Chatbot - Embedded Systems

Student report (2019)

Authors

N.B. Posner Electrical Engineering, Mathematics and Computer Science
Y.F. Runhaar Electrical Engineering, Mathematics and Computer Science
Q. Fantazia Electrical Engineering, Mathematics and Computer Science
M. Khattat Electrical Engineering, Mathematics and Computer Science
M.S.A. Tariq Electrical Engineering, Mathematics and Computer Science
V.G.A. Wernet Electrical Engineering, Mathematics and Computer Science

Contributors

W.P. Brinkman Interactive Intelligence - EEMCS (supervisor 1)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2019 Noah Posner, Yohan Runhaar, Qusay Fantazia, Mostafa Khattat, Sameer Tariq, Victor Wernet
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Published Date

07-04-2019

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

The most crucial choices a student will make is about which college and major they decide to join. Accord- ing to a statistical analysis performed by Koenig (2018) in the U.S. News World Report, majors such as Computer and information science, Engineering and Engineering technology yield the highest employment rates and salaries compared to other majors. In an article they wrote about the factors that influence youths career choices, Akosah-Twumasi (2018) argued that the knowledge of issues related to ’job security’ and ’salaries’ may pressure youth to choose a career path based on the benefits associated with a particular profession. This causes an influence in the decision making of a student who will not necessarily apply for a major they would enjoy doing, but instead their choice is going to shift to a more reliable major. Thus, many students will apply for studies such as Computer Science even though it might not be well-suited for them. Our team has been asked by the Delft University of Technology’s communication department to develop a Chatbot in order to help students with their decision making, and specifically students interested in the master program Embedded Systems. The communication department gave our team a set of requirements that needed to be fulfilled. The final product needed to be a chatbot with which it is possible to have a conversation on the Embedded Systems study program. It should coach the student into making a decision as well as be able to answer frequently asked questions. The chatbot needed to be accompanied by a content management system which should allow the communication department to modify some of the content of the chatbot as well as provide them with useful statistics about the interactions with the chatbot. Our team was also required to use the Rasa (2019) open source machine learning tool for conversational artificial intelligence as back-end of our chatbot system in order to provide feedback about this framework which might be used in future projects at TU Delft.