build a computer science (CS) and computational thinking (CT)-focused STEM ecosystem at two middle schools. Creating such an ecosystem to broaden student participation in computing through an RPP approach involves all stakeholders in the research process. Borrowing upon visual participatory research methods, we developed a graphic research instrument to engage teachers in the research process and elicit their perspectives on strategies for building the ecosystem. This experience report describes our research methodology across two distinct cases to demonstrate the utility of this drawing activity as an investigative and partnership development tool. The contribution is in offering a flexible approach to other university-based RPP teams that enables a synergistic partnership development tool and data collection instrument that can be tailored to a variety of RPP contexts, facilitating more productive and equitable ways of engaging stakeholders in the research process. We describe our project contexts and share results from the pilot study with practitioner-members of our RPP teams. We discuss two cases to highlight the contribution this approach made to the development of our partnerships.

Many block-based programming environments have proven to be effective at engaging novices in learning programming. However, most restrict access to the outside world, limiting learners to commands and computing resources built in to the environment. Some allow learners to drag and drop files, connect to sensors and robots locally or issue HTTP requests. But in a world where most of the applications in our daily lives are distributed (i.e., their functionality depends on communicating with other programs or accessing resources and data on the internet), the lack of support for beginners to envision and create such distributed programs is a lost opportunity. This paper argues that it is not only feasible, but crucial, to create environments with simple yet powerful abstractions that open up distributed computing and other widely used but advanced computing concepts including networking, the Internet of Things, and cybersecurity to novices. By thus removing the walls around our environments, we can expand opportunities for learning considerably: programs can access a wealth of online data and web services, and communicate with other projects. Moreover, these changes can enable young learners to collaborate with each other during program construction whether they share their physical location or study remotely. Importantly, providing access to the wider world will also help counter widespread student perceptions that block-based environments are mere toys, and show that they are capable of creating compelling applications. The paper presents NetsBlox, a programming environment that supports these ideas and shows that tools can be designed to democratize access to powerful ideas in computing.

In this paper, we perform a predictive analysis of a curriculum-integrated math game, ST Math, to suggest a partial ordering for the game's curriculum sequence. We analyzed the sequence of ST Math objectives played by elementary school students in 5 U.S. districts and grouped each objective into difficult and easy categories according to how many retries were needed for students to master an objective. We observed that retries on some objectives were high in one district and low in another district where the objectives are played in a different order. Motivated by this observation, we investigated what makes an effective curriculum sequence. To infer a new partially-ordered sequence, we performed an expanded replication study of a novel predictive analysis by a prior study to find predictive relationships between 15 objectives played in different sequences by 3,328 students from 5 districts. Based on the predictive abilities of objectives in these districts, we found 17 suggested objective orderings. After deriving these orderings, we confirmed the validity of the order by evaluating the impact of the suggested sequence on changes in rates of retries and corresponding performance. We observed that when the objectives were played in the suggested sequence, we record a drastic reduction in retries, implying that these objectives are easier for students. This indicates that objectives that come earlier can provide prerequisite knowledge for later objectives. We believe that data-informed sequences, such as the ones we suggest, may improve efficiency of instruction and increase content learning and performance.

Despite the increasing attention to infusing CT into middle and high school content area classrooms, there is a lack of information about the most effective practices and models to support teachers in their efforts to integrate disciplinary content and CT principles. To address this need, this paper proposes the Code, Connect and Create (3C) professional development (PD) model, which was designed to support middle and high school content area teachers in infusing computational thinking into their classrooms. To evaluate the model, we analyzed quantitative and qualitative data collected from Infusing Computing PD workshops designed for in-service science, math, English language arts, and social studies teachers located in two Southeastern states. Drawing on findings from our analysis of teacher-created learning segments, surveys, and interviews, we argue that the 3C professional development model supported shifts in teacher understandings of the role of computational thinking in content area classrooms, as well as their self-efficacy and beliefs regarding CT integration into disciplinary content. We conclude by offering implications for the use of this model to increase teacher and student access to computational thinking practices in middle and high school classrooms.

Pair Programming is often employed in educational settings as a means of promoting collaboration and scaffolding the assignment difficulty for teams. While much research supports its inclusion as a pedagogical practice at the university level, some research has demonstrated in K-12 contexts, it can potentially lead to inequitable learning enviroments and create dynamics between partners that might negatively effect novice learners. New block-based programming environments like Netsblox have attempted to address this by creating ways for both partners to program simultaneously, but this feature has yet to be examined in detail. In this paper, we introduce several modes of Collaboration afforded by Netsblox. This includes Pair-Separate, Pair-Together, and Partner Puzzles - a mode that Splits the necessary blocks to build the assignment between team members. From an initial pilot study involving 25 pairs of middle and high school students, we find that most pairs preferred working on assignments in the Partner Puzzle mode as it presented a fun challenge to teams. We end on recommendations for building assignments using this methodology and future research directions investigating the role of collaboration in programming

This paper illustrates coding decisions by in-service teachers and high school interns working independently versus collaboratively to build computing activities for non-computing classrooms. We investigate code written in Snap! to gain insights on project type and subject matter. We also share case studies on how intern collaboration influences final product execution. Through our research, we found student-only teams often created tutorial projects whereas teachers-only teams create interactive narratives. We found students were able to reuse code across projects to replicate similar mechanics and that students specialize in different aspects of project creation. Overall, we find it beneficial to have collaborative teacher-student teams.

