Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1最新文献_第8页

Using Context-Free Grammars to Scaffold and Automate Feedback in Precise Mathematical Writing 在精确的数学写作中使用上下文无关语法来支撑和自动反馈

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569728

Jason Xia, C. Zilles

引用次数: 3

Artificial Intelligence Literacy Research Field: A Bibliometric Analysis from 1989 to 2021 人工智能素养研究领域:1989 - 2021年文献计量学分析

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569874

Kamilla Tenório, Viktoriya Olari, Margarita Chikobava, R. Romeike

{"title":"Artificial Intelligence Literacy Research Field: A Bibliometric Analysis from 1989 to 2021","authors":"Kamilla Tenório, Viktoriya Olari, Margarita Chikobava, R. Romeike","doi":"10.1145/3545945.3569874","DOIUrl":"https://doi.org/10.1145/3545945.3569874","url":null,"abstract":"Artificial Intelligence (AI) literacy is a rapidly evolving research field. Due to the broad scope of AI literacy-related publications, a comprehensive analysis of the field is needed in order to examine the main characteristics of the current scientific output. Based on it, we conducted a bibliometric analysis of the field where we investigated the publications' evolution over time, research constituents (authors, countries, institutions, publication venues), collaboration patterns, and emerging trends. The findings point out that the United States of America (USA), China, Spain, and Germany are the most contributing countries in the AI literacy field. Moreover, the organizations that most contribute to the AI literacy field are the Massachusetts Institute of Technology, the University of Eastern Finland, and the Georgia Institute of Technology. Furthermore, KI - Künstliche Intelligenz, ACM Transactions on Computing Education, and IEEE Access are the most disseminating journals, and FIE, AAAI, SIGCSE, and CHI are the most disseminating conferences of AI literacy research. According to keywords co-occurrence analysis, machine learning, data, big data, deep learning, and ethics are the most addressed AI topics. Finally, based on the achieved results, this bibliometric analysis draws some conclusions regarding the AI literacy field and points out potential directions for future works.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"144 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":"115561725","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}

引用次数: 1

What is an Algorithms Course?: Survey Results of Introductory Undergraduate Algorithms Courses in the U.S. 什么是算法课程?:美国本科算法导论课程调查结果

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569820

Michael Luu, Matthew Ferland, Varun Nagaraj Rao, Arushi Arora, Randy Huynh, Frederick Reiber, Jennifer Wong-Ma, Michael Shindler

引用次数: 3

Replication and Expansion Study on Factors Influencing Student Performance in CS2 CS2学生学习成绩影响因素的复制与拓展研究

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569867

M. Ellis, Sara Hooshangi

{"title":"Replication and Expansion Study on Factors Influencing Student Performance in CS2","authors":"M. Ellis, Sara Hooshangi","doi":"10.1145/3545945.3569867","DOIUrl":"https://doi.org/10.1145/3545945.3569867","url":null,"abstract":"While many studies have focused on students' performance in CS1 courses, research related to the performance and persistence of students in CS2 classes is not as widely performed. In this work, we will extend our previous work to examine students' performance in CS2. We examined a data set that spanned over seven years on more than 5300 student records. In addition to typical factors studied by others (i.e. gender, race, CS1 performance), our work also took into account the relationship between various CS1 pathways to CS2, student major, and the number of previous college CS courses (including transfer credits) and student performance in CS2. CS1 grade is a good indicator of performance in CS2. Gender was not a significant factor in determining performance in CS2 and undeclared engineering majors stood out as high performers. CS majors passed the course at higher rates than other majors. Our large data set allowed for more granular analysis according to race and ethnicity and additional access to students' underserved status. Race and ethnicity had a significant correlation with performance, and so did the underserved status. Our large data set confirmed some of the findings of our previous work, while providing some new insight.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"19 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":"128190283","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}

