| Code |
15022
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| Year |
1
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| Semester |
S1
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| ECTS Credits |
18
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| Workload |
TP(32H)
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| Scientific area |
Metodologia de Investigação
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Entry requirements |
Not applicable.
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Learning outcomes |
The subject aims the advanced training in Research Methodology. It aims to deepen the methodological foundations of research in Psychology (Clinical and Health) and develop knowledge and applied skills on the process, designs and research strategies and the main methods and techniques for quantitative and qualitative data analysis using specialized software. As a result of this curricular unit, students are expected to Update and deepen knowledge within the methodology and technologies of research and data analysis; Deepen knowledge about development, adaptation and validation of instruments; Develop skills in planning and implementing qualitative research; Recognize and know how to select different strategies and research designs; Develop analytical, and critical capacity on its use and its potential and implications; Know how to select and perform different data analysis quantitative and qualitative, using analysis software; Know how to analyze, interpret, communicate the results.
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Syllabus |
I - Quantitative Methodologies.
1. Quantitative research methodologies: processes, strategies and designs.
2. Development and validation (exploratory) of assessment instruments in quantitative research.
3. Fundamentals of multivariate data analysis.
4. Multivariate models of moderation, mediation and moderated mediation.
5. Structural Equation Modeling - Fundamentals and applications:
5.1. Measurement model - Confirmatory validation of assessment instruments;
5.2. Structural model - Processes: Specification; Estimation, Evaluation and Re-Especification.
II - Qualitative Methodologies:
1. Fundamentals and challenges/contributions of qualitative research;
2. Approaches to qualitative data analysis;
3. Mixed designs;
4. Resources and Software.
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Main Bibliography |
Cohen, J., Cohen, P., West, S., & Aiken, L. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. LE.
Creswell, J. (2014). Research design: qualitative, quantitative, and mixed methods approaches. Sage.
De Vellis, R. (2016). Scale development: Theory and applications. Sage.
Hair, J., Black, W., Babin, B., & Anderson, R. (2018). Multivariate data analysis. Cengage.
Hayes, A. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford.
Kline, P. (2000). Handbook of psychological testing. Routledge.
Lyons, E., & Coyle, A. (Eds). (2007). Analysing qualitative data in psychology. Sage.
Pituch, K. A., & Stevens, J. P. (2015). Applied multivariate statistics for the social sciences: Analyses with SAS and IBM´s SPSS. Routledge.
Smith, J. (Ed). (2008). Qualitative psychology: a practical guide to research methods. Sage.
Tabachnick, B., & Fidell, L. (2007). Using multivariate statistics. A&B.
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Teaching Methodologies and Assessment Criteria |
Teaching is organized in T-P sessions. Expositive and demonstrative methodologies are adopted, but, above all, active and student-centred methodologies, which stimulate autonomous work skills (individual tasks) and cooperative work (tasks performed in small working groups), with the resolution of exercises and simulation and training practices, focusing on the application of knowledge and research skills and data analysis (quantitative and qualitative). The assessment will be carried out through the completion of a digital portfolio.
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Language |
Portuguese. Tutorial support is available in English.
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