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Information Systems and Applied Computer Sciences

Information Systems and Energy Efficient Systems

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  8. Bachelor and Master Theses

Bachelor and Master Theses

Please send an email to the contact person in case of questions related to the topic of interest. 

Templates for theses and the expose are available at the  VC course (EESYS-Allgemeine Info Energieeffiziente Systeme).

Note: We offer our students the service of an R-Helpdesk as part of our degree dissertations. For further information, please enroll in the VC course for theses of the chair.

Available Topics  

Working TitleContactAdditional Information
Evaluation of battery technologies for Internet of Things devices(52.2 KB, 1 page)Prof. Dr. Thorsten StaakeBachelor thesis
Ground truth data collection for AI applicationsDr. Konstantin Hopf

Master thesis (literature review)

Information systems to promote healthy eatingJoanna GraichenMaster thesis
Impact assessment of infectious diseases in kindergartens as part of a cost-benefit analysis of digital feedback on hand washing(122.7 KB, 1 page)Joanna GraichenMaster thesis

Forecasting residential electricity consumption with statistical and machine learning techniques

Dr. Konstantin Hopf, Felix HaagLiterature analysis (Bachelor / Master thesis)
Data Science as craftwork: An explorative studyDr. Konstantin HopfSurvey and data analysis (Bachelor / Master thesis)
Empirical differences between IT governance and data analytics governanceDr. Konstantin HopfSurvey and data analysis (Bachelor / Master thesis)
Environmental appeals vs. financial incentives in promoting pro-environmental behavior: A literature reviewSebastian GüntherLiteraturanalyse (Masterarbeit)
To what extent do behavioral interventions in digital learning platforms support students' self-regulated learning? A literature reviewSebastian GüntherLiteraturanalyse (Masterarbeit)
Leveraging data analytics techniques to predict student dropout within learning platforms: Insights from an online university courseSebastian GüntherAuswertung (Masterarbeit)
Empowering adaptive learning instructions in digital learning environments by using counterfactual explanationsSebastian Günther & Felix HaagAuswertung (Masterarbeit)