Master Thesis Class (Wintersemester 2023/2024)
Lecturer:
Dr. Julia von Thienen
General Information
- Weekly Hours: 2
- Credits: 3
- Graded:
yes
- Enrolment Deadline: 01.10.2023 - 22.10.2023
- Teaching Form: Seminar
- Enrolment Type: Compulsory Elective Module
- Course Language: English
Programs, Module Groups & Modules
- Professional Skills
- Professional Skills
- HPI-PSK-DTA Design Thinking Advanced
- Professional Skills
- HPI-PSK-CO Communication Skills
- Professional Skills
- HPI-PSKDTA Design Thinking Advanced
- Professional Skills
- Professional Skills
- HPI-PSK-DTA Design Thinking Advanced
- Professional Skills
- HPI-PSK-DT Design Thinking
- Professional Skills
- HPI-PSK-DT Design Thinking
Description
Course Details:
- Starting Date: October 19th, 2023
- Schedule: Thursdays, 11:00 am - 12:30 pm
- Location: Online and HPI UX Lab
- Format: The class takes place online, except for two on-site sessions that encompass a tour of the HPI facilities for UX testing, and a hands-on introduction to a variety of devices for data acquisition.
- Online access: https://uni-potsdam.zoom.us/j/67830358163; Meeting ID: 678 3035 8163; Passcode: 17579769
This seminar assists participants during the planning and writing of their master 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 facilities. Participants are introduced to a number of consumer-grade devices for capturing and analyzing behavioral as well as physiological data. 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. Additionally, it 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 master thesis, 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 in 2023, while sessions in 2024 are dedicated to working with your text material.
Requirements
There are no prerequisites for taking this class.
Literature
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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.
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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.
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25% of your grade will be based on either a questionnaire you design on a subject of your choice, or alternatively, on the acquisition and analysis of data (e.g., video, audio, EEG, skin conductance, or another parameter of your choice).
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 Nov 29, 2023. On Nov 30, the first grading-relevant homework submissions are expected in class.
Dates
19.10.23 Introduction to Academic Writing
26.10.23 Literature Research and Article Skimming
2.11.23 Study Design – From Randomized Experiments to Time Series Data
9.11.23 Designing Surveys and Test Items
16.11.23 Conducting, Coding, and Analyzing Interviews
23.11.23 Psychometric Properties of Scales and Study Critique
7.12.23 (On-site) Tour through the UX Lab and Behavior Assessments
14.12.23 Mastering UX: Research, Metrics, and Objectives (by Cato Zantman)
21.12.23 Introduction to the Basics of Statistics
11.1.24 Abstract & Keyword Review
18.1.24 Introduction Review
25.1.24 Methods Review
1.2.24 Results and Conclusion Review
8.2.24 Short Paper Presentations & Feedback
Further submission dates:
- Nov 30, 2023: A study designed by you
- Jan 18, 2024: Your self-designed questionnaire, or alternatively, the analysis of self-recorded data
- March 31, 2024: Your academic paper (four pages max.)
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