Although computational thinking (CT) and computer science (CS) skills are important for all students, less attention exists in research and practice for CT and CS and students with disabilities. Researchers conducted a systematic review of the literature following the PRISMA protocol to examine the current state of literature regarding CT and/or CS instruction for students with disabilities; researchers also analyzed the existing literature with regards to quality indicators. Over the last decade (2014-2024), researchers found six articles focused on CT and/or CS and students with disabilities. Of these, two were found to be methodologically-sound based on the quality indicators from the Council for Exceptional Children, both conducted by the same research team and focused on block-based coding of robots. Overall, the researchers concluded the systematic review highlighted the lack of attention to CT and CS for students with disabilities and the need for both more research as well as high-quality research that adheres to quality indicators for the research design implemented.

As generative AI (GenAI) becomes an integral component of the socio-technical landscape in teaching and learning, it is crucial for teacher education programs to prepare pre-service teachers to assess its affordances and limitations. However, research on pre-service teachers' attitudes toward GenAI is still emerging. Understanding these perspectives is essential for informing teacher education programs about where pre-service teachers stand and how to advance their AI literacy. This article explores pre-service teachers' understanding and application of GenAI for their envisioned future classrooms. We collected data from pre-service teachers at a Midwestern United States public university, analyzing 17 survey responses quantitatively and conducting qualitative analyses of eight interviews and two lesson design challenge case studies. Our findings indicate that pre-service teachers generally held positive views about GenAI, particularly in terms of its potential for lesson planning, resource creation, and reducing workload. However, they expressed concerns about students' over-reliance on AI, which they thought could potentially undermine teacher-student interactions. Furthermore, the study found that pre-service teachers identified limitations while using ChatGPT for lesson design and recognized its shortcomings, especially when they had strong content knowledge.

As demand for K-12 computer science (CS) education grows, we argue that most students would be best served by CS classes that not only teach computational thinking/programming, but also challenge them to critically analyze the role of technology in society. One of the main barriers to implementing this in K-12 classrooms is a lack of research on how in-service CS teachers can integrate critical pedagogy into their school context and existing curricula. This poster presents results from a study to co-design lessons with current K-12 CS teachers to integrate critical perspectives into their classrooms. Teacher participants participated in a synchronous professional learning series in whichwe taught them critical computing content drawn from relevant books and frameworks. Following this, we collaborated with the teacher participants to design or modify lessons that engage their students in critical analysis, which the participants then implemented in their classrooms. Teachers were encouraged to include content relevant to their students and the communities they are a part of. We conducted thematic analysis of transcripts from the interviews, professional learning series, and co-design sessions. The resulting eight (8) themes demonstrate the challenges and opportunities inherent in integrating critical perspectives into K-12 computing education. In the long term, results from this work will inform future sociocultural content integration into K-12 CS courses (e.g. "ethics content").

As generative AI reshapes K-12 education, U.S. states are rapidly developing guidance to navigate its implementation. This study investigates the structural composition of AI education guidance across thirty-five states through qualitative document analysis. Utilizing the CAPE framework and the concepts of policy resilience versus fragility, the research examines how state-level signals influence systemic preparedness for AI education. Findings reveal a landscape of structural fragmentation, where guidance often prioritizes risk mitigation over pedagogical innovation. These early policy choices have potential to shape teacher capacity and sustainability, determining whether AI fulfills its promise of empowerment or widens existing education opportunity gaps.

Justice-centered computing scholarship has made significant efforts in broadening the participation of underrepresented groups, particularly along the lines of race, gender, and class. However, the role of immigrant students' national identities in these efforts have been largely ignored. In this lightning talk, we present preliminary findings from an ongoing study that explores the perspectives of computer science teachers - who work in classrooms with students from diverse national backgrounds - about national identity and national culture. The study examines how these computer science teachers understand the role of students' national identities and national cultures within the CS classroom. Our study was guided by the following research question: how do computer science teachers understand the national identities and national cultures of their students? We focus on three findings: first, the role that teachers place on national identity and national culture in students' sense of self, second, the ways in which teachers understand how national culture intersects with students' family cultures and age groups, and third, the influence of national identity and national culture on students' learning experiences within the classroom. These insights provide nuanced perspectives to broadening participation efforts in computer science education.

