Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1最新文献

{"title":"On Students' Usage of Tracing for Understanding Code","authors":"Mohammed Hassan, C. Zilles","doi":"10.1145/3545945.3569741","DOIUrl":"https://doi.org/10.1145/3545945.3569741","url":null,"abstract":"Explain in Plain English (EiPE) questions evaluate whether students can understand and explain the high-level purpose of code. We conducted a qualitative think-aloud study of introductory programming students solving EiPE questions. In this paper, we focus on how students use tracing (mental execution) to understand code in order to explain it. We found that, in some cases, tracing can be an effective strategy for novices to understand and explain code. Furthermore, we observed three problems that prevented tracing from being helpful, which are 1) not employing tracing when it could be helpful (some struggling students explained correctly after the interviewer suggested tracing the code), 2) tracing incorrectly due to misunderstandings of the programming language, and 3) tracing with a set of inputs that did not sufficiently expose the code's behavior (upon interviewer suggesting inputs, students explained correctly). These results suggest that we should teach students to use tracing as a method for understanding code and teach them how to select appropriate inputs to trace.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Complexities in Computer Science Teaching Attitudes and Beliefs: Findings of a Baseline Study of Elementary School Educators","authors":"Darcy M. Ronan, Dennis Brylow, Maverick Berner, Sydney Crespo, Heidi Williams, Christine Thorp, D. C. Erdil","doi":"10.1145/3545945.3569746","DOIUrl":"https://doi.org/10.1145/3545945.3569746","url":null,"abstract":"Teacher dispositions have strong empirical and theoretical ties to teacher motivation, professional choices, and classroom practices. The attitudes and beliefs of teachers can mediate students' access to and experience with computer science (CS) instruction. This paper presents a baseline study to illuminate initial characteristics, beliefs, and experiences with CS of an elementary school teaching population in multiple districts across two states. As part of their onboarding to a large CS outreach project, U.S. teachers (N = 791) from partnering elementary schools (N = 28) completed the T-ABC, a survey instrument designed to measure teachers' beliefs about CS education, growth-mindset and self-efficacy. Prior CS professional development experiences were associated with statistically significant differences in the CS Beliefs and Self-Efficacy dimensions of the T-ABC. We present and discuss an additional principal component analysis producing a seven factor model, with psychometric overview of factor extraction and loading. Further we begin to define emergent factors such as teacher determination, teacher fear, and epistemologically confused positivity from this analysis. Identification and measurement of teacher dispositions enables further analysis of how teacher beliefs may support or hinder effective practice in CS instruction, how teacher populations may differ, and how identified dispositions may change with exposure to various CS learning experiences.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122719680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Teamwork in CS1: Student Learning and Experience with POGIL","authors":"Helen H. Hu, Aman Yadav, Donna M. Gavin, Clifton Kussmaul, Chris Mayfield","doi":"10.1145/3545945.3569813","DOIUrl":"https://doi.org/10.1145/3545945.3569813","url":null,"abstract":"Employers regularly list teamwork as one of the most desirable skills they are seeking in college graduates. This paper describes a study about the effect of teamwork on student learning and classroom culture in a CS1 college class. In Fall 2021, an experienced college professor taught with POGIL for the first time in three sections of CS1. In two sections, students completed the POGIL activities in teams. In the third section, students completed the same POGIL activities individually. This study was then repeated in Spring 2022. In the fall semester, we observed a noticeable effect on classroom culture but no differences in student learning. In the spring semester, students in the sections with POGIL teams performed better on quizzes and programming assignments than those in the section where students worked individually. We discuss the implications of these results on collaborative learning in CS courses and the importance of student teams for faculty adopting POGIL.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128353566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Logistics, Affordances, and Evaluation of Build Programming: A Code Reading Instructional Strategy","authors":"A. Kapoor, Tianwei Xie, Leong Kwan, Christina Gardner-Mccune","doi":"10.1145/3545945.3569756","DOIUrl":"https://doi.org/10.1145/3545945.3569756","url":null,"abstract":"Computing students are expected to contribute to large unfamiliar codebases as they transition from university to industry settings. While computing courses provide students ample opportunities to write code independently or utilize abstract functionalities from standard libraries, students have fewer opportunities to read or extend codebases written by other programmers. This paper presents the logistics, affordances, and