Artificial Intelligence-Based Higher Education Students Advising System: The Case of Ethiopia

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Abstract Academic advisors assist students in academic matters such as registration, warning, probation and other personal matters. Successful advising systems increase student retention, improve graduation rates and help students meet educational goals. Research in academic advising shows a trend of integrating electronic technologies that advisors must adopt to increase their roles in student education, while resources are limited and the proportion of students increases. The main objective of this work is to design a model of academic advising dialogue system for higher education. In this research work, a Higher Education Students Advising System (HESAS) has developed as an academic advising dialogue system, to allow advising session to be more centered on students and to help advisors and advisees in making better informed-decision and improved services. The design of HESAS is composed of six main components. These are user interface, spelling corrector, natural language understanding, dialogue manager, response generator and advisement service. The students have used the system during the experimental phases. For the second experimental phase, the system performed well, obtaining close to 83%, on the traditional language processing measures of precision, recall and F1 score.

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