AI and Data Science

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° DA2122-M9 EN

Description

NVivo is a widely used computer assisted qualitative data analysis software package which provides a potentially useful tool for the management and analysis of qualitative research data. This course is intended as a basic introduction to using NVivo for qualitative data analysis. Whether you are completely new to NVivo or have some previous experience with it, you will find this course both useful and enjoyable. This course blends lectures with hands-on exercises which allows you to try out the tools you've seen in the class under guidance.

This course is part of a larger course series in Data Analysis consisting of 19 individual modules. Find more information and enroll for this module via www.ipvw-ices.ugent.be

Program

What you will learn:

At the end of this course you will master the core functionalities to apply the latest version of NVivo (1.0) to your project, including:

  • Import - Creating a research project and importing different data formats such as Word documents, PDFs, webpages, audio, video and images into NVivo; classifying data files and managing their classifications
  • Organize - Organizing codes, code text and create codes; apply coding stripes and highlights; use cases with classification and attributes; make annotations and memos, create sets and links to files
  • Explore - Exploring lexical queries, word frequency and text search; apply code and matrix queries; illustrate with visualizations such as mind maps, concept maps, and coding matrix charts; coordinate team work by applying coding comparison

Not included in this course:

  • Theoretical framework of qualitative data analysis - Although this course will introduce some basic concepts of qualitative data analysis it is not a systematic review of the different theories.
  • Advanced qualitative methodologies - This course covers only the most salient features of NVivo and does not teach how to analyse qualitative data according to specific qualitative methods or designs, such as thematic analysis, grounded theory, content analysis, discourse analysis etc.

Course number:
DA2122-M9
Type:
Short- en long-term programmes
Area of interest:
AI and Data Science, Sciences
Language:
EN
Academic year:
2021 - 2022
Lecturers:
Limin Liu
Contact person:
ipvw.ices@ugent.be
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