Abstract
This paper presents an overview of the last decade of research on Artificial Intelligence in Education by conducting keyword and social network analysis on the time-evolving co-authorship networks in four major research conferences: the International Conference on Artificial Intelligence in Education, the International Conference on Educational Data Mining, the International Conference on Learning Analytics and Knowledge, and the ACM Conference on Learning at Scale. Time-evolving co-authorship networks were used as a proxy for the collaboration dynamic in the field, while keyword analysis was conducted to supplement the social network analysis in order to pinpoint foci of individuals and cliques. Recent research foci and the level of openness of the four research communities were examined to inform strategies on how to promote diverse ideas and further collaborations within the field of AI in Education.
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Notes
- 1.
The IAIED conference was held bi-annually up to 2017 and annually later, so our dataset on IAIED covers full conference papers in 2013, 2015, and 2017–2020. Additionally, the first L@S conference was held in 2014, so there are no papers from L@S in 2013.
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Zheng, Y., Zhou, Z., Blikstein, P. (2022). Towards an Inclusive and Socially Committed Community in Artificial Intelligence in Education: A Social Network Analysis of the Evolution of Authorship and Research Topics over 8 Years and 2509 Papers. In: Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2022. Lecture Notes in Computer Science, vol 13355. Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_34
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