To combat the decline of teaching computing courses in high schools, a plan was created to offer professional development (in both content and pedagogy) to high school computing teachers, and to have college faculty p...
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ISBN:
(纸本)9781605588858
To combat the decline of teaching computing courses in high schools, a plan was created to offer professional development (in both content and pedagogy) to high school computing teachers, and to have college faculty partner with those high school teachers to implement innovative curricula. This paper describes a pilot program that was run in support of an NSF Innovative Technology Experiences for Students and Teachers (ITEST) project that funded this plan of action. Professional development activities were offered during summer 2006 and the resulting curriculum was taught in high school the following academic year (2006-2007).
xDIVA, a 3D debugging visualization tool, provides a platform by which visualization metaphors are interactive, composable and de-coupled from data, i.e. a complicated visualization can be composed and assembled from ...
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ISBN:
(纸本)9781450304948
xDIVA, a 3D debugging visualization tool, provides a platform by which visualization metaphors are interactive, composable and de-coupled from data, i.e. a complicated visualization can be composed and assembled from basic ones, each of which is independently replaceable. Based on the progress of xDIVA, this tool demo paper describes an automatic animation system to generate interpolated frames between key frames, where key frames are snapshots of the 3D scene at breakpoints. This approach does not require users to add or write any animation code and is more feasible for practical use.
visualization software in all fields becomes increasingly interactive with more and more elements to support users. Elements that help an observer to interpret given data sets by computing certain properties of the da...
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ISBN:
(纸本)9781450300766
visualization software in all fields becomes increasingly interactive with more and more elements to support users. Elements that help an observer to interpret given data sets by computing certain properties of the data to enrich their visualization we call "visual scouts". Many visualizationprograms implement visual scouts, but few is known about how users apply them in a real setting. In order to learn more about how users work with interactive visualization software we provide them with clustering methods (k-mean and hierarchical clustering), as one possibility to manipulate the data. Subsequently we evaluate how natural science students use these clustering methods as provided by an interactive comparative visualization software for high dimensional data (VisuLab~(?)). The students are introduced to four different visualization methods (figure 1) and given the possibility to apply four clustering methods to help them when interpreting two sample datasets (table 1 first two rows). This is part of a guided instruction after which they independently interpret two new but related real data sets (table 1 last two rows). In total they work for about six hours. During our evaluation we were able to record the clustering activities of ~250 students, by directly logging the user's activities within the software. Based on this data we computed how many times the data was clustered and with which visualization methods the results were visualized. In total we registered over 57'000 clustering activities of which 30% where
TinyOS is an effective platform for developing lightweight embedded network applications. But the platform's lean programming model and power-efficient operation come at a price: TinyOS applications are notoriousl...
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TinyOS is an effective platform for developing lightweight embedded network applications. But the platform's lean programming model and power-efficient operation come at a price: TinyOS applications are notoriously difficult to construct, debug, and maintain. The development difficulties stem largely from a programming model founded on events and deferred execution. In short, the model introduces non-determinism in the execution ordering of primitive actions - an issue exacerbated by the fact that embedded network systems are inherently distributed and reactive. The resulting set of possible execution sequences for a given system is typically large and can swamp developers' unaided ability to reason about program behavior. In this paper, we present a visualization toolkit for TinyOS 2.0 to aid in program comprehension. The goal is to assist developers in reasoning about the computation forest underlying a system under test and the particular branches chosen during each run. The toolkit supports comprehension activities involving both local and distributed runtime *** constituent components include (i) a full-featured static analysis and instrumentation library, (ii) a selection-based probe insertion system, (iii) a lightweight event recording service, (iv) a trace extraction and reconstruction tool, and (v) three visualization front-ends. We demonstrate the utility of the toolkit using both standard and custom system examples and present an analysis of the toolkit's resource usage and performance characteristics. (C) 2009 Elsevier B.V. All rights reserved.
