Proceedings of the 17th ACM Conference on International Computing Education Research最新文献

{"title":"Teachers’ Views and Experiences on Teaching Second and Subsequent Programming Languages","authors":"Ethel Tshukudu, Q. Cutts, Olivier Goletti, Alaaeddin Swidan, F. Hermans","doi":"10.1145/3446871.3469752","DOIUrl":"https://doi.org/10.1145/3446871.3469752","url":null,"abstract":"Motivation More and more high schools are teaching programming, and in many cases, teachers teach multiple programming languages to the same group of students. Objectives The goal of this paper is to explore the views of high-school teachers on second and subsequent programming languages, including their motivation for teaching multiple languages, their struggles, and their use of transfer strategies when they teach their second or third programming language. Method The study consists of semi-structured interviews with 23 high-school teachers in two European countries. Results Our findings indicate that school pupils face the same issues as university students when moving from first to subsequent languages. Furthermore, the teachers’ attitudes towards second language learning are highly variable, both positive and negative, with some supportive teaching strategies used, but many less helpful ones in evidence too. Discussion Our findings suggest that the value of second language learning needs to be highlighted in teacher professional development materials more strongly and that teachers might need more support in implementing transfer strategies.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123407862","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":"Incentivized Spacing and Gender in Computer Science Education","authors":"Iman YeckehZaare, Elijah Fox, Gail Grot, Sea-Shon Chen, Claire Walkosak, Kevin Kwon, A. Hofmann, Jessica Steir, Olivia McGeough, Nealie Silverstein","doi":"10.1145/3446871.3469760","DOIUrl":"https://doi.org/10.1145/3446871.3469760","url":null,"abstract":"Extensive prior research shows that spacing – the distribution of studying over multiple sessions – significantly improves long-term learning in many disciplines. However, in computer science education, it is unclear if 1) spacing is effective in an incentivized, non-imposed setting and 2) when incentivized, female and male students space their studying differently. To investigate these research questions, we examined how students in an introductory computer science course (378 female and 310 male) spaced their studying. A retrieval practice tool in the course (for 5% of the course grade) incentivized students to space their studying, by awarding a point per day of usage. To measure how much each student spaced, we examined their interactions with the course eBook, which served as their primary learning resource. Specifically, when comparing two students with the same academic and demographic characteristics, the same measure of course easiness, and the same amount of content studied, we considered the student who distributed their studying over more days to be the one who spaced more. Using this definition, our structural equation modeling (SEM) results show that, 1) on average, students who spaced their studying over 14.516 more days (one standard deviation) got 2.25% higher final exam scores; and 2) female students spaced their studying over 4.331 more days than their male counterparts. These results suggest that, in an introductory computer science course, incentivized spacing is effective. Notably, when compared to their male counterparts, female students both exhibited more spacing and obtained higher final exam scores through spacing.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131123692","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":"Evaluating Proof Blocks Problems as Exam Questions","authors":"Seth Poulsen, Mahesh Viswanathan, Geoffrey L. Herman, Matthew West","doi":"10.1145/3446871.3469741","DOIUrl":"https://doi.org/10.1145/3446871.3469741","url":null,"abstract":"Proof Blocks is a novel software tool which enables students to write mathematical proofs by dragging and dropping prewritten lines into the correct order, rather than writing a proof completely from scratch. We used Proof Blocks problems as exam questions for a discrete mathematics course with hundreds of students, allowing us to collect thousands of student responses to Proof Blocks problems. Using this data, we provide statistical evidence that Proof Blocks are easier than written proofs, which are typically very difficult. We also show that Proof Blocks problems provide about as much information about student knowledge as written proofs. Survey results show that students believe that the Proof Blocks user interface is easy to use, and that the questions accurately represent their ability to write proofs.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127390876","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":"Refute: An Alternative to ‘Explain in Plain English’ Questions","authors":"Viraj Kumar","doi":"10.1145/3446871.3469791","DOIUrl":"https://doi.org/10.1145/3446871.3469791","url":null,"abstract":"Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). ICER 2021, August 16–19, 2021, Virtual Event, USA © 2021 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-8326-4/21/08. https://doi.org/10.1145/3446871.3469791 analyzing student answers to “Explain in Plain English” (EiPE) [12] (or “Explain in your own words” [5]) questions. In line with Xie et al.’s theory of instruction for introductory programming [13], such questions can be used as summative and formative items [3] to assess code reading skills. However, we highlight four concerns with EiPE questions, and we propose an alternative question type – Refute (Figure 1) – that seeks to address these concerns.