As computer science (CS) becomes a foundational part of K-12 education, universities face increasing pressure to prepare pre-service teachers to deliver highly effective CS instruction. However, most teacher preparation programs lack structured pathways to develop CS teachers, and leaders of these programs often feel unprepared to provide CS instruction. Therefore, the PrepareCS Project is a three-year initiative that brings together university teams from across the United States to develop sustainable CS teacher preparation programs. This paper reports on the first year of the project, using data from focus groups with university representatives to explore the challenges they faced while developing their CS teacher pathways. Findings reveal that teams encountered issues with program constraints, policy barriers, and communication problems. Lessons learned include the importance of establishing clear roles and communication protocols, strategically building community, applying best practices for interdisciplinary virtual teams, and developing marketing plans in tandem with program development. These findings offer timely guidance to researchers, policymakers, and educational leaders seeking to meet the growing demand for CS education and expand access

Identifying students who struggle during programming tasks remains a persistent challenge in computer science education, often resulting in delayed interventions and untimely support. Keystroke data analysis has emerged as an approach for capturing students' coding behaviors and identifying those who might have difficulties. This is made possible due to the granular nature of the data. By examining the keystroke dynamics such as typing speed, frequency of deletions, pauses and code reconstruction, it becomes possible to make an inference of the level of confidence, frustration and hesitations students experience during programming tasks. Nevertheless, while keystroke data can reveal insightful patterns, the interpretation of the results is complex and requires complementary data sources to validate inferences about students' struggles or confidence. This study introduces TrackIt a rule-based system designed to detect struggling programming students by analyzing keystroke data in conjunction with self-reported survey responses. By applying a series of predefined thresholds and scoring rules, TrackIt computes a struggling score that categorizes students into five struggle levels. The system was validated in an introductory Python course involving 40 students with data collected from 547 labs and 130 homework keystroke logs, alongside structured post-assignment surveys. Results revealed that TrackIt effectively identified key struggle behaviors such as long pauses, frequent deletions, low insert-delete ratios and copy-paste events. These indicators closely aligned with students' self-reports, particularly for challenging assignments

The continuous rising of digital learning platforms has unarguably brought about a surge in the amount of data obtained from different learning environments, which presents a great opportunity for computer science teachers to gain an understanding of students' coding processes. This is vital for enhancing student support as teachers can gain insights into students' thought process, strategies and identify areas where students might be struggling while tackling programming tasks. Traditional assessment methods such as feedback after homework submissions or completed lab assignments often results in late and untimely intervention that would prevent early dropouts and massive failures as the students' learning journey is neglected. We leverage students' keystroke data obtained from Python and Java-based introductory programming courses delivered through CODIO learning platform - covering 3 semesters and having 13 programming assignments each, to design an interactive code visualization platform using Streamlit. The application features an interface that reproduces students' code snippets with JavaScript enabled syntax highlighting. It includes a combination of dropdown menu and an adjustable slider which enables an instructor to navigate through the timestamps and have a detailed view of students' coding processes. The intervention ultimately fosters a more supportive learning environment and helps boost students' confidence.

The application of mastery learning, where students progress through their learning in a self-paced manner until they have mastered specific concepts, is considered appealing for teaching introductory programming courses. Despite its growing popularity in computing and its extensive use in other disciplines, there is no overview of the design of courses that use mastery learning. In this position paper, we present an overview of five mastery learning models and discuss examples of how these can be applied in practice, both in foundational programming as well as more advanced courses. Our analysis focuses on the student progression through the course, the assessment structure, and the support for self-paced learning, including for struggling students. This work provides a greater understanding of mastery learning and its application in a computing education context.

In the United States 1 in 5 people live in a rural area, and many other countries also have large rural populations. These rural populations face many challenges that make them less likely to engage with computer science education. Studies with specific rural populations have demonstrated that those students have less access to and engagement with educational opportunities involving computer science, and that these disparities are even greater for intersectional populations who are both rural and from a recognized group underrepresented in computer science. Moreover recent sociological research has suggested that rural populations share a complex and cohesive group identity that goes beyond "living in a rural area". While many universities and institutions are making inroads in understanding and engaging our rural populations, these efforts are often in their infancy and there is much for us to learn. In this session, we will facilitate a discussion of the challenges facing our varied rural populations and how the members of this community are seeking to address them. We invite anyone who wants to learn and/or share about ongoing efforts, identify challenges (and potential research questions), disseminate best practices, and forge new collaborations to join us.

As K-12 computer science education grows, so does the imperative for universities to prepare highly qualified computer science teachers. An increasing number of SIGCSE participants either have developed programs at their universities to credential CS teachers in their states, or are interested in doing so. This BOF provides an opportunity to build community, share best practices, and address challenges in creating CS teacher preparation programs. We particularly welcome participants from Colleges of Education.

