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Proceedings of the 50th ACM Technical Symposium on Computer Science Education

作者： Bita Akram Wookhee Min Eric Wiebe Bradford Mott Kristy Elizabeth Boyer James Lester North Carolina State University Raleigh NC USA University of Florida Gainesville FL USA

ISBN: (纸本)9781450358903

With national K-12 education initiatives such as "CSForAll," block-based programming environments have emerged as widely used tools for teaching novice programming. A key challenge presented by block-based programming environments is assessing students' computational thinking (CT) and programming competencies. Developing assessment methods that can evaluate students' use of CT practices such as testing and refining, and developing and using appropriate algorithms, can help teachers evaluate students learning and provide appropriate scaffolding. In this work, we utilize an evidence-centered assessment design approach to devise a three-dimensional assessment to evaluate students' CT competencies based on evidence extracted from their programming trajectories in a block-based programming environment. In this assessment, the first dimension assesses students' knowledge of essential CT concepts, the second dimension assesses students' dynamic testing and refining strategies, and the third dimension assesses their overall problem-solving efficiency. We apply the assessment framework to data collected from students' interactions with a game-based learning environment designed to develop middle-grade students' CT competencies and programming skills. The results demonstrate that students' knowledge of basic CT constructs, such as appropriate use and combination of control structures, serves as the foundation for designing and implementing effective algorithms. Further, we assessed students testing and refining strategies over the three dimensions of novelty, positivity, and scale. The results demonstrate that students with higher algorithmic capabilities tend to make more novel, positive, and small-scale changes. The results reveal distinctive patterns in students' approaches to computational thinking problem solving and make a step toward identifying and assessing productive computational thinking practices.

关键词： evidence-centered design computational thinking assessment game-based learning programming trajectories block-based programming

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Snap! 9 - Support for Teachers and programming with Data 2024

Snap! 9 - Support for Teachers and Programming with Data

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Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2

作者： Michael Ball Daniel Garcia Victoria Phelps Yuan Garcia UC Berkeley Berkeley USA Harvey Mudd College Claremont USA

ISBN: (纸本)9798400704246

This year's Snap! 9 release represents 10 years since Snap! 4.0 was initially released as a web application. Version 9 includes hundreds of new features, focused on providing students and teachers with new cloud tools, continued development of tools for working with data, and ''quality of life'' *** Snap! Cloud has been upgraded to support dedicated student and teacher accounts. Teachers can create accounts on behalf of their students, and manage students in their class. Everyone can also choose to ''follow'' users and see a feed of new projects shared with the ***'s also never been easier to work with data! Snap! 9 adds the ability to treat lists as ''dictionaries'' (lists of lists can now be indexed by arbitrary alphanumeric values). A number of blocks have been made variadic (i.e., supporting a variable number of inputs), saving the user the tedium of dragging over multiple copies of the same block. These include and, or, all comparison operators, and if, which adds more intermediate else if cases when the right arrow is ***, Parsons Puzzles can be created with a single click. The Generate Puzzle command generates a microworld with only the blocks present in the selected sprite (and hides the answer behind a menu choice).In this demo, we'll share ways that you can use new Snap! features in the classroom, and provide attendees with the tools to build engaging experiences for *** materials from this demonstration will be shared at https://***/snap-sigcse24

关键词： block-based programming metaprogramming programming paradigms snap!

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Visual Data Science with blockly-DS 2024

Visual Data Science with Blockly-DS

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Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2

作者： Luiz Barboza Rafael Ferreira Mello Erico Souza Teixeira Andrew M. Olney University of Memphis Memphis TN USA Federal Rural University of Pernambuco Pernambuco Brazil CESAR Pernambuco Brazil

ISBN: (纸本)9798400704246

The workshop will give educators an introduction to graphical data analysis techniques for exploring, summarizing, and effectively communicating data using Visual blocks (blockly) and Jupiter Notebooks. Participants will gain skills to create and interpret various graphs and plots, fostering insights into data patterns and relationships. The emphasis will be on adeptly selecting visualizations. Upon completion of this course, educators should be proficient in: Understanding the principles of graphical data analysis and their practical applications; and creating and interpreting diverse graph types and plots. The workshop will further delve into statistical methods essential for data analysis, guiding educators on employing descriptive statistics to explore data and derive meaningful business insights. The focus will be on fostering an understanding of statistical concepts and their practical application, as well as the effective interpretation and communication of findings. Additionally, the program will introduce educators to machine learning regressors, with a primary focus on linear regression. Participants will learn the skills to train, evaluate, and apply regressors to predict continuous target variables from input features. The emphasis will be on grasping and applying machine learning principles, as well as effectively interpreting and communicating model predictions. Furthermore, participants will engage in hands-on experience with machine learning classifiers, encompassing logistic regression, decision trees, naive Bayes, and neural networks. Educators will acquire the expertise to train, evaluate, and apply classifiers for predicting categorical target variables from input features. The emphasis here is on understanding and applying machine learning principles, as well as adeptly interpreting model predictions.

