The difficulties faced by lecturers and students in order to teach and learn programming on computer science courses have been a research topic over the years. The hardship to understand the abstract and logic concepts and consequent demotivation has been resulting in high rates of novices' failure and class abandonment. This study adopted statistical concepts to analyze students' final grades in programming subjects and compare their performance. Data were gathered from a computer science course at a Brazilian University. The period analyzed was from 2010 to 2015 including six programming subjects from the first and second academic year. The results pointed a significant number of student failure (43%) and abandonment (25%). It was also discovered that even with different teachers, semesters and programming subjects, the students' performance mean were nearly equal. The discoveries of this work contributed to point the hardship faced by students and teachers to learn and teach programming.
Among the most interesting problems in competitive programming involve maximum
flows. However, efficient algorithms for solving these problems are often difficult for students to understand at an intuitive level. One reason for this difficulty may be a lack of suitable metaphors relating these algorithms to concepts that the students already understand. This paper introduces a novel maximum flow algorithm, Tidal Flow, that is designed to be intuitive to undergraduate andpre-university computer science students.
Performance Analysis of Computer Science Students in Programming Learning
