This participatory study utilizes the IDC 2026 Research & Design Challenge on sustainability to explore how middle school youth, with varied backgrounds and experiences with emerging technologies, develop maker identities and responsible technology design skills through a series of co-design workshops. We engaged a team of three youth participants and four adult researchers, to develop Milfoil Milly, an AI-powered robotic fish system for detecting invasive milfoil. The process of developing Milfoil Milly through co-design offered an opportunity to investigated (Q1) how designing technology solutions shapes youth identity as technology creators, (Q2) their conceptualizations of sustainability in design solutions, (Q3) their consideration of responsible technology development, and (Q4) how the co-design process impacts both the learning and design experience for youth.

AI technologies have become increasingly embedded in children’s lives. While there are many frameworks for designing AI technologies for children’s well-being, few have been tested against the tensions children experience when using AI across different global contexts. This workshop explores how to design AI technologies that enhance children’s digital well-being in accordance with various developmental and child-computer interaction frameworks, as well as what developers and designers should consider as they do so. Our goal is to convene an interdisciplinary international community to pave the way for future research and practice that seeks to design AI technologies with children’s well-being in mind.

Background: Prior research argues that positive learning environments support student learning, belonging, and the desire to continue learning. In order to create joyful learning environments, we must first study what characterizes such learning spaces. However, prior research has not yet asked students what makes CS learning environments joyful. Objective: In this study, we sought to understand students’ joyful experiences in secondary CS classrooms and the elements of the learning environments that fostered those experiences. Method: We interviewed 8 students who had joyful CS experiences about those experiences, the environments in which they occured, and about the pedagogies their teachers used. We then interviewed 5 of their teachers to better understand the environments and pedagogies that cultivated joyful CS experiences. Findings: We found 4 elements in common in each student’s experience: teachers worked to relate to students, prioritize a relationship with learning, frame CS with purpose, and reify a joyful CS experience. Implications: These findings offer the opportunity for researchers and educators to reconsider pedagogies and design learning environments that engender joyful CS experiences for students. This will better enable students to build relationships with CS.

This workshop will bring together researchers and educators to imagine a future of low-cost, widely-available digital making for children, both within the STEAM classroom and beyond. In particular, we are interested in expanding the reach of digital making with programmable microcontrollers (such as Arduino, the BBC micro:bit, etc.) to underrepresented children in the STEAM fields, which includes historically excluded or marginalized children as well as those lacking access to computers and/or the Internet. Participants will report on their experience helping children learn about digital technology while creating wearables, robotics, environmental sensors and more. Participants who submit a position paper or work-in-progress report will have an opportunity to present their work and ideas. From these presentations, we will select emerging themes to discuss.

Beyond broadening access to computer science (CS), we want to provide just and excellent CS instruction to all of our students. We have not yet reached that goal. In addition to explicit access barriers to CS, we need to know what implicit barriers are preventing students from engaging in deep CS learning? and where are these power structures disassembled, and classrooms are re-imagined? To surface some of these barriers, I used qualitative methods to examine a secondary CS elective summer classroom and the counternarratives students created, and what tensions they faced. I conducted semi-structured interviews with candidate CS teachers as they decide whether or not to enroll into a certification program to better understand what factors enabled and prevented them from becoming CS teachers. I conducted semi-structured interviews with secondary CS teachers, post secondary instructors, and students to understand what they perceived rigorous learning to be and learned what prevented rigorous learning. I want to identify and find spaces where these power structures have been disassembled – and examine what those spaces hold in common.

Objectives: Assessments play a crucial role in computer science courses by providing insights into student learning. While previous research has explored various aspects of assessments, little attention has been given to assessment policies that instructors devise and their impact on students’ experiences. Our goal was to investigate: How do assessment policies shape marginalized students’ experiences in coding classes?Method: We conducted 19 semi-structured interviews with post-secondary students currently enrolled in or completed a class where their code was evaluated. To recruit, we primarily targeted students from underrepresented racial groups in computer science. Many of these students attended large 4-year public universities. During the interviews, we inquired about students’ experience with different assessment policies and how those policies affected their lives and experiences completing the assignments. Results: Our findings revealed ten distinct ways policy and students’ lives interacted to create or heighten inequities, which significantly shaped marginalized students’ lives. Many policies did not consider the unique experiences of their students and students’ needs. Additionally, due to unclear and strict policies, students experienced frustration, confusion, and demotivation, consequently diminishing their sense of belonging in computer science and weakening their self-efficacy as programmers. This reveals the negative consequences of poor assessment policy choices and provides insight into how assessment policies can create barriers to learning computer science for marginalized students.

