Syllabus

Title
0835 Thesis Seminar: How to Write a Thesis
Instructors
Univ.Prof. Dr. Anne d'Arcy, Ass.Prof. Dr. Otto Janschek
Type
AG
Weekly hours
2
Language of instruction
Englisch
Registration
09/09/24 to 09/19/24
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Dates
Day Date Time Room
Thursday 10/03/24 10:00 AM - 11:00 AM Online-Einheit
Tuesday 10/08/24 09:00 AM - 05:00 PM D5.0.002
Friday 10/25/24 09:00 AM - 02:00 PM EA.5.034
Monday 12/16/24 09:00 AM - 04:00 PM Ort nach Ankündigung
Wednesday 12/18/24 09:00 AM - 04:00 PM Ort nach Ankündigung
Contents

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

 

Part 2:

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)

 

 

Learning outcomes
  • 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 
Attendance requirements

≥ 80 % Attendance Requirement

 

Teaching/learning method(s)

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.

 

Assessment

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.

Prerequisites for participation and waiting lists
  • Writing skills
Readings

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Recommended previous knowledge and skills
Availability of lecturer(s)
Last edited: 2024-09-12



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