filmeu

Class Research Methodologies and Conception

  • Presentation

    Presentation

    This course focuses on developing scientific skills that enable students to create and critically evaluate academic work, in line with SDG 4 - Quality Education, by promoting rigorous training. The course aims to provide students with the essential knowledge to design and implement research strategies, using coherent and rigorous data collection and analysis methods, respecting ethical principles and good practices, in line with SDG 9 - Industry, Innovation and Infrastructure. These competences are essential and should be applied across the different curricular units of the Master's programme.
  • Code

    Code

    ULP6573-24059
  • Syllabus

    Syllabus

    Introduction 1.1– Ideas that fuel the research process 1.2– Drawing inferences from the results: internal, external, construct and instrument validity The replicability of quantitative designs 2.1– Descriptive design: to characterize the phenomenon 2.1.1 – Cross-sectional survey study 2.2 – Correlational design: observing to forecast 2.2.1 – Case-control study 2.2.2 – Longitudinal cohort study 2.3 – Semi-experimental design: to circumscribe the cause 2.3.1 – Quasi-experimental Design 2.3.2 – Twin studies 2.4 – Experimental design: to determine the cause 2.4.1 – Randomization, manipulation and control 2.4.2 – Simple designs: pre/post-test design with control group 2.4.3 – Complex designs: factorial, counterbalanced, with repeated measures The emergent feature of qualitative designs 3.1 –Focused on the individual: narrative and phenomenological studies 3.2 –Focused on the processes: case studies and grounded theory studies 3.3 –Focused on the group of individuals: ethnographical studies
  • Objectives

    Objectives

    This course focuses on the conceptualisation of research in management areas, promoting training in line with the Sustainable Development Goals (SDGs). The approach includes: (1) the critical analysis of research designs, integrating SDG 4 - Quality Education, by promoting rigorous training; (2) the presentation of practical examples that encourage sustainability and innovation, in line with SDG 9 - Industry, Innovation and Infrastructure; (3) the involvement of students in original research, following sustainable and ethical practices, in line with SDG 12 - Sustainable Production and Consumption. At the end of the course, the master's student should be able to: discuss factors that limit the validity of inferences and apply quantitative and qualitative research designs to scientific problems, focussing on sustainability management and innovation.
  • Teaching methodologies and assessment

    Teaching methodologies and assessment

    An active and participatory methodology will be adopted, using innovative techniques. Theoretical-practical classes will include the discussion of research articles, project-based learning, where students will carry out real research in groups, and flipped learning, which encourages students to prepare in advance for debates and the practical application of concepts. Simulation workshops will allow you to explore research scenarios, while online collaborative learning will facilitate content sharing. Assessment includes: Preparation of a scientific article in groups (30%), using project-based learning to apply concepts in a practical way; Scientific article reading sheets (20%), using discussion of articles to critically analyse research methods; and Research project (50%), with simulation workshops and online collaborative learning to prepare students for autonomous project development.
  • References

    References

    Kurtaliqi, F., Miltgen, C. L., Viglia, G., & Pantin-Sohier, G. (2024). Using advanced mixed methods approaches: Combining PLS-SEM and qualitative studies. Journal of Business Research, 172, 114464. Proudfoot, K. (2023). Inductive/deductive hybrid thematic analysis in mixed methods research. Journal of mixed methods research, 17(3), 308-326. Saunders, M., Thornhill, A. e Lewis, P. (2016). Research Methods for Business Students. 7th Ed. Prentice-Hall. Vilelas, J.  (2020). Investigação: O Processo de Construção do Conhecimento. Lisboa: Edições Sílabo Wieckowski, J., & Salabun, W. (2023). Sensitivity analysis approaches in multi-criteria decision analysis: A systematic review. Applied Soft Computing, 148, 110915. Bernard, H. R. e Ryan, G. W. (2009). Analyzing qualitative data: Systematic approaches. Sage. Bryman, A. (2008). Social Research Methods. 3rd ed. Oxford University: Press Inc.
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