Many computer science education efforts promise liberation and equality, but that promise often goes unfulfilled. Teaching computation through E-textiles has been one way to achieve this promise because it has increased student engagement and enabled identity work. Although some approaches to teaching CS through E-textiles have been demonstrated as effective, there is not yet work using a programmable electronic embroidery machine (computational embroidery), or work that makes culture itself a topic of learning. In a six-week summer school course, we explored this opportunity, teaching a culture-centric embroidery class that combined hand embroidery and computational embroidery. Students incorporated their identities into their projects by using a block-based coding language to create embroidered patterns. They enthusiastically engaged with the programming aspects of the course and sought to make complicated and beautiful work that interwove their diverse cultures and identities. This paper offers insights into what it is like to teach computing with a cultural lens. Our curriculum and pedagogy offer instructors a template to incorporate these technologies and topics into their courses.

In this Birds of a Feather (BoF) session, we aim to foster a safe and open environment that allows CS education (CSEd) graduate students to share about their graduate experiences and learn from each other about graduate school, conducting research, and navigating the inherently multi-disciplinary space of CSEd. We have two main goals: (1) create specific networking opportunities between CSEd graduate students attending SIGCSE TS (hereafter just "SIGCSE") in order to foster a community of support, and (2) elicit discussions on the triumphs and tribulations that come as part of being a CSEd-focused graduate student. We plan for all attendees to leave our session with connections to fellow CSEd graduate students from other institutions (through email and a dedicated Slack) and a greater awareness of the community available to them within CS education research.

Automated hiring algorithms are increasingly used in computing job recruitment. Prior work has examined perceptions of algorithmic fairness and established bias in hiring algorithms, but there is limited work on the ability of computer science students, who are applying for their first computing job, to overcome new barriers posed by automated hiring. To investigate what challenges students face, how they work through them, and their perceptions of these systems, we conducted semi-structured interviews with post-secondary students who were first-time computing job applicants. Analyses revealed that participants had diverse knowledge of hiring algorithms; some people knew to use strategies, such as keywords in resumes, online assessment practice, and referrals to circumvent automated processes to progress to in-person interviews, but others were entirely unaware of the automation. Participants also expressed that current systems prevented them from demonstrating the full extent of their skills and attributed job offers to personal contacts within the company. While some deemed automation a "necessary evil" to combat scale, many struggled with the inequity automated hiring processes perpetuated. Understanding student experiences and perspectives with automated hiring has relevance for how current computer science curricula prepares students for the transition to computing jobs post-graduation. Our findings have implications for how to develop new practices to better support students in their transitions amid a changing hiring landscape.

Abstract Beyond broadening access to computer science (CS), we want to provide just and excellent CS instruction to all of our students. We have not yet reached that goal. In addition to explicit access barriers to CS, we need to know what implicit barriers are preventing students from engaging in deep CS learning? To surface some of these barriers, I used qualitative methods to examine a secondary CS elective summer classroom and the counternarratives students created, and what tensions they faced. I conducted semi-structured interviews with candidate CS teachers as they decide whether or not to enroll into a certification program to better understand what factors enabled and prevented them from becoming CS teachers. I conducted semi-structured interviews with secondary CS teachers, post secondary instructors, and students to understand what they perceived rigorous learning to be and learned what prevented rigorous learning.

Teachers are essential to equitably broadening participation in computing in schools, but the creation of CS teacher education pathways faces many challenges. In this experience report, we share the many political, administrative, institutional, and sustainability barriers our institution faced in creating a secondary CS pre-service pathway. Throughout, we discuss the particular design choices we made in order to center equity and justice, both in the content of the program, but also in its structure, policies, and resources, which were often in tension with state standards and policies. We also describe our experience teaching and supporting the inaugural cohort of graduates as well as the graduates' experiences, which revealed tension between utopian and dystopian futures of computing and their role in helping students navigate them. We end with a reflection on key factors that we believe led to its successful first year launch, including leadership, interdisciplinarity, capacity, timing, and funding, and on sustainability concerns, including tuition subsidy and instructional capacity.