引用次数: 0

Student Expectations of Tutors in Computing Courses 学生对计算机课程导师的期望

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569766

Rachel S. Lim, Sophia Krause-Levy, Ismael Villegas Molina, Leo Porter

{"title":"Student Expectations of Tutors in Computing Courses","authors":"Rachel S. Lim, Sophia Krause-Levy, Ismael Villegas Molina, Leo Porter","doi":"10.1145/3545945.3569766","DOIUrl":"https://doi.org/10.1145/3545945.3569766","url":null,"abstract":"Many institutions use undergraduate teaching assistants (tutors) in their computing courses to help provide more resources to students. Because of the role tutors play in students' learning experiences, recent work in computing education has begun to explore student-tutor interactions through the tutor's perspective and through direct observation of the interactions. The results suggest that these interactions are cognitively challenging for tutors and may not be as beneficial for students' learning as one might hope. Given that many of these interactions may be unproductive, this work seeks to understand how student expectations of these sessions might be impacting the interactions' effectiveness. We interviewed 15 students in a CS2 course to learn about the expectations and desires that students have when they attend tutoring sessions. Our findings indicate that there is variation in what students consider a desired result from the interaction, that assignment deadlines affect students' expectations and desires for interactions, and that students do not always want what they believe is beneficial for their learning. We discuss implications for instructors and potential guidance for students and tutors to make tutoring sessions more effective.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"11 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":"114459361","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}

引用次数: 0

Reaching for "All":: Understanding the Challenges and Needs of Schools Lagging in CS for All Efforts 实现“人人享有”:了解在“人人享有社会服务”方面落后的学校的挑战和需要

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569783

Janice Lee, C. Fancsali, Symantha Clough

{"title":"Reaching for \"All\":: Understanding the Challenges and Needs of Schools Lagging in CS for All Efforts","authors":"Janice Lee, C. Fancsali, Symantha Clough","doi":"10.1145/3545945.3569783","DOIUrl":"https://doi.org/10.1145/3545945.3569783","url":null,"abstract":"Over the last decade, substantial strides have been made in the CS for All movement, with the widespread the enactment of policies that promote the implementation of CS education in K-12 schools. Despite this progress, at the current rate of growth, it is estimated that it will take four decades to actually reach CS for all students. This sobering finding highlights the urgent need to understand why so many schools are lagging in implementation, and to identify solutions that could address this gap. Using school-level survey data and administrative school records, we investigate the barriers to scaling up CS education in New York City. Common to many school reform initiatives, some schools were early adopters and eagerly embraced the call to provide CS to all students. Others, despite years of effort and support, have yet to offer CS or serve a small percentage of their enrollment. Our findings suggest that while \"normative'' perceptions of CS (e.g., beliefs about it's value) are similar among lower- and higher-implementing schools, some \"technical'' challenges-such as lacking an implementation plan and shared school-wide vision for CS-and \"political'' challenges-such as the lack of support from administrators, are greater for schools struggling to offer CS. Though these findings focus on one district, they are relevant to the many others engaged in CS for all efforts. This study builds on previous research by shedding light on the distinct challenges and needs of \"lagging'' schools, and provides insight into effective strategies for bringing CS education to all.","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":"114626176","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}

引用次数: 0

Studying the Impact of Auto-Graders Giving Immediate Feedback in Programming Assignments 研究自动评分者在编程作业中给予即时反馈的影响

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569726

Joydeep Mitra

引用次数: 1

Building upon the CAPE Framework for Broader Understanding of Capacity in K-12 CS Education 以CAPE框架为基础，更广泛地了解K-12 CS教育的能力

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569799

Monica Mcgill, A. Thompson, Isabella Gransbury, S. Heckman, J. Rosato, Leigh Ann Delyser

{"title":"Building upon the CAPE Framework for Broader Understanding of Capacity in K-12 CS Education","authors":"Monica Mcgill, A. Thompson, Isabella Gransbury, S. Heckman, J. Rosato, Leigh Ann Delyser","doi":"10.1145/3545945.3569799","DOIUrl":"https://doi.org/10.1145/3545945.3569799","url":null,"abstract":"Research Problem. The CAPE Framework has been used in multiple studies to situate capacity-building efforts within schools to offer equitable student access to and participation in K-12 computer science (CS) education. CAPE defines four major components of capacity, access, participation and experience. However, to define what each of the CAPE components can entail, well-defined subcomponents are needed. Research Question. Our research questions for this study were: What are the possible subcomponents for Capacity in the CAPE framework? and How feasible is it to use the newly defined subcomponents in a gap analysis study? Methodology. We conducted a qualitative content analysis by creating a codebook from an existing data framework and literature review. We reframed earlier findings on factors that influence student learning and academic achievement into the CAPE. Findings. We vetted an expanded framework that includes eight Capacity subcomponents, a third (categories) layer and a fourth (subcategories) layer that can be used to disaggregate the many elements that comprise Capacity. For our trial analysis of 196 articles, we added several codes at the category and subcategory level, but found no gaps in the codes for our a priori defined subcomponents. Implications. The extended Capacity framework can be used by others to inform its usage and develop a consensus of what is included within each subcomponent for Capacity, develop instrumentation and protocols for exploring Capacity at a more granular level, conduct scoping and literature reviews, and understand how various variables play a part in the CS educational ecosystem.","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":"115206416","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}