关键词： block-based programming data science ia machine learning

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Ten Years of Snap! - Where Should We Go Next? 2023

Ten Years of Snap! - Where Should We Go Next?

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Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2

作者： Michael Ball Dan Garcia Yuan Garcia UC Berkeley Berkeley CA USA Mills High School Milbrea CA USA

ISBN: (纸本)9781450394338

Spring 2023 marks 10 years since \snap was first used with students, and the Snap! Cloud was developed for sharing projects. Since then, nearly 700,000 students and educators have worked on more than 6 million Snap! projects. This BOF serves as an opportunity to meet with the large community of Snap! users that attend SIGCSE. The past three releases have focused on power ideas, such as native array-based data programming, building microworlds, and metaprogramming. We want to have a chance to share success stories, and then discuss: what's next?Notes, projects and examples from this BOF will be shared at https://***/snap-bof-sigcse23

关键词： programming paradigms snap block-based programming metaprogramming

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Affective Reporting: Improving Student programming Self-assessments in CS0 2023

Affective Reporting: Improving Student Programming Self-asse...

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Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2

作者： Ally Limke North Carolina State University Raleigh USA

ISBN: (纸本)9781450394338

CS1 students who program in textual languages often think they are bad at programming, largely because they experience negative self-assessments as they program. I investigate whether students in CS0 contexts using a block-based language have similar self-assessment moments, to find ways to amplify positive self-assessments and ameliorate negative ones. Toward this end, I have designed an affective reporting tool and a study to understand the programming moments that lead to positive or negative student affect for CS0 students. The affective reporting tool was piloted in a CS0 course. 69 out of 75 students voluntarily used the tool, reporting 528 responses over two course periods. This willingness to share their affective data through the new tool shows that students may need such outlets to reflect on and share how they are feeling while programming. The tool was also used in a study where students programmed using the affective reporter, then reflected on and reviewed a video of their programming to tell us more about how they felt while programming. Initial findings show that while some moments are interpreted to be positive or negative by all students, the interpretation of other moments can differ. In future work, the results of these studies will be used to design interventions to help students and improve their programming self-assessments.

关键词： block-based programming novice programmers affect cs0 self-assessment self-efficacy

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Comparison of user experience in online programming learning platforms: Case study in novice programmers from Huancayo, Peru 20

Comparison of user experience in online programming learning...

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Proceedings of the 12th International Conference on Education Technology and Computers

作者： Gino Joel Taipe Miranda Pedro Yuri Marquez Solis Continental University Peru

ISBN: (纸本)9781450388276

This research was comparison of user experience between the Scratch and *** platforms, for being used by novice programmers. The comparison was taking into seven factors that influence user experience, including usefulness, usability, desirability, findability, accessibility, credibility, and value. The research was carried out with the participation of 40 people with little or no knowledge about programming topics, the people carried out the following tasks: Register on the platform, use a sample project, create a project, program using block-based programming, explore the features and functionalities of the platform. In general, both platforms offer a good user experience for novice programmers. Finally, it is concluded that Scratch offers a better user experience, because it exceeded *** in 4 of the 7 factors.

关键词： programming User experience (UX) learning platform code scratch block-based programming

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Beyond CS Principles: Bringing the Frontiers of Computing to K12 21

Beyond CS Principles: Bringing the Frontiers of Computing to...

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Proceedings of the 52nd ACM Technical Symposium on Computer Science Education

作者： Ákos Lédeczi Shuchi Grover Veronica Catete Brian Broll Vanderbilt University Nashville TN USA Looking Glass Venture Palo Alto CA USA North Carolina State University Raleigh NC USA

ISBN: (纸本)9781450380621

The AP Computer Science Principles (CSP) high school course introduces students to computer science and programming. What should motivated students study after successful completion of AP CSP? The AP CSA class teaches Java programming and it has traditionally not attracted students from underrepresented groups. We are working on an alternative, projects-based course that will teach cutting edge CS concepts, such as distributed computing, computer networking, cybersecurity, the internet of things and machine learning, in a hands-on, accessible manner. Such an approach enables students to work on problems that interest them making computing more relevant and the curriculum more engaging. We utilize NetsBlox, a collaborative, block-based programming environment that extends Snap! with a few carefully selected abstractions that open up the vast array of resources freely available on the internet for student programs. Moreover, the tool enables students to work together on the same project remotely similarly to how Google Docs operate. This demonstration will introduce the environment and highlight its utility in creating distributed applications such as a shared whiteboard app and projects that access public domain scientific data sources and visualize them in various ways using online services such as Google Maps or charting. More information is available at https://***.

