Collaborative Research: Increasing Conceptual Understanding through Annotation Visualization

Computer Science (31) This project's goal is to conduct a large study involving more than 400 students at two different institutions to study the relationship between conceptual misunderstandings, code testing and development times. Conceptual understanding is measured by engaging students in reading and annotating documents that contain both accurate and erroneous concepts, and measuring how many students detect the errors and how many iterations it takes to detect all errors. This is then compared with code debugging times with the expectation that the text engagement process will actually reduce the amount of time spent on project tasks. The project establishes a scalable model of Reading-Annotation-Visualization (RAV) that can be deployed in any of the early programming courses. RAV model proceeds by pre-analyzing the important conceptual challenges students will encounter in the programming phase and then supporting the comprehension of these concepts prior to the programming phase through annotation, visualization and classroom discussions. This project assesses the potential of a participatory reading, discussion and learning environment to improve the reading comprehension, writing, and programming skills of computer science undergraduates. It contributes to the understanding of the relationship between reading and discussion and programming skills in computer science. The project results are disseminated via conference proceedings. RAV model and Classroom Salon are shared with any other institution willing to implement a classroom instruction model where understanding of student misconceptions early in the learning process is critical to better learning outcomes.