International Artificial Intelligence in Education (AIED) Society (Founded 1993 as part of another association, came into its own January 1, 1997)
Interdisciplinary community of computer science, education, and psychology
International Journal of AI in Education (IJAIED) (Inaugural issue 1989)
International Alliance to Advance Learning in the Digital Era (IAALDE), an information-sharing cooperation bringing together independent societies that overlap in teaching, learning, and technology (e.g., AIEd, International Society of the Learning Sciences ISLS)
Chaudhry, M. A., & Kazim, E., (2022). Artificial intelligence in education (AIEd): A high-level academic and industry note 2021. AI and Ethics, 2, 157-165. https://doi.org/10.1007/s43681-021-00074-z
Identifies latest domains in AIEd: 1. reducing teachers’ workload, 2. contextualized learning for students, 3. intelligent assessment, 4. intelligent tutoring systems (ITS). Notes the leadership of ed tech companies (e.g., Pearson) in the space and ethical concerns of the field. Seems to suggest that the growth of the AIEd field has been stunted to date by limited capabilities of AI.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Boston: Center for Curriculum Redesign. https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf
Hinogo-Lucena, F., Aznar-Diaz, I., Cacered, Reche, M., & Romero-Rodriguez, J. (2019). Artificial intelligence in higher education: A bibliometric study on its impact in the scientific literature. Education Sciences, 9(1), 51. https://doi.org/10.3390/educsci9010051
A bibliometric review of 2007-2017 literature on artificial intelligence in education (n=132) to detect scope and identify research trends in the field. The most cited article in the same concerns virtual tutoring and was published in 2011. Show that AI in education is of international concern; the U.S. is the country with the highest production, but highest impact rate obtained by Turkey.
Williamson, b., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Mediat, and Technology 45(3). https://doi.org/10.1080/17439884.2020.1798995
Editorial using genealogical analysis methods to trace evolution of AI in education. Identifies historical developments in research field, commercial ed tech (notes Pearson as major ed tech player), technology infrastructure driven by corporations, and policy and governance. Identifies gaps: ethnographies, educational philosophy, collaboration. Asserts that we don’t know much about how AI is used on the classroom ground, and case studies could help. Recommends integration of philosophy to ground AI in educational philosophies. Argues for greater collaboration between commercial interests and academic sector to align and further progress. Appears to lament that commercial enterprise may have eclipsed academia in the last sentence of the article: “An important additional trajectory of research is for academics to develop ways to more directly intervene in shaping the future imaginaries of AIed.”
Zawacki-Richter, O., Marin, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education 16(39). https://doi.org/10.1186/s41239-019-0171-0
The authors report that Artificial Intelligence in Education (AIEd) is a currently emerging and interdisciplinary field in educational technology. This systematic literature review identifies gaps in the literature in this field, with most research quantitative and coming from Computer Science and STEM fields for the period 2007-2018. Findings include four areas of AIEd applications in academic support services, and institutional and administrative services: 1. Profiling and prediction, 2. Assessment and evaluation, 3. Adaptive systems and personalisation, and 4. Intelligent tutoring systems. Calls for stronger theoretical pedagogical perspectives and further exploration of ethical and educational approaches of AI applications.