Taxonomy of effortless creation of algorithm visualizations (original) (raw)
Related papers
A Language and System for Constructing and Presenting Low Fidelity Algorithm Visualizations
Lecture Notes in Computer Science, 2002
Computer science educators have traditionally used algorithm visualization (AV) software to create graphical representations of algorithms that are later used as visual aids in lectures, or as the basis for interactive labs. Typically, such visualizations are high fidelity in the sense that (a) they depict the target algorithm for arbitrary input, and (b) they tend to have the polished look of textbook figures. In contrast, low fidelity visualizations illustrate the target algorithm for a few, carefully chosen input data sets, and tend to have a sketched, unpolished appearance. Drawing on the findings of ethnographic studies we conducted in a junior-level algorithms course, we motivate the use of low fidelity AV technology as the basis for an alternative learning paradigm in which students construct and present their own visualizations. To explore the design space of low fidelity AV technology, we present a prototype language and system derived from empirical studies in which students constructed and presented visualizations made out of simple art supplies. Our prototype language and system pioneer a novel technique for programming visualizations based on spatial relations, and a novel presentation interface that supports reverse execution and dynamic mark-up and modification
Proceeding 2000 IEEE International Symposium on Visual Languages, 2000
Computer science educators have traditionally used algorithm visualization (AV) software to create graphical representations of algorithms that are later used as visual aids in lectures, or as the basis for interactive labs. Based on ethnographic field studies we have conducted in an undergraduate algorithms course, we advocate an alternative teaching approach in which students use simple art supplies to construct and present their own visualizations to their peers and instructor for feedback and discussion. To support this approach, we have built SALSA and ALVIS, a prototype language and system that enable students to (a) quickly construct rough, unpolished ("low fidelity") visualizations in much the same way they would do so with simple art supplies, and (b) interactively present those visualizations to an audience. Our prototype pioneers a novel technique for programming visualizations based on spatial relations, and a novel presentation interface that supports reverse execution and dynamic mark-up and modification.
Getting algorithm visualizations into the classroom
2011
Algorithm visualizations (AVs) are widely viewed as having the potential for improving computer science education. However, the rate of AV use and overall impact on education does not match the positive interest in their use that instructors report. Surveys of CS faculty show that impediments to successful use of AVs in the classroom include difficulties in finding quality AVs on desired topics, difficulties in adapting AVs to a given classroom setting, and lack of knowledge on the best way to deploy AVs. This indicates a need for better support for instructors, to get them past these barriers. We seek to provide this support through an online educational community that relies on a new model based less on the "digital library" approach of information gained by going to a site and searching. Instead, the focus is on community-added content through members' discussions, reviews, and ratings of content items. The AlgoViz community effort will better focus the future direction of AV development and use.
Algorithm Visualization: The State of the Field
ACM Transactions on Computing Education / ACM Journal of Educational Resources in Computing, 2010
We report on the state of the field of algorithm visualization, both quantitatively and qualitatively. Computer science educators seem to find algorithm and data structure visualizations attractive for their classrooms. Educational research shows that some are effective while many are not. Clearly, then, visualizations are difficult to create and use right. There is little in the way of a supporting community, and many visualizations are downright poor. Topic distribution is heavily skewed towards simple concepts with advanced topics receiving little to no attention.
Addressing Pedagogical Requirements in Algorithm Visualizations
Although algorithm visualizations have become numerous, they still have not been successfully adapted into mainstream computer science education. Algorithm visualization systems need to better address pedagogical requirements for effective educational use. We discuss the relevance of several such requirements that are not supported in most systems. The combination of two existing algorithm visualization systems implements these requirements and thereby provides a rich testbed for future studies of effectiveness.
A Meta-Study of Algorithm Visualization Effectiveness
Journal of Visual Languages & Computing, 2002
Algorithm visualization (AV) technology graphically illustrates how algorithms work. Despite the intuitive appeal of the technology, it has failed to catch on in mainstream computer science education. Some have attributed this failure to the mixed results of experimental studies designed to substantiate AV technology's educational e¡ectiveness. However, while several integrative reviews of AV technology have appeared, none has focused speci¢cally on the software's e¡ectiveness by analyzing this body of experimental studies as a whole. In order to better understand the e¡ectiveness of AV technology, we present a systematic meta-study of 24 experimental studies.We pursue two separate analyses: an analysis of independent variables, in which we tie each study to a particular guiding learning theory in an attempt to determine which guiding theory has had the most predictive success; and an analysis of dependent variables, which enables us to determine which measurement techniques have been most sensitive to the learning bene¢ts of AV technology. Our most signi¢cant ¢nding is that how students use AV technology has a greater impact on e¡ectiveness than what AV technology shows them. Based on our ¢ndings, we formulate an agenda for future research into AV e¡ectiveness. r
Addressing Pedagogical Requirements in Algorithm Visualuzation
2002
Although algorithm visualizations have become numerous, they still have not been successfully adapted into mainstream computer science education. Algorithm visualization systems need to better address pedagogical requirements for effective educational use. We discuss the relevance of several such requirements that are not supported in most systems. The combination of two existing algorithm visualization systems implements these requirements and thereby provides a rich testbed for future studies of effectiveness.