If computer science programs face a challenge of convincing students that programming is fun and achievable, they have nothing on mathematics departments who face societal beliefs that math is hard and scary. Several movements in computer science education have focused on broadening participation within computer science and across disciplines. The "CS + X" efforts have focused on helping computer science integrate into other disciplines. The "CS For All" movement has highlighted the importance of providing high quality computing education for all students. Simultaneously, there is increasing attention to the need to provide general education alternatives to college algebra. This paper describes a course designed to combine these goals: a course that uses programming to introduce students to functions, patterns, and spatial and computational thinking in order to meet quantitative reasoning goals set by the university. The course initially used Bricklayer as the programming environment, then transitioned to Processing. Students were successful in writing programs that created art, demonstrated mastery of quantitative literacy, and had improved attitudes following the course. This project suggests that in addition to the creation of introductory computer science classes, courses which embed computer science into disciplinary requirements can be a successful pathway to expand opportunities for students to learn computing.

The Computer Science Teachers Association (CSTA) Professional Development (PD) committee is responsible for curating a list of PD opportunities for dissemination to CS teachers. The committee developed and revised a research-based rubric and has used it to accredit PD programs that meet a baseline of quality. This paper reports on the process of accreditation and trends in CS teacher PD, as well as recommendations to PD providers based on trends in the data collected by the committee. This paper is a story of the evolution of the accreditation process and the tool used to measure quality PD. PD providers are encouraged to adopt best practices in supporting teacher growth.

In order to fully prepare high-quality teachers to deliver on the promise of CS for All, teacher preparation programs must ensure teacher candidates have mastered both content and the pedagogy to teach that content well. University CS departments are well-positioned to teach the content, but "methods courses" are an important source of pedagogical and pedagogical content knowledge for future computer science teachers. This panel will describe a variety of approaches: Colleges of Education or CS departments; in-person, hybrid, or online course delivery; and standalone "CS Methods" courses or CS integrated in broader methods courses. Each panelist will describe their course. The moderator will elicit common features between the courses as well as the strengths and weaknesses between different approaches.

Through the eyes of professional women in computing, we can better understand the impact of workplace structures, higher education pathways, and the particular closed nature of the tech industry. This study of women's life histories contributes to the work of in-depth qualitative examinations of CS learning contexts and psychological studies investigating phenomena such stereotype threat which contextualize the experience of women in computing environments. Drawing inspiration from Margolis and Fisher's (2002) work drawing the "blueprints" of the "boy's clubhouse" of computing education, as well as McDermott and Webber's (2013) analysis of when math learning occurs, we ask when, where, and how is gender being invoked and created, as a way to unpack the places, events, and interactions that shape women's participation in the Silicon Valley workforce. This qualitative analysis of 13 life history interviews with professional women in computing shows that gender becomes salient for women in public settings, particularly in early adulthood when women enter male-dominated classrooms, teams, and workplaces that foster 'brogramming' culture. CS educators, hiring managers, and recruiters all need to be aware that the effects of gender go beyond just including more women in classrooms and on teams. The learning environment, incentives for participation, and the goal of diversity all need to be better aligned in order to foster an equitable workforce.

As primary and secondary computer science offerings expand across the United States and other countries, there is a growing demand for educators who can teach CS. One way to meet the demand is to include CS content and instruction in teacher preparation programs, at the inservice (practicing teachers) and/or preservice (becoming a teacher) levels. This workshop is designed for higher education faculty from CS and Education departments as well as teachers who support CS education programs and would like to learn more about creating pathways for preparing teachers to teach CS. The workshop will provide rationales for CS teacher preparation programs (including how to develop and sustain the programs), detail what teachers need to know and be able to do to teach CS, review dimensions and examples of existing programs, and share resources to support CS teacher preparation program development. Participants will have an opportunity in the last hour to work on developing a CS program for their institution and writing an action plan of 2-3 short term goals to support program development.

What teacher knowledge and skills are necessary for effective instruction of K-12 computer science? In recent years, standards and a national framework have delineated universal learning student outcomes in K-12 computer science (CS) education, but there has been less focus and coherence on what is required of teachers to prepare their students to equitably meet these learning outcomes. The 2020 CSTA Standards for CS Teachers were designed to meet this need. In this BoF session, we will provide a platform to discuss the evidence base aligned to each of the five teacher standards: (1) CS Content Knowledge and Skills, (2) Equity and Inclusion, (3) Professional Growth and Identity, (4) Instructional Design, and (5) Classroom Practice. Participants will share their knowledge and experience in a facilitated conversation organized around focal questions for each standard.

