User-adaptive visualization and explanatory visualization have been suggested to increase educational effectiveness of program visualization. This paper presents an attempt to assess the value of these two approaches....
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User-adaptive visualization and explanatory visualization have been suggested to increase educational effectiveness of program visualization. This paper presents an attempt to assess the value of these two approaches. The results of a controlled experiment indicate that explanatory visualization allows students to substantially increase the understanding of a new programming topic. Furthermore, an educational application that features explanatory visualization and employs a user model to track users' progress allows students to interact with a larger amount of material than an application which does not follow users' activity. However, no support for the difference in short-term knowledge gain between the two applications is found. Nevertheless, students admit that they prefer the version that estimates and visualizes their progress and adapts the learning content to their level of understanding. They also use the application's estimation to pace their work. The differences in eye movement patterns between the applications employing adaptive and non-adaptive explanatory visualizations are investigated as well. Gaze-based measures show that adaptive visualization captivates attention more than its non-personalized counterpart and is more interesting to students. Natural language explanations also accumulate a big portion of students' attention. Furthermore, the results indicate that working memory span can mediate the perception of adaptation. It is possible that user-adaptation in an educational context provides a different service to people with different mental processing capabilities.
The visualization of programs and algorithms has been demonstrated to be essential when learning to program. Nevertheless, existing graphic representations require a high level of abstraction that most beginner progra...
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The visualization of programs and algorithms has been demonstrated to be essential when learning to program. Nevertheless, existing graphic representations require a high level of abstraction that most beginner programmers cannot understand. Current state-of-the-art approaches provide promising alternatives, but a significant part leaves the advantages of graphic representation in the background. These advantages include abstracting the source code by means of symbols that make them easier to understand without previous training. This work introduces the evolution of a 2-D graphic notation to a 3-D environment, which represents an improvement to a complete platform for collaborative programming learning through problem solving, named COLLECE-2.0. This improvement provides the platform with capabilities to visualize programs through augmented reality by using a new set of graphic representations, which are based on roads and traffic signs in the context of programming learning. These visual models have been evaluated by Computer Science students to know whether the proposed notation is intuitive and useful. The obtained results show that the proposed notation is suitable for representing programming concepts and easy to understand. We also present a series of improvements, integrated as a new subsystem in the aforementioned platform, which allows the automatic construction of 3-D visualizations on an augmented reality environment. These visualizations use the proposed notation and leverage the scalability and architecture of COLLECE-2.0.
An increase in student motivation is often cited as an expected effect of software visualization, but, as far as the authors are aware, no controlled experiments have yet demonstrated this. This paper therefore presen...
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An increase in student motivation is often cited as an expected effect of software visualization, but, as far as the authors are aware, no controlled experiments have yet demonstrated this. This paper therefore presents a controlled evaluation of this effect, conducted within the framework of self-determination theory. Students were tasked with removing redundant recursion in a multiple recursive algorithm. The experimental group (N = 19) used the SRec program visualization system, while the control group (N = 17) could use any programming tool in which they were proficient, such as BlueJ or Eclipse. The increase in motivation was measured by the difference between student scores in pre-and post-tests of their motivation. Statistically significant increases were observed for the two more determined forms of motivation, intrinsic motivation (p = 0.01), and extrinsic motivation via identified regulation (p = 0.03). Student feedback about their subjective acceptance of SRec reinforced these results. These findings give experimental support to expectations for software visualization in terms of motivation. Several paths for future work are identified, in particular, the need for more experiments under various conditions to achieve deeper understanding of the motivational effect of program visualization.
Pictorial representations of program structure, control flow, and data have always been part of the programmer's repertoire of tools and techniques. Such representations can simplify and enhance the explanation of...
