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 effectiveness. However, while several integrative reviews of AV technology have appeared, none has focused specifically on the software's effectiveness by analyzing this body of experimental studies as a whole. In order to better understand the effectiveness of AV technology, we present a systematic metastudy 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 benefits of AV technology. Our most significant finding is that how students use AV technology has a greater impact on effectiveness than what AV technology shows them. Based on our findings, we formulate an agenda for future research into AV effectiveness.

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.

Abstract — Animation has been used to show trends in multi-dimensional data. This technique has recently gained new prominence for presentations, most notably with Gapminder Trendalyzer. In Trendalyzer, animation together with interesting data and an engaging presenter helps the audience understand the results of an analysis of the data. It is less clear whether trend animation is effective for analysis. This paper proposes two alternative trend visualizations that use static depictions of trends: one which shows traces of all trends overlaid simultaneously in one display and a second that uses a small multiples display to show the trend traces side-by-side. The paper evaluates the three visualizations for both analysis and presentation. Results indicate that trend animation can be challenging to use even for presentations; while it is the fastest technique for presentation and participants find it enjoyable and exciting, it does lead to many participant errors. Animation is the least effective form for analysis; both static depictions of trends are significantly faster than animation, and the small multiples display is more accurate. Index Terms—Information visualization, animation, trends, design, experiment. 1 INTRODUCTION: TREND

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.

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.

Recent advances in programming environments have focused on improving programmer productivity by utilizing the inherent structure in computer programs. However, because these environments represent code as plain text, it is difficult and sometimes impossible to embed interactive tools, annotations, and alternative views in the code itself. Barista is an implementation framework that enables the creation of such user interfaces by simplifying the implementation of editors that represent code internally as an abstract syntax tree and maintain a corresponding, fully structured visual representation on-screen. Barista also provides designers of editors with a standard text-editing interaction technique that closely mimics that of conventional text editors, overcoming a central usability issue of previous structured code editors.

Jeliot 2000 is a program animation system intended for teaching computer science to high school students. This paper describes the design and implementation of Jeliot 2000 and an experiment in its use in a year-long course. The experiment showed that animation provides a vocabulary and a concrete model that can improve the learning of students who would otherwise have di#culty with abstract computerscience concepts. 1

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This paper describes the design of the CIspace interactive visualization tools for teaching and learning Artificial Intelligence. Our approach to design is to iterate through three phases: identifying pedagogical and usability goals for supporting both educators and students, designing to achieve these goals, and then evaluating our system. We believe identifying these goals is essential in confronting the usability deficiencies and mixed results about the pedagogical effectiveness of interactive visualizations reported in the Education literature. The CIspace tools have been used and positively received in undergraduate and graduate classrooms at the University of British Columbia and internationally. We hope that our experiences can inform other developers of interactive visualizations and encourage their use in classrooms and other learning environments.