Visualization technology can be used to graphically illustrate various concepts in computer science. We argue that such technology, no matter how well it is designed, is of little educational value unless it engages learners in an active learning activity. Drawing on a review of experimental studies of visualization effectiveness, we motivate this position against the backdrop of current attitudes and best practices with respect to visualization use. We suggest a new taxonomy of learner engagement with visualization technology. Grounded in Bloom’s wellrecognized taxonomy of understanding, we suggest metrics for assessing the learning outcomes to which such engagement may lead. Based on these taxonomies of engagement and effectiveness metrics, we present a framework for experimental studies of visualization effectiveness. Interested computer science educators are invited to collaborate with us by carrying out studies within this framework.

JAWAA is a simple command language for creating animations of data structures and displaying them with a Web browser. Commands are stored in a script file that is retrieved and run by the JAWAA applet when the applet's Web page is accessed through the Web. JAWAA commands allow for creation and movement of primitive objects (circles, lines, text, rectangles) and data structure objects (arrays, stacks, queues, lists, trees and graphs). A JAWAA script can be generated as the output of a program written in any language. 1 Introduction An animation of a data structure is helpful to students as an educational aid in two ways, first as an alternative view in understanding a newly presented data structure or algorithm and second as an aid in debugging a program that uses the data structure. An animation can be easier to understand and remember than a textual representation, especially when one can interact with the animation by trying different input. Furthermore, using animations to debug p...

In this paper we present LEONARDO, an integrated environment for software visualization that allows the user to edit, compile, execute, and animate general-purpose C programs.

In this paper, we present ANIMAL, a new tool for developing animations to be used in lectures. ANIMAL offers a small but powerful set of graphical operators. Animations are generated using a visual editor, by scripting or via API calls. All animations can be edited visually. ANIMAL supports source and pseudo code inclusion and highlighting as well as precise user-defined delays between actions. The paper evaluates the functionality of ANIMAL in comparison to other animation tools.

Despite the intuitively compelling adage "a picture is worth a thousand words," attempts over the past decade to use animations to explain algorithms to students have produced disappointing results. In most cases interesting algorithm animations were designed, but no formal, systematic evaluations were conducted. When such evaluations were performed the results were mixed, with compelling evidence for the instructional superiority of algorithm animations failing to emerge. It is in this context that we embarked on a research program to develop educationally effective algorithm visualizations. This program was based on the premise that animations needed to be embedded in a knowledge and context providing hypermedia environment in order to effectively harness their power to enhance learning. This paper describes the architecture of the resulting Hypermedia Algorithm Visualization system HalVis. Four empirical studies with HalVis are described, which demonstrated that the extent of learning exhibited by students who used HalVis was significantly greater than that of students who used means of traditional instruction or a typical algorithm animation.

We present JAWAA 2.0, a scripting language for creating animations easily over the web. JAWAA includes primitives, easy creation of data structures and operations on these structures, and an editor for easy creation of complex objects. We show how to use JAWAA in a range of computer science courses including CS 0, CS 1, CS 2 and advanced courses. Instructors can quickly build animations for demos in lecture, and students can enhance their programming projects with an animation.

Many algorithm visualizations have been created, but little is known about which features are most important to their success. We believe that pedagogically useful visualizations exhibit certain features that hold across a wide range of visualization styles and content. We began our efforts to identify these features with a review that attempted to identify an initial set of candidates. We then ran two experiments that attempted to identify the e#ectiveness for a subset of features from the list. We identified a small number of features for algorithm visualizations that seem to have a significant impact on their pedagogical e#ectiveness, and found that several others appear to have little impact. The single most important feature studied is the ability to directly control the pace of the visualization. An algorithm visualization having a minimum of distracting features, and which focuses on the logical steps of an algorithm, appears to be best for procedural understanding of the algorithm. Providing a good example for the visualization to operate on proved significantly more e#ective than letting students construct their own data sets. Finally, a pseudocode display, a series of questions to guide exploration of the algorithm, or the ability to back up within the visualization did not show a significant e#ect on learning.

this paper, however, we limit ourselves to the discussion of some of the implications of the Web paradigm on computing education. We should clearly state that our aim is not to discuss future computer science curricula. Instead, our focus is on the teaching and learning environment that will result from the Web paradigm and---by implication--- the profound influence it will have on any new curriculum models. In the Web paradigm, instructors will tend away from a traditional lecture style towards the role of a facilitator, and students will become more active in exploratory learning

Computer animation is an excellent medium for capturing the dynamic nature of data structure manipulations, and can be used to advantage in the teaching of algorithms and data structures. A major educational issue is the necessity of providing a means for the student to manage the complexity of the material. We have addressed this issue in a multimedia teaching tool called “Algorithms in Action ” by allowing students to view an algorithm at varying levels of detail. Starting with a high level pseudocode description of the algorithm, with accompanying high level animation and textual explanation, students can expand sections of the pseudocode to expose more detail. Animation and explanation are controlled in a coordinated fashion, becoming correspondingly more detailed as the pseudocode is expanded. The tool also supports dofferem,pdes. corresponding to different stages in the learning process. Student feedback suggests that the availability of multiple levels detail and the facility for the user to control the level of detail being viewed is an effective way to manage content complexity.

Understanding data structures and algorithms, both of which are abstract concepts, is an integral part of software engineering and elementary computer science education. However, people usually have difficulty in understanding abstract concepts and processes such as procedural encoding of algorithms and data structures. One way to improve their understanding is to provide visualizations to make the abstract concepts more concrete. This thesis presents the design, implementation and evaluation for the Matrix application framework that occupies a unique niche between the following two domains. In the first domain, called algorithm animation, abstractions of the behavior of fundamental computer program operations are visualized. In the second domain, called algorithm simulation, the framework for exploring and understanding algorithms and data structures is exhibited. First, an overview and theoretical basis for the application framework is presented. Second, the different roles are defined and examined for realizing the idea of algorithm