Block-based programming languages were originally designed for educational purposes. Due to their low requirements for a user's programming capability, such languages have great potential to serve both introductory programmers in educational settings as well as domain experts as a data processing tool. However, the current design of block-based languages fails to address critical factors for these two audiences: 1) domain experts do not have the ability to perform crucial steps: import data sources, perform efficient data processing, and visualize results; 2) the focus of online assignments towards introductory programmers on entertainment (e.g. games, animation) fails to convince students that computer science is important, relevant, and related to their day-to-day experiences. In this thesis, we present the design and implementation of DataSnap, which is a block-based programming language extended from Snap!. Our work focuses on enhancing the state of the art in block-based programming languages for our two target audiences: domain experts and introductory programmers. Specifically, in this thesis we: 1) provide easy-to-use interfaces for big data import, processing, and visualization methods for domain experts; 2) integrate relevant social media, geographic, and business-related data sets into online educational platforms for introductory programmers and enable teachers to develop their own real-time and big-data access blocks; and 3) present DataSnap in the Open edX online courseware platform along with customized problem definition and a dynamic analysis grading system. Stemming from our research contributions, our work encourages the further development and utilization of block-based languages towards a broader audience range. / Master of Science

Students with upper body motor impairments, such as cerebral palsy, multiple sclerosis, ALS, etc., face challenges when learning to program in block-based programming environments, because these environments are highly dependent on the physical manipulation of a mouse or keyboard to drag and drop elements on the screen. In my dissertation, I make the block-based programming environment Blockly, accessible to students with upper body motor impairment by adding speech as an alternative form of input. This voice-enabled version of Blockly will reduce the need for the use of a mouse or keyboard, making it more accessible to students with upper body motor impairments. The voice-enabled Blockly system consists of the original Blockly application, a speech recognition API, predefined voice commands, and a custom function. Three user studies have been conducted, a preliminary study, a usability study, and an A/B test. These studies revealed a lot of information, such as the need for simpler, shorter, and more intuitive commands, the need to change the target audience, the shortcomings of speech recognition systems, etc. The feedback received from each study influenced design decisions at different phases. The findings also gave me insight into the direction I would like to go in the future. This work was started and finished in 2 years.

As Scratch has become one of the most popular educational programming languages, understanding its common programming idioms can benefit both computing educators and learners. This understanding can fine-tune the curricular development to help learners master the fundamentals of writing idiomatic code in their programming pursuits. Unfortunately, the research community's understanding of what constitutes idiomatic Scratch code has been limited. To help bridge this knowledge gap, we systematically identified idioms as based on canonical source code, presented in widely available educational materials. We implemented a tool that automatically detects these idioms to assess their prevalence within a large dataset of over 70K Scratch projects in different demographic and project categories. Since communal learning and the practice of remixing are one of the cornerstones of the Scratch programming community, we studied the relationship between common programming idioms and remixes. Having analyzed the original projects and their remixes, we observed that different idioms may associate with dissimilar types of code changes. Code changes in remixes are desirable, as they require a meaningful programming effort that spurs the learning process. The ability to substantially change a project in its remixes hinges on the project's code being easy to understand and modify. Our findings suggest that the presence of certain common idioms can indeed positively impact the degree of code changes in remixes. Our findings can help form a foundation of what comprises common Scratch programming idioms, thus benefiting both introductory computing education and Scratch programming tools. / Master of Science / With over 68 million users and growing, Scratch has become one of the most popular programming languages for introductory computing learners. As with learning any programming language, understanding common programming idioms used in the language's application domain is important for both computing educators and learners. Educators need this understanding in order to fine-tune their curricular development, while learners can leverage this knowledge to effectively master the fundamentals by writing idiomatic code. Unfortunately, our understanding of what constitutes idiomatic Scratch code thus far has been limited. To address this knowledge gap, we systematically identified idioms based on source code with good code quality, as presented in widely available educational materials. We implemented a tool that automatically detects these idioms to assess their prevalence within a large, diverse dataset of over 70K Scratch projects. Since communal learning and the practice of remixing are one of the cornerstones of the Scratch programming community, we studied the relationship between common programming idioms and remixes. Having analyzed the original projects and their remixes, we found that different idioms may associate with dissimilar types of code changes. The ability to change a project in its remixes hinges on the project's code being easy to understand and modify. Our findings suggest that the presence of certain common idioms can positively impact the degree of code changes in remixes. Our findings can help form a foundation of what comprises common Scratch programming idioms, thus benefiting both introductory computing education and Scratch programming tools.

