The Application of Data Analytics to Career Choice Prediction: A Literature Review

Finding the right career is one of the most critical yet challenging decisions individuals must make through different academic and professional stages. This review aims to tackle the modern career guidance approaches by adapting data analytics techniques and methods. The most relevant papers were synthesized and presented in terms of overall purpose, methodology, the dataset used, and data analytics applications. This review offers a reference for career guidance practitioners in different educational settings; it presents an overview of the latest data analytics applications within the domain of career guidance. It was recognized that artificial intelligence and machine learning techniques are successfully utilized to aid individuals by offering them career choice prediction and recommendations. The main findings of this review also indicate that machine learning algorithms such as Naive Bayes and Random Forest are the most accurate predictors of career choices. However, future research should be extended to measure how successfully individuals continue within career pathways recommended by data analytics applications.