empirical evaluation of a novel instructional strategy, Build Programming, which is designed to promote code reading and extension in CS courses. In this strategy, a student (1) solves a programming problem, (2) is assigned a new codebase from a peer who solved the same problem, and (3) is asked to extend the assigned codebase to solve another problem. This allows a student to understand and extend an authentic codebase that is situated in a familiar context. In this paper, we shed light on the logistics of operationalizing this strategy in the context of an undergraduate Data Structures and Algorithms course (N=206). We also describe the affordances of this strategy through student experiences and evaluate the efficacy of one of these affordances, improving code quality through source code analysis. Most students (91%) proposed continuing Build Programming and students' code quality significantly improved after our strategy. Our findings underscore the benefits of Build Programming, and we hope that more instructors incorporate it in CS courses.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125162340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Executable Exams: Taxonomy, Implementation and Prospects","authors":"Chris Bourke, Yael Erez, O. Hazzan","doi":"10.1145/3545945.3569724","DOIUrl":"https://doi.org/10.1145/3545945.3569724","url":null,"abstract":"Traditionally exams in introductory programming courses have tended to be multiple choice, or \"paper-based\" coding exams in which students hand write code. This does not reflect how students typically write and are assessed on programming assignments in which they write code on a computer and are able to validate and assess their code using an auto-grading system. Executable exams are exams in which students are given programming problems, write code using a computer within a development environment and submissions are digitally validated or executed. This format is far more consistent with how students engage in programming assignments. This paper explores the executable exam format and attempts to gauge the state-of-the-practice and how prevalent it is. First, we formulate a taxonomy of characteristics of executable exams, identifying common aspects and various levels of flexibility. then give two case studies: one in which executable exams have been utilized for nearly 10 years and another in which they've been recently adopted. Finally, we provide results from faculty surveys providing evidence that, though not standard practice, the use of executable exams is not uncommon and appears to be on the rise.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123489682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foundations First: Improving C's Viability in Introductory Programming Courses with the Debugging C Compiler","authors":"Andrew Taylor, J. Renzella, Alexandra Vassar","doi":"10.1145/3545945.3569768","DOIUrl":"https://doi.org/10.1145/3545945.3569768","url":null,"abstract":"This paper presents the Debugging C Compiler (DCC), a system that composes a suite of compilers with static and dynamic analysis tools to support introductory C programming students. Using C in our introductory computing courses exposes students to low-level mechanics of the operating system, such as pointers and manual memory management - concepts critical in establishing a solid foundation of computing. Unlike typical C implementations, DCC provides programmers with enhanced, approachable run- and compile-time checking and messages. DCC clarifies C's cryptic operating system errors such as segmentation faults and alleviates the need for students to analyse memory dumps and tackle undefined behaviours. This paper describes DCC's implementation and features, and measures the tool's efficacy in aiding novice C programmers. We further present our deep reflections as to how DCC has enabled us to continue to use C in our large introductory programming courses, with an estimated five million compilations to date. Our research also outlines avenues for future work, which we hope will support others in delivering a foundations-first approach to introductory programming.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126369300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Do Intentions to Persist Predict Short-Term Computing Course Enrollments: A Scale Development, Validation, and Reliability Analysis","authors":"Rachel Harred, T. Barnes, Susan R. Fisk, Bita Akram, T. Price, Spencer Yoder","doi":"10.1145/3545945.3569875","DOIUrl":"https://doi.org/10.1145/3545945.3569875","url":null,"abstract":"A key goal of many computer science education efforts is to increase the number and diversity of students who persist in the field of computer science and into computing careers. Many interventions have been developed in computer science designed to increase students' persistence in computing. However, it is often difficult to measure the efficacy of such interventions, as measuring actual persistence by tracking student enrollments and career placements after an intervention is difficult and time-consuming, and sometimes even impossible. In the social sciences, attitudinal research is often used to solve this problem, as attitudes can be collected in survey form around the same time that interventions are introduced and are predictive of behavior. This can allow