Many K-12 CS education instructors are new to teaching computing and use block-based programming (BBP), allowing them and their students to learn computing concepts with less frustration. Based on prior work with instructors, we found that they need assistance with grading student projects as they are new to coding and developing corresponding assessments. Existing methods are either not intuitive and too restrictive for custom assignments, or tediously unnecessary. Additionally, providing a grading support tool will help increase adoption of our Advanced Placement Computer Science Principles curriculum. Therefore, we began developing a tool to assist teachers with grading BBP projects. This paper reports on a modified User Experience Research method, which we used to determine the critical and necessary features needed for the tool to allow teachers to successfully and efficiently assess BBP student artifacts.

We present a new framework describing how teachers use ST Math, a curriculum-integrated, year-long educational game, in 3rd-4th grade classrooms. We combined authentic classroom observations with teacher interviews to identify teacher needs and practices. Our findings extended and contrasted with prior work on teachers' behaviors around classroom games, identifying differences likely arising from a digital platform and year-long curricular integration. We suggest practical ways that curriculum-integrated games can be designed to help teachers support effective classroom culture and practice.

In summer 2018, we conducted two week-long professional development workshops for 116 middle and high school teachers interested in infusing computational thinking (CT) into their classrooms. Teachers learned to program in Snap!, connect CT to their disciplines, and create infused CT learning segments for their classes. This paper investigates the extent to which teachers were able to successfully infuse CT skills of pattern recognition, abstraction, decomposition, and algorithms into their learning products.

Computational Thinking (CT) is being infused into curricula in a variety of core K-12 STEM courses. As these topics are being introduced to students without prior programming experience and are potentially taught by instructors unfamiliar with programming and CT, appropriate lesson design might help support both students and teachers. "Use-Modify-Create" (UMC), a CT lesson progression, has students ease into CT topics by first "Using" a given artifact, "Modifying" an existing one, and then eventually "Creating" new ones. While studies have presented lessons adopting and adapting this progression and advocating for its use, few have focused on evaluating UMC's pedagogical effectiveness and claims. We present a comparison study between two CT lesson progressions for middle school science classes. Students participated in a 4-day activity focused on developing an agent-based simulation in a block-based programming environment. While some classrooms had students develop code on days 2-4, others used a scaffolded lesson plan modeled after the UMC framework. Through analyzing student's exit tickets, classroom observations, and teacher interviews, we illustrate differences in perception of assignment difficulty from both the students and teachers, as well as student perception of artifact "ownership" between conditions.

The Advanced Placement Computer Science Principles (AP CSP) course has been fully active for 2 years, garnering a large group of diverse students [2], and flaming the need for highly trained CSP teachers, especially in effective practices for diversity and equity. We have conducted summer professional development (PD) workshops from 2012-2018 which have prepared 748 teachers to teach AP CSP using the Beauty and Joy of Computing (BJC) curriculum. To improve equity and readiness for teaching, we have refined our PD by: shortening the PD from 6 weeks to 1 week; developing new, highly scaffolded pre-PD work; and modifying the in-person schedule to incorporate more pedagogy and teaching experiences, while continuing to provide in-depth, hands-on support for teachers to learn the basics of programming. The most recent revisions to our PD schedule resulted in improved post-PD survey results, with teachers from the 2018 cohort planning to adopt more of the BJC curriculum than in past years. From 2017 to 2018, planned adoption rates increased by 13%, resulting in 73% of the 2018 PD participants planning to adopt more than $60%$ of the BJC curriculum and 58% planning to adopt 80-$100% of the BJC curriculum in their classrooms in 2018-2019. In this paper, we discuss the most recent BJC PD implementation and provide evidence of increased teacher self-efficacy in areas including fostering interest in computing for underrepresented populations.