Ethnocomputing describes the study of computational ideas and thinking as they appear in the artifacts, epistemologies, designs, and practices of temporally and spatially situated communities (e.g., from computational scientists to textile artisans). It is also about how such communities embed their beliefs and values within computational artifacts. One outcome of ethnocomputing research is the demonstration of how Indigenous and diasporic communities have dynamic computational histories and innovations that are relevant to computer science and computer science education today. From lessons on e-textiles and Native American botanical knowledge to visual programming environments that reveal the algorithms of cornrow braiding in the Black diaspora, this has allowed for anti-racist challenges to white supremacist myths of primitivism in primary and secondary computer science education. While there are studies about how ethnocomputing tools and lessons shape children's attitudes toward and knowledge of computing, there is no research on what computer science teachers think about one of ethnocomputing's foundational assumptions: computational ideas and thinking are embedded within Indigenous and vernacular artifacts, epistemologies, designs, and practices. This paper reports findings from interviews with 14 K12 computer science teachers who had been exposed to ethnocomputing educational technologies and activities. From our qualitative analyses, we found that most (n=12) teachers believed that Indigenous and/or vernacular artisans think computationally. We detail their lines of reasoning before turning toward teachers who had ambivalent (n=1) or negative (n=1) positions about this assumption of ethnocomputing research. We discuss the implications of these findings for anti-racist K12 computer science teacher professional development.

This poster examines the commitment of the computer science (CS) education community to equity and justice. By analyzing 146 public pledges from 119 organizations using the Kapor Center's Culturally Responsive-Sustaining Computer Science (CR-SCS) Framework, we assessed focus areas such as racism, inclusive classroom cultures, rigorous curriculum, student voice, community engagement, and diverse experts. Findings show efforts in affirming student identities and community involvement but reveal gaps in addressing racism and recruiting diverse speakers. The results highlight the need for a comprehensive approach to ensure equity and inclusions in CS education. This study provides crucial insights into the current state of CS education and emphasizes the importance of holistic commitments towards justice.

This study explores the impact of computational thinking (CT) on enhancing metacognitive strategies among young learners. We conducted one-on-one video interviews with four fifth-grade students as they participated in an adapted version of the unplugged CT activity, Bebras's (2019) Programming Lamps Task. Our findings suggest that CT particularly contributes to the development of self-monitoring and evaluation strategies, such as continuous assessment of one's performance and adopting new strategies and exploring alternatives when existing solutions fail. These were particularly evident as students decomposed problems and developed step-by-step solutions in response to evolving challenges within the task scenarios. Overall, this paper discusses the potential connection between CT and metacognitive strategies, focusing how CT can be a valuable tool for teachers in developing their students' problem-solving abilities and academic performance.

With over 22 million students enrolled in PreK-5 grades in the United States alone, we recognize that this is an important opportunity to bring computer science (CS) education to millions more students than who have traditionally had access. It also presents a unique opportunity to embrace teaching computer science in these early grades that is highly inclusive, engaging, and even blended with traditional subjects taught in these early years. In this panel, we bring together a collection of experts in the PreK-5 field, including researchers, a curriculum designer, and teachers, to discuss promising practices for including CS instruction in the PreK-5th grades, focusing in particular on PreK-2nd grades. The intended audience for this panel includes researchers and practitioners who are interested in CS in the early elementary and early childhood years. This topic is highly relevant to the SIGCSE community since it brings together teachers, curriculum designers, and researcher perspectives into a shared space to highlight the ways schools, teachers, and researchers can think about successfully adding computer science into young children's education.