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Pictorial representations of program structure, control flow, and data have always been part of the programmer's repertoire of tools and techniques. Such representations can simplify and enhance the explanation of specific aspects of a program. Now that workstations are equipped with powerful graphics capabilities, interest has shifted from simple, static representations to dynamic representations of program behavior. Generating and using graphical program representations has become a recognized scientific endeavor called program visualization. This field is attracting considerable attention from researchers who hope to put their results to practical use in areas as diverse as software design, performance monitoring, and soft-ware training. However, a significant gap exists between program visualization research and its practical application to programming environments and design tools. To remedy this situation, the authors present a taxonomy of program visualization systems (excluding related work in visual programming and scientific visualization). The authors illustrate the taxonomy with three program visualization systems representative of research trends: Zeus, Tango, and Pavane. They represent examples of their taxonomic criteria, generating color images by using Pavane, except as noted.
We propose Observer architecture for program visualization. The principles of Observer architecture are modular, model-driven visualization with one-directional coupling, hierarchical delegation, message-passing and a...
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We propose Observer architecture for program visualization. The principles of Observer architecture are modular, model-driven visualization with one-directional coupling, hierarchical delegation, message-passing and archival by visualizers. The architecture is scalable. The resulting visualization can be distributed and modified independent of the model. The Observer architecture has been implemented in online tutors for programming called problets.
Based on previous research, it seems that the activities performed by and the engagement of the students matter more than the content of the visualization. One way to engage students to interact with a visualization i...
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Based on previous research, it seems that the activities performed by and the engagement of the students matter more than the content of the visualization. One way to engage students to interact with a visualization is to present them with prediction questions. This has been shown to be beneficial for learning. Based on the engagement taxonomy and benefits of the question answering during the algorithm visualization, we propose to implement an automatic question generation into a program visualization tool, Jeliot 3. In this paper, we explain how the automatic question generation can be incorporated into the current design of Jeliot 3. In addition, we provide various example questions that could be automatically generated based on the data obtained during the visualization process.
This paper presents the results of an experiment aimed at investigating how different methods of viewing visual programs affect users' understanding. The first two methods used traditional flat and semantic zoomin...
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ISBN:
(纸本)0780381548
This paper presents the results of an experiment aimed at investigating how different methods of viewing visual programs affect users' understanding. The first two methods used traditional flat and semantic zooming models of program representation;the third is a new representation that uses semantic zooming combined with blending and proximity. The results of several search tasks performed by approximately 80 participants showed that the new method resulted in both faster and more accurate searches than the other methods.
In this paper, we describe the development of an instructional tool called JavaHelper for teaching the basics of Java programming. The tool can help beginner students understand the inner workings of programming by an...
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ISBN:
(纸本)193241584X
In this paper, we describe the development of an instructional tool called JavaHelper for teaching the basics of Java programming. The tool can help beginner students understand the inner workings of programming by animating the data flow, control flow, and dynamic execution of a program. JavaHelper can be used as an instructional aide in introductory programming courses. We describe the development and use of the system, and also discuss its role in improving learning outcomes for beginner programmers.
Acquisition of programming concepts and skills is a key goal of computer science and engineering curricula. It has been shown that students find programming to be a difficult and complex cognitive task. program visual...
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ISBN:
(纸本)9780769551418
Acquisition of programming concepts and skills is a key goal of computer science and engineering curricula. It has been shown that students find programming to be a difficult and complex cognitive task. program visualizations have been shown to improve students' understanding, but most studies have been conducted in resource equipped classrooms, for example, in which students have personalized access to laptops. In this paper, we report findings from a two-group experimental study (N=60) in a resource constrained classroom with a single computer and mounted LCD. One group was taught with an interactive program visualization tool and the other with traditional chalk and blackboard approach. Analysis showed a statistically significant higher performance on a post-test for the program visualization group compared to the traditional group. This difference was seen regardless of students' visual / verbal learning style, leading to the conclusion that use of program visualization in large resource constrained classroom is an effective strategy to teach computer programming.
Multiple studies report that Computer Science (CS) instructors face problems on how to integrate visualizations in their teaching. This problem gets compounded for instructors in technology-constrained classrooms that...
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