Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI

Master & PhD Thesis Class (Sommersemester 2024)

Lecturer: Dr. Julia von Thienen

General Information

  • Weekly Hours: 2
  • Credits: 3
  • Graded: yes
  • Enrolment Deadline: 01.04.2024-30.04.2024
  • Teaching Form: Seminar
  • Enrolment Type: Compulsory Elective Module
  • Course Language: English

Programs, Module Groups & Modules

IT-Systems Engineering MA
Digital Health MA
Cybersecurity MA
Data Engineering MA
Software Systems Engineering MA
  • Professional Skills
    • HPI-PSK-DT Design Thinking


Course Details:

  • Starting Date: April 8th, 2024
  • Schedule: Modays, 11:00 am - 12:30 pm
  • Location: K-1.03

This seminar assists participants during the planning and writing of their master or phd thesis. It offers hands-on sessions to address various aspects of ongoing thesis work, and provides training in two subject areas: (i) research methodology and (ii) scientific writing.

Within the research methodology domain, participants learn how to assess the impact of IT tools they may develop. The curriculum provides a systematic guide on designing randomized experiments, quasi-experiments, and studies with repeated measures (time series data). It offers instructions on how to design survey and test items, along with strategies to assess the psychometric properties of scales. The seminar also teaches participants how to conduct, code and analyze interviews. An overview of UX testing is presented, alongside pointers on where and how to undertake UX research within the HPI. Additionally, the seminar offers a succinct introduction to the fundamentals of statistical data analysis.

The domain of scientific writing familiarizes participants with the basic structure of scientific texts, offering strategies for efficient time management during the writing process. It also delves into various facets of scientific publication, covering topics such as selecting appropriate journals, understanding the review process, and addressing ethical considerations, particularly in the context of using AI tools. It also provides guidance on formatting literature references and other formalities.

Regular practice sessions are embedded within the course structure, providing participants with opportunities to present sections of their writing, and receive feedback. The presented sections can be (shortened) passages taken from one's thesis, from other emerging paper drafts, or sections written solely for the 4-pages academic paper to be submitted by the end of the term.  

The class will start with input sessions by the beginning of the semester, while closing with a number of practice sessions dedicated to changing sections of your paper.


There are no prerequisites for taking this class.


  • 50% of your grade will be based on a short article you write on an academic subject of your choice. You do not need to publish it (publication is not part of the grading), but you are encouraged to use the effort invested and refinement time in class to work towards a paper publication. You can select publishing venues of your choice. One possibility is https://ecdtr.org.

  • 25% of your grade will be based on a study design (experiment, quasi-experiment, or time series analysis) you plan on a subject of your choice. You are only expected to submit the planned study design; there is no need to actually conduct the study.

  • 25% of your grade will be based on either a questionnaire you design on a subject of your choice, or alternatively, on the analysis of data making use of the statistical methods covered in class.

You are welcome to look into the course. In case you decide to step back, you need to resign by contacting the Studienreferat and/or writing an e-mail to Julia.vonThienen [at] hpi.de by May 4, 2024. On May 5,  the first grading-relevant homework submissions are expected in class.


8.4.24                   Introduction to Academic Writing

15.4.24                 Literature Research and Article Skimming

22.4.24                 Study Design – From Randomized Experiments to Time Series Data

29.4.24                 Designing Surveys and Test Items

6.5.24                   Conducting, Coding, and Analyzing Interviews

13.5.24                 Psychometric Properties of Scales

27.5.24                 Mastering UX: Research, Metrics, and Objectives

3.6.24                   Introduction to the Basics of Statistics

10.6.24                 Your Turn: Discussing Your Research Subjects, Questions/Hypotheses

17.6.24                 Your Turn: Paper & Study Design Critique

24.6.24                 Your Turn: Abstract & Keyword Review

1.7.24                   Your Turn: Introduction Review

8.7.24                   Your Turn: Methods Review

15.7.24                 Your Turn: Results and Conclusion Review


Further submission dates:

  • 5.5.24: A study designed by you
  • 16.6.24: Your self-designed questionnaire, or alternatively, your data analysis
  • 31.8.24: Your academic paper (four pages max.)