There is an increased use of block-based programming environments in K-12 education and computing outreach activities to introduce novices to programming and computational thinking skills. However, despite their appealing design that allows students to focus on concepts rather than syntax, block-based programming by design is inaccessible to people with visual impairments and people who cannot use the mouse. In addition to this inaccessibility, little is known about the instructional experiences of students with visual impairments on current block-based programming environments. This dissertation addresses this gap by (1) investigating the challenges that students with visual impairments face on current block-based programming environments and (2) exploring ways in which we can use the keyboard and the screen reader to create block-based code. Through formal survey and interview studies with teachers of students with visual impairments and students with visual impairments, we identify several challenges faced by students with visual impairments on block-based programming environments. Using the knowledge of these challenges and building on prior work, we explore how to leverage the keyboard and the screen reader to improve the accessibility of block-based programming environments through a prototype of an accessible block-based programming library. In this dissertation, our empirical evaluations demonstrate that people with visual impairments can effectively and efficiently create, edit, and navigate block-based code using the keyboard and screen reader alone. Addressing the inaccessibility of block-based programming environments would allow students with visual impairments to participate in programming and computing activities where these systems are used, thus fostering inclusion and promoting diversity.

A block-based adaptive mesh refinement (AMR) finite-volume scheme is developed for solution of hyperbolic conservation laws on two-dimensional hybrid multi-block meshes. A Godunov-type upwind finite-volume spatial-discretization scheme, with piecewise limited linear reconstruction and Riemann-solver based flux functions, is applied to the quadrilateral cells of a hybrid multi-block mesh and these computational cells are embedded in either body-fitted structured or general unstructured grid partitions of the hybrid grid. A hierarchical quadtree data structure is used to allow local refinement of the individual subdomains based on heuristic physics-based refinement criteria. An efficient and scalable parallel implementation of the proposed algorithm is achieved via domain decomposition. The performance of the proposed scheme is demonstrated through application to solution of the compressible Euler equations for a number of flow configurations and regimes in two space dimensions. The efficiency of the AMR procedure and accuracy, robustness, and scalability of the hybrid mesh scheme are assessed.

A block-based adaptive mesh refinement (AMR) finite-volume scheme is developed for solution of hyperbolic conservation laws on two-dimensional hybrid multi-block meshes. A Godunov-type upwind finite-volume spatial-discretization scheme, with piecewise limited linear reconstruction and Riemann-solver based flux functions, is applied to the quadrilateral cells of a hybrid multi-block mesh and these computational cells are embedded in either body-fitted structured or general unstructured grid partitions of the hybrid grid. A hierarchical quadtree data structure is used to allow local refinement of the individual subdomains based on heuristic physics-based refinement criteria. An efficient and scalable parallel implementation of the proposed algorithm is achieved via domain decomposition. The performance of the proposed scheme is demonstrated through application to solution of the compressible Euler equations for a number of flow configurations and regimes in two space dimensions. The efficiency of the AMR procedure and accuracy, robustness, and scalability of the hybrid mesh scheme are assessed.

This study aims to investigate CT in relation to students’ experience with visual programming - particularly visual programming language Scratch. The study looks at the level of CT among Swedish high school students. Two research questions are investigated; one related to students’ general programming experience, one related to their level of experience with programming language Scratch. The method used in the study is the Computational Thinking test (CTt). Data from 162 students is presented. The study finds that the students’ performance is relatively high, but not as high as expected given the fact that Swedish education has become heavily focused on teaching programming in recent years. The study also finds that the level of Scratch experience alone is not found to impact the performance, which implies that Scratch does not allow users to deepen their CT knowledge the more they use it. Visual programming is found to play an important role in the level of computational thinking, although the participants with the best results have additional experience of normal programming. The study concludes that visual programming needs to be combined with normal programming in order for students to achieve the best result within computational thinking