This Full Paper in the Research to Practice Category reports on an empirical empirical study in which novel educational tools and techniques were employed to teach fundamentals of problem decomposition - a cognitive task transcending disciplines. Within the discipline of computer science, problem decomposition is recognized as a foundational activity of software development. Factors that contribute to the complexity of this activity include: (1) recognizing patterns within an algorithm, (2) mapping the understanding of an algorithm to the syntax of a given programming language, and (3) complexity intrinsic to the problem domain itself. Cognitive load theory states that learning outcomes can be positively affected by reducing the extraneous cognitive load associated with learning objectives as well as by changing the nature of what is learned. In the study reported upon here, a novel instructional method was developed to decrease students' cognitive load. Novel instructional content supported by a custom visualization tool was used in a classroom setting in order to help novice programmers develop an understanding of function-based problem decomposition within the context of a visual domain. Performance on outcome measures (a quiz and assignment) were compared between the new method and the traditional teaching method demonstrated that students were significantly more successful at demonstrating mastery when using the new instructional method.

Computational Thinking Bins are stand alone, individual boxes, each containing an activity for groups of students that teaches a computing concept.We have a devised a system that has allowed us to create an initial set, test the set, continually improve and add to our set. We currently use these bins in outreach events for middle and high school students. As we have shared this resource with K-12 teachers, many have expressed an interest in acquiring their own set. In this paper we will share our experience throughout the process, introduce the bins, and explain how you can create your own set.

As computer science becomes more prevalent in the K-12 world, elementary schools are increasingly adopting computing curricula. Computer scientists have recognized the connection between math and computer science, but little work has demonstrated how and whether computer science can support improved learning in math. This paper reports on a project in which elementary students in a gifted program used Bricklayer, a functional programming environment that supports artistic and mathematical expression. A pre- and post-test design demonstrates significant learning gains in coordinate graphing and visual-spatial skills.

The underrepresentation of women in computing is an enduring problem in the U.S. This work seeks to increase women's retention in computing, to change the culture of introductory computer science classes to make them comfortable for diverse students, and to understand what factors are affiliated with interest and persistence in computing.

In this basic interpretative qualitative study, middle school girls with no formal experience in algorithmic reasoning, abstraction, or algebra were interviewed individually in order to help understand and explain how they think about algorithmic efficiency. A contextually relevant problem (determining the maximum height an "egg-drop contraption" could be dropped without breaking) was described to the students who were then asked 1) to come up with the most efficient solution they could to the problem while describing their thinking for the interviewer; and 2) to determine, from a choice of three solutions proposed by the interviewer, which is the most efficient.

Mobile phone programming can provide teens an authentic and engaging hook into computer science. With App Inventor, developed by Google and moved to MIT, programming Android apps is as easy as clicking blocks together. App Inventor has been used successfully in after school programs, roadshows, summer camps, teacher workshops, and computer science classrooms from middle school through college. Participants will get an overview of App Inventor including project ideas and sample student code, hear outreach planning suggestions, write programs, develop outreach plans, and see how the Java Bridge helps transition from App Inventor to Java. Please bring a laptop with App Inventor. Even the most time-stretched professor or teacher can encourage students in computer science with App Inventor.

We often learn of successful pedagogical experiments, but we seldom hear of the the ones that failed. For this special session we solicited submissions from the SIGCSE membership, selected the best from among these, and will have presentations at the session by the selected authors. Our contributions describe pedagogical approaches that seemed to be good ideas but turned out as failures. Contributors will describe their pedagogical experiment, the rationale for the experiment, evidence of failure, and lessons learned.

In 2006, computing education was suffering from a crisis - enrollments were dropping sharply at universities and colleges across the United States, and interest in computing from high school and middle school students was waning significantly. At the 2007 SIGCSE Symposium, the ACM Education Board organized a special session to explore the underlying causes [7]. In his keynote at the same conference, Grady Booch exhorted us to share the "passion, beauty, joy and awe" (PBJA) of computing [4]. This led to a series of room-packed sessions at the following three SIGCSE symposia to explore that idea from different perspectives [8, 9, 12]. They have provided a forum for sharing: " What we've done: Highlighting successful PBJA initiatives the presenters have undertaken or seen and wish to celebrate. - What we should do (curriculum): Pointing out where our curriculum is lacking in PBJA, and how to fix it. - How we should do it (pedagogy): Sharing how a change in attitude / focus / etc. can make strides to improving PBJA. Fortunately, enrollments have been continually rising, and there are colleges where the numbers are so strong (returning to historic highs), that some claim the crisis is over [10, 13]. Many dispute this, however, citing statistics that indicate under-represented students have not returned, and continuing negative connotations about the field [2]. Also, recent news of limited hiring in the information technology sector could have a damping affect [11]. This PBJA "movement" was born out of this enrollment crisis, but is not tied to it. There is always value in sharing novel best practices and advocating techniques that make computing fun. In the past, we tried to gather educators who brought a wide variety of perspectives (e.g., in 2010 we heard from international, domestic, high school, university and industrial representatives). This year, we've shifted from that "breadth-first" model to a "depth-first" one, and have invited three K-12 teachers who, collectively, have taught computing at an all-girls middle school, an under-served high school, and an affluent high school. The hope with this panel is to be able to drill down and understand the K-12 space, in terms of extolling the PBJA of computing.