One way to increase access to education on computing is to integrate computational thinking (CT) into K12 disciplinary courses. However, this challenges teachers to both learn CT and decide how to best integrate CT into their classes. In this position paper, we present PRADA, an acronym for Pattern Recognition, Abstraction, Decomposition, and Algorithms, as a practical and understandable way of introducing the core ideas of CT to non-computing teachers. We piloted the PRADA model in two, separate, week-long professional development workshops designed for in-service middle and high school teachers and found that the PRADA model supported teachers in making connections between CT and their current course material. Initial findings, which emerged from the analysis of teacher-created learning materials, survey responses, and focus group interviews, indicate that the PRADA model supported core content teachers in successfully infusing CT into their existing curricula and increased their self-efficacy in CT integration.

Tinkering has been shown to have a positive influence on students in open-ended making activities. Open-ended programming assignments in block-based programming resemble making activities in that both of them encourage students to tinker with tools to create their own solutions to achieve a goal. However, previous studies of tinkering in programming discussed tinkering as a broad, ambiguous term, and investigated only self-reported data. To our knowledge, no research has studied student tinkering behaviors while solving problems in block-based programming environments. In this position paper, we propose a definition for tinkering in block-based programming environments as a kind of behavior that students exhibit when testing, exploring, and struggling during problem-solving. We introduce three general categories of tinkering behaviors (test-based, prototype-based, and construction-based tinkering) derived from student data, and use case studies to demonstrate how students exhibited these behaviors in problem-solving. We created the definitions using a mixed-methods research design combining a literature review with data-driven insights from submissions of two open-ended programming assignments in iSnap, a block-based programming environment. We discuss the implication of each type of tinkering behavior for learning. Our study and results are the first in this domain to define tinkering based on student behaviors in a block-based programming environment.

With increased numbers of K-12 computing courses, we also see an increase in teachers new to the subject, making it difficult for them to properly assess student programming assignments. Many of these teachers require project-specific rubrics to help assess student learning. Researchers have attempted to create systematic, validated, and reliable rubrics for these courses with only minor success. In this research, we make an argument for the validity of our low-stakes computing rubrics. In doing so, we establish a validated method for creating a full-suite of project-based rubrics for K-12 computing courses, helping teachers, researchers, and practitioners make much-needed course materials. Evaluating these rubrics, we see grader consistency as well as heatmaps of where teachers are looking for computational thinking concepts in code.

When novice students encounter difficulty when learning to program, some can seek help from instructors or teaching assistants. This one-on-one tutoring is highly effective at fostering learning, but busy instructors and large class sizes can make expert help a scarce resource. Increasingly, programming environments attempt to imitate this human support by providing students with hints and feedback. In order to design effective, computer-based help, it is important to understand how and why students seek and avoid help when programming, and how this process differs when the help is provided by a human or a computer. We explore these questions through a qualitative analysis of 15 students' interviews, in which they reflect on solving two programming problems with human and computer help. We discuss implications for help design and present hypotheses on students' help-seeking behavior.

Growing public demand for computer science (CS) education in K-12 schools requires an increase in well-qualified and well-supported computing teachers. To alleviate the lack of K-12 computing teachers, CS education researchers have focused on hosting professional development workshops to prepare in-service teachers from other disciplines to teach introductory level computing courses. In addition to the curriculum knowledge and pedagogical content knowledge taught in the professional development workshops, these new teachers need support in computer science subject matter knowledge throughout the school year. In particular, these new teachers find it difficult to grade programs and labs. This research study uses two variations of the Delphi Method to create learning-oriented rubrics for Computer Science Principles teachers using the Beauty and Joy of Computing curriculum. To perform this study we implemented (1) a heavy-weight, heterogeneous wide-net Delphi, and (2) a lower-weight, homogeneous Delphi composed of master teachers. These methods resulted in the creation of two systematically- and rigorously-created rubrics that produce consistent grading and very similar inter-rater reliabilities.

Computer science education in high school is fundamental for increasing the diversity in computing majors at a university level. However, computer science is not often taught in America before university, and usually, the professionals who teach it are not trained experts in computer science concepts and terminology. In this paper, we introduce a new style of coding rubric, which allows teachers to better understand the fundamentals of the course being taught. In the scope of this research, we focus solely on the Beauty and Joy of Computing, an AP Computer Science Principles course. Coding assignments were collected from two groups of students, and assignments were graded and compiled by raters. After being rated, the rubrics were modified to be better adapted to teachers' expectations.

The "Beauty and Joy of Computing" Computer Science Principles class has inspired many new teachers to learn to teach creative computing classes in high schools. However, new computer science teachers feel under-prepared to grade open-ended programming assignments and support their students' successful learning. Rubrics have widely been used to help teaching assistants grade programs and are a promising way to support new teachers to learn how to grade BJC programs. In this paper, we adapt general coding criteria from auto-graders to a lab where students write code to draw a brick wall. We tested the rubric on student assignments and showed that we can achieve high inter-rater agreement with the refined rubric.

