6 ECTS credits
180 h study time

Offer 2 with catalog number 4021326DNR for all students in the 2nd semester at a (D) Master - preliminary level.

2nd semester
Enrollment based on exam contract
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Taught in
Faculty of Psychology and Educational Sciences
Educational team
Jerich Faddar (course titular)
Activities and contact hours
26 contact hours Lecture
5 contact hours Seminar, Exercises or Practicals
Course Content

This course provides an introduction into the basics of data analysis in educational sciences. Given the wide array of educational data, both quantitative and qualitative approaches to data analysis are handled throughout the course. By means of hands-on practice with computer-aided software, the student is challenged to conduct several techniques of analysis taking into account the specific nature of the data. This means that the course is oriented towards the practical application of data analysis to solve problems without focussing too much on mathematical proofs and background. The course includes the following core contents:

  • Introduction to educational data, organisation and handling
  • Descriptive statistics
    • Parameters of centrality
    • Parameters of spread
    • Normal distribution
    • Chance distribution, central limit theorem
  • Inferential statistics
    • Testing differences
    • Correlation
    • Regression analysis
  • Scale development and reliability analysis
  • Qualitative analysis
    • Content analysis
    • Coding strategies
    • Integrative procedures
Course material
Digital course material (Required) : Slides, datasets, etc., Canvas
Handbook (Required) : Discovering statistics using IBM SPSS Statistics, Andy Field, 5ed, Sage, 9781526419521, 2017
Additional info

Handbook (required): "Discovering Statistics Using IBM SPSS Statistics" by Andy Field (5th Edition, 2018, ISBN 978-1-5264-1951-4)

Lecture powerpoints and other reading material will be provided through the learning platform.

Additional material (such as datasets, assignments, answer keys and additional reading materials) will be provided through the learning platform.

Generative AI can be used in this course, further details will be provided during course activities and the Canvas Course Platform. Any use of generative AI should be properly referenced.

Learning Outcomes

Algemene competenties

At the end of the course Data Analysis in educational sciences students will be able to:

  • Explain and illustrate different approaches to data analysis and identify levels of measurement
  • Translate a problem into a model of analysis and select an appropriate technique to analyse the data
  • Explain and calculate measures for centrality and spread (for example, the mean, quantiles and standard deviation)
  • Describe and perform inferential statistical tests by means of IBM SPSS (for example, t-test, correlation, regression analysis)
  • Describe and explain central concepts and procedures required to approach a dataset through qualitative techniques of analysis (for example, content analysis)
  • Use NVivo software to analyse qualitative  data
  • Understand and apply procedures for analysing qualitative data
  • Interpret the results from analyses and report on it in a written way


The final grade is composed based on the following categories:
Written Exam determines 70% of the final mark.
PRAC Practical Assignment determines 30% of the final mark.

Within the Written Exam category, the following assignments need to be completed:

  • Written exam with a relative weight of 1 which comprises 70% of the final mark.

    Note: Written exam on PC (theory and exercises)

Within the PRAC Practical Assignment category, the following assignments need to be completed:

  • Practical assignment with a relative weight of 1 which comprises 30% of the final mark.

Additional info regarding evaluation

Not applicable.

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Master of Educational Sciences: Standaard traject (only offered in Dutch)
Master of Educational Sciences: Standaard traject