Unix system calls to create and execute processes are usually hard to understand for novice students. Using graphics for visualizing the behaviour of these system calls can be useful both for the teacher to explain an...
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Unix system calls to create and execute processes are usually hard to understand for novice students. Using graphics for visualizing the behaviour of these system calls can be useful both for the teacher to explain and for the students to understand them. The problem here is that there is no software specifically addressed to generate graphical representations of these kind of programs, and to develop it would be costly. Instead of developing a complete system to visualize programs that use Unix system calls, we turned to a "cheaper" alternative solution. In this paper we show how we have used the open source graphviz tool to develop a simple way of generating graphical representations of the behaviour of these system calls, thus facilitating the comprehension of this important part in the learning of the Unix operating system.
jGRASP 1.8.7 has integrated three approaches for interacting with its dynamic viewers for data structures: the debugger, the workbench, and a new text-based interactions tab that allows individual Java statements to b...
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jGRASP 1.8.7 has integrated three approaches for interacting with its dynamic viewers for data structures: the debugger, the workbench, and a new text-based interactions tab that allows individual Java statements to be executed and expressions to be evaluated. While each of these approaches is distinct and can be used independently of the others, they can also be used together to provide a complementary set of interactions with the dynamic viewers. In order to integrate these approaches, the jGRASP visual debugger, workbench, and viewers had to be significantly redesigned. During this process, the structure identifier, which provides for the identification and rendering of common data structures, was also greatly improved by examining the examples from 20 data structure textbooks. The overall result of this integration effort is a highly flexible approach for user interaction with the dynamic data structure visualizations generated by a robust structure identifier.
Visualizing impacts of an optimization pass helps to reason about, and to gain insight into, the inner workings of the optimization pass. In this paper, we visualize the impacts of two procedural abstraction passes. F...
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Visualizing impacts of an optimization pass helps to reason about, and to gain insight into, the inner workings of the optimization pass. In this paper, we visualize the impacts of two procedural abstraction passes. For this, we modified two procedural abstraction post pass optimizers to visualize for each the difference in machine code before and after optimization by drawing abstracted fragments in the original program. We then explain how the generated visualizations aid in better understanding the optimization passes.
In this paper we survey experiments with program and algorithm visualizations (PAVs) where learning improvements have been detected. We analyze these experiments based on the student's level of engagement with the...
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In this paper we survey experiments with program and algorithm visualizations (PAVs) where learning improvements have been detected. We analyze these experiments based on the student's level of engagement with the visualizations. There are some features present in most of these, successful, experiments. Therefore they should be taken into account as important factors affecting pedagogical effectiveness of PAVs, these features are: narrative and textual contents, feedback to students' answers and a student centered approach when designing PAV construction kits.
EduVisor software visualization component is a new pedagogical tool specifically developed to address some wide-spread problems in teaching object-oriented technology to novice programmers. The visualization tool is i...
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EduVisor software visualization component is a new pedagogical tool specifically developed to address some wide-spread problems in teaching object-oriented technology to novice programmers. The visualization tool is integrated in a world-class IDE, and shows the students the structure of their own creations at runtime. EduVisor is based on a solid grounding in literature and over 25 years of combined experience in teaching a CS1 course. With this component we have set the goal of helping our students progress faster through the most difficult initial stages of programming.
We present two tools that make students more productive during various object-oriented design activities. The first one, Trace Modeler, is a smart UML sequence diagram editor that helps students understand and apply r...
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ISBN:
(纸本)9781605583815
We present two tools that make students more productive during various object-oriented design activities. The first one, Trace Modeler, is a smart UML sequence diagram editor that helps students understand and apply responsibility-driven design. The second tool, Trace4J, is used to record and process the execution of a java program. Both tools are complementary. Students use Trace4J to produce focused sequence diagrams for (part of) a program's execution. Trace Modeler's support for huge diagrams lets them navigate and understand the large results in the initial stages of their processing experiments.
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