The rationale behind teaching computational thinking (CT) integrated science activities is to provide students with a more meaningful context to learn CT and introduce computational tools and practices that support science learning. However, the current literature primarily focuses on students' CT learning within computer science and programming environments at the secondary school level, with less research on how CT can support science learning at the elementary level. Furthermore, there are even fewer studies on how to support elementary teachers and develop their knowledge and efficacy to connect CT to their science instruction. This study examines the influence of CT-integrated science professional development (PD) on elementary teachers' CT understanding and their teacher self-efficacy when planning and facilitating CT-integrated science lessons. A mixed-method design was used, incorporating surveys and interviews to gain a deeper understanding of the impact of PD on elementary teachers. Results suggested that the PD increased teachers' understanding of the value of CT instruction, their self-efficacy for teaching CT, and their belief in their ability to plan and facilitate CT-integrated science lessons. These findings suggest the need for subject-specific PD to support teachers in integrating CT to enhance disciplinary learning in science and to increase their confidence. Additionally, teachers require further PD to integrate plugged CT activities into their classroom instruction.

Computational Thinking (CT) is viewed as a set of foundation skills required to solve problems efficiently and effectively, with or without the use of technology. It has also been argued that CT can provide connections between computing and other core curriculum areas which can be beneficial for student learning outcomes. However, there are still gaps in elementary teachers’ understanding of CT, and how to integrate CT within the core curriculum. This qualitative study used a case study approach and examined how elementary teachers from a school district in the Midwest of the United States learned CT and designed CT-integrated lessons. We used the Interconnected Model of Professional Growth (IMPG) as a framework to structure our understanding of what factors within each domain supported or undermined the teachers when learning and integrating CT across core curriculum areas. Our study provides insight on what factors can support or impede elementary teachers’ understanding of CT and CT integration.

Teachers are increasingly integrating computational thinking (CT) into subject-area learning opportunities with the aim to meet both subject-area and CT learning goals. While prior work has identified CT practices synergistic to subject-area learning, less is published about pedagogical frameworks for instructional practices when integrating CT into content area teaching. This poster presents data from educators (teachers and professional developers) about what they find to be crucial factors for designing and implementing CT integrated lessons. Preliminary analysis indicates educators advocate for twenty practices including creating reflection opportunities, actively using CT vocabulary, opportunities for students to practice CT skills, meaningful real-world connections, utilizing scaffolding strategies, explicitly introducing CT practices, clear connections between CT and curricular content, using multiple modalities, and encouraging student discourse.

To address racial and gender inequality in K12 STEM and computer science education, there needs to be mutli-pronged approach. In addition to the needed work for curricula that is culturally responsive and sustaining, inclusive of all student group, and positively welcomes the identities of historically marginalized people groups, K12 computer science teachers need to be equipped with the training and tools to implement the curricula, pedagogy, and instruction to mitigate the racial and gender gaps in K12 computer science education. To address racial and gender inequality in K12 STEM and computer science education, there needs to be a multi-pronged approach. In addition to the needed work for curricula that is culturally responsive and sustaining, inclusive of all student groups, and positively welcome the identities of historically marginalized people groups, K12 computer science teachers need to be equipped with the training and tools to implement the curriculum, pedagogy, and instruction to mitigate the racial and gender gaps in K12 computer science education. Professional learning is an oft-used medium by curriculum providers as a means for teachers to adequately use boxed computer science curricula on computer science topics and content only. The panel proposes and will share how to implement culturally responsivesustaining pedagogy within K12 teacher professional learning, the importance of the integration of culturally relevant computational thinking and computer science strategies for K12 teachers, improved understanding of instructional practices that benefit all students in the CS classroom, and equity centered instructional coaching can all greatly improve chances of decreasing racial and gender equity gaps at the K12 level for historically marginalized student groups. Much of the presentation will share current tools and programming available to K12 teachers as well as propose scalable and replicable models for use in in-service teacher education broadly, and in-service computer science and STEM teacher professional learning across the nation.

