Artificial intelligence innovation in education: A twenty-year data-driven historical analysis

• Main Authors: Chong Guan, Jian Mou, Zhiying Jiang
• Format: Article
• Language: English
• Published: KeAi Communications Co., Ltd. 2020-12-01
• Series: International Journal of Innovation Studies
• Subjects: Artificial intelligence; Systematic review; Intelligent tutoring systems; Virtual reality; Educational data mining
• Online Access: http://www.sciencedirect.com/science/article/pii/S2096248720300369

Reflecting on twenty years of educational research, we retrieved over 400 research article on the application of artificial intelligence (AI) and deep learning (DL) techniques in teaching and learning. A computerised content analysis was conducted to examine how AI and DL research themes have evolved in major educational journals. By doing so, we seek to uncover the prominent keywords associated with AI-enabled pedagogical adaptation research in each decade, due to the discipline’s dynamism. By examining the major research themes and historical trends from 2000 to 2019, we demonstrate that, as advanced technologies in education evolve over time, some areas of research topics seem have stood the test of time, while some others have experienced peaks and valleys. More importantly, our analysis highlights the paradigm shifts and emergent trends that are gaining prominence in the field of educational research. For instance, the results suggest the decline in conventional tech-enabled instructional design research and the flourishing of student profiling models and learning analytics. Furthermore, this paper serves to raise awareness on the opportunities and challenges behind AI and DL for pedagogical adaptation and initiate a dialogue.