Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries

This open access book presents contributions on a wide range of scientific areas originating from the BUiD Doctoral Research Conference (BDRC 2023)

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Assayed, Suha Khalil (author)
مؤلفون آخرون: Alkhatib, Manar (author), Shaalan, Khaled (author)
منشور في: 2024
الموضوعات:
الوصول للمادة أونلاين:https://bspace.buid.ac.ae/handle/1234/2568
https://link.springer.com/chapter/10.1007/978-3-031-56121-4_24
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author Assayed, Suha Khalil
author2 Alkhatib, Manar
Shaalan, Khaled
author2_role author
author
author_facet Assayed, Suha Khalil
Alkhatib, Manar
Shaalan, Khaled
author_role author
dc.creator.none.fl_str_mv Assayed, Suha Khalil
Alkhatib, Manar
Shaalan, Khaled
dc.date.none.fl_str_mv 2024-04-05T12:31:09Z
2024-04-05T12:31:09Z
2024
dc.identifier.none.fl_str_mv Assayed, S.K., Alkhatib, M., Shaalan, K. (2024). Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries. In: Al Marri, K., Mir, F.A., David, S.A., Al-Emran, M. (eds) BUiD Doctoral Research Conference 2023. Lecture Notes in Civil Engineering, vol 473. Springer, Cham. https://doi.org/10.1007/978-3-031-56121-4_24
Print: 978-3031561207 Online: 978-3031561214
https://bspace.buid.ac.ae/handle/1234/2568
https://link.springer.com/chapter/10.1007/978-3-031-56121-4_24
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv SpringerLink
dc.relation.none.fl_str_mv https://link.springer.com/chapter/10.1007/978-3-031-56121-4_24
dc.subject.none.fl_str_mv intent recognition, LSTM, Naive-Bayes, chatbot, high school, machine learning
dc.title.none.fl_str_mv Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
dc.type.none.fl_str_mv Conference paper
description This open access book presents contributions on a wide range of scientific areas originating from the BUiD Doctoral Research Conference (BDRC 2023)
id budr_bb766594a48260eed26c4e82e9249016
identifier_str_mv Assayed, S.K., Alkhatib, M., Shaalan, K. (2024). Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries. In: Al Marri, K., Mir, F.A., David, S.A., Al-Emran, M. (eds) BUiD Doctoral Research Conference 2023. Lecture Notes in Civil Engineering, vol 473. Springer, Cham. https://doi.org/10.1007/978-3-031-56121-4_24
Print: 978-3031561207 Online: 978-3031561214
language_invalid_str_mv en
network_acronym_str budr
network_name_str The British University in Dubai repository
oai_identifier_str oai:bspace.buid.ac.ae:1234/2568
publishDate 2024
publisher.none.fl_str_mv SpringerLink
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spelling Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School InquiriesAssayed, Suha KhalilAlkhatib, ManarShaalan, Khaledintent recognition, LSTM, Naive-Bayes, chatbot, high school, machine learningThis open access book presents contributions on a wide range of scientific areas originating from the BUiD Doctoral Research Conference (BDRC 2023)Purpose - This paper aims to develop a novel chatbot to improve student services in high school by transferring students’ enquiries to a particular agent, based on the enquiry type. In accordance to that, comparison between machine learning and neural network is conducted in order to identify the most accurate model to classify students’ requests. Methodology - In this study we selected the data from high school students, since high school is one of the most essential stages in students’ lives, as in this stage, students have the option to select their academic streams and advanced courses that can shape their careers according to their passions and interests. A new corpus is created with (1004) enquiries. The data is annotated manually based on the type of request. The label high-school-courses is assigned to the requests that are related to elective courses and standardized tests during high school. On the other hand, the label majors & universities is assigned to the questions that are related to applying to universities along with selecting the majors. Two novel classifier chatbots are developed and evaluated, where the first chatbot is developed by using a Naive Bayes Machine Learning Algorithm, while the other is developed by using Recurrent Neural Networks (RNN)-LSTM. Findings - Some features and techniques are used in both models in order to improve the performance. However, both models have conveyed a high accuracy score which exceeds (91%). The models have been validated as a pilot testing by using high school students as well as experts in education and six questions and enquiries are presented to the chatbots for the evaluation. Implications and future work - This study can add value to the team of researchers and developers to integrate such classifiers into different applications. As a result, this improves the users’ services, in particular, those implemented in educational institutions. In the future, it is certain that intent recognition will be developed with the addition of a voice recognition feature which can successfully integrated into smartphones.SpringerLink2024-04-05T12:31:09Z2024-04-05T12:31:09Z2024Conference paperAssayed, S.K., Alkhatib, M., Shaalan, K. (2024). Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries. In: Al Marri, K., Mir, F.A., David, S.A., Al-Emran, M. (eds) BUiD Doctoral Research Conference 2023. Lecture Notes in Civil Engineering, vol 473. Springer, Cham. https://doi.org/10.1007/978-3-031-56121-4_24Print: 978-3031561207 Online: 978-3031561214https://bspace.buid.ac.ae/handle/1234/2568https://link.springer.com/chapter/10.1007/978-3-031-56121-4_24enhttps://link.springer.com/chapter/10.1007/978-3-031-56121-4_24oai:bspace.buid.ac.ae:1234/25682024-04-16T05:22:04Z
spellingShingle Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
Assayed, Suha Khalil
intent recognition, LSTM, Naive-Bayes, chatbot, high school, machine learning
title Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
title_full Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
title_fullStr Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
title_full_unstemmed Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
title_short Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
title_sort Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
topic intent recognition, LSTM, Naive-Bayes, chatbot, high school, machine learning
url https://bspace.buid.ac.ae/handle/1234/2568
https://link.springer.com/chapter/10.1007/978-3-031-56121-4_24