researchers to assess the potential efficacy of an intervention before devoting the time and energy to conduct a longitudinal analysis. In this paper, we develop and validate a scale to measure intentions to persist in computing, and demonstrate its use in predicting actual persistence as defined by enrolling in another computer science course within two semesters. We conduct two analyses to do this: First, we develop a computing persistence index and test whether our scale has high alpha reliability and whether our scale predicts actual persistence in computing using students' course enrollments. Second, we conduct analyses to reduce the number of items in the scale, to make the scale easy for others to include in their own research. This paper contributes to research on computing education by developing and validating a novel measure of intentions to persist in computing, which can be used by computer science educators to evaluate potential interventions. This paper also creates a short version of the index, to ease implementation.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126571047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Wolf in Lamb's Clothing: Computer Science in a Mathematics Course","authors":"Michèlle Friend, A. Swift, Betty Love, Victor Winter","doi":"10.1145/3545945.3569736","DOIUrl":"https://doi.org/10.1145/3545945.3569736","url":null,"abstract":"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.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134454337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opportunity Landscaping: Infrastructuring Healthy Learning Communities to Power Positive STEM Futures","authors":"Nichole Pinkard","doi":"10.1145/3545945.3569707","DOIUrl":"https://doi.org/10.1145/3545945.3569707","url":null,"abstract":"The communities in which we live and learn are largely the product of historical decisions related to race and ethnicity made by politicians, elected officials, and others with power and money. In Chicago, during the Great Migration, the Chicago Real Estate Board set up a committee that determined where Black residents could and could not live. In the 1930's redlining and greenlining funneled money and resources away from areas identified as \"bad investments,\" which were communities that were non-white, and toward white communities deemed to be a \"better investment.\" In the 1970s, desegregation mandates resulted in new magnet and selective enrollment schools that were open to anyone but required young people to travel far from their homes to attend. Today, boundaries, such as Wards and neighborhood school districts, continue to be drawn and redrawn-sometimes with the best intentions-in ways that fracture communities. These imprints of the past continue to impact ways of being today that continue to create an inequitable present that is not authentic to the needs and desires of the communities in those places. Creating a more equitable landscape for learning science, technology, engineering, arts, mathematics, and sports (STEAMS) in the future requires making the past and present of places visible and giving agency to communities to change their landscapes in ways that serve their current and future needs. Using lessons learned from over 20 years designing learning ecosystems in collaboration with cities, neighborhoods, affinity groups, civic learning institutions, and families, I will put forth the concept of opportunity landscaping as a hyperlocal ecosystem approach to supporting communities in visualizing and tuning their learning infrastructure to provide the learning places, spaces, resources, caring adults, and peers to nurture healthy STEM identities and lifestyles for youth and families living in historically disinvested communities. Given my background as a computer scientist, I will focus examples of efforts to develop computational making activities throughout the ecosystems discussed.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124150336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Moving a Bootcamp-Style Computer Science Programme Online: An Experience Report","authors":"A. Meads, Yu-Cheng Tu, G. Dobbie","doi":"10.1145/3545945.3569814","DOIUrl":"https://doi.org/10.1145/3545945.3569814","url":null,"abstract":"The Postgraduage Certificate in Information Technology at the University of Auckland is a bootcamp-style transition programme for students without prior programming experience. The programme's part-time variant, designed for working professionals, has traditionally been offered with intensive evening classes, with extensive tutor and instructor support. Spurred on by the COVID-19 pandemic, our University has moved this part-time variant fully online. Benefits of the online offering include a wider, more inclusive audience and flexibility of student learning schedules. However, it has introduced several pedagogical challenges, including but not limited to how instructors can continue to provide meaningful support, feedback, and student engagement in an online environment. In this paper, we reflect on our experience, analyse qualitative and quantitative feedback such as student evaluations and grades, and provide recommendations for those wishing to undertake a similar transformation in the future.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114534999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}