Publication | Open Access
Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education
245
Citations
88
References
2021
Year
Artificial IntelligenceEngineeringEducational InformaticsEducationIntelligent Tutoring SystemInstitutional AnalyticsTeacher EducationIntelligent Tutoring SystemsExploratory ReviewTeaching AiHuman LearningEthics In Knowledge RepresentationCognitive ScienceLearning AnalyticsPrisma FrameworkArtificial Intelligence ApplicationsAi EducationLearning DesignArtificial Intelligence Ethics
This exploratory review sought to synthesize evidence on the emerging impact of artificial intelligence in education. The authors applied the PRISMA framework to search, screen, code, and analyze 141 items. The review produced a taxonomy of AI applications, a teacher development framework, ethical implications, and propositions for AI‑enabled teaching, underscoring AI’s potential to empower teachers as designers and orchestrators of AI‑driven learning.
This exploratory review attempted to gather evidence from the literature by shedding light on the emerging phenomenon of conceptualising the impact of artificial intelligence in education. The review utilised the PRISMA framework to review the analysis and synthesis process encompassing the search, screening, coding, and data analysis strategy of 141 items included in the corpus. Key findings extracted from the review incorporate a taxonomy of artificial intelligence applications with associated teaching and learning practice and a framework for helping teachers to develop and self-reflect on the skills and capabilities envisioned for employing artificial intelligence in education. Implications for ethical use and a set of propositions for enacting teaching and learning using artificial intelligence are demarcated. The findings of this review contribute to developing a better understanding of how artificial intelligence may enhance teachers’ roles as catalysts in designing, visualising, and orchestrating AI-enabled teaching and learning, and this will, in turn, help to proliferate AI-systems that render computational representations based on meaningful data-driven inferences of the pedagogy, domain, and learner models.
| Year | Citations | |
|---|---|---|
Page 1
Page 1