引用次数: 1

First Steps Towards Predicting the Readability of Programming Error Messages 预测编程错误消息可读性的第一步

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569791

J. Prather, Paul Denny, Brett A. Becker, Robert Nix, B. Reeves, Arisoa S. Randrianasolo, Garrett B. Powell

{"title":"First Steps Towards Predicting the Readability of Programming Error Messages","authors":"J. Prather, Paul Denny, Brett A. Becker, Robert Nix, B. Reeves, Arisoa S. Randrianasolo, Garrett B. Powell","doi":"10.1145/3545945.3569791","DOIUrl":"https://doi.org/10.1145/3545945.3569791","url":null,"abstract":"Reading a programming error message is the first step in understanding what it is trying to tell the programmer about how to fix an error in their code. However, these are often difficult to read, especially for novices which is not surprising given that error messages in many of the most popular languages in which novices learn to code were not written with readability in mind. As a result, novices frequently struggle to understand them. This is a long-standing problem, with researchers highlighting concerns about programming error message readability over the last six decades. Very recent work has put forward evidence of the need for measuring readability in error messages and a framework for doing so. This framework consists of four factors of readability for programming error messages: message length, vocabulary, jargon, and sentence construction. We use this framework to implement an approach to automatically assess the readability of programming error messages. Using established readability factors as predictors in a machine learning model, we train several models using a dataset of C and Java error messages. We examine the performance of these models, and apply the best performing model to a previously published set of messages evaluated for readability by experts, non-experts and students. Our results validate the previously proposed readability factors, and our model classifies messages similarly to human raters. Finally, we discuss future work needed to improve the accuracy of the model.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"14 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":"122640409","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}

引用次数: 1

Piloting an Interactive Ethics and Responsible Computing Learning Environment in Undergraduate CS Courses 在本科计算机科学课程中试行互动伦理和负责任的计算机学习环境

Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 Pub Date : 2023-03-02 DOI: 10.1145/3545945.3569753

Francisco Castro, Sahitya Raipura, H. Conboy, Peter Haas, L. Osterweil, I. Arroyo

{"title":"Piloting an Interactive Ethics and Responsible Computing Learning Environment in Undergraduate CS Courses","authors":"Francisco Castro, Sahitya Raipura, H. Conboy, Peter Haas, L. Osterweil, I. Arroyo","doi":"10.1145/3545945.3569753","DOIUrl":"https://doi.org/10.1145/3545945.3569753","url":null,"abstract":"This experience report details pilot deployments of the Platform for Ethics and Responsible Computing Education (PEaRCE) in undergraduate computer science (CS) courses. PEaRCE is an online learning environment designed to immerse undergraduate CS students in realistic interactive work scenarios. The simulated work scenarios illustrate how technical CS course material can be readily exploited towards the creation of appealing systems, which nevertheless can be instruments of harm to others. Students take the role of an employee within a project and are given details about the project. Students then decide whether to continue with the project immediately, or to first talk to various project stakeholders who could provide additional information about the project and its impacts. At the end of the simulation, students are provided information about the project scenario, including the potential impacts of the project and feedback on stakeholder conversation choices. We report on preliminary findings from pilot deployments of PEaRCE in undergraduate CS courses, including student feedback about PEaRCE and the simulation scenarios and discuss future directions for the design of the system and its use in future CS courses.","PeriodicalId":371326,"journal":{"name":"Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1","volume":"13 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":"120944430","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}

引用次数: 0