HRM RESEARCH SEMINAR
Année du cours : 1 année(s)
Etablissement : IÉSEG School of Management
Langue : English
Formation(s) dans laquelle/lesquelles le cours apparait :
Période : S2
An understanding of what research is and what it involves.
An understanding of how to search for relevant literature/academic articles/publications.
An understanding of how to collect qualitative data.
Students who are less familiar with the above are recommended to review the contents of the “ENT/HRM Research Methodology” course
The research seminar is a ‘hands-on’ practical course in qualitative and quantitative research methodology using software. Its overall learning objective is to allow students to master the appropriate analytical research techniques. It is designed according to the “inversed class” principle. Students will be informed about the specific working principles of the course shortly before the start of the course.
Part 1: Quantitative (SPSS software)
1. Effectively use SPSS for data entry and data management
2. Understand how to calculate and evaluate scales for research and report descriptive statistics
3. Perform analyses that examine associations amongst variables, including correlation, simple/multiple/hierarchical regression, moderation, and mediation
4. Perform analyses that compare groups, including t-tests and ANOVAs
5. Choose the appropriate statistical test for a given research question
6. Understand and clearly report the results of quantitative analyses
Part 2: Qualitative (Nvivo software)
1. Perform a literature review
2. Use Nvivo software for qualitative research, more specifically:
– Import documents into Nvivo to analyse them
– Code sections of text using Nvivo
– Create nodes and sub-nodes in Nvivo
– Use specific features of Nvivo to help analyse the text
3. Understand how to write a short case study
Part 1: Quantitative:
Session 1: Getting to know SPSS, descriptive statistics, and data management
Session 2: Creating scales, more data management, and correlations
Session 3: Simple, multiple, and hierarchical regression
Session 4: Hierarchical regression and moderation analysis
Session 5: Hierarchical regression and mediation analysis
Session 6: Comparing groups, including t-tests and ANOVA
Session 7: Remedial and coaching session (individual in-class assignment covering topics from the previous sessions; providing remedial support on problems encountered during the previous sessions and advice on the future thesis/consulting project/PCE)
Part 2: Qualitative:
Session 8: Introduction to Nvivo (e.g., importing document, coding, identifying themes, etc.) and performing literature review
Session 9: Auto coding; Word frequency search; Emergent coding
Session 10: Deductive coding
Session 11: Developing a case study based on secondary data
Session 12: Coaching Session
