Review on Mentoring Chatbot

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Sanchi Satam
Tejal Nimje
Shreya Shetty
Samidha Kurle

Abstract

Mentoring can provide valuable support for students at critical points in their academic as well as personal life. Students need mentors to assist them in the areas where they need to improve, to stimulate their personal and professional growth. In standard forms of educational mentoring, students schedule appointments with their assigned mentor, a professor who very well knows the academic curriculum and potential trajectories students goes through. However it is necessary for the college professor to perform various roles and responsibilities that are as much important as student mentoring for their own performance evaluation. To mitigate the issue of student mentoring, we are proposing an automation called Mentoring Chatbot using Artificial Intelligence framework. This technological solution can be beneficial not only students’ mentoring but also for prioritizing effectiveness of professors’ time toward other major issues and other imperative duties. According to our research, we found the following Bots that also provide approximate answers to the existing problem. One of them is Chatbot for College Student Programme Advisement. This College Student Programme Advisement chatbot can give appropriate responses to users requesting for course details and studens’ views. Another available answer in the market is ‘An Intelligent Career Counseling Bot’. It proposes an intelligent chatbot system for career counseling, which will help the user in selecting the right career by giving a proper response to the user’s query. By analyzing these bots we concluded that there exists no system that can act as a virtual mentor and help students whenever needed. This paper presents a literature review that describes the uniqueness of this Mentoring Chatbot.

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How to Cite
1.
Satam S, Nimje T, Shetty S, Kurle S. Review on Mentoring Chatbot. sms [Internet]. 30Jun.2020 [cited 12Oct.2025];12(SUP 1):147-50. Available from: https://smsjournals.com/index.php/SAMRIDDHI/article/view/1924
Section
Research Article