SYSTEM FOR PREDICTING PLACEMENTS OF STUDENTS

Abstract

ABSTRACT A system (100) for predicting placements of students, the system comprising: a user interface (102) configured to enable a user to enter a plurality of details associated with a student; a processor (104) communicatively coupled with the user interface (102), wherein the processor (104) is configured to: receive data from the user interface (102), analyze the data using an artificial intelligence (AI)/machine learning (ML) module (106), and predict placement results of the students.

Specification

Description:
FIELD OF THE DISCLOSURE
[0001] This invention generally relates to a field of educational analytics and, in particular, to a system designed to enhance the prediction and analysis of student placements through the application of artificial intelligence (AI) and machine learning (ML) techniques.
BACKGROUND

[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] Traditional methods of predicting student placements often rely on manual data collection and subjective interpretation, leading to inconsistencies and inaccuracies in pl , Claims:1. A system (100) for predicting placements of students, the system (100) comprising:
a user interface (102) configured to enable a user to enter a plurality of details associated with a student;
a processor (104) communicatively coupled with the user interface (102), wherein the processor (104) is configured to:
receive data from the user interface (102),
analyse the data using an artificial intelligence (AI)/ machine learning (ML) module (106), and
predict placement results of the students.

2. The system (100) as claimed in claim 1, wherein the plurality of details includes but not limited to academic performance, specialization and work experience, academic history, current academics, and socioeconomic background details of students.

Documents