Working for Sustainability Transformation in an Academic Environment: The Case of itdUPM

2017 ◽  
pp. 217-234
Author(s):  
Carlos Mataix ◽  
Sara Romero ◽  
Javier Mazorra ◽  
Jaime Moreno ◽  
Xosé Ramil ◽  
...  
Keyword(s):  
Academic Environment ◽  
Sustainability Transformation

KEY CHALLENGES IN ESTABLISHING AN ENTREPRENEURIAL CULTURE IN AN ACADEMIC ENVIRONMENT: A CASE STUDY

2012 ◽  
Vol 14 (3) ◽  
pp. 387-401
Author(s):  
Christos Christodoulatos ◽  
Thomas Lechler ◽  
Sandra Furnbach ◽  
Vikki Hazelwood
Keyword(s):  
Academic Environment ◽  
Entrepreneurial Culture

COMSOL in the Academic Environment at USNA

2009 ◽  
Author(s):  
Kevin L. McIlhany ◽  
Reza Malek-Madani
Keyword(s):  
Academic Environment

scholarly journals Longevity of risks in software development projects: a comparative analysis with an academic environment

2021 ◽  
Vol 181 ◽  
pp. 827-834
Author(s):  
Luís M. Alves ◽  
Gustavo Souza ◽  
Pedro Ribeiro ◽  
Ricardo J. Machado
Keyword(s):  
Comparative Analysis ◽  
Software Development ◽  
Development Projects ◽  
Academic Environment

APPLYING EXPERT JUDGMENT TO IMPROVE AN INDIVIDUAL'S ABILITY TO PREDICT SOFTWARE DEVELOPMENT EFFORT

2012 ◽  
Vol 22 (04) ◽  
pp. 467-483 ◽  
Author(s):  
CUAUHTÉMOC LÓPEZ-MARTÍN ◽  
ALAIN ABRAN
Keyword(s):  
Software Development ◽  
Software Process ◽  
Development Effort ◽  
Academic Environment ◽  
Academic Institutions ◽  
Graduate Courses ◽  
Software Projects ◽  
Personal Software Process ◽  
Software Development Effort ◽  
Effort Prediction

Expert-based effort prediction in software projects can be taught, beginning with the practices learned in an academic environment in courses designed to encourage them. However, the length of such courses is a major concern for both industry and academia. Industry has to work without its employees while they are taking such a course, and academic institutions find it hard to fit the course into an already tight schedule. In this research, the set of Personal Software Process (PSP) practices is reordered and the practices are distributed among fewer assignments, in an attempt to address these concerns. This study involved 148 practitioners taking graduate courses who developed 1,036 software course assignments. The hypothesis on which it is based is the following: When the activities in the original PSP set are reordered into fewer assignments, the result is expert-based effort prediction that is statistically significantly better.

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