Performance Prediction System for University Course Selection
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Authors
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Publication date
2023
Typ of student thesis
Master
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11 - Student thesis
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Hochschule für Wirtschaft FHNW
Place of publication / Event location
Olten
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Abstract
Due to the limited availability of human academic advisors, and the high demand for academic advising by students, students’ needs are not satisfied. In a digital world, collecting data has become increasingly important. Algorithms can be used for analysing data and building predictive models. More and more industries are using recommender systems to improve their services and personalize recommendations to satisfy every customer’s need better. Compared to humans, algorithms can also consider implicit data, which refers to information that is not explicitly stated but can be deducted from available data.
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English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
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Review
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Citation
Mäder, D. (2023). Performance Prediction System for University Course Selection [Hochschule für Wirtschaft FHNW]. https://irf.fhnw.ch/handle/11654/48847