Data Analisys - Qualitative and mixed methods

Objectives

At the end of the curricular unit students will be able to:

1) Recognize key techniques for qualitative data collection;

2) Describe the main types of content analysis;

3) Identify the procedures / steps in performing content analysis with computer programs and their advantages and limitations;

4) Identify and adopt content analysis software adapted to different types of qualitative research;

5) Plan, execute and report the results of a thematic content analysis in the MAXQDA program;

6) Perform qualitative analyzes articulated with qualitative analyzes based on the analysis of clusters and multiple correspondences.

General characterization

Code

02103032

Credits

10.0

Responsible teacher

Sílvia Maria Cândido de Almeida

Hours

Weekly - 3

Total - 280

Teaching language

Portuguese

Prerequisites

Available soon

Bibliography

Bardin, L. (2016). Análise de Conteúdo. São Paulo: Edições 70.

Bertaux, D. (2010). Le récit de vie: perspective ethnosociologique (3e edition). Paris: Armand Colin.

Creswell, J. W., & Clark, V. L. (2011). Designing and conducting mixed methods research. (2nd ed). Thousand Oaks, CA: Sage.

Denzin, N.K., & Lincoln, Y.S. (2000). Handbook of Qualitative Research. London: Sage.

Foddy, W. (1996). Como perguntar. Teoria e prática da construção de perguntas em entrevistas e questionários. Oeiras: Celta Editora.

Ghiglione, R. & Matalon, B. (1992). O inquérito. Teoria e prática. Lisboa: Celta Editora.

Kuckartz, U. (2014). Qualitative text analysis: a guide to methods, practice and using software. Los Angeles: Sage.

Lewins, A. & Silver, C. (2007). Using Software in Qualitative Research. A Step-by-Step Guide. Los Angeles: Sage.

Maroco, J. (2010). Análise Estatística com o PASW Statistics. Pero Pinheiro: ReportNumber.

Matthew, B. M., Huberman, A. M. & Saldaña, J. (2014). Qualitative data analysis: a methods sourcebook (3r edition). London: Sage.

Teaching method

The combination of several teaching methods, namely the expository, demonstrative, interrogative and active, is favored.

Evaluation method

Of the assessment instruments presented below, students choose only 1 (100%) or choose another of those proposed in the contents of this curricular unit:

1. Construction of a semi-structured interview guide and online administration;

2. Construction of a semi-structured interview guide;

3. Construction of a category system in the MAXQDA program and respective content analysis;

4. Essay on preparation and implementation of focus groups;

5. Application of cluster analysis.

6. Essay on types of interviews and how to ask questions.

Assessment should be planned to create feedback opportunities that engage students in reflecting on their learning and support their progress. Assessment has implications for teaching, and it is important to ensure alignment between teaching, learning and assessment. Feedback is an assessment for learning (reinforces students' self-regulation capacity and the formative and interactive process of knowledge construction) and to adapt teaching practices (allows teachers to improve teaching practices

Subject matter

1. Qualitative analysis and Qualitative data collection techniques

1.1. Qualitative Analysis: diversity of Perspectives and Methodologies

1.2 Data collection techniques: observation, interview and questionnaire

1.2.1 Methodology of the interview: types of interviews. Initiation to the construction of interview scripts

1.2.2 Focus group interview and its specificities

1.2.3 Biographical method: elaboration and analysis

1.2.4 Forms of administration. Construction of online questionnaires.

2. Content Analysis Techniques and CAQDAS

2.1. Different types: content analysis and discourse analysis

2.2 Content Analysis and CAQDAS: types of Programs

2.3 Introduction to MAXQDA

2.3.1 Construction of the database in MAXQDA

2.3.2 Validation, outputs, analysis and reporting of results

3. Mixed Methods

3.1 What are mixed search designs?

3 .2 Cluster analysis as a sample construction method

3.3 Analysis of multiple correspondences for characterization of profiles under analysis

Programs

Programs where the course is taught:

Master in Education Studies