{"title":"Assessment and Plagiarism","authors":"T. Lancaster, A. Robins, S. Fincher","doi":"10.1017/9781108654555.015","DOIUrl":"https://doi.org/10.1017/9781108654555.015","url":null,"abstract":"","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123081153","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":"Computational Thinking","authors":"P. Curzon, T. Bell, Jane Waite, Mark Dorling","doi":"10.1017/9781108654555.018","DOIUrl":"https://doi.org/10.1017/9781108654555.018","url":null,"abstract":"","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129071327","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":"Teacher Learning and Professional Development","authors":"S. Fincher, Y. Kolikant, K. Falkner","doi":"10.1017/9781108654555.026","DOIUrl":"https://doi.org/10.1017/9781108654555.026","url":null,"abstract":"","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133111142","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":"Programming Paradigms and Beyond","authors":"S. Krishnamurthi, Kathi Fisler","doi":"10.1017/9781108654555.014","DOIUrl":"https://doi.org/10.1017/9781108654555.014","url":null,"abstract":"Programming is a central concern of computer science, so its medium—programming languages—should be a focus of computing education. Unfortunately, much of the community lacks useful tools to understand and organize languages, since the standard literature is mired in the ill-defined and even confusing concept of paradigms. This chapter suggests the use of notional machines, i.e., human-accessible operational semantics, as a central organizing concept for understanding languages. It introduces or re-examines several concepts in programming and languages, especially state, whose complexity is understood well in the programming languages literature but is routinely overlooked in computing education. It identifies and provides context for numerous open problems worthy of research focus, some of which are new twists on long-running debates while others have not received the attention in the literature that they deserve.","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"58 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125931938","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":"The History of Computing Education Research","authors":"M. Guzdial, John Benedict du Boulay","doi":"10.1017/9781108654555.002","DOIUrl":"https://doi.org/10.1017/9781108654555.002","url":null,"abstract":"Teachers have been educating students about computing for many years. For almost as many years, computing education researchers have been studying, in particular, how students learn programming and how to improve that process. Programming languages such as Fortran (1957) and COBOL (1959) were originally invented to be easier than assembler and other early notations so that programming could be made available to a wider range of programmers. Programming languages such as BASIC (1964) and Pascal (1970) were invented explicitly to ease learning how to program. In the late 1960’s, researchers started gathering data, studying how learners were learning programming, when they did not, and how they experienced programming.","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126168158","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 Study Design Process","authors":"Amy J. Ko, S. Fincher","doi":"10.1017/9781108654555.005","DOIUrl":"https://doi.org/10.1017/9781108654555.005","url":null,"abstract":"","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132022153","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":"Student Knowledge and Misconceptions","authors":"Colleen M. Lewis, M. Clancy, J. Vahrenhold","doi":"10.1017/9781108654555.028","DOIUrl":"https://doi.org/10.1017/9781108654555.028","url":null,"abstract":"ion is frequently mentioned as a core skill developed when learning programming (Ginat & Blau, 2017). This is similar to the ways in which the learning of algebra is described (Sfard, 1995). Research about practices for helping students adapt to the abstraction involved in algebra may be helpful for identifying pedagogical strategies that could be applicable to CS. In particular, here we will focus on a sequence of instruction called concretetorepresentationaltoabstract, or CRA (Witzel et al., 2008), which we argue might be applicable to computing instruction. 3.4.1 Evidence from Outside of Computing To introduce the basics of CRA we will use the example of a classroom where young students are learning addition. CRA begins by introducing a physical (i.e., concrete) object. For example, this could be physical blocks that could be counted to add them together. once students are comfortable adding together sets of physical blocks, the class could advance to solving the same problems given only a picture (i.e., representation) of the blocks, but not the physical blocks. once students are comfortable using only the pictures, the class could advance to solving the same problems using only numbers (i.e., abstraction). If a student has trouble adding together only numbers (i.e., working at the abstract level), they could be encouraged to draw pictures (i.e., returning to the representation level). If a student has trouble adding together numbers using a drawing, they could be encouraged to work with the physical blocks (i.e., returning to the concrete level). As shown in this example, the concrete, representational, and abstract forms of the problem can be used to “promote overall conceptual understanding and procedural accuracy and fluency” (Witzel et al., 2008, p. 271). Witzel et al. (2008, Table 27.2 Overlap between logical operators AND, ifthen, and ifandonlyif. A B ANd ifthen ifandonlyif","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115300872","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 Case Study of Qualitative Methods","authors":"Colleen M. Lewis","doi":"10.1017/9781108654555.032","DOIUrl":"https://doi.org/10.1017/9781108654555.032","url":null,"abstract":"In research – and many parts of life – we only see the finished product, a snapshot of calm and certainty even when the reality is chaotic. When people meet me, they might learn that I am a computer science (CS) professor. I assume they would never guess that I nearly failed data structures in college and still struggled in my second attempt. They would never imagine how many interviews I bombed and graduate schools I did not get into. They don’t see the inevitable paper and grant rejections or poor teaching evaluations. Those things aren’t on my CV, but reflecting back, I see these as some of the most influential elements for my learning. This chapter is a narrative of the actual doing of a research study, what Roth (2006) calls a praxis narrative. I hope to give you a “feel for the game” (Bourdieu, 1992) of doing one type of qualitative research. Ideally, you will gain some insights into qualitative methods, or at least recognition that if it feels chaotic, it is not necessarily wrong. Textbooks about qualitative methods have a burden of providing clarity to the methods. This chapter instead seeks to show all of the mess and ambiguity. In our current context, where computing knowledge is often perceived as only available to the intellectual elite or people with a “geek gene,” it is our responsibility to challenge these notions and help others see our humanness. I will attempt to do that while telling the backstory of this paper. In this chapter, I will share some of what I learned through writing, revising, and now reflecting on a paper that traversed a particularly rocky path. My qualitative analysis was eventually published in a paper at the Association for Computing Machinery (ACM) Special Interest Group on Computer Science Education (SIGCSE) International Computing Education Research (ICER) conference (Lewis, 2012a), but the path there was a bit bumpy. The analysis came from my master’s thesis (submitted December 2009), abbreviated to submit to ICER in April of 2010. It was rejected from ICER in 2010 and again in 2011. Despite the suspicion that the manuscript was doomed, I decided to revise and resubmit it again in 2012. Only in this third submission to ICER was it accepted. I received incredibly thoughtful – and harsh – reviews of my first submission to ICER in 2010. At that time, my work was described as preliminary and that the contribution was fairly minimal.","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124379482","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":"Tools and Environments","authors":"L. Malmi, I. Utting, Amy J. Ko","doi":"10.1017/9781108654555.022","DOIUrl":"https://doi.org/10.1017/9781108654555.022","url":null,"abstract":"Powered by TCPDF (www.tcpdf.org) This material is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user. Malmi, Lauri; Utting, Ian; Ko, Andrew J.","PeriodicalId":262179,"journal":{"name":"The Cambridge Handbook of Computing Education Research","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127912338","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}