scholarly journals Data Mining Applied to the Improvement of Project Management

10.5772/48734 ◽  
2012 ◽  
Author(s):  
Joaquin Villanueva ◽  
Vicente Rodriguez ◽  
Francisco Ortega ◽  
Carlos Alba
Keyword(s):  
Data Mining ◽  
Project Management

Data Mining to Identify Project Management Strategies in Learning Environments

2019 ◽  
pp. 532-545
Author(s):  
Ana González-Marcos ◽  
Joaquín Ordieres-Meré ◽  
Fernando Alba-Elías
Keyword(s):  
Data Mining ◽  
Project Management ◽  
Learning Environments ◽  
Team Building ◽  
Management Strategies ◽  
Educational Data Mining ◽  
Effective Learning ◽  
Virtual Teamwork ◽  
Teachers And Students ◽  
Management Policies

Projects have become a key strategic working form. It is agreed that project performance must achieve its objective and be aligned with criteria that the project stakeholders establish. The usual metrics that are considered are cost, schedule, and quality. Configuration for the management of projects is a matter of decision that influences the project's evolution. There also are factors like virtual teamwork and team building processes that are relevant to that evolution. Effectiveness in managing projects depends on these factors and is investigated in this work by means of educational data mining as they can help to build more effective learning and operating procedures. The conclusions from this study can help higher education course designers as well as teachers and students by making apparent the influence of smarter strategies in the learning process. In fact, the same benefits will help practitioners too, as they can improve their continuous learning procedures and adjust their project management policies and strategies.

How e-Learning Experience Enhances the Social Presence in Community of Practice

2012 ◽  
pp. 75-120 ◽  
Author(s):  
Constanta-Nicoleta Bodea ◽  
Radu Mogos ◽  
Maria-Iuliana Dascalu
Keyword(s):  
Data Mining ◽  
Project Management ◽  
Community Of Practice ◽  
Social Presence ◽  
Learning Experience ◽  
Main Research ◽  
The Social ◽  
Analytical Perspective ◽  
Management Area ◽  
E Learning

The chapter presents a study made in order to find out how the e-learning experience enhances the social presence in the community of practice. The study was carried out for the online master degree programme in project management, delivered by the Academy of Economic Studies, Bucharest. The main research method was a survey and the research instrument was a questionnaire. Statistics and data mining were applied. Statistics was applied to check hypothesis and quantify the correlation significance. Due to the large number of the variables and the indirect relationships, the analysis paths become very complex and it would be extremely difficult to manage the analysis workflow. So, the data mining approach was chosen. As a theoretical framework and analytical perspective for this research, Wenger’s theories of learning in Community of practice (CoP), and the social presence model of Garisson et al., are applied. The study revealed that the characteristics of the online social presence in learning environments enhanced the students’ interest for CoPs. Another finding of this study is that for project management area there is not a significant correlation between the learning domain and that of the CoPs chosen to get involved. The reason is that most of the project personnel hold a first degree in an area other than project management.

Data Mining of Project Management Data

2017 ◽  
Author(s):  
Gurdal Ertek ◽  
Murat Mustafa Tunc ◽  
Allan Nengsheng Zhang ◽  
Omer Tanrikulu ◽  
Sobhan Asian
Keyword(s):  
Data Mining ◽  
Project Management

Data Mining Techniques for Software Quality Prediction

2014 ◽  
pp. 401-428
Author(s):  
Bharavi Mishra ◽  
K. K. Shukla
Keyword(s):  
Data Mining ◽  
Project Management ◽  
Software Engineering ◽  
Software Development ◽  
Vital Role ◽  
Software Systems ◽  
Software Artifacts ◽  
Formidable Challenge ◽  
Management Processes ◽  
Support Software

In the present time, software plays a vital role in business, governance, and society in general, so a continuous improvement of software productivity and quality such as reliability, robustness, etc. is an important goal of software engineering. During software development, a large amount of data is produced, such as software attribute repositories and program execution trace, which may help in future development and project management activities. Effective software development needs quantification, measurement, and modelling of previous software artefacts. The development of large and complex software systems is a formidable challenge which requires some additional activities to support software development and project management processes. In this scenario, data mining can provide a helpful hand in the software development process. This chapter discusses the application of data mining in software engineering and includes static and dynamic defect detection, clone detection, maintenance, etc. It provides a way to understand the software artifacts and processes to assist in software engineering tasks.

Data Mining-Based Metrics for the Systematic Evaluation of Software Project Management Methodologies

2021 ◽  
pp. 35-51
Author(s):  
Patricia R. Cristaldo ◽  
Daniela López De Luise ◽  
Lucas La Pietra ◽  
Anabella De Battista ◽  
D. Jude Hemanth
Keyword(s):  
Data Mining ◽  
Project Management ◽  
Systematic Evaluation ◽  
Software Project ◽  
Software Project Management
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