While the 2020-2021 COVID-19 pandemic is the most widespread and longest lasting educational disruption of the modern era, it joins a host of other natural and human-made crises affecting university education, such as Hurricane María in Puerto Rico (2017), the Islamic State's closure of Al-Furat University in Syria (2014), Hurricane Katrina in New Orleans (2005), and many others. For service learning classes, generally defined as students learning as they provide service to a community partner, these large scale disruptions create special challenges even when it is possible to move classes online. The COVID-19 pandemic seriously affected the active involvement of community partners, including non-profit organizations, local schools and hospitals, and local governments. Many community organizations struggled to meet increased demand for their assistance while simultaneously cutting personnel due to budget shortfalls. In this paper, we report results from 34 survey respondents who offered service learning classes in undergraduate computer and information science during spring 2020. Despite the turmoil, only three faculty respondents lost their community partner entirely. In response to disruption, nearly half of faculty removed some of the assignments’ requirements, while others made the service project optional or removed it completely. Going online negatively affected students’ ability to collaborate with each other and interact with community partners, activities that are considered important for reaching learning outcomes for service learning. Nevertheless, about two-thirds of faculty reported that their students completed their service assignments and described conditions that led to or detracted from their success. Based on the findings, the authors present several implications for development of future computer and information science service learning offerings that are resilient during times of crisis.
{"title":"Service Interruption: Managing Commitment to Community Partners During a Crisis","authors":"L. Barker, A. Voida, Vaughan Nagy","doi":"10.1145/3446871.3469756","DOIUrl":"https://doi.org/10.1145/3446871.3469756","url":null,"abstract":"While the 2020-2021 COVID-19 pandemic is the most widespread and longest lasting educational disruption of the modern era, it joins a host of other natural and human-made crises affecting university education, such as Hurricane María in Puerto Rico (2017), the Islamic State's closure of Al-Furat University in Syria (2014), Hurricane Katrina in New Orleans (2005), and many others. For service learning classes, generally defined as students learning as they provide service to a community partner, these large scale disruptions create special challenges even when it is possible to move classes online. The COVID-19 pandemic seriously affected the active involvement of community partners, including non-profit organizations, local schools and hospitals, and local governments. Many community organizations struggled to meet increased demand for their assistance while simultaneously cutting personnel due to budget shortfalls. In this paper, we report results from 34 survey respondents who offered service learning classes in undergraduate computer and information science during spring 2020. Despite the turmoil, only three faculty respondents lost their community partner entirely. In response to disruption, nearly half of faculty removed some of the assignments’ requirements, while others made the service project optional or removed it completely. Going online negatively affected students’ ability to collaborate with each other and interact with community partners, activities that are considered important for reaching learning outcomes for service learning. Nevertheless, about two-thirds of faculty reported that their students completed their service assignments and described conditions that led to or detracted from their success. Based on the findings, the authors present several implications for development of future computer and information science service learning offerings that are resilient during times of crisis.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"12 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":"134145120","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}
The recent growth of computing education globally has resulted in a growing number of Computer Science Education (CSEd) graduate students. To support and make a global impact in computing education, there is a need for these graduates to be in a diversity of careers/roles both within and beyond academia. Currently pursuing a CSEd PhD requires a leap of faith that one can overcome issues not only associated with pioneering a new discipline within the host institution but also is often undertaken without knowing what career opportunities will be available upon graduation. Surveys conducted in Spring 2020 and 2021 with graduate students and advisors document these challenges [3]. Following these surveys, the project team identified the need to support the growth of research in CS Education. By investigating career pathways for CSEd Graduate students, the need to expand the endeavor and discover what the future holds for CSEdGrad was made clear. This project also seeks to connect with CSEd graduates internationally. The current team leading this initiative comes from the United States, the Caribbean (Puerto Rico), Brazil, Thailand, and UK (via Botswana). Among the research initiatives that the team has undertaken is identifying non-academic career opportunities (jobs, conferences, publication opportunities, and fellowships) for CSEd graduate students. While seeking to promote and share international opportunities in non-academic settings, the researchers are faced with defining CSEd Research, the opportunities that CSEd graduate students can pursue, and how these vary across countries and regions. To gain preliminary insights into existing career opportunities, the team explored five countries (USA, UK, Brazil, Puerto Rico, and Thailand) for four months using online research methods. The data collected included country, type of organization, job description, and job qualification. This data was imported into Excel for detailed analysis. Content analysis was used to code collected data into career and organization categories systematically. Initial categories were generated deductively with the guideline from Amy Ko’s blog [1] on career paths, and new categories evolved as well. These categories were then merged and collapsed through an iterative process that led to developing a CSEd career path mind-map (See figure 1). In total, 83 jobs from 35 different non-academic organizations were reported. Furthermore, 15 career path categories and 6 organization categories emerged from these findings. Among the emerging themes that the team has found are limited opportunities within the developing countries, the varying definitions, and broad requirements for CSEd professions, and the dominant and leading role of the United States and the United Kingdom in CSEd. The research team understands that this can be an opportunity to create and pave the way to new opportunities within the field [2]. This poster seeks to generate a discussion within the ICER community
