Enhancing Student Performance Insights Through Multi Parametric STBO Based Analysis in Engineering Education

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Author(s)

Santhosh Kumar Medishetti 1,* Ravindra Eklarker 2 Kommuri Venkatrao 3 Maheswari Bandi 4 Rameshwaraiah Kurupati 5

1. Nalla Narasimha Reddy Education Society's Group of Institutions, Hyderabad, Telangana, India

2. Geenthanjali College of Engineering and Technology, Hyderabad, India

3. Lakireddy Bali Reddy College of Engineering (Autonomous), Mylavaram, NTR District

4. Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur

5. University of Sudbury, 935 Ramsey Lake Rd, Sudbury, ON P3E 2C6, Canada

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2025.05.05

Received: 2 Mar. 2025 / Revised: 29 Apr. 2025 / Accepted: 25 Jun. 2025 / Published: 8 Oct. 2025

Index Terms

Students, Academic Performance, STBO Algorithm, NNRG, Internal Assessments, Learning Pace

Abstract

This research presents a novel approach to evaluating student academic performance at Nalla Narasimha Reddy Group of Institutions (NNRG) by implementing a Student Training Based Optimization (STBO) algorithm. The proposed method draws inspiration from the structured training and adaptive learning behavior of students, simulating their progression through knowledge acquisition, skill refinement, and performance enhancement phases. The STBO algorithm is applied to optimize academic performance assessment by identifying key parameters such as attendance, internal assessments, learning pace, participation, and project outcomes. By modelling student development as a dynamic optimization process, the algorithm effectively predicts academic outcomes and recommends personalized strategies for improvement. Experimental evaluation on real academic datasets from NNRG CSE, CSE (Data Science), and CSE (AIML) Students demonstrates that the STBO algorithm achieves higher prediction accuracy and adaptive feedback generation when compared to traditional statistical and machine learning techniques. This approach also facilitates early identification of at-risk students and promotes data-driven decision-making for faculty and administration. Overall, the STBO-based framework not only enhances performance assessment but also contributes to academic excellence by aligning learning strategies with individual student needs.

Cite This Paper

Santhosh Kumar Medishetti, Ravindra Eklarker, Kommuri Venkatrao, Maheswari Bandi, Rameshwaraiah Kurupati, "Enhancing Student Performance Insights Through Multi Parametric STBO Based Analysis in Engineering Education", International Journal of Modern Education and Computer Science(IJMECS), Vol.17, No.5, pp. 77-95, 2025. DOI:10.5815/ijmecs.2025.05.05

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