NOVA Information Management School

Research Seminar I

Code

300003

Academic unit

NOVA Information Management School

Credits

7.5

Teacher in charge

Fernando José Ferreira Lucas Bação

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Objectives

Not Available

Prerequisites

Be a PhD student

Subject matter

The Research Seminar I begins with the presentation by the  ISEGI teachers, of the most important lines of research at the Institute. It is intended that students may have a comprehensive understanding of the research being developed at the Institute so that they can make an informed choice about the subject they choose to study and also about their thesis supervisor. Thus, each teacher will make a presentation of approximately 30 minutes, about the work that has developed, as well as the areas he's interested in pursuing.

A very significant proportion of the scientific work in information managemen today, is based on very sophisticated quantitative methodologies. The second part of the seminar is designed to provide doctoral students with an introduction to these methodologies, including the processes of problem formulation, the definition and data collection, the definition of experimental designs and the use of techniques for building quantitative models All these methodologies are instrumental in the development of research projects in information management and information systems.

This is a seminar about the research process and not on statistical theory. The aim is to understand the relationship between theory, data and statistical methods. Thus, the course focuses on the idea: "how to use statistical techniques to answer research questions?" It is essential that the student develops the ability to translate ideas into theoretical propositions that can be tested. This ability will be gained through the analysis of scientific papers published in refereed journals, data manipulation and estimation of models and also the analysis of the doctoral work of colleagues in more advanced stages. At the end of the seminar students should be more comfortable with the use of statistical techniques to formulate and answer research questions and be able to critically evaluate solutions proposed by other researchers
.
At the conclusion of the course the student should:

Bibliography

Martha Davies (1997), Scientific Papers and Presentations, Academic Press. Capítulos 1 a 5; Webster, J., and Watson, R. T. (2002) ¿Analyzing the Past to Prepare for the Future: Writing a Literature Review,¿ MIS Quarterly (26:2), pp. xiii-xxiii.; Langley, P. (1990). Advice to authors of machine learning papers. Machine Learning, 5, 233-237.; 0; 0

Teaching method

The course works based on a series of seminars held by researchers of the Institute ofStatistics and Information Management and from partner institutions that foster in students comprehensive overview of research in

Evaluation method

The evaluation of the course will be based on two elements of assessment: presentation of the thesis proposal (25% of final grade); thesis proposal (75% of final grade)

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