{"title":"Identifying Opportunities and Potential Roadblocks for CSEd Professionals","authors":"Alejandra Méndez, Ethel Tshukudu, Carolina Moreira, Weena Naowaprateep, A. Peterfreund, Brianna Johnston","doi":"10.1145/3446871.3469789","DOIUrl":"https://doi.org/10.1145/3446871.3469789","url":null,"abstract":"The recent growth of computing education globally has resulted in a growing number of Computer Science Education (CSEd) graduate students. To support and make a global impact in computing education, there is a need for these graduates to be in a diversity of careers/roles both within and beyond academia. Currently pursuing a CSEd PhD requires a leap of faith that one can overcome issues not only associated with pioneering a new discipline within the host institution but also is often undertaken without knowing what career opportunities will be available upon graduation. Surveys conducted in Spring 2020 and 2021 with graduate students and advisors document these challenges [3]. Following these surveys, the project team identified the need to support the growth of research in CS Education. By investigating career pathways for CSEd Graduate students, the need to expand the endeavor and discover what the future holds for CSEdGrad was made clear. This project also seeks to connect with CSEd graduates internationally. The current team leading this initiative comes from the United States, the Caribbean (Puerto Rico), Brazil, Thailand, and UK (via Botswana). Among the research initiatives that the team has undertaken is identifying non-academic career opportunities (jobs, conferences, publication opportunities, and fellowships) for CSEd graduate students. While seeking to promote and share international opportunities in non-academic settings, the researchers are faced with defining CSEd Research, the opportunities that CSEd graduate students can pursue, and how these vary across countries and regions. To gain preliminary insights into existing career opportunities, the team explored five countries (USA, UK, Brazil, Puerto Rico, and Thailand) for four months using online research methods. The data collected included country, type of organization, job description, and job qualification. This data was imported into Excel for detailed analysis. Content analysis was used to code collected data into career and organization categories systematically. Initial categories were generated deductively with the guideline from Amy Ko’s blog [1] on career paths, and new categories evolved as well. These categories were then merged and collapsed through an iterative process that led to developing a CSEd career path mind-map (See figure 1). In total, 83 jobs from 35 different non-academic organizations were reported. Furthermore, 15 career path categories and 6 organization categories emerged from these findings. Among the emerging themes that the team has found are limited opportunities within the developing countries, the varying definitions, and broad requirements for CSEd professions, and the dominant and leading role of the United States and the United Kingdom in CSEd. The research team understands that this can be an opportunity to create and pave the way to new opportunities within the field [2]. This poster seeks to generate a discussion within the ICER community ","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"10 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":"122511189","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}
There are about one billion persons with disabilities (PWDs) in the world [8]. Between 40 and 80 million of them are in India [5]. In 2015, the Government of India launched the Sugamya Bhārat Abhiyān (Accessible India Campaign), a “nation-wide Campaign for achieving universal accessibility for PWDs”. One of its three components, “Information and Communication Eco-System Accessibility”, focuses on accessible softwares and digital artifacts. The private industry is also increasingly emphasizing developing softwares that are accessible to everyone [See, e.g., 3, 4, 7, 1]. However, the CS curricula that ought to prepare the future professionals to develop such accessible softwares hardly cover topics related to accessibility. This project is aimed at understanding the status of accessibility education in India and developing appropriate course content. I present initial ideas, solicit feedback, and invite collaborators through the discussion on this poster. It is important to note that teaching accessibility (including accessibility topics in your courses) and teaching accessibly (making your course content accessible) are two different things; my focus is on the former. (1) Understanding the challenges to accessibility integration in CS education in India. We first need to understand the faculty’s preparedness for and attitude towards teaching accessibility topics. Shinohara et al. [6] report that very few CS faculty in the US teach accessibility (20% of the respondents but only 2.5% of all faculty surveyed). Moreover, most of them include accessibility topics in specialized human-computer interaction (HCI) courses rather than core CS courses such as Software Engineering. The numbers in India are likely to be much lower due to various factors; for instance, a cursory survey of CS faculty profiles in the twenty “Institutes of Eminence” in India revealed that only three have someone with HCI expertise. I am developing an instrument to investigate the following initial research questions: (2) Developing accessibility-themed courses and evaluating their effects. I will teach a software engineering course with a focus on Android app development in Fall 2021. I am currently developing materials for this course such that accessibility will be an underlying theme throughout the semester. I plan to include the following four topics, observed in the literature [2], in the course learning objectives: I will evaluate the effects of this course on how students learned certain software engineering concepts and their attitude towards accessibility.
