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.

Engaging students in the learning process has been shown to be an effective means for education. Several methods have been proposed to achieve this engagement for computer science and other disciplines. Active learning is one such technique that incorporates interactive classroom activities to reinforce concepts and involve the students. Visualizations of computer science concepts such as algorithm animations can be used for these activities. To be most effective in this environment, they need to be designed and used with active learning in mind. This paper describes the design characteristics of such visualizations, ways of using them in the classroom, and our experience with developing and using visualization tools across different courses in the computer science curriculum.

algorithm visualization, data structure visualization, algorithm animation, algoviz, algoviz wiki, community, open source

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We present our findings on the state of the field of algorithm visualization, based on extensive search and analysis of links to hundreds of visualizations. We seek to answer questions such as how content is distributed among topics, who created algorithm visualizations and when, the overall quality of available visualizations, and how visualizations are disseminated. We have built a wiki that currently catalogs over 350 algorithm visualizations, contains the beginnings of an annotated bibliography on algorithm visualization literature, and provides information about researchers and projects. Unfortunately, we found that most existing algorithm visualizations are of low quality, and the content coverage is skewed heavily toward easier topics. There are no effective repositories or organized collections of algorithm visualizations currently available. Thus, the field appears in need of improvement in dissemination of materials, informing potential developers about what is needed, and propagating known best practices for creating new visualizations.

There are inherent challenges in teaching and learning Artificial Intelligence (AI) due to the complex dynamics of the many fundamental AI concepts and algorithms. Interactive visualization tools have the potential to overcome these challenges. However, there are reservations towards adopting interactive visualizations due to mixed results on their pedagogical effectiveness. Previous work has also often failed to directly assess student preferences and motivation. CIspace is a set of nine interactive visualization tools demonstrating fundamental principles in AI. The CIspace tools are currently in use in undergraduate and graduate classrooms at the University of British Columbia and around the world. In this paper, we present two experiments aimed at assessing the effectiveness of one the tools in terms of knowledge gain and user preference. Our results provide evidence that the tool is as effective as a traditionally accepted form of learning in terms of knowledge gain, and that students significantly prefer to use the tools over traditional forms of study. These results strengthen the case for the incorporation of CIspace, and other interactive visualizations, into courses.

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 effectiveness 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 effectiveness, 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 effective 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 effect on learning.

In this paper, we present our vision for OpenDSA, an opensource, community-based effort to create a complete activeeBook for Data Structures and Algorithms courses at the undergraduate level. We define active-eBooks as going beyond classic hypertextbooks, being a close integration of text and images with interactive visualizations/simulations and assessment activities. The OpenDSA project is meant to proceed with broad participation from the CS Education community, with maximum flexibility on reuse of materials, and with the ability for a given instructor to pick and choose material from the collection and modify as desired. We discuss the goals of the project, our initial community organization efforts, and the technical infrastructure that we envision for the project. Initial progress is described. 1.