Computer Science Principles (CSP) will become an Advanced Placement course during the 2016-17 school year, and there is an immediate need to train new teachers to be leaders in computing classrooms. From 2012-2015, the Beauty and Joy of Computing team offered professional development (PD) to 133 teachers, resulting in 89 BJC CSP courses taught in high schools. Our data show that the PD improved teachers' confidence in our four core content categories and met its primary goal of training teachers in equitable, inquiry-based instruction. In this paper, we present the evolution of the BJC PD, its challenges and lessons that we learned while continually adapting to teachers' needs and contexts.

Students often take computing classes because they are eager to create games, to learn to create meaningful and useful software, or both. Connecting computing to real, cutting-edge applications has been shown to increase engagement of women and minorities. The new CS Principles curriculum, a pilot Advanced Placement course, seeks to broaden the participation in computing to a larger and more diverse audience. This curriculum emphasizes that computing is a creative activity where people work together to solve relevant problems. In this workshop, we introduce free software and curricula to enable novice high school and college students in a first computing course to learn basic game and mobile phone development. We discuss how these activities facilitate teaching high school and non-major (CS0) course topics, but they can also be used to illustrate more advanced topics. Participants will learn GameMaker and mobile phone programming using AppInventor, and/or Touch Develop. These tools allow students to create and have fun with computing while teaching object-oriented and event-driven programming and game architectures. We will provide links to curricular modules for the CS Principles: Beauty and Joy of Computing course, as well as links to the GameMaker, AppInventor, and Touch Develop platforms and tutorials. Participants must bring a network-connected laptop with a modern browser, and the latest version of Java, and may optionally bring an Android, Windows, or iPhone.

Researchers in CS have heard of disparities between underrepresented groups and the lack of people to ll future jobs. Initiatives focus on strengthening the computing pipeline and getting more students interested. This research goes further by analyzing factors that affect behavioral change and get students to enroll in computing courses. We focus on a middle grades outreach program called SPARCS that has a 84% transfer rate into high school courses. We approach with a lens on identity, social cognitive career theory, and other attitudes and demographics perspectives.

The new CS Principles curriculum, a pilot Advanced Placement course, offers novice students an exciting opportunity to learn computing in a hands-on, fun way. High school and college teachers of introductory computer science course are invited to this workshop to learn basic game and mobile phone development. Participants will learn GameMaker, AppInventor, and Touch Develop. These tools allow students to create and have fun with computing while teaching object-oriented and event-driven programming and game architectures. Participants should bring their own laptops (ideally with AppInventor installed). Windows 7 phones will be provided during the workshop. We will provide links to curricular modules for the CS Principles: Beauty and Joy of Computing course.

This design research paper examines the implementation and curriculum changes of an after school computer science program that promotes computational thinking to middle school students. The program, Students in Programming, Robotics, and Computer Science (SPARCS), can adapt to different presentation environments, such as independent after school sessions or a semester-long apprenticeship program. We trace one implementation of the program through the initial deployment, the development of infrastructure, and a reorganization of content to address student interests. We found that student attrition dropped and the average session enjoyment increased when our sessions integrated consumer technologies such as mobile applications, video games, and the Minecraft computer game. In this paper, we provide readers a framework for running computing outreach activities around similar consumer technologies.

Students often take computing classes because they are eager to create games, to learn to create meaningful and useful software, or both. Connecting computing to real, cutting-edge applications has been shown to increase engagement of women and minorities. The new CS Principles curriculum, a pilot Advanced Placement course, seeks to broaden the participation in computing to a larger and more diverse audience. This curriculum emphasizes that computing is a creative activity where people work together to solve relevant problems. In this workshop, we introduce free software and curricula to enable novice high school and college students in a first computing course to learn basic game and mobile phone development. We discuss how these activities facilitate teaching high school and non-major (CS0) course topics, but they can also be used to illustrate more advanced topics. Participants will learn GameMaker and mobile phone programming using AppInventor, and/or Touch Develop. These tools allow students to create and have fun with computing while teaching object-oriented and event-driven programming and game architectures. If possible, Windows 7 phones will be provided for use during the workshop. We will provide links to curricular modules for the CS Principles: Beauty and Joy of Computing course, as well as links to the GameMaker, AppInventor, and Touch Develop platforms and tutorials. Participants must bring a network-connected laptop with a modern browser, and the latest version of Java (ideally with AppInventor installed), and may optionally bring an Android or Windows 7 phone.

Social capital implies that social networks have value. It is therefore important that when a person is at an academic conference, they must strive to build a strong professional social network for themselves. This can be difficult for many academic conference attendeees. We present Table Tilt, a two-minute ice-breaker game for 2--6 players with iPhones or iPods, that was built to facilitate team building and help individuals build social capital. Table Tilt leverages human sociality and game rules to promote communication and teamwork.