{"title":"Teaching Accessibility in India: A Work in Progress","authors":"Swaroop Joshi","doi":"10.1145/3446871.3469783","DOIUrl":"https://doi.org/10.1145/3446871.3469783","url":null,"abstract":"There are about one billion persons with disabilities (PWDs) in the world [8]. Between 40 and 80 million of them are in India [5]. In 2015, the Government of India launched the Sugamya Bhārat Abhiyān (Accessible India Campaign), a “nation-wide Campaign for achieving universal accessibility for PWDs”. One of its three components, “Information and Communication Eco-System Accessibility”, focuses on accessible softwares and digital artifacts. The private industry is also increasingly emphasizing developing softwares that are accessible to everyone [See, e.g., 3, 4, 7, 1]. However, the CS curricula that ought to prepare the future professionals to develop such accessible softwares hardly cover topics related to accessibility. This project is aimed at understanding the status of accessibility education in India and developing appropriate course content. I present initial ideas, solicit feedback, and invite collaborators through the discussion on this poster. It is important to note that teaching accessibility (including accessibility topics in your courses) and teaching accessibly (making your course content accessible) are two different things; my focus is on the former. (1) Understanding the challenges to accessibility integration in CS education in India. We first need to understand the faculty’s preparedness for and attitude towards teaching accessibility topics. Shinohara et al. [6] report that very few CS faculty in the US teach accessibility (20% of the respondents but only 2.5% of all faculty surveyed). Moreover, most of them include accessibility topics in specialized human-computer interaction (HCI) courses rather than core CS courses such as Software Engineering. The numbers in India are likely to be much lower due to various factors; for instance, a cursory survey of CS faculty profiles in the twenty “Institutes of Eminence” in India revealed that only three have someone with HCI expertise. I am developing an instrument to investigate the following initial research questions: (2) Developing accessibility-themed courses and evaluating their effects. I will teach a software engineering course with a focus on Android app development in Fall 2021. I am currently developing materials for this course such that accessibility will be an underlying theme throughout the semester. I plan to include the following four topics, observed in the literature [2], in the course learning objectives: I will evaluate the effects of this course on how students learned certain software engineering concepts and their attitude towards accessibility.","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":"122059782","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}
Alexandra Milliken, Veronica Catété, Ally Limke, Isabella Gransbury, Hannah E. Chipman, Yihuan Dong, T. Barnes
This article examines the grading process and profiles of secondary computer science teachers as they assess block-based student programming submissions. Through an iterative design process, we have created a new tool, Gradesnap, which streamlines how teachers can open, review, and evaluate student submissions within the same interface. Our study compares teachers’ grading processes using the different assessment formats, so that we can understand how their grading processes can be augmented or supported to reduce ’pain points’ and to enable teachers to provide more constructive and formative feedback for students. We use a case study approach to examine the experiences and outcomes of four secondary computer science teachers with varied teaching and assessment experience, when grading as usual, grading with a rubric, and grading with GradeSnap. Our study shows that when participants use GradeSnap, they are able to give supportive comments to lower performing and borderline students who need critical feedback to better understand misconceptions. We also discovered that the different grading processes provided a vehicle for reflection for some teachers in understanding their grading goals and how they enact them. This research is the first to examine teacher grading processes for computer science, and highlights the need for teacher preparation and support for providing programming feedback and assessment.
