Subject Stream Prediction: A Machine learning Approach to Select the Suitable Subject Stream for Senior Secondary Students in Sri Lanka

Authors : K. G. Kaushalya Abeywardhane; Anjalie Gamage

Volume/Issue : Volume 7 - 2022, Issue 12 - December

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Education is an important factor that measures the nation’s wealth and education directly affects the country’s future development. All children at all levels in Sri Lanka are entitled to free education up to the university level. During that period, the students have to face two essential examinations to complete their senior secondary education. According to the Sri Lankan education schema, students happen to select one subject stream to start their senior secondary education key stage 2. Most of the students select that subject stream without thinking deeper, thereby that decision will cause them to create a good future as well as not create. A prediction system which is called ‘Subject Stream Prediction’ predicts the appropriate subject stream to begin senior secondary education based on students’ previous examination results as well as their skills, and preferred working area for their target career. If some student does not satisfy with one predicted answer, the model proposes ten appropriate subject streams with relevant jobs and educational and technical qualifications that need for those careers based on the above features. I have done a performance analysis between four machine learning algorithms to select the best-suited algorithm to predict the suitable subject stream by accessing their accuracy levels. That analysis demonstrates that the ‘Random Forest Classifier’ algorithm gives high accuracy (72).

Keywords : Machine Learning Algorithm, Subject Stream, Prediction System


Paper Submission Last Date
31 - March - 2023

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In 1-2 Days

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