Predicting At-Risk Students Using the Deep Learning BLSTM Approach

Souai, Wiem; Mihoub, Alaeddine; Tarhouni, Mounira; Zidi, Salah; Krichen, Moez; Mahfoudhi, Sami

doi:10.1109/smarttech54121.2022.00022

Cited by 2 publications

(1 citation statement)

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“…The evolution of technology, especially for e-learning ( Mejbri et al, 2022 ), academic library applications ( Rafique et al, 2021 ), automatic programming, and the application of artificial intelligence ( Souai et al, 2022 ) have made the virtual world a reality 1 . Fully virtual study is another focus of future education, particularly for people with disabilities.…”

Section: Related Workmentioning

confidence: 99%

Development of an intelligent system based on metaverse learning for students with disabilities

2022

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Due to the coronavirus-2019 pandemic, people have had to work and study using the Internet such that the strengthened metaverse has become a part of the lives of people worldwide. The advent of technology linking the real and virtual worlds has facilitated the transmission of spatial audio and haptics to allow the metaverse to offer multisensory experiences in diverse fields, especially in teaching. The main idea of the proposed project is the development of a simple intelligent system for meta-learning. The suggested system should be self-configurable according to the different users of the metaverse. We aimed to design and create a virtual learning environment using Open Simulator based on a 3D virtual environment and simulation of the real-world environment. We then connected this environment to a learning management system (Moodle) through technology for 3D virtual environments (Sloodle) to allow the management of students, especially those with different abilities, and followed up on their activities, tests, and exams. This environment also has the advantage of storing educational content. We evaluated the performance of the Open Simulator in both standalone and grid modes based on the login times. The result showed times the standalone and grid modes of 12 s and 16 s, which demonstrated the robustness of the proposed platform. We also tested the system on 50 disabled learners, according to the t-test of independent samples. A test was conducted in the mathematics course, in which the students were divided into two equal groups (n = 25 each) to take the test traditionally and using the chair test tool, which is one of the most important tools of the Sloodle technology. According to the results, the null hypothesis was rejected, and we accepted the alternative hypothesis that demonstrated a difference in achievement between the two groups.

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Section: Related Workmentioning

confidence: 99%