Educational data mining keywords redistribute across new clusters over time, showing evolving specialization in AIED¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2021 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The educational data mining cluster of 2010–13 dissolves, with its central keywords becoming representative keywords of separate clusters in later periods. → Shihui Feng & Nancy Law 2021

Evidence¶

Shihui Feng & Nancy Law 2021¶

Shihui Feng & Nancy Law. (2021). Mapping Artificial Intelligence in Education Research: A Network-based Keyword Analysis. International Journal of Artificial Intelligence in Education, 31, 277–303. https://doi.org/10.1007/s40593-021-00244-4

q