Towards a Tripartite Research Agenda: A Scoping Review of Artificial Intelligence in Education Research
Lecture Notes on Data Engineering and Communications Technologies, ISSN: 2367-4520, Vol: 104, Page: 3-24
2022
- 11Citations
- 41Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Book Chapter Description
This paper reports on a scoping review of research studies on artificial intelligence in education (AIED) published over the last two decades (2001–2021). A wide range of manuscripts were yielded from the education and educational research category of the Social Sciences Citation Index (SSCI) database, and papers from an AIED-specialised journal were also included. 135 of those meeting the selection criteria were analysed with content analysis and categorical meta-trends analysis. Three distinctive and superordinate AIED research agenda were identified: Learning from AI, Learning about AI, and Learning with AI. By portraying the current status of AIED research and depicting its tripartite research agenda, gaps and possible directions were discussed. This paper serves as a blueprint for AIED researchers to position their up-and-coming AIED studies for the next decade.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85127074202&origin=inward; http://dx.doi.org/10.1007/978-981-16-7527-0_1; https://link.springer.com/10.1007/978-981-16-7527-0_1; https://dx.doi.org/10.1007/978-981-16-7527-0_1; https://link.springer.com/chapter/10.1007/978-981-16-7527-0_1
Springer Science and Business Media LLC
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