Work Plan (Dissertation / Work Project /Internship)
| Keywords |
| Classification |
Keyword |
| OFICIAL |
Management Studies |
Instance: 2021/2022 - 1S 
Cycles of Study/Courses
| Acronym |
No. of Students |
Study Plan |
Curricular Years |
Credits UCN |
Credits ECTS |
Contact hours |
Total Time |
| MIM |
35 |
Bologna Official Syllabus |
2 |
- |
7,5 |
56 |
202,5 |
Teaching language
English
Objectives
To allow students to apply the knowledge acquired in the first year of the Master in Management programme, in preparing their dissertation plan.
Learning outcomes and competences
At the final essay, the student is expected to:
- clearly identify the research question(s) and discuss the gap(s) he/she wants to address in the master dissertation;
- fully perform a literature review and systematize the relevant literature on the chosen topic;
- identify the most suitable methodology to address the research problem and questions.
Working method
B-learning
Pre-requirements (prior knowledge) and co-requirements (common knowledge)
n.a.
Program
Introduction
Part I. RESEARCH PROCESS
1 – Stages of the research process (1/2 class)
- Research question;
- Exploratory readings;
- Theoretical framework: theories and concepts;
- Model analysis and research hypotheses construction;
- Methodology;
- Collecting and treating the data;
- Conclusions.
Bibliography:
- Hart, C. (2008), Doing your Masters Dissertation: Realizing your Potential as a Social Scientist, London: SAGE.
2 – Scientific writing (1/2 class)
- Rules for presentation of dissertations and reports;
- How to structure a scientific work;
- Academic integrity.
Bibliography:
- Hart, C. (2008), Doing your Masters Dissertation: Realizing your Potential as a Social Scientist, London: SAGE.
- Saunders, M., P. Lewis and A. Thornhill (2002), Research Methods for Business Students, 3rd ed., Edinburgh: Prentice-Hall.
3 – Bibliometrics (1 class)
- Key concepts (bibliometrics, scienciometrics, meta-analysis);
- Bibliometrics as a tool for literature review;
- Data, sources, variables & methods;
- Practical application of bibliometrics using Scopus Sci Verse and Web of Science bibliographic databases.
Bibliography:
- Castro e Silva, M. and A. A. C. Teixeira (2012), "Methods of assessing the evolution of science: a review ", European Journal of Scientific Research, Vol. 68(4): 616-635.
- Cronin, B. and C. R. Sugimoto (eds.) (2014), Beyond Bibliometrics: Harnessing Multidimensional Indicators of Scholarly Impact, London: MIT Press.
- Gingras, Y. (2016), Bibliometrics and Research Evaluation: Uses and Abuses, Cambridge: MIT Press.
- Osareh, F. (1996), Bibliometrics, Citation Analysis and Co-Citation Analysis: a review of analysis, in Libri., vol.46: 149-158.
Part II. RESEARCH METHODS
4 – Sampling and surveys (1 class)
- Data collection: Introduction;
- Steps of research process;
- Data collection;
- Sampling (first concepts)
- Sample survey/questionnaires
- General overview of some Statistical Databases available in FEP.
Bibliography:
- Cohen L., L. Manion and K. Morrison (2005), Research Methods in Education, 5th ed., Taylor & Francis.
- Norland-Tilburg, E. V. (1990), “Controlling error in evaluation instruments”, Journal of Extension, 28(2) (http://www.joe.org/joe/1990summer/tt2.html).
-Trochim, W. M. K. (2006), The Research Methods Knowledge Base, 2nd (http://www.socialresearchmethods.net/kb/).
5A – Qualitative Methods (3 classes)
- Qualitative research;
- Theoretical Frameworks: narrative inquiry, phenomenology, ethnography, generic qualitative inquiry, action-research;
- Qualitative designs;
- Data collection: observation, interview, focus-group;
- Data analysis: Content analysis (using or not NVivo11);
- Advantages & disadvantages of qualitative research;
- Ethical considerations.
Bibliography:
- Patton, M. (2014), Qualitative Research and Evaluation Methods, 4th ed., London: Sage Publications.
5B – Quantitative Methods (2 classes)
- Parametric and non parametrical statistical tests:
- Introduction;
- Types of data;
- Descriptive statistics;
- Distributions, inference and hypothesis testing (assumptions and applications);
- Parametrical tests: T-Student test for 1 population; T-Student test for 2 independent populations; T-Student test for 2 paired samples; ANOVA.
- Non parametrical tests: Normality tests; Wilcoxon test for 1 population; Mann-Whitney test for 2 independent populations; Wilcoxon test for 2 paired populations; Kruskall-Wallis test for k independent populations.
- Correlations;
- Chi-Square independence test.
- Multivariate data analysis:
- Data matrix and variables;
- Types of methods;
- Multiple Regression;
- MANOVA;
- Discriminant analysis;
- Factorial analysis;
- Principal component analysis;
- Cluster analysis: Hierarchical method; K-means.
Bibliography:
- Conover, W. J. (1999), Practical Nonparametric Statistics, 3rd ed., New York: John Wiley & Sons.
