• Atharva Kalidas Pandharikar
• Deepti Deepak Dabal
• Rina Sunil Gholap
• Harshada Tukaram Sonawane
• I .Priyadarshini ,Ganesh Jadhav

The aim of this paper is to investigate the impact of various input parameters on engineering students' first-semester grades in order to identify influential input parameters. The decline in students' academic performance is a major issue in engineering education nowadays. Hence based on academic performance the present study aims to develop a Machine learning based classifier which classifies the learner as slow learner, average learner and fast learner. Every learner has different learning needs and learning styles. Learning styles play an important role in helping learners retain learned concepts longer and improve their understanding of concepts .In addition to type of learner each student is suggested his or her preferred method of study based on the results of a learning style test.

Learning Style, Support Vector Classifier (SVC), Multi Class Classification, students’ academic performance

"IDENTIFY DIFFERENTIATED LEARNERS TO ENHANCE LEARNING OUTCOMES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.g60-g65, March-2023, Available :http://www.jetir.org/papers/JETIR2303611.pdf

"IDENTIFY DIFFERENTIATED LEARNERS TO ENHANCE LEARNING OUTCOMES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppg60-g65, March-2023, Available at : http://www.jetir.org/papers/JETIR2303611.pdf