Pedagogy of Emerging Technologies in Chemical Education during the Era of Digitalization and Artificial Intelligence: A Systematic Review
The technological advancement and rapid development of artificial intelligence have led to a growing number of studies investigating pedagogical innovations incorporated with emerging technologies in this digital era. An increasing amount of empirical evidence has suggested the potential benefits of...
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Formato: | article |
Lenguaje: | EN |
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MDPI AG
2021
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Acceso en línea: | https://doaj.org/article/79f29f548ce344a5b520a74be882db0d |
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Sumario: | The technological advancement and rapid development of artificial intelligence have led to a growing number of studies investigating pedagogical innovations incorporated with emerging technologies in this digital era. An increasing amount of empirical evidence has suggested the potential benefits of incorporating digital technologies and artificial intelligence in various educational contexts, such as the K-12 education, and a change in learning modality in the unprecedented period of COVID-19. In chemical education, various types of emerging technologies, such as eye-tracking techniques, learning analytics, robotics, virtual reality (VR), and augmented reality (AR), have seen wide applications and promising prospects. In this paper, a systematic review of emerging technologies adopted in chemical education during this era of digitalization and artificial intelligence is presented. The current study aims to identify the major types of technologies adopted in chemical education and analyze the empirical findings from relevant studies. A total of 45 studies between 2010 and 2021 were analyzed through a literature search in three inter-disciplinary databases: Web of Science, Scopus, and the Educational Information Resource Center. Full-text retrieval and analysis of the included studies were conducted. The present study finds that AR and VR applications were most extensively investigated among the identified types of technologies adopted in chemical education, while the major focus areas were associated with virtual chemistry laboratories, visualization and interaction with chemical structures, and classroom hands-on activities. The evidence presented in this study also indicates the promising applications of artificial intelligence and learning analytics in the analysis of students’ feedback and behavior, assessment of students’ understanding of chemical concepts, and investigations of students’ reasoning and cognitive processes during chemical tasks such as spectral interpretation. Furthermore, areas requiring more research, investigations, potential future applications, as well as pedagogical implications of education for sustainable development will be identified based on the evidence presented in this study. The findings of this study are expected to give insight on the evolving areas of chemical education research and technology-enhanced teaching and learning. |
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