Adoption of 3D Holograms in Science Education: Transforming Learning Environments

被引:1
|
作者
Salloum, Said A. [1 ,2 ]
Alhumaid, Khadija [3 ]
Alfaisal, Aseel M. [4 ]
Aljanada, Rose A. [4 ]
Alfaisal, Raghad [5 ]
机构
[1] Univ Sharjah, Hlth Econ & Financing Grp, Sharjah, U Arab Emirates
[2] Univ Salford, Sch Sci Engn & Environm, Salford M5 4WT, England
[3] Rabdan Acad, Student Serv, Abu Dhabi, U Arab Emirates
[4] Northern Border Univ, Appl Coll, English Unit, Ar Ar 91431, Saudi Arabia
[5] Univ Pendidikan Sultan Idris, Fac Comp & Meta Technol, Tanjung Malim 35900, Malaysia
来源
IEEE ACCESS | 2024年 / 12卷
关键词
3D holographic technology; importance-performance matrix analysis (IPMA); machine learning algorithms; science education; technology adoption; NEURAL-NETWORK; PLS-SEM; ACCEPTANCE; DETERMINANTS; TECHNOLOGY; SERVICES; STUDENTS; SYSTEMS; UNIVERSITY; MODEL;
D O I
10.1109/ACCESS.2024.3402549
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This study delves into the deployment of 3D holographic technologies within the realm of science education, with the goal of evaluating their effects on both student engagement and learning achievements. It also seeks to understand the perceptions of consumers in the UAE regarding the adoption of 3D holography in educational environments. The study employs a theoretical framework that incorporates variables such as Perceived Compatibility, Observability, Trialability, Relative Advantage, Ease of Doing Business, and Technology Export. Data were collected through 828 questionnaires distributed across various educational institutions. To analyze the collected data, the study utilized a combination of Machine Learning (ML) algorithms and Partial Least Squares-Structural Equation Modeling (PLS-SEM), focusing on responses from the student surveys. Additionally, Importance-Performance Matrix Analysis (IPMA) was employed to assess the significance and performance of various factors. What distinguises this study is its theoretical framework, which integrates individual and technological characteristics, offering a novel perspective on the subject matter. Results revealed that factors derived from diffusion theory notably surpassed those concerning the Ease of Doing Business and Technology Export in their influence on technology adoption. Notably, the J48 decision tree classifier demonstrated superior accuracy over other classifiers in predicting the value of the dependent variable. The outcomes of this study highlight the revolutionary capabilities of 3D holograms to enrich science education through creating a dynamic, interactive learning space, thereby significantly boosting learners' comprehension and participation. The implications of this research are profound, providing essential insights for educators, policy makers, and technology developers on the pivotal factors driving 3D holography adoption. This facilitates the development of educational strategies that leverage cutting-edge technologies to enhance learning outcomes. Ultimately, the integration of 3D holographic technology not only aids in the visualization of intricate scientific ideas but also cultivates a more captivating and efficacious educational experience, setting the stage for the advancement of teaching methodologies.
引用
收藏
页码:70984 / 70998
页数:15
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