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129026836","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":"Promoting Learning Transfer in Computer Science Education by Training Teachers to use Explicit Programming Strategies","authors":"Olivier Goletti","doi":"10.1145/3446871.3469776","DOIUrl":"https://doi.org/10.1145/3446871.3469776","url":null,"abstract":"Some Computer Science concepts, and programming in particular, are hard to learn. As CS is (re-)entering national school curricula throughout the world, qualified CS teachers need to be trained. In this PhD work we will propose a training that will help teachers teach those concepts effectively. Based on the educational framework of learning transfer and cognitive load theory, we will do this through evidence-based instructional strategies. These explicit programming strategies aim to decrease cognitive load and foster learning transfer. My PhD will advance the topic of CS teacher training by understanding how CS teachers apply those programming strategies in their teaching through qualitative studies and by designing a validated training that can be used with tutors and teacher trainers.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"605 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116128001","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":"Exploring the Impact of Gender Bias on Pair Programming","authors":"Aslihan Akalin, Nathaniel Weinman, Katherine Stasaski, A. Fox","doi":"10.1145/3446871.3469790","DOIUrl":"https://doi.org/10.1145/3446871.3469790","url":null,"abstract":"Pair programming, two partners working on a programming task together, is an effective tool for teaching computer science (CS), as measured by performance, confidence, and improved retention in CS programs [4]. These positive effects are especially impactful for women [9, 11]. In pair programming, mutual student engagement is key. But what makes a good pair? Gender affects the experience of (any pairing of) students due to phenomena such as implicit gender bias (e.g., assuming a woman will be less technically competent than a man). Previous work has found conflicting results about whether same-gender or mixedgender pairings are more effective [2, 3, 6, 8]. One explanation is that gender correlates with other dimensions that may affect collaboration, such as relative skill level, personality traits, or existing friendships [1–3, 5, 7, 10, 13]. However, it is not feasible to control for these other factors in a between-subject study design. We propose an IRB-approved within-subject methodology to gain insight into the effect of the perceived gender of a partner and the actual gender of a partner (Figure 1). This allows us to separate effects of factors such as implicit gender bias, which rely on perceived gender, and larger systemic factors, which affect people based on their actual gender. For perceived gender, we acknowledge the current study focuses on binary gender roles.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"09 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114633451","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":"Learning together: Collaboration and community in PK–12 computing education","authors":"Paulina Haduong","doi":"10.1145/3446871.3469771","DOIUrl":"https://doi.org/10.1145/3446871.3469771","url":null,"abstract":"In PK–12 computing education, researchers and practitioners have often focused on supporting individual learning gains, instead of considering opportunities for structures that may foster collective flourishing. In this three-article dissertation, I employ both quantitative and qualitative methods to explore the concept of learning together, considering the design and implementation of a new creative computing design studio model for 4th–6th grade classrooms learning Scratch. This model creates opportunities for students and teachers to explore, create, share, and reflect on their self-directed and open-ended programming projects together. By participating in the design studio, students and teachers can collaboratively develop both their creative and conceptual fluency with computer programming, which can support broader aspirations of inclusive and equitable computational participation.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127392334","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 Multi-Modal Investigation of Self-Regulation Strategies Adopted by First-Year Engineering Students During Programming Tasks","authors":"E. Wert, Jeremy Grifski, Sijia Luo, Zahra Atiq","doi":"10.1145/3446871.3469795","DOIUrl":"https://doi.org/10.1145/3446871.3469795","url":null,"abstract":"This study aims to understand the self-regulation strategies first-year engineering students use to cope with emotions during programming tasks. We used Zimmerman's framework to identify the processes of self- regulated learning (SRL) as students worked on programming tasks [1, 2]. The SRL framework is a cyclical process that involves three main stages: forethought (preparation for the task), performance (engagement with the task), and self-reflection (reflection on their performance on