Navigation

Bachelor Thesis

General Informations

The supervision of bachelor theses at our chair is based on a sequentially structured process that is repeated every six months. Deviations from the deadlines are not possible. The application period begins three weeks before the beginning of the lecture period of the respective semester and lasts two weeks. During the first week of lectures, the selection interviews take place, following which you will receive either an acceptance or a rejection.

Application process

If you want to write your thesis at our chair, please note the application period: 30.03.2020 – 11.04.2020

  • Selection interviews: 20.04.2020 – 24.04.2020
  • Seminar for the Bachelor thesis: 29.04.2020 – 08.07.2020
  • Latest date for registration of the work: 13.07.2020

It is essential that you stay in regular contact with your supervisor in order to coordinate your work.

Seminar for Bachelor Thesis

Our chair offers a bachelor thesis seminar, which is especially aimed at students of business informatics and those interested in other courses of study who would like to write a bachelor thesis at the Schöller Endowed Chair for Business Informatics. The seminar is mandatory for students that write their bachelor thesis at our chair.

Prerequisites

Course of study Conditions
International Business Studies attended in-depth module at the chair or application for exemption
International Production Engineering and Management attended module at the chair
Sozialökonomik attended in-depth module at the chair or application for exemption
Wirtschaftsinformatik none
Wirtschaftsingenieurwesen attended module B24, B25 or B26 at the chair
Wirtschaftswissenschaften mit Schwerpunkt Wirtschaftsinformatik none
Wirtschaftswissenschaften mit anderen Schwerpunkten attended in-depth module at the chair or application for exemption

Open Topics

 

Topic Supervisor

Students focus on digital student advisory, which subsumes the use of artificial intelligence and data analytics regarding the support of students during their studies. The idea is to develop an early warning system that enable students and student advisor to identify challenges during the student lifecycle early on. For this purpose, use scenarios for different contexts known from one’s own study (for example, applying for a degree program, basic studies, advances studies) can be studied, a literature review can be conducted, concrete challenges can be solved by prototypes or questions of acceptance can be analyzed. This thesis and the related application can be handed in in German or English. Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments

Prof. Dr. Sven Laumer,

Daniel Schömer

Students focus on different questions regarding data science. In this context, several data science and data management approaches can be reviewed, prototypes for applying these approaches can be implemented and concepts for using this approaches in (online) tutorials can be developed. The idea is to use R and corresponding frameworks to focus on one of the phases of the data management lifecycle. This thesis and the related application can be handed in in German or English. Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments

Prof. Dr. Sven Laumer

Students focus on different questions regarding „digital learning“. For this purpose, use scenarios for different contexts known from one’s own study (for example, online tutorials, online tests, online exams, chatbots for Q&A) can be studied, a literature review can be conducted, concrete challenges can be solved by prototypes or questions of acceptance can be analyzed. This thesis and the related application can be handed in in German or English. Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments
Prof. Dr. Sven Laumer

“Digital nudging is the use of user-interface design elements to guide people’s behavior in digital choice environments.” (Weimann et al. 2016). Students can focus on different questions regarding digital nudging in different contexts (learning, advisory, sports, health, etc.). For this purpose, a literature review can be conducted, concrete challenges can be solved by prototypes or questions of acceptance can be analyzed. Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments
Prof. Dr. Sven Laumer

Students focus on different questions regarding „digital books and publication processes“. For this purpose, use scenarios for different contexts can be studied, a literature review can be conducted, concrete challenges can be solved by prototypes or questions of acceptance can be analyzed. This thesis and the related application can be handed in in German or English. Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments
Prof. Dr. Sven Laumer

A literature review should be conducted that summarizes the literature published about the use of machine learning (and similar approaches) in recruiting. The idea is to summarize the status quo, explain the basic principles and to derive a research agenda for the use of machine learning in recruiting. Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments

