Learning Management System for Data Structures and Algorithm

Abstract

The study addressed the adjustments of academic institutions to online class and modular learning caused by the Covid-19 pandemic. It focused on the development of Learning Management System (LMS) for Data Structures and Algorithms with the main feature that allows students to take modular online learning. The research and development approach includes (i) stages of system development using the Waterfall Method, (ii) level of acceptability of the developed system based on the ISO 25010 standard, (iii) difference in the evaluation of the three groups of respondents, (iv) challenges encountered while using the system, and (v) implementation plan. The respondents chosen through convenience sampling were 60 students, 15 faculty members, and 15 Information Technology (IT) experts. The checklist-format questionnaire was based on the ISO 25010 which determined acceptability using functional suitability, performance efficiency, usability, and reliability criteria. An interview was also conducted to evaluate respondents' experiences using the system. Based on the respondents' evaluation, the developed system was 'acceptable' as reflected by the obtained weighted means. Further results showed no significant difference in the evaluation of the three groups of respondents in terms of functional suitability, performance efficiency, usability, and reliability.