In response to the enrollment surge that started in many CS depart- ments around 2006, the Computing Research Association published a report on "Generation CS", which named a pervasive theme in computing education: more and a greater diversity of students are seeking computing education, even if not as traditional CS ma- jors. However, our curricula and departments have stayed much the same. We still mostly prepare students for software develop- ment jobs in the technology industry, while we rarely identify the damage that same industry has caused in our democratic societies. How do we do better? How do we change to meet the needs of a changing society? What strategies should we apply? We know that large-scale change will require structural shifts, but such shifts are likely to be slow and expensive, whereas smaller, "boots on the ground" initiatives can positively impact individuals but do little to change the systems that underlie the deeper-seated problems in computing. Navigating this paradox is imperative to our success as a field. Our panel will address the big questions about how to make structural changes in computing education in order to meet the greater needs of Generation CS.

As demand for K-12 computer science (CS) education grows, we argue that most students would be best served by CS classes that not only teach computational thinking/programming, but also challenge them to critically analyze the role of technology in society. One of the main barriers to implementing this into K-12 classrooms is a lack of research on how in-service CS teachers can integrate critical pedagogy into their school context and existing curricula. This lightning talk presents a proposed method to co-design lessons with current K-12 CS teachers to integrate critical perspectives into their classrooms. Teacher participants will join a synchronous summer professional development where we will teach them critical computing content drawn from relevant books and frameworks, and collaborate with them to design or modify lessons that will engage their students in critical analysis. Teachers will be encouraged to include content relevant to their communities. For example, a teacher in Detroit might teach facial recognition in the context of continued use of the technology by police, despite wrongful arrests. Results from this work will inform future sociocultural content integration into K-12 CS courses (e.g. "ethics content"). Feedback from the audience will be used to improve the methods and literature review of the study.

Background and ContextRecent research suggests that there is work to be done in overcoming color-evasive ideologies in Computer Science (CS) education. In particular, we have limited insight into how to support white teachers in using Culturally Responsive Computing (CRC) approaches. This paper addresses this gap in the literature by analyzing interviews with white high school CS teachers through the lens of hegemonic whiteness.ObjectiveWe ask two questions 1) What are the gaps between these teachers' views on culture, community, and responsiveness, and how CRC envisions the interplay of these three elements? 2) How can we use teachers' understandings to reconceptualize presenting CRC to them in a manner that may best benefit their students?MethodWe use semi-structured interviews of nine teachers until data saturation. We use in-vivo and values coding in the first round and code-weaving in the second round to come up with emergent themes.FindingsOur findings show that these teachers did one or more of the following: 1) had dynamic but content-agnostic views about culture in the classroom; 2) focused on community connections with academia, industry, and/or parents; 3) framed the challenges of implementing CRC through a deficit lens; and 4) valued students' individuality, but were essentialist about student culture.ImplicationsWe have implications for practitioners, e.g. to have professional developments that allow teachers to name and challenge white supremacy in CS. We also have implications for researchers, e.g. to investigate ways in which white students and teachers can benefit from anti-racist CS education.

Neoliberal capitalism - the favoring of privatization, marketization, and deregulation of public resources - is hegemonic in education. It shapes our institutions and everyday life, including educational practices. The increasing push for market driven computing curriculum and large tech companies' involvement in research grants and educational programs are some examples of neoliberal influences in CS education. It is not only industry and industry-backed not-for-profits such as Code.org that reify neoliberal agendas, but in many cases, our very own communities, educational institutions, and curricula. Thus, a critical and reflective examination of our educational practices is necessary. In this Birds-of-a-Feather (BoF) session, we aim to conduct reflections and discussions on the role and influence of neoliberal capitalism in computing education. We will explore 1) the influence of deregulation, 2) public-private partnerships, 3) state-subsidized corporate wealth accumulation, and 4) centralization on pedagogy, research, and academic "success". We will discover reflective questions and practices that could help us critically examine our roles and responsibilities as computing educators and professionals. Eventually, we hope to begin a larger conversation and form a community to develop collective strategies and pedagogical ideologies to resist neoliberal influences, reimagine alternatives, and repair damages caused by neoliberal computing education.