• DR.R.HEMALATHA
• M V SETHURAMALINGAM

The analysis of student performance based on the Program outcomes, Course Learning outcomes, Assessment, and course is known as outcome-based education (OBE). Predicting and analyzing performance based on deep learning algorithms can benefit from data analysis. This makes it easier to combine student performance with program and learning outcomes and to classify them according to quality indicators, which show how much of a goal is accomplished through studying. Graduates from educational institutions ought to be prepared to deal with technological advancement. Outcome-Based Education (OBE), which includes OBE-based curriculum development, teaching and learning process assessment, and Program Educational Objectives (PEO), is the only way to meet the challenges of the future. PEO, PO, PSO, and CO are the most common buzzwords for OBE. The findings of this study demonstrate the significance of OBE in today's educational system for achieving the desired outcomes. Based on Outcome-Based Education (OBE) and the specific program educational objectives and outcomes, the primary objective of this paper is to examine the performance of the students. However, these analyses only take into account the students' academic performance. For a better prediction, an adaptive approach that takes into account the student's personal characteristics as well as academic data can be used. It is possible to obtain accurate predictions and more significant analyses by utilizing various data mining algorithms. A student performance prediction model based on the DSN neural network model and the Deep Learning Model Using the OBE Framework was proposed in this work. Profound learning based strategy is applied to work on the exhibition of the classifier. This study demonstrates the significance of data preprocessing, which resolves issues with data quality. A comparison of OBE module experimental results and data analysis for OBE is presented in this paper. For a comprehensive examination of the OBE-based implementation, the experimental results include predictive, data, and comparative analyses of student performance.

Deep learning, Outcome Based Education, DSN

"ANALYSIS OF STUDENT PERFORMANCE USING DEEP LEARNING APPROACHES FOR OUTCOME BASED EDUCATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.e55-e58, March-2025, Available :http://www.jetir.org/papers/JETIR2503420.pdf

"ANALYSIS OF STUDENT PERFORMANCE USING DEEP LEARNING APPROACHES FOR OUTCOME BASED EDUCATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppe55-e58, March-2025, Available at : http://www.jetir.org/papers/JETIR2503420.pdf