Citation

Lim, Mei Shyan and Ho, Sin Ban and Chai, Ian (2021) Design and Functionality of a University Academic Advisor Chatbot as an Early Intervention to Improve Students’ Academic Performance. In: 7th International Conference on Computational Science and Technology, ICCST 2020, 29 - 30 August 2020, Pattaya, Thailand.

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Abstract

This paper introduces the design and functionality of a university academic advisor chatbot, which leverages on the result of a prediction model to predict students’ academic performance, to do early intervention to assist students who may need academic guidance. The prediction model is based on students’ attendance and scores of formative assessments to predict the score of the final summative assessment using a suitable machine learning algorithm. Scikit-learn library using Python will be used in this research to run the machine learning algorithms. The chatbot will be developed using Dialogflow which is integrated with one of the text messaging apps and established connection to a database. The database stores students’ attendance, scores of formative assessments, scores of final summative assessments and the status of students whom the chatbot has reached out to. This research aims to reduce the workload of lecturers to reach out to every student who is predicted to have problems in their academic studies and at the same time, be able to assist students using a chatbot.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Machine Learning
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	01 May 2021 14:18
Last Modified:	01 May 2021 14:18
URII:	http://shdl.mmu.edu.my/id/eprint/8640

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