21 Aprile – 5 maggio 2022 • Fondazione Marco Biagi
Ciclo di Seminari organizzati nell’ambito del Corso di Dottorato in Lavoro, Sviluppo e Innovazione
Visiting professor: Dr Tiziana C. Callari
Senior Research Fellow in Human Factors
Socio-Technical Centre (Leeds University Business School)>
Institute of Design, Robotics and Optimisation (School of Mechanical Engineering) University of Leeds, Leeds, United Kingdom
SEMINAR 1 – Performing a literature review analysis using NVivo
21 Aprile 2022, dalle 9 alle 13
Focus of this seminar is to present the process of performing a literature review using NVivo. After clarifying the research objective, and selected key papers for our study.
SEMINAR 2 – Designing a qualitative research design project/ intervention
26 Aprile 2022, dalle 9 alle 13
This seminar will aim to provide the PhD students with strategic understanding and applied skills in planning, conducting, and reporting the process of qualitative research interventions. The course combines theory and applied exercises to appreciate the influence that epistemology and research design has on choosing a qualitative method. Qualitative methods (such as: Interviews, Observations, Focus Groups, etc.) will be critically reviewed.
SEMINAR 3 – Qualitative Content Analysis
27 Aprile 2022, dalle 9 alle 13
Qualitative Content Analysis (QCA) is particularly suited to describe and conceptualise the meaning of qualitative data. The core characteristics of the method and its variants (such as deductive and inductive, thematic and formal, and type-building qualitative content analysis) will be presented. This will be followed by describing and illustrating the steps in qualitative content analysis.
SEMINAR 4 – Thematic Analysis
28 Aprile 2022, dalle 9 alle 13
Thematic Analysis (TA) is a method for identifying, analysing and reporting patterns (themes) within data. Thematic analysis is a well-known method in the social sciences that can be used for examining the perspectives of different research participants, highlighting similarities and differences, and for summarizing key features of a large data set. In this seminar, Boyatzis’ (1998) approach and his procedure will be presented.