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Boosting Retention: Evaluating and Enhancing SENATI's uRetention System to Cut Dropout Rates

Kebing Bi collaborated with SENATI (Servicio Nacional de Adiestramiento en Trabajo Industrial) to evaluate the performance of the uRetention system, designed to predict and mitigate student dropout risks. By analyzing student records, algorithm performance, and tutor interventions, the project aimed to assess uRetention’s accuracy and offer recommendations for improving retention strategies at SENATI.



During the project with SENATI, student consultant Kebing Bi assessed the effectiveness of the uRetention system, which was implemented to predict student dropout risk. The analysis showed a significant decrease in dropout rates from 6.5% to 3.6% over the past three years, but also highlighted the system’s shortcomings with low precision and sensitivity in predicting at-risk students. Inaccuracies in student records, insufficient data inputs, and algorithmic limitations contributed to false negatives, undermining the system’s potential. Kebing provided actionable recommendations, including refining the dropout prediction algorithm, addressing data inaccuracies, and improving tutor involvement in early intervention strategies. The project contributed to SENATI’s broader retention strategy by identifying gaps and suggesting improvements to better predict and address student dropouts, ensuring better academic outcomes and operational sustainability.




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