Qualitative Data Analyses Assisted by MAXQDA

Qualitative Data Analyses Assisted by MAXQDA

03/06/2024 to 07/06/2024
18:30 - 21:30

The main objective of this course is to provide training in computer-assisted qualitative data analysis that guarantees knowledge of the main tools and resources currently available, as well as the main trends in this area. A strong and diverse conceptual and epistemological component will be combined with practical and operational training, which will allow participants to understand the existing options and thus correctly direct their work. Particular emphasis will be given to content analysis as a methodological approach capable of communicating with a microinformatics tool to support the research and data analysis process.
In this course, there will be space to carry out operations with the most common types or sources of data, including interviews, focus groups, images, tabulated data, legal diplomas, press collections, bibliographic references, audio or video files, or even data coming from new sources of digital data, such as internet pages or social networks. Assisted practice activities will be combined with a wide range of support materials, including the provision of detailed tutorials for future reference.

Target Audience

The course is aimed at higher education students, teachers, researchers, senior company managers, specialists from different fields (e.g. marketing, market research, human resources, opinion polls, among others), who wish to obtain knowledge in terms of scientific research methodology in the analysis of qualitative data and that use or intend to use applications to carry out qualitative data analysis of different types.


General Public € 195
ICS Community

€ 120

These prices include the application, enrolment, and attendance fee as well as the fee for a certificate in Portuguese.

This School is organised in 5 sessions, with a minimum of 15 hours of face-to-face contact. Participants must bring a laptop with internet access.

Obtaining 3 ECTS is subject to the presentation of a final project in MAXQDA within 7 days after the end of the course.

Day 1 - Epistemological and conceptual aspects of research using qualitative data, support resources

  • Epistemology of qualitative data analysis;
  • Objectives and areas of application;
  • Stages of qualitative data analysis;
  • Content analysis procedures
  • Construction of analysis grids;
  • Implications and particularities of using applications in qualitative data analysis;
  • Qualitative data repositories;
  • Tools for managing and manipulating qualitative data.

Day 2 - Introduction to MAXQDA and project file management

  • Data collection and preparation (i.e. collection of text, image, audio and/or video);
  • Interface, internal organization and information management in MAXQDA;
  • Creation and management of project files;
  • Creation of new documents and insertion of data;
  • Audio and/or video transcription in MAXQDA;
  • Preparation and import of documents;
  • Import of pre-processed documents (e.g. discussion groups or questionnaires);
  • Import of bibliographic data;
  • Capture and import of Internet pages;
  • Collection of data from Social Networks: Twitter and YouTube;
  • Operations with tabulated data.

Day 3 - Data preparation, analysis and categorization

  • Categorization and coding through an analysis grid;
  • Use of colors in data categorization;
  • Definition of code favorites and shortcuts;
  • Coding by paraphrasing information;
  • Transformation of the Code System;
  • Annotation and annotation management tools;
  • Search for coded information;
  • Linking documents;
  • Teamwork with MAXQDA;
  • Data referencing in MAXQDA;
  • Definition of variables, import and export.

Day 4 - Research, consult and define analysis criteria

  • Search and retrieval of information;
  • Simple lexical searches and extended/complex searches;
  • Activation by variable and activation by colors;
  • Transformation of codes into variables;
  • Autocoding of data and results;
  • Data export and import;
  • Group comparison;
  • Summaries and analysis grids;
  • QTT: Questions, Themes, Theories;
  • Visual implementation and testing tools;
  • Concept maps;
  • Graphs, statistics, quantitative information processing.

Day 5 - Report findings and conclusions

  • Extraction of tabulated information;
  • Extraction of project metadata;
  • Codebook extraction;
  • Export of results;
  • Predefined result tables;
  • Sharing and printing content;
  • Exporting information to other data analysis applications;
  • Abstracts;
  • Reports.

For personal project sessions (tutoring):

  • Organization of participants into groups according to interests or research methodologies in use;
  • The service will be provided by registration and managed through the Moodle platform;
  • Each student must submit a work proposal (i.e., research project);
  • Individualized support will be provided for the implementation of research projects;
  • Projects must be carried out using empirical material from each participant;
  • Advice and testing of specific functionalities adjusted to the work in question;
  • The confidentiality of all work proposals is guaranteed.

Assessment Methodology

In this course, the Moodle platform will be used to manage training content and centralize communication. The course will feature contact hours for group work, assisted by a set of support materials.
Participants will be given the possibility of carrying out a small qualitative data analysis project according to their research and/or professional interests. This project will be discussed during additional sessions, which take place, preferably, in the afternoon. Participants are guaranteed assistance in carrying out the proposed tasks.
Obtaining ECTS is subject to the presentation of the final work. The course is not subject to summative assessment.



Bernard, Harvey Russel; Ryan, Gery Wayne (2010). Analyzing Qualitative Data: Systematic Approaches. London: SAGE Publications.
Fielding, Nigel; Lee, Raymond (1998), Computer Analysis and Qualitative Research. London: SAGE Publications.
Gibbs, Graham R. (2007), Analyzing Qualitative Data. London: SAGE Publications.
Krippendorff, Kimberly (2004). Content analysis: an introduction to its methodology. Thousand Oaks: SAGE Publications.
Kuckartz, U. (2014). Qualitative Text Analysis: A Guide to Methods, Practice & Using Software. London: SAGE Publications.
Kuckartz, U., & Rädiker, S. (2019). Analyzing qualitative data with MAXQDA: Text, audio, and video. London: SAGE Publications.
Lewins, Ann; Silver, Christina (2014), Using Software in Qualitative Research: A Step-by-Step Guide. London: SAGE Publications.
Michael Huberman & Matthew B. Miles (Eds.) (2002). The Qualitative Researcher's Companion. Thousand Oaks: SAGE Publications.
Neuendorf, K. A. (2002). The Content Analysis Guidebook. London: SAGE Publications.
Silverman, David (2013). Doing Qualitative Research. London: SAGE Publications.


To attend the course, the candidate must be 18 years old or over and fit into the defined target audience. A good command of the English language is recommended to use the bibliography.


Applications until 29 May 2024.

Applications through the ICS FenixEdu platform: https://fenix.ics.ulisboa.pt.
To create a registration, please access https://fenix.ics.ulisboa.pt/accountCreation.
In case you already have a registration, you can recover the access at https://fenix.ics.ulisboa.pt/passwordResetRequest.
In case you already have a student number at ICS, you should use your Campus account credentials. You may recover your access to this account at https://utilizador.ulisboa.pt.


The School operates with a minimum of 10 participants and a maximum of 30 participants. If all vacancies are filled, preference will be given to candidates preparing theses or dissertations involving research projects related to the proposed methodologies.