A Review of Artificial Intelligence (AI) in Education from 2010 to 2020
By Xuesong Zhai, Xiaoyan Chu, Ching Sing Chai, M. Jong, A. Istenič, Michael Spector, Jia-bao Liu, Jing Yuan, Yan Li. Complex, 2021
1,069 citations recorded by the source corpus.
This study provided a content analysis of studies aiming to disclose how artificial intelligence (AI) has been applied to the education sector and explore the potential research trends and challenges of AI in education. A total of 100 papers including 63 empirical papers (74 studies) and 37 analytic papers were selected from the education and educational research category of Social Sciences Citation Index database from 2010 to 2020. The content analysis showed that the research questions could be classified into development layer (classification, matching, recommendation, and deep learning), application layer (feedback, reasoning, and adaptive learning), and integration layer (affection computing, role-playing, immersive learning, and gamification). Moreover, four research trends, including Internet of Things, swarm intelligence, deep learning, and neuroscience, as well as an assessment of AI in education, were suggested for further investigation. However, we also proposed the challenges in education may be caused by AI with regard to inappropriate use of AI techniques, changing roles of teachers and students, as well as social and ethical issues. The results provide insights into an overview of the AI used for education domain, which helps to strengthen the theoretical foundation of AI in education and provides a promising channel for educators and AI engineers to carry out further collaborative research.
Subfields: Computer Science Applications
View Paper: https://www.semanticscholar.org/paper/83311744b174550032cfe09cb2940703dc9c9245
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In Computer Science Applications
Citations in the corpus
- Rethinking the entwinement between artificial intelligence and human learning: What capabilities do learners need for a world with AI? (2022, neutral): “We argue that there are two important points to consider when thinking about digital competencies in relation to creating learning experiences and teaching opportunities that take advantage of AI (for an overview see Zhai et al., 2021).”
- Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020 (2022, background): “For instance, existing review work has summarized the trends of AIEd (Tang et al., 2021; Xie et al., 2019; Zhai et al., 2021), applications (Alyahyan & Düştegör, 2020; Hooshyar et al., 2016; Liz-Domínguez et al., 2019; Shahiri et al., 2015), theoretical paradigms (Ouyang & Jiao, 2021) and AI…”