One of the greatest achievements of Scratch as an educational tool is the eager willingness of programmers to use existing projects as the starting point for their own projects, a practice known as remixing. Despite the importance of remixing as a foundation of collaborative and communal learning, the practice remains poorly understood. Without a clear picture of how and why Scratch programmers remix a project as a starting point of their own projects, this programming community would remain in the dark about which programming practices encourage and facilitate remixing. The designers of programming environments for blocks lack feedback on how the remixing facility is used in the wild. To gain a deeper insight into remixing, this thesis presents the results of a comprehensive study of this practice in Scratch that investigates the following heretofore unexplored dimensions of remixing: (1) the prevailing modifications that remixes perform on existing projects, (2) the impact of the original project's code quality on the granularity, extent, and development time of the modifications in the remixes, and (3) the propensity of the dominant programming practices in the original project to remain so in the remixes. Our findings can be used to promote those programming practices in the Scratch community that encourage remixing while also improving this practice's effectiveness, thus benefiting the educational and end-user programming communities. / Master of Science / The Scratch programming language has become an intrinsically important tool in introductory CS education. A visual, block-based language, Scratch is web-based, featuring an enormous online programming community, through which projects are eagerly shared. One of the unique learning provisions of Scratch is the ability to easily start a project by modifying someone else’s project, a practice referred to as remixing. Despite the central role that remixing plays in enabling the communal and collaborative learning styles in the Scratch community, the practice of remixing remains inadequately understood. This knowledge gap leaves the Scratch community in the dark about which programming practices encourage and facilitate remixing, as well as deprives Scratch environment designers from actionable feedback on how the remixing facility is used in the wild. To address this problem, this thesis reports on the results of an exploratory study of remixing in Scratch that investigates three heretofore unexplored dimensions of this practice. First, we study the general remixing trends in terms of how remixes modify the original projects. Second, we infer the impact of a project’s code quality on the modifications in its remixes and the development time. Finally, we investigate whether programmers adopt the techniques and practices of the remixed projects. Computing educators can apply our findings to enhance the educational effectiveness of Scratch by encouraging the practice and magnitude of remixing.

Much of software engineering research and practice is concerned with improving software quality. While enormous prior efforts have focused on improving the quality of programs, this dissertation instead provides the means to educate the next generation of programmers who care deeply about software quality. If they embrace the culture of quality, these programmers would be positioned to drastically improve the quality of the software ecosystem. This dissertation describes novel methodologies, techniques, and tools for introducing novice programmers to software quality and its systematic improvement. This research builds on the success of Scratch, a popular novice-oriented block-based programming language, to support the learning of code quality and its improvement. This dissertation improves the understanding of quality problems of novice programmers, creates analysis and quality improvement technologies, and develops instructional approaches for teaching quality improvement. The contributions of this dissertation are as follows. (1) We identify twelve code smells endemic to Scratch, show their prevalence in a large representative codebase, and demonstrate how they hinder project reuse and communal learning. (2) We introduce four new refactorings for Scratch, develop an infrastructure to support them in the Scratch programming environment, and evaluate their effectiveness for the target audience. (3) We study the impact of introducing code quality concepts alongside the fundamentals of programming with and without automated refactoring support. Our findings confirm that it is not only feasible but also advantageous to promote the culture of quality from the ground up. The contributions of this dissertation can benefit both novice programmers and introductory computing educators. / Doctor of Philosophy / Software remains one of the most defect-prone artifacts across all engineering disciplines. Much of software engineering research and practice is concerned with improving software quality. While enormous prior efforts have focused on improving the quality of programs, this dissertation instead provides the means to educate the next generation of programmers who care deeply about software quality. If they embrace the culture of quality, these programmers would be positioned to drastically improve the quality of the software ecosystem, akin to professionals in traditional engineering disciplines. This dissertation describes novel methodologies, techniques, and tools for introducing novice programmers to software quality and its systematic improvement. This research builds on the success of Scratch, a popular visual programming language for teaching introductory students, to support the learning of code quality and its improvement. This dissertation improves the understanding of quality problems of novice programmers, creates analysis and quality improvement technologies, and develops instructional approaches for teaching quality improvement. This dissertation contributes (1) a large-scale study of recurring quality problems in Scratch projects and how these problems hinder communal learning, (2) four new refactorings, quality improving behavior-preserving program transformations, as well as their implementation and evaluation, (3) a study of the impact of introducing code quality concepts alongside the fundamentals of programming with and without automated refactoring support. Our findings confirm that it is not only feasible but also advantageous to promote the culture of quality from the ground up. The contributions of this dissertation can benefit both novice programmers and introductory computing educators.

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