Pedagogical practices and benefits of using auto-generation approach to facilitate teaching data structures and algorithms
Sen Zhang, Jim Ryder · Journal of computing sciences in colleges · 2013
Data Structures and Algorithms (DSAAs) are always important for Computer Science (CS) undergraduate students to learn. However, they are becoming more and more difficult to teach, especially when facing a new generation of CS students with hindered computing and programming proficiency levels due to the diminishing high school CS AP offering and many CS 1 courses that have been designed to be more forgiving than in the past in response to huge recruiting pressure. The data structures and algorithms education is further complicated by the contradiction between the growing amount of materials to be learned in the field and the pressure for students to graduate in four years, which has resulted in that students have less time to spend on many important topics including DSAAs. How to efficiently teach classical DSAAs remains a challenge to undergraduate computer science education (UCSE) instructors. This is especially true in small liberal arts colleges, where CS programs are small and limited faculty members need to learn ever-changing new things in order to keep abreast with the fast evolving field. In respond to the above observations, we have been exploring a novel and practical approach to facilitate teaching and learning DSAAs using auto-generated visualization-based teaching materials. This approach helps CS instructors quickly prepare running examples of DSAAs in the PowerPoint format, a de facto standard lecture presentation format, to facilitate teaching of DSAAs.