the task). Most literature about SRL focuses on how students regulate their learning during the forethought and self-reflection stages [3, 4]. There is very little attention on students’ self-regulated learning experiences during the performance stage because it is hard to observe students while they work on the task. This study provides a unique opportunity to understand students’ self-regulation as they worked on programming problems. Seventeen first-year engineering students at a large midwestern university in the United States participated in this study during Spring 2018 [5]. As students worked on the programming task, multi-modal data were collected (video screen capture, eye-gaze data, facial expressions). Following the programming task, students reflected on their experience in a retrospective think-aloud interview. A key finding from this study showed students’ perseverance during the programming task. All students reported negative emotions while working on the task, especially while they encountered errors, or if they got stuck on a problem. First, some students reported pushing through the task, even though they experienced negative emotions. This group of students used negative emotions as fuel to persist through the adverse circumstances they experienced. These students gave up only when they could not find any solution to the problem. Second, some students gave up and moved to the next problem, as soon as they realized the problem was too hard, and they would not be able to complete the problem. Literature categorizes these two groups of students as “movers” and “stoppers” respectively [6, 7]. Students' persistence through challenges indicated the positive role that negative emotions can play in students’ learning and motivation. According to the control-value theory, students experience frustration when they fail at a task [8]. In this case, most students experienced frustration because they failed at the task, but their reaction to frustration is different. The movers kept pushing through, despite experiencing frustration. This study also provides a unique opportunity to observe exemplars of near real-time biometric data of two students who participated in this study. Using these exemplars, we will discuss how different sources of data could be triangulated to provide a rich understanding of students’ self-regulated learning behaviors during programming tasks. The first exemplar is of a ‘mover’ who persisted through the task and completed it. The ","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126828172","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":"Automated, Personalised, and Timely Feedback for Awareness of Programming Plagiarism and Collusion","authors":"Oscar Karnalim","doi":"10.1145/3446871.3469768","DOIUrl":"https://doi.org/10.1145/3446871.3469768","url":null,"abstract":"It is important to educate students about acceptable practices with regard to programming plagiarism and collusion. However, the current approach is quite demanding since it is manual, relying heavily on instructors. The information is delivered briefly, along with other general information, and students may not understand how it applies to their own cases. There is also no warning when students might be about to breach the rules. This doctoral project proposes a system that provides automated, personalised, and timely feedback about programming plagiarism and collusion. If a submission shares undue similarity with other students’ submissions, all involved students will be given similarity feedback, showing their program with similar code fragments highlighted and the similarities explained in natural language, and they are expected to resubmit. Students whose programs do not show clear similarities will be shown a simulation feedback with comparable information. The system is evaluated with some technical measurements and three quasi-experiments.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"103 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124355381","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":"How should we ‘Explain in plain English’? Voices from the Community","authors":"Max Fowler, Binglin Chen, C. Zilles","doi":"10.1145/3446871.3469738","DOIUrl":"https://doi.org/10.1145/3446871.3469738","url":null,"abstract":"“Explain in plain English” (EipE) questions are seen as an important developmental activity and assessment tool in the research community studying how people learn to program, but they aren’t widely used in practice because of difficulty of grading and workload issues. In this paper, we interviewed eleven members of the introductory programming education research community about their thoughts on EipE questions as a whole and how individual borderline student answers should be graded. Through inductive coding of the interview transcripts, we identify: (1) themes relating to how EipE questions should be used in class, (2) the importance of training students to complete EipE questions, (3) standards for the selection and presentation of code in EipE questions, (4) the theoretical and practical considerations relating to grading EipE questions, and (5) English as a second language (ESL) concerns. In addition, we attempt to extrapolate from our observations what the underlying grading process is that faculty are using to grade EipE questions.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134604091","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}