关键词： distributed computing block-based programming internet of things computer networking cybersecurity

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Weather Radar Algorithm Development using Google blockly: (Abstract Only) 18

Weather Radar Algorithm Development using Google Blockly: (A...

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Proceedings of the 49th ACM Technical Symposium on Computer Science Education

作者： Eric Tilley University of Alabama Tuscaloosa AL USA

ISBN: (纸本)9781450351034

NADER (NEXRAD Algorithm Development Environment) is a desktop-based programming environment that allows users to build algorithms for the analysis of NEXRAD level-II Doppler weather radar data. NEXRAD level-II data provides a high-resolution 3D mapping of precipitation intensity and wind speeds around a radar site. These datasets are available from NCEI (National Centers for Environmental Information, a division of the National Oceanic and Atmospheric Administration) both from archives and in real-time, providing nearly endless opportunities for automated algorithmic analysis of weather features. The language provided by NADER is block-based and is built on the powerful Google blockly platform. In addition to blocks for logic, math, and control flow functions, NADER also presents the user with a succinct set of blocks providing abstractions for common radar data structures. NADER also includes a visualization tool for level-II data, allowing users to clearly see exactly what data is passed into their algorithms and exactly what data is output. With NADER, users can develop a huge variety of algorithms' for example, an algorithm for hail detection, an algorithm for tracking snowfall, or even an algorithm for estimating tornado damage. NADER strives to accomplish two main objectives. One objective is to provide beginning programmers with a straightforward programming environment with an intriguing, real-life application. The other objective is to provide meteorology experts with a rapid-feedback prototyping environment for developing new algorithms.

关键词： meteorology block-based programming computer science education

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Measuring Learning of Code Patterns in Informal Learning Environments (Abstract Only) 17

Measuring Learning of Code Patterns in Informal Learning Env...

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Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education

作者： Sayamindu Dasgupta Benjamin Mako Hill Massachusetts Institute of Technology Cambridge MA India University of Washington Seattle WA USA

ISBN: (纸本)9781450346986

Quantitative studies of learning using block-based programming languages in informal environments have relied on identifying the presence or absence of individual visual blocks in learners' projects. Many important programming concepts (e.g., initializing a variable) involve the combination of several blocks. In this poster, we present a technique that uses a statistical method from epidemiology called "survival analysis" to model the rate at which programmers begin to use new code patterns. By analyzing data drawn from the trajectories of over 90,000 users from the Scratch online community, we demonstrate the potential of our approach. In particular, we model when users are at higher and lower levels of "risk" of demonstrating two particular code patterns -- variable initialization and counting collisions. We show that learning of these patterns is associated with behaviors like viewing the source code of other projects, remixing, and commenting. We explain how our method can be extended to help understand predictors of skill acquisition in informal environments more generally and how it can inform the design of more effective learning support structures.

关键词： quantitative methods measures scratch block-based programming informal learning

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The effect of robotics on six graders ' academic achievement, computational thinking skills and conceptual knowledge levels

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THINKING SKILLS AND CREATIVITY 2020年 38卷 100714-100714页

作者： Kert, Serhat Bahadir Erkoc, Mehmet Fatih Yeni, Sabiha Leiden Univ Leiden Inst Adv Comp Sci LIACS Leiden Netherlands Yildiz Tech Univ Dept Comp Educ & Instruct Technol Istanbul Turkey

This study compared the pedagogical effects of educational robot development and the block based programming perspectives, which are used in programming education, on middle school students. Its participants were 78 sixth graders. Considering the students' preferences, 38 students were assigned to the experimental group, which studied with robotics (Lego EV3) sets, and 40 students were assigned to the control group, which studied with block-based programming environment (Scratch). All the topics of the programming unit, which are shown in the methods section, were taught to both groups for 10 weeks using the two different approaches. The change created by the implementation between the groups was tested for academic achievement, computational thinking skill efficacy perceptions, and conceptual knowledge levels. The results indicate that educational robotics develop middle school students' academic achievement and computational thinking skill efficacy perceptions more effectively than block-based programming environments. The connections between the concepts of the students who did robotics were also found to be more solid than those who worked with block-based software.

关键词： programming education Robotics block-based programming Computational thinking Conceptual knowledge level

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