{"title":"Exploring and Influencing Teacher Grading for Block-based Programs through Rubrics and the GradeSnap Tool","authors":"Alexandra Milliken, Veronica Catété, Ally Limke, Isabella Gransbury, Hannah E. Chipman, Yihuan Dong, T. Barnes","doi":"10.1145/3446871.3469762","DOIUrl":"https://doi.org/10.1145/3446871.3469762","url":null,"abstract":"This article examines the grading process and profiles of secondary computer science teachers as they assess block-based student programming submissions. Through an iterative design process, we have created a new tool, Gradesnap, which streamlines how teachers can open, review, and evaluate student submissions within the same interface. Our study compares teachers’ grading processes using the different assessment formats, so that we can understand how their grading processes can be augmented or supported to reduce ’pain points’ and to enable teachers to provide more constructive and formative feedback for students. We use a case study approach to examine the experiences and outcomes of four secondary computer science teachers with varied teaching and assessment experience, when grading as usual, grading with a rubric, and grading with GradeSnap. Our study shows that when participants use GradeSnap, they are able to give supportive comments to lower performing and borderline students who need critical feedback to better understand misconceptions. We also discovered that the different grading processes provided a vehicle for reflection for some teachers in understanding their grading goals and how they enact them. This research is the first to examine teacher grading processes for computer science, and highlights the need for teacher preparation and support for providing programming feedback and assessment.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"42 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":"127891802","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}
1 MOTIVATION Teachers are faced with many challenges when teaching programming in school such as helping students with their programming problems and assessing students [12, 15, 17]. Both activities lead to teachers giving feedback to their students. However, powerful feedback has to fulfill certain criteria and must use appropriate strategies [4, 10]. An even more basic requirement is that the teacher has to know the solution and preferably also has a deeper understanding of the underlying concepts. However, many teachers consider their lack of subject knowledge a main challenge when teaching programming and elementary school teachers mentioned it even more often than secondary school teachers [12]. As programming is increasingly introduced at elementary schools, the question of how to support elementary school teachers with giving feedback arises. Automated code analysis tools might provide an opportunity as they give information that can be used to give appropriate feedback to the students. These tools address different aspects of programming and exist for different programming languages. When programming in elementary schools, block-based programming languages are of interest because they can reduce the complexity compared to text-based programming languages. We focus on Scratch which is one of the most frequently studied programming languages in the K-12 context [7]. However, automated analysis tools for Scratch also involve challenges. They contain technical terms and often require a deeper understanding of programming concepts. Thus, elementary school teachers have to adapt the provided information to pass it on to their students. As the teachers
{"title":"Effective Feedback on Elementary School Scratch Programs","authors":"Luisa Greifenstein","doi":"10.1145/3446871.3469779","DOIUrl":"https://doi.org/10.1145/3446871.3469779","url":null,"abstract":"1 MOTIVATION Teachers are faced with many challenges when teaching programming in school such as helping students with their programming problems and assessing students [12, 15, 17]. Both activities lead to teachers giving feedback to their students. However, powerful feedback has to fulfill certain criteria and must use appropriate strategies [4, 10]. An even more basic requirement is that the teacher has to know the solution and preferably also has a deeper understanding of the underlying concepts. However, many teachers consider their lack of subject knowledge a main challenge when teaching programming and elementary school teachers mentioned it even more often than secondary school teachers [12]. As programming is increasingly introduced at elementary schools, the question of how to support elementary school teachers with giving feedback arises. Automated code analysis tools might provide an opportunity as they give information that can be used to give appropriate feedback to the students. These tools address different aspects of programming and exist for different programming languages. When programming in elementary schools, block-based programming languages are of interest because they can reduce the complexity compared to text-based programming languages. We focus on Scratch which is one of the most frequently studied programming languages in the K-12 context [7]. However, automated analysis tools for Scratch also involve challenges. They contain technical terms and often require a deeper understanding of programming concepts. Thus, elementary school teachers have to adapt the provided information to pass it on to their students. As the teachers","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"6 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":"128757692","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}
In this paper, we perform a comparative analysis using a within-subjects ‘think-aloud’ protocol of introductory programming students solving tracing problems in both paper-based and computer-based formats. We demonstrate that, on computer-based exams with compiler/interpreter access, students can achieve significantly higher scores on tracing problems than they do on similar paper-based questions, through brute-force execution of the provided code. Furthermore, we characterize the students’ usage of machine execution as they solve computer-based tracing problems. We, then, suggest “reverse-tracing” questions, where a block of code is provided and students must identify an input that will produce a specified output, as a potential alternative means of assessing the same skill as tracing questions on such computer-based exams. Our initial investigation suggests correctly-designed reverse-tracing problems on computer-based exams more closely track a student’s performance on similar questions in a paper-based format. In addition, we find that the thought process while solving tracing and reverse-tracing problems is similar, but not identical.
