Abstract
Abstract The sentimental analysis relates to structural detection, extraction, quantification, and evaluation of effects and knowledge in natural language processing, text analysis, computer-language sociology, and biometric data. Many emotional hurdles prevent student-teacher communication's intellectual progress that can promote healthy feelings towards the class environment. Therefore, in this paper, sentimental analysis assisted student-teacher communication (SAA-STC) has been proposed for effective learning in higher education purposes. Using sentiment analysis, feelings were drawn from the students' teaching records based on the concurrent exploratory approach. STC is introduced, which can manage numerous e-learning fields to check the student-teacher communication for effective learning. STC allows any initial checks to be completed, focusing on a few transparent challenges to enable the framework to continue expanding higher education learning communication.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
