Abstract :
In the Introduction to Analysis of Algorithms, students traditionally apply a combination of computer science theory and mathematics to paper-based problem solving, analysis of pre-developed algorithms and proofs of algorithmic run-times. In this paper, we suggest that a major factor that determines the success in the Analysis is the discrepancy between the programming styles of CS1 and CS2, with immediate feedback of student solutions, a dynamic working environment and non-sequential implementation, and the learning requirements of a theory-based course, with delayed feedback of student solutions, a static working environment and sequential problem solving. Since they are not (as yet) supported by empirical evidence, these discussions do not lead to definitive claims about the analysis and student performance; on the other hand, they do generate theories for research that could enhance the undergraduate experience in theory based courses
Keywords :
computer science education; educational courses; mathematics; Analysis of Algorithms; computer science theory; mathematics; paper-based problem solving; sequential problem solving; theory based courses; Algorithm design and analysis; Computer science; Difference equations; Dynamic programming; Education; Feedback; Mathematical programming; Performance analysis; Problem-solving; Programming profession; Algorithms; Computer Science; Learning Styles; Programming; Theory;
