A Comprehensive Survey on the Investigation of Machine-Learning-Powered Augmented Reality Applications in Education

Author:

Khan Haseeb Ali1ORCID,Jamil Sonain23ORCID,Piran Md. Jalil4ORCID,Kwon Oh-Jin2ORCID,Lee Jong-Weon1ORCID

Affiliation:

1. Department of Software, Sejong University, Seoul 05006, Republic of Korea

2. Department of Electronics Engineering, Sejong University, Seoul 05006, Republic of Korea

3. Department of Computer Science, Norwegian University of Science and Technology (NTNU), 2815 Gjøvik, Norway

4. Department of Computer Engineering, Sejong University, Seoul 05006, Republic of Korea

Abstract

Machine learning (ML) is enabling augmented reality (AR) to gain popularity in various fields, including gaming, entertainment, healthcare, and education. ML enhances AR applications in education by providing accurate visualizations of objects. For AR systems, ML algorithms facilitate the recognition of objects and gestures from kindergarten through university. The purpose of this survey is to provide an overview of various ways in which ML techniques can be applied within the field of AR within education. The first step is to describe the background of AR. In the next step, we discuss the ML models that are used in AR education applications. Additionally, we discuss how ML is used in AR. Each subgroup’s challenges and solutions can be identified by analyzing these frameworks. In addition, we outline several research gaps and future research directions in ML-based AR frameworks for education.

Publisher

MDPI AG

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