Syllabus
Registration via LPIS
Pre-course assignment:
Read Chapter 1-6 of Emma Bell, Bill Harley, and Alan Bryman: Business Research Methods, 6th edition, Oxford University Press, 2022, ISBN: 9780198869443. https://global.oup.com/ukhe/product/business-research-methods-9780198869443?cc=at&lang=en&
We expect you to be familiar with the core concepts from these chapters (quiz in the first unit).
Part 1:
Input lectures and discussion
- What is research?
- Scientific analysis in a Master thesis
- What is a research question and how to find one for your Master thesis?
- Research idea generation
- Major steps to write a Master thesis
Methods and data: Elaborate the main methods used in empirical research, develop a master thesis proposal that uses that method (assignment 1, group presentations)
Part 3:
Assignment 2: Learn from examples: Choose a paper and reflect on it, develop a master thesis proposal that builds on this paper (individual assignment)
- Students get a first rough idea of what is scientific research
- Students understand the concept of a research question and how and why different research designs are used to answer certain research questions
- Students can identify major steps in assessing a scientific paper and can develop a master thesis topic and proposal research based on prior research
Input presentations by instructors, individual assignments, group work.
Compulsory attendance for input lectures (part 1), for group presentations (part 2) and individual presentations (part 3). One to one consultation for the individual assignment (part 3) will be individually scheduled with the lecturers.
Pre-course-assignment/multiple-choice quiz: 10% Attention: For all four masters thesis courses, the quiz will take place Online on October 3, 2024.
Group Assignment “Part 2”: 30%
Individual Assignment “Part 3”: 60%
For this course, only one of two grades (pass/fail) will be awarded.
A "pass" grade requires a minimum score of 50% for each assignment and 75% in total.
Usage of AI-Tools:
The responsible use of AI tools is encouraged. Students may leverage AI to support their individual academic learning and development needs, which include but are not limited to text summarization, data analytics, and language/grammar correction. However, it is imperative to maintain a transparent record of their use and to reflect critically on the output. Students should take responsibility for carefully evaluating the results produced by AI tools. While these tools offer valuable assistance, they must be applied thoughtfully to ensure alignment with core objectives and scientific rigor. Students take full responsibility for any output generated by AI.
Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.
- Ability to identify relevant literature using research databases. EBSCO, Proquest are accessible via https://www.wu.ac.at/en/library/finding-literature/databases/ (requires VPN connection (https://www.wu.ac.at/en/it/services/network/vpn) if not accessed from within WU network). Other resources: http://www.jstor.org (papers), http://katalog.wu.ac.at/primo_library/libweb/action/search.do?vid=WUW&prefLang=en_US (books from the various WU libraries). WU library’s CatalogPLUS also allows for easy searching for papers including SFX links for full text access.
- If you are new to WU or not familiar with the tools mentioned above, see https://learn.wu.ac.at/bibliothek/ which offers short introductions to searching by topic, search strategy, search tools, and reference management tools (Citavi, Endnote Web).
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