Literature DB >> 34025824

Artificial Intelligence and Machine Learning to Predict Student Performance during the COVID-19.

Ahajjam Tarik1, Haidar Aissa1, Farhaoui Yousef1.   

Abstract

Artificial intelligence is based on algorithms that enable machines to make decisions instead of humans. This technology improves user experiences in a variety of areas. In this paper we discuss an intelligent solution to predict the performance of Moroccan students in the region of Guelmim Oued Noun through a recommendation system using artificial intelligence techniques during the COVID-19.
© 2021 The Author(s). Published by Elsevier B.V.

Entities:  

Keywords:  COVID-19; Data Analysis; Data Science; Machine Learning; Recommendation; artificial intelligent; high school; prediction

Year:  2021        PMID： 34025824      PMCID： PMC8128667          DOI： 10.1016/j.procs.2021.03.104

Source DB:  PubMed          Journal:  Procedia Comput Sci


  5 in total

1.  A systematic review on machine learning models for online learning and examination systems.

Authors:  Sanaa Kaddoura; Daniela Elena Popescu; Jude D Hemanth
Journal:  PeerJ Comput Sci       Date:  2022-05-18

2.  Developing Multiagent E-Learning System-Based Machine Learning and Feature Selection Techniques.

Authors:  Shrouk H Hessen; Hatem M Abdul-Kader; Ayman E Khedr; Rashed K Salem
Journal:  Comput Intell Neurosci       Date:  2022-01-30

3.  Multi-classification deep CNN model for diagnosing COVID-19 using iterative neighborhood component analysis and iterative ReliefF feature selection techniques with X-ray images.

Authors:  Narin Aslan; Gonca Ozmen Koca; Mehmet Ali Kobat; Sengul Dogan
Journal:  Chemometr Intell Lab Syst       Date:  2022-03-30       Impact factor: 4.175

4.  Prospects and Challenges of Using Machine Learning for Academic Forecasting.

Authors:  Edeh Michael Onyema; Khalid K Almuzaini; Fergus Uchenna Onu; Devvret Verma; Ugboaja Samuel Gregory; Monika Puttaramaiah; Rockson Kwasi Afriyie
Journal:  Comput Intell Neurosci       Date:  2022-06-17

5.  Predictive modelling and analytics of students' grades using machine learning algorithms.

Authors:  Yudish Teshal Badal; Roopesh Kevin Sungkur
Journal:  Educ Inf Technol (Dordr)       Date:  2022-09-08
  5 in total

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