Research Methods 1

Recommended Prerequisites

English (B1 level).

Teaching Methods

The contents are taught mainly as lectures, including the discussion of relevant case-studies. The assessment consists in a report that covers the design and analysis of experiments (50%) and a written midterm exam (50%). There is no exam.

Learning Outcomes

Development of the ability to conduct scientific research based on quantitative methods. Competency acquisition in analysis and synthesis, organisation and planning, decision making, research, critical reasoning, self-criticism and self-assessment.

Work Placement(s)

No

Syllabus

Introduction

• Science, technology and research
• Critical thinking and scientific thinking
• Integrity and conduct

Quantitative research methods in computing

• Modelling
• Formal methods
• Experimental methods
• Computer simulation.

Head Lecturer(s)

Carlos Manuel Mira da Fonseca

Assessment Methods

Assessment
Frequency: 50.0%
Project: 50.0%

Bibliography

• G. Dodig-Crnkovic, Theory of Science, 2003.
• ESF and ALLEA, The European Code of Conduct for Research Integrity, Strasbourg: Ireg, 2011
• A. V. Aho and J. D. Ullman, Foundations of Computer Science, W. H. Freeman, 1992.
• M. Kirby and G. Dangelmayr, Mathematical Modeling: A Comprehensive Introduction, in preparation (draft).
• R. Sheldon, Probability and Statistics for Engineers and Scientists, Academic Press, 2009.
• P. Cohen, Empirical Methods for Artificial Intelligence, MIT Press, 1995.
• T. Bartz-Beielstein, M. Chiarandini, L. Paquete, and M. Preuss, Experimental Methods for the Analysis of Optimization Algorithms, Springer, 2010.
• K. Dooley (2002), “Simulation research methods,” in Companion to Organizations, Joel Baum (ed.), London: Blackwell, p. 829-848, 2002.
• J. P. Davis, K. M. Eisenhardt and C. B. Bingham, “Developing theory through simulation methods,” Academy of Management Review, 32(2):480-499, 2007