Dissertation/Project/Internship Monitorisation

N/A

The work with the students will be organized in two phases: 1) expository method to frame the explanation of the syllabus; 2) practical work with the support of NVivo 12, VosViewer, SmartPLS, Amos, and XXX softwares. With this exercise, students will be motivated to apply the acquired knowledge and become familiar with the qualitative techniques of data analysis. Approval in the subject is obtained with a minimum grade of ten values.

This curricular unit aims to apply the knowledge acquired previously, in the handling of techniques of treatment and analysis of qualitative and quantitative data, appropriate to the research projects that students develop in the context of their master’s dissertations.

2. The seminar on qualitative data analysis aims to provide students with skills for: a) conceptual elaboration between categories and coding systems; b) application of models of relationships between variables; c) classification and processing of qualitative data and its quantification

3. The seminar on structural equation modelling aims to provide students with skills to; a) analysis of the psychometric properties of the measurement scales; b) analysis of the relations that compose the structural model.

4. The seminar on text mining aims to equip students with skills in processing unstructured text in a format that identifies patterns and knowledge.

I – Qualitative data analysis

1. The model of content analysis or categorical analysis

1.1.  Selection of documents and constitution of a corpus

1.2.  Construction of categories and development of coding systems

1.3.  Information classification and consistency control

2. Content analysis

2.1.  Open, axial or selective coding procedures

2.2.  Memos and diagrams.

3. Practical work that focuses on the analysis of qualitative data with computational support, using software: NVivo 12 and VosViewer.

II. Structural equation modeling

1. Analysis of the measurement model

1.1.  Reliability

1.2.  Convergent validity

1.3.  Discriminant validity

2. Analysis of the structural model

2.2.  Direct effects

2.3.  Indirect effects

2.4.  Overall effects

3. Practical applications using software: AMOS and SmartPLS

4. Text mining

4.1.  Text classification

4.2.  Topic modeling

4.3.  Sentiment analysis

4.4.  Document embeddings

5. Practical applications using software: Orange

• - Work - 70.0%
• - Oral presentation - 30.0%

• - Written test - 50.0%
• - Individual work - 50.0%

NAO

Mozzato, A., Grzybovski, D., & Teixeira, A. (2016). Análises qualitativas nos estudos organizacionais: As vantagens no uso do software NVivo®. Revista Alcance, Eletrónica, 23(4), 578-587.

Philimore, J., & Goodson, L. (2009). Qualitative research in tourism: Ontologies, epistemologies and methodologies. Routledge.

Saur-Amaral (2012). Curso completo de NVivo 10: Como tirar maior proveito do software para a sua investigação. Bubok Publishing S.L.

Byrne, B. M. (2016). Structural Equation Modeling With AMOS Basic Concepts Applications and Programming (3rd ed.). Routledge.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd ed.). Sage.

Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling (4th ed.). The Guilford Press.

Berry, M. W., & Kogan, J. (2010). Text Mining: Applications and Theory (1st ed.). Willey. Ignatow, G., & Mihalcea, R. (2013). Text Mining (1st ed.). SAGE.