THE VIRTUAL LABORATORY IN THE ANALYSIS OF ALGORITHMS AS DIDACTIC STRATEGY
Journal: PEOPLE: International Journal of Social Sciences (Vol.5, No. 3)Publication Date: 2019-11-15
Authors : Beatriz Dolores Guardian Soto; Abel Camacho Galván;
Page : 38-50
Keywords : Electronic Manual; Concept Maps; Virtual Laboratory; Gowin UVE. MMCC; Techniques of Design; Analysis of Computational Algorithm; Computer Science;
Abstract
The objective of the present work was to apply a methodology in the teaching of the Techniques of Design and Analysis of Computational Algorithms, for the construction of optimal algorithms in the solution of problems. The methodology followed in the investigation began with the construction and selection of measurement tools. The subject of the Techniques of Design and Analysis of Computational Algorithms in Computer Science is very important, since they are a tool for the optimal and effective solution in the solution of problems through the design of computer algorithms, being necessary to investigate what ideas students have or preconceived ideas through diagnostic tests. This document first describes the methodology followed and the results obtained when applied through the virtual material implemented with Gowin's UVE and the conceptual maps (MMCC) to achieve significant learning in the topic of algorithm analysis. The data recorded at the beginning, during and at the end of the course were analyzed qualitatively and quantitatively in a comparative manner. This research was carried out in the School of Mechanical and Electrical Engineering of the Culhuacán Unit of the National Polytechnic Institute of Mexico in the course of the analysis of algorithms of the fifth semester of.
Other Latest Articles
- A Provably Secure Public Key Encryption Scheme Based on Isogeny Star
- A Deadlock-Free Dynamic Reconfiguration Protocol for Distributed Routing on Interconnection Networks
- Developing an Appliance Real Time Control in Heterogeneous Operating Systems
- A Comparative Assessment of the Performance of Ensemble Learning in Customer Churn Prediction
- A Real Time Adaptive Resource Allocation Scheme for OFDM Systems Using GRBF-Neural Networks and Fuzzy Rule Base System
Last modified: 2019-11-18 18:06:35