Objectives. Teachers are essential to making computing education available to students. A key place to sustainably prepare computer science (CS) teachers is in pre-service preparation programs, which are often required for certification in the United States. Prior work has examined many reasons that people choose to become teachers — or choose not to — but little prior work has examined factors that shape the pursuit of CS certifications in pre-service in particular.

Computing education research (CER) has used demographic data to understand learners’ identities, backgrounds, and contexts for efforts such as culturally-responsive computing. Prior work indicates that failing to elucidate and critically engage with the implicit assumptions of a field can unintentionally reinforce power structures that further marginalize people from non-dominant groups. The goal of this paper is two-fold: to understand what populations CER researchers have studied, and to surface implicit assumptions about how researchers have collected, reported, and used demographic data on these populations. We conducted a content analysis of 510 peer-reviewed papers published in 12 CER venues from 2012 to 2021. We found that (1) 60% of papers studied older learners in formal contexts (i.e. post-secondary education); (2) 68% of papers left unclear how researchers collected demographic data; and (3) while 94% of papers were single-site studies, only 14% addressed the limitations of their contexts. We also identified hegemonic norms through ambiguous aggregate term usage (e.g. underrepresented, diverse) in 23% of papers, and through incomplete reporting of demographics (i.e. leaving out demographics for some participants in their sample) in 35% of papers. We discuss the implications of these findings for the CER field, raising considerations for CER researchers to keep in mind when collecting, reporting, and using demographic data.

Part of broadening participation in computer science (CS) is understanding what experiences and identities students bring with them to the classroom and building upon them. Prior work has often achieved this by connecting CS concepts to cultural ideas and practices. Increasingly, however, youth may be encountering sociotechnical and sociopolitical counternarratives about computing, power, and justice, offering new opportunities to connect CS to students' lives. To understand what role these emerging counternarratives have in secondary CS classrooms, we taught a co-constructed high school course to a racially, ethnically, socioeconomically, and gender diverse classroom, framing the course as both a creative and critical introduction to CS, giving agency to students to incorporate critical themes into their learning. We gathered notes, artifacts, and student responses over the course of 6-weeks, and analyzed the extent to which students brought critical themes into their creative work, developing critical consciousness of CS concepts. We found that before there was space for critical conversations about computing, we had to navigate students' issues of trust, positionality, and the broader inequitable systems of education in which the class occurred. Only after navigating those tensions did students feel safe to have those critical conversations. Once they did, they rapidly embraced the counternarratives, structured their learning around them, and used them to build community and support each other.

Motivated by the need to develop equitable and just computer science education, we implemented a resubmission policy. We ran a large-scale, end-of-term survey of all students across two large introductory CS courses asking about their reasons for resubmission. Though some students were motivated primarily by grades, many responses suggested intrinsic motivation. We interviewed 9 students and found that in our competitive program, resubmissions take the pressure off the need to submit work that earns a perfect grade the first time. However, our findings suggest that resubmissions alone can't create space for equity and belonging.

As computing courses become larger, students of minoritized groups continue to disproportionately face challenges that hinder their academic and professional success (e.g. implicit bias, microaggressions, lack of resources, assumptions of preparatory privilege). This can impact career aspirations and sense of belonging in computing communities. Instructors have the power to make immediate changes to support more equitable learning, but they are often unaware of students' challenges. To help both instructors and students understand the inequities in their classes, we developed StudentAmp, an interactive system that uses student feedback and self-reported demographic information (e.g. gender, ethnicity, disability, educational background) to show challenges and how they affect students differently. To help instructors make sense of feedback, StudentAmp ranks challenges by student-perceived disruptiveness. We conducted formative evaluations with five large college computing courses (150 - 750 students) being taught remotely during the COVID-19 pandemic. We found that students shared challenges beyond the scope of the course, perceived sharing information about who they were as useful but potentially dangerous, and that teaching teams were able to use this information to consider the positionality of students sharing challenges. Our findings relate to a central design tension of supporting equity by sharing contextualized information about students while also ensuring their privacy and well-being.