{"title":"Exploring ‘reverse-tracing’ Questions as a Means of Assessing the Tracing Skill on Computer-based CS 1 Exams","authors":"Mohammed Hassan, C. Zilles","doi":"10.1145/3446871.3469765","DOIUrl":"https://doi.org/10.1145/3446871.3469765","url":null,"abstract":"In this paper, we perform a comparative analysis using a within-subjects ‘think-aloud’ protocol of introductory programming students solving tracing problems in both paper-based and computer-based formats. We demonstrate that, on computer-based exams with compiler/interpreter access, students can achieve significantly higher scores on tracing problems than they do on similar paper-based questions, through brute-force execution of the provided code. Furthermore, we characterize the students’ usage of machine execution as they solve computer-based tracing problems. We, then, suggest “reverse-tracing” questions, where a block of code is provided and students must identify an input that will produce a specified output, as a potential alternative means of assessing the same skill as tracing questions on such computer-based exams. Our initial investigation suggests correctly-designed reverse-tracing problems on computer-based exams more closely track a student’s performance on similar questions in a paper-based format. In addition, we find that the thought process while solving tracing and reverse-tracing problems is similar, but not identical.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"86 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":"133564911","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}
SQL is the most commonly taught database query language. While previous research has investigated the errors made by novices during SQL query formulation, the underlying causes for these errors have remained unexplored. Understanding the basic misconceptions held by novices which lead to these errors would help improve how we teach query languages to our students. In this paper we aim to identify the misconceptions that might be the causes of documented SQL errors that novices make. To this end, we conducted a qualitative think-aloud study to gather information on the thinking process of university students while solving query formulation problems. With the queries in hand, we analyzed the underlying causes for the errors made by our participants. In this paper we present the identified SQL misconceptions organized into four top-level categories: misconceptions based in previous course knowledge, generalization-based misconceptions, language-based misconceptions, and misconceptions due to an incomplete or incorrect mental model. A deep exploration of misconceptions can uncover gaps in instruction. By drawing attention to these, we aim to improve SQL education.
{"title":"Identifying SQL Misconceptions of Novices: Findings from a Think-Aloud Study","authors":"Daphne Miedema, Efthimia Aivaloglou, G. Fletcher","doi":"10.1145/3446871.3469759","DOIUrl":"https://doi.org/10.1145/3446871.3469759","url":null,"abstract":"SQL is the most commonly taught database query language. While previous research has investigated the errors made by novices during SQL query formulation, the underlying causes for these errors have remained unexplored. Understanding the basic misconceptions held by novices which lead to these errors would help improve how we teach query languages to our students. In this paper we aim to identify the misconceptions that might be the causes of documented SQL errors that novices make. To this end, we conducted a qualitative think-aloud study to gather information on the thinking process of university students while solving query formulation problems. With the queries in hand, we analyzed the underlying causes for the errors made by our participants. In this paper we present the identified SQL misconceptions organized into four top-level categories: misconceptions based in previous course knowledge, generalization-based misconceptions, language-based misconceptions, and misconceptions due to an incomplete or incorrect mental model. A deep exploration of misconceptions can uncover gaps in instruction. By drawing attention to these, we aim to improve SQL education.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"70 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":"132337003","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}
Mathematician Eugenia Cheng offers a fresh framework for thinking about the problem of the under-representation of women in STEM. Cheng’s approach is grounded in her research field, category theory, which leads to her proposal that instead of focusing on a gender binary, we instead consider each person as being on a continuum from “congressive” (that is, focused on interdependence) to “ingressive” (focused on independence). The purpose of this poster is to consider the application of Cheng’s framework to computing education by focusing on three main questions: If we base computing education research on this framework, what might that look like? What might we gain, and what might we lose? Cheng’s framework applied to computing education research would change the methodology used in interventions that consider the participants’ gender. Gains from Cheng’s framework therefore include a way to research, analyze, and implement interventions in computer science education to improve representation that do not reify the gender binary and (further) marginalize non-cis-gendered students. However, adopting Cheng’s framework would create several hurdles, including the need for a valid instrument to assess placement on the continuum. And the framework may well fail to rectify the problem of under-representation. Nonetheless, Cheng’s framework, particularly in its ability to include all students, regardless of gender identity, is worth considering as a tool in computing education, not the least because it suggests a possible contrast to the status quo.
