Visualization as effective instructional and learning tools in the computer science curriculum

Abstract

Visualization (the use of images, diagrams, presentations, animations, gaming, and video) represents a potentially effective aid in teaching and learning, especially in the STEM (Science, Technology, Engineering, and Mathematics) fields where abstract complex ideas and concepts are abound. Educators, especially in academia, are always searching for effective pedagogical methodologies to use in the classroom to enhance students' understanding and retention of key concepts of the subject area they are teaching. With the rapid advancements in software, hardware, networking, computing and storage technologies, including laptops, tablets, smartphones, cloud and distributed computing, the use of multimedia as an effective tool and aid in the classroom has become a standard procedure, rendering obsolete the traditional pure "chalk and talk." The next natural step to take is to enhance the presented course content through effective multimedia techniques. Of those techniques, visualization and animation have the most potential to revolutionize the way students learn and understand complex concepts that usually arise in the STEM fields, as they inherently appeal to our highly developed and specialized visual system that effortlessly identifies patterns, trends, and outliers. Our paper presents a set of student-developed visualizations in strategically selected CS courses that enabled them to learn STEM related concepts in general (such as limits, differentiation, integration, and projectiles to name a few), and CS concepts/algorithms in particular. In creating these visualizations, the professors and the graduate assistants focused on incorporating into them a set of overarching themes that are effective and can be expanded to other fields. The themes were inspired by findings from a leading NSF Cutting Edge grant on teaching with visualization in a closely related field, although not one in STEM. The visualizations created were clear and simple; they are built on top of proven educational activities that were used in the past; the students' feedback was a central component as the visualizations were built step by step; the visualizations defined the pre-conditions before which a student can watch or run them, so that context is welldefined and not lost; and finally, the visualizations were organized to reflect the mental organization that the student is creating. The paper gives details about the visualization algorithms, the criteria for their selection and inclusion in the curriculum, the students' immediate feedback, and survey results, taken by the students, that contrast the traditional ways of teaching CS and STEM concepts vs. The additional use of the developed visualizations. Our survey results shed light on whether visualizations make good tools for teaching, and if they have an effect on the rate (how quickly) of learning. Conclusions and recommendations are also presented.