Online student achievement prediction model based on Data Envelopment Analysis (DEA) for multidimensional educational internet of data mining

2018 ◽  
pp. 1-5 ◽  
Author(s):  
Wang Tiancheng
Keyword(s):  
Data Mining ◽  
Student Achievement ◽  
Data Envelopment Analysis ◽  
Prediction Model ◽  
Data Envelopment ◽  
Online Student ◽  
Achievement Prediction ◽  
Model Based

A Model Based on Data Envelopment Analysis for the Measurement of Productivity in the Software Factory

2020 ◽  
Vol 13 (2) ◽  
pp. 1-26 ◽  
Author(s):  
Pedro Castañeda ◽  
David Mauricio
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Numerical Tests ◽  
Model Based ◽  
Software Production ◽  
Software Factory ◽  
Proposed Model ◽  
Efficiency And Effectiveness ◽  
Work Units ◽  
Two Phases

Productivity in software factories is very important because it allows organizations to achieve greater efficiency and effectiveness in their activities. One of the pillars of competitiveness is productivity, and it is related to the effort required to accomplish the assigned tasks. However, there is no standard way to measure it, making it difficult to establish policies and strategies to improve the factory. In this work, a model based on data envelopment analysis is presented to evaluate the relative efficiency of the software factories and their projects, to measure the productivity in the software production component of the software factory through the activities that are carried out in their different work units. The proposed model consists of two phases in which the productivity of the software factory is evaluated and the productivity of the projects it conducts is assessed. Numerical tests on 6 software factories with 160 projects implemented show that the proposed model allows one to assess the software factories and the most efficient projects.

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