Prof. Dr. Sven Laumer

The (further) development of innovative technologies and the changed communication behaviour caused by social media can lead to new forms of work in the long term and thus also have a lasting influence on the recruitment of talent. The aim of this thesis is to review the state of research on automated recruiting approaches by means of a systematic literature analysis. The Bachelor thesis can be written in English or German. Please apply to jessica.ochmann@fau.de by using the chair’s application form together with all of your attachments .
Jessica Ochmann

The HR industry is faced with the challenging task of filling vacancies on the labour market with increasingly complex candidate profiles and highly competitive, scarce talent. Within the framework of the bachelor thesis, the requirements of the candidates as well as the individual acceptance of innovative technologies in personnel management (e.g. chatbots, data-driven recruiting) are to be examined on the basis of explorative interviews.
The Bachelor thesis can be written in English or German. If you are interested, please use the application form to apply to jessica.ochmann@fau.de.
Jessica Ochmann

Automated recruitment approaches and the use of social media lead to increased efficiency in personnel management. But how do candidates perceive these developments? Which innovations are accepted by candidates and which factors promote or inhibit acceptance?
The bachelor thesis will use interviews or quantitative methods to discuss and analyse how data-driven approaches and automated dialogue systems are accepted by society in general.
The bachelor thesis can be written in English or German. If you are interested, please use the application form to apply to jessica.ochmann@fau.de.
Jessica Ochmann

Everyone is talking about artificial intelligence at the moment. In many non-scientific formats and discussions, it is considered a revolutionary solution to a wide range of different problems, including those in healthcare, retail and manufacturing. Behind it are often commercial interests, e.g. the desire to sell consulting services for the design and implementation of AI strategies and systems. But how is the topic of AI presented in science? The aim of this thesis is to systematically analyze and present the consideration of the topic AI in the leading scientific journals since 2010. In particular, the focus is on the topics in which the use of AI is primarily discussed and which AI methods and algorithms are primarily the focus of interest. The Bachelor thesis can be written in English or German. If you are interested, please apply to Quirin Demlehner (quirin.demlehner@fau.de) using the application form within the application period.

Quirin Demlehner

The demand for image recognition, processing and analysis is growing daily. The rapid development of computer capacities and the development of new innovative technologies provide a platform for the application of image processing algorithms. Convolutional Neuronal Networks (CNN) are one of the most promising algorithms in the field of computer vision.
The aim of the work is to identify existing applications by means of a systematic literature analysis, to classify them into the different economic sectors (energy supply, transport, construction, …) and to evaluate the adaptation rate or degree of maturity in the respective area. Within the scope of the work, the results will then be presented in a use case matrix.
This thesis and the associated proposal can be submitted in German or English. If you are interested, please apply using the application form at daniel.schoemer@fau.de

Daniel Schömer

Recommendation systems (so-called recommender systems) are used in numerous companies, as they effectively lead users to better and faster results and thus facilitate the decision-making process. Recommender systems can often be found in the field of e-commerce (e.g. Amazon or Zalando) or streaming services such as Netflix or Spotify.
A similar recommender system or AI-based consulting system can be developed to support students during their studies in selecting suitable courses. For example, individual course recommendations can be made and early predictions made based on student evaluations and identical preferences for courses. A further criterion for the selection of elective modules can be requirement profiles from job advertisements. In this way, it is possible to find courses for which a student might want to enrol but which he/she had not previously thought of or which are necessary for the design of a career.
Another scenario is the support and recommendation in selecting a course of study. The Friedrich-Alexander-University currently offers 261 courses of study, of which 77 are Bachelor, 92 Master and 92 State Examination courses. A recommendation system can be used to support prospective students based on their personal interests and academic performance in selecting a suitable one of a study program while at the same time reducing the number of dropouts or changes of study program.
The idea is to develop a recommendation system that enables students or prospective students to make better decisions when choosing their course or program.
To this end, recommendation/evaluation data and a suitable filter technique (e.g. content-based, collaborative or hybrid) will be identified and, based on this, a prototype will be modelled or alternatively questions of acceptance will be analysed.
This thesis and the associated proposal can be submitted in German or English. If you are interested, please apply using the application form at daniel.schoemer@fau.de

Daniel Schömer