Research Seminar I
Code
300003
Academic unit
NOVA Information Management School
Credits
7.5
Teacher in charge
Weekly hours
2.0
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:
1. Possess a comprehensive understanding of the lines of existing research in ISEGI-UNL;
2. Understand how to formulate a research problem;
3. Thorough understanding of the processes of development of scientific projects;
4. Understanding of the main methods and research tools in Statistics and Information Management;
5. Present a plan for the thesis to demonstrate their familiarity with the main references of the work area;
6. Have a plan of the research work to develop in subsequent years;
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.
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 a comprehensive overview of research in Information Systems and Decision Support Systems. Through the seminars students have contact with different research projects or research pathways which promotes the sharing of experiences with active researchers. The seminars are also a source of motivation and ideas for future research. Additionally, there will be a set of sessions with practical classes, which will address the main research tools in these areas.
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).
Regarding the thesis proposal presented by the student, it should be noted that in this phase should include a literature review of the work area, proposals for the tools to use in the PhD project, as well as precisely defined objectives.
The criteria for evaluating proposals are:
A. Quality of literature review (20%);
B. Innovation of the ideas proposed (20%);
C. Scientific relevance of the research proposal (20%);
D. Proposed methodology (20%);
E. Presentation (20%).