CODE SPRINT: AN INTERACTIVE LEARNING PLATFORM FOR COMPETITIVE PROGRAMMING

Abstract

Competitive programming has proven to be a great way to build algorithmic thinking, problem-solving skills and coding skills in students & software developers. However, many new students experience difficulties in finding problems to solve, motivating themselves to solve the problems or in recalling the solution for a complex algorithm. It introduces adaptive learning paths, real time code evaluation, gamification and analytics dashboards, all of which are based on AI, to make education in competitive programming more interactive through a paper it introduces a new concept for a learning platform (CodeSprint), a system that is making this approach to competitive programming education more interactive. The suggested platform integrates Online Judge (OJ) system and suggestion and collaborative learning system. It is suggested that codes are modifiable to make it scalable, safe and efficient to execute codes in the program. Experimental studies show that the platform increases the engagement level of learners, their ability to reason and solve problems, and the performance of their programming. This work adds to an emerging cadre of "intelligent programming education systems" by offering a broad framework for competitive programming education. Competitive Programming platforms and Online judges have been well established as learning and automatic assessment tools for programming education.

Keywords: Competitive Programming, Online Judge System, Gamification, Adaptive Learning, Programming Education, Artificial Intelligence, Learning Analytics.