{"title":"Beyond the Gender Binary in Computing Education Research","authors":"Julie M. Smith","doi":"10.1145/3446871.3469794","DOIUrl":"https://doi.org/10.1145/3446871.3469794","url":null,"abstract":"Mathematician Eugenia Cheng offers a fresh framework for thinking about the problem of the under-representation of women in STEM. Cheng’s approach is grounded in her research field, category theory, which leads to her proposal that instead of focusing on a gender binary, we instead consider each person as being on a continuum from “congressive” (that is, focused on interdependence) to “ingressive” (focused on independence). The purpose of this poster is to consider the application of Cheng’s framework to computing education by focusing on three main questions: If we base computing education research on this framework, what might that look like? What might we gain, and what might we lose? Cheng’s framework applied to computing education research would change the methodology used in interventions that consider the participants’ gender. Gains from Cheng’s framework therefore include a way to research, analyze, and implement interventions in computer science education to improve representation that do not reify the gender binary and (further) marginalize non-cis-gendered students. However, adopting Cheng’s framework would create several hurdles, including the need for a valid instrument to assess placement on the continuum. And the framework may well fail to rectify the problem of under-representation. Nonetheless, Cheng’s framework, particularly in its ability to include all students, regardless of gender identity, is worth considering as a tool in computing education, not the least because it suggests a possible contrast to the status quo.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"175 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":"128904659","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}
Novice programmers often make haphazard mistakes due to their incomplete and inconsistent mental models. Previous studies have indicated that students have a non-viable mental model of fundamental programming concepts. From theories of mental model, Mayer [13] showed the effectiveness of explanative diagrams in shaping a novice’s mental model. My dissertation aims to evaluate the role of Mayer’s explanative diagram as a representation of a notional machine to shape novice programmers’ mental models of the array.
{"title":"Investigating the Role of Explanative Diagrams as a Representation of Notional Machine on a Novice Programmer’s Mental Model","authors":"S. F. Mazumder","doi":"10.1145/3446871.3469775","DOIUrl":"https://doi.org/10.1145/3446871.3469775","url":null,"abstract":"Novice programmers often make haphazard mistakes due to their incomplete and inconsistent mental models. Previous studies have indicated that students have a non-viable mental model of fundamental programming concepts. From theories of mental model, Mayer [13] showed the effectiveness of explanative diagrams in shaping a novice’s mental model. My dissertation aims to evaluate the role of Mayer’s explanative diagram as a representation of a notional machine to shape novice programmers’ mental models of the array.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"56 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":"129442419","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}
Most text-based programming languages found in introductory programming courses use English words. This fact alone can deter non-English speakers who wish to learn to program: how can we expect them to learn a programming language if they do not even understand the meaning of the keywords they are manipulating? In addition, the syntax and semantics of programming languages are also known causes of learners’ mistakes. In this paper, we highlight these difficulties and then present PseuToPy, a programming language which can be localized in several tongues on the one hand and produce instructions close to these natural languages on the other. PseuToPy is still a work in progress: we have developed a version in French and hope to study its use in an educational context to see whether or not programming beginners find it easier to learn programming by implementing algorithms in their native tongues.
{"title":"PseuToPy: Towards a Non-English Natural Programming Language","authors":"Patrick Wang","doi":"10.1145/3446871.3469787","DOIUrl":"https://doi.org/10.1145/3446871.3469787","url":null,"abstract":"Most text-based programming languages found in introductory programming courses use English words. This fact alone can deter non-English speakers who wish to learn to program: how can we expect them to learn a programming language if they do not even understand the meaning of the keywords they are manipulating? In addition, the syntax and semantics of programming languages are also known causes of learners’ mistakes. In this paper, we highlight these difficulties and then present PseuToPy, a programming language which can be localized in several tongues on the one hand and produce instructions close to these natural languages on the other. PseuToPy is still a work in progress: we have developed a version in French and hope to study its use in an educational context to see whether or not programming beginners find it easier to learn programming by implementing algorithms in their native tongues.","PeriodicalId":309835,"journal":{"name":"Proceedings of the 17th ACM Conference on International Computing Education Research","volume":"100 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":"125199465","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}
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