UV9111 – Qualitative analysis by using NVivo
Schedule, syllabus and examination date
Course content
The course will provide an introduction to NVivo as a tool in qualitative analysis and project management.
Learning outcome
The course will provide a short overview of the development of, and the experiences within, computer supported qualitative analysis. Further, an overview of the main strategies for coding and analysis, and a presentation of the key terms and functions in NVivo. The main focus in the course is aimed at the possibilities in the programme within analysis of different types of data (text, audio files, video etc.), with emphasis on demonstrations and self-training. In addition to the analysis functions, NVivo also contains numerous possibilities for project organization. During the PhD course you will also learn more about the main tools for project management in NVivo.
Admission
PhD candidates at the Faculty of Educational Sciences will be given priority, but it is also possible for others to apply for the course. As a minimum requirement, all participants must hold at least a Master's degree.
Candidates admitted to the PhD programme at the Faculty of Educational Sciences should apply through Studentweb
Other applicants apply through this application form
Registration deadline: 7 September 2020.
Teaching
Lectures, demonstrations and self-training. During the first part of the course, we will be working together on a training project (a tutorial) that contains different types of data. In the latter part of the course, we will be focusing on procedures around creating a new project. Participants may use their own material during parts of the excersises.
The course consists of 12 hours of teaching (distributed over three days).
Date: October 7-9, 2020.
Place: Room 241, Helga Eng's building.
You will find the timetable on the semester webpage for this course.
Examination
1 credit point for course participation. 80% attendance is required.
3 credit points for course participation and submitted paper. 80% attendance is required.
Deadline for paper submission is: 24 November 2020.
You will find the guidelines for the paper here (coming).
Papers are to be submitted electronically to Kathrine H?egh-Omdal (kathrine.hoegh-omdal@isp.uio.no).
Examiner guide
For information about the assessment criteria, please read the examiner guide (coming).
Grading scale
Grades are awarded on a pass/fail scale. Read more about the grading system.
Evaluation
Evaluation form.