- Everitt, B. S. & G. Dunn (2013), Applied Multivariate Data Analysis, 2nd ed., Wiley.
- Hair Jr., J. F., W. C. Black, B. J. Babin & R. E. Anderson (2010), Multivariate Data Analysis – A Global
Perspective, 7th ed., Pearson Prentice Hall.
- Keller, G. (2008), Statistics for Management and Economics, Thomson.
- Sharma, S. (1996), Applied Multivariate Techniques, Wiley.
5Bi.
5Bi. - Quantitative methods: Social network analysis, opinion mining, sentiment analysis (1 class)
- Social network analysis. Social networks: interactions between actors. Professional social networks, e.g. LinkedIn. Social network analysis:
- The role of actors in the network: centralities and influence;
- Communities and interactions;
- Information diffusion in social networks.
- Sentiment analysis:
- Opinions in the digital age: social media, blogs, tweets, etc.;
- Text mining: identifying entities, and polarity.
Bibliography:
- Liu, B. (2012), Sentiment Analysis and Opinion Mining, Human Language Technologies.
- Zafarani, R., M. Ali Abbasi and H. Liu (2014), Social Media Mining, Cambridge University Press.
5Bii. - Econometric Methods (1 class)
- Object and method of Econometrics;
- Brief revision of the linear regression model;
- Binary choice models (logit/probit);
- Time series models;
- Panel data models.
Bibliography:
- Asteriou, D. & S. G. Hall (2015), Applied Econometrics, 3rd ed., Palgrave.
- Griffiths, W. E., R. C. Hill & G. C. Lim (2012), Using EViews for Principles of Econometrics, 4th ed., John
Wiley & Sons.
- Gujarati, D. (2014), Econometrics by Example, 2nd ed., Palgrave.
- Gujarati, D. N. & D. C. Porter (2009), Basic Econometrics, 5th ed., McGraw-Hill.
- Heij, C., P. De Boer, P. H. Franses, T. Kloek & H. K. Van Dijk (2004), Econometric Methods with
Applications in Business and Economics, Oxford University Press.
- Hill, R.C., W. E. Griffiths & G. C. Lim (2012), Principles of Econometrics, 4th ed., John Wiley & Sons.
Part III. TUTORIALS and PRESENTATIONS
Mandatory literature
Saunders, Mark; Lewis, Philip and Thornhill, Adrian; Research Methods for Business Students, Prentice-Hall, Edinburgh, 2002
Bryman, Alan; Bell, Emma; Business Research Methods, Financial Times / Prentice Hall, London, 2006
To be Defined by the Lecturers of the Thematic subjects; Quantitative and Qualitative research methods
Teaching methods and learning activities
1. Pre-recorded sessions
The sessions concerning parts I and II of the syllabus are made available as pre-recorded video sessions. They will be made available on the Moodle platform.
2. Classroom sessions
These sessions include the introductory session; sessions of students presentations of their first and second drafts of the work plan.
Note: for students in international mobility, or having a plausible and acceptable reason, the classroom presentations may be replaced by videoconference presentations.
3. Tutorial sessionsThese sessions will tend to be held by the student' supervisor.
Evaluation Type
Distributed evaluation without final exam
Assessment Components
| Designation |
Weight (%) |
| Trabalho escrito |
100,00 |
| Total: |
100,00 |
Amount of time allocated to each course unit
| Designation |
Time (hours) |
| Elaboração de projeto |
60,00 |
| Estudo autónomo |
20,00 |
| Frequência das aulas |
33,00 |
| Trabalho de investigação |
89,50 |
| Total: |
202,50 |
Eligibility for exams
To pass the students must have a score equal or higher than 50% in the dissertation proposal (10 points out of 20).
Calculation formula of final grade
Assessment Type and Calculation of final grade
- 100% of the final grade: Final essay delivery (Dissertation proposal) – Report.
Penalties
- Submission of 1 page summary containing the research topic (first draft). If the student does not send an adequate summary until the date defined in the schedule, 1 point (out of 20) will be deducted from the final grade.
- Research Topic/Idea presentation. If the student does not make this presentation according to the recommended guidelines, 1 point (out of 20) will be deducted from the final grade (if the student did not submit the summary mentioned in the previous point, he/she does not make the presentation and does not suffer a penalty in the current point).
- Submission of the 2nd draft: a report containing information about the research topic (reformulated, if needed), literature review, research questions. If the student does not submit this second draft according to the recommended guidelines until the date defined in the schedule, 2 points (out of 20) will be subtracted from the final grade.
- Students’ oral presentation of the 2nd draft of the dissertation project. If the student does not make this presentation according to the recommended guidelines, 2 points (out of 20) will be deducted from the final grade (if the student did not submit the report mentioned in the previous point, he/she does not present it and does not suffer a penalty in the current point).
Examinations or Special Assignments
n.a.
Internship work/project
n.a.
Special assessment (TE, DA, ...)
n.a.
Classification improvement
Not available.
Observations
There is no extra season to get approval.
On Moodle platform, there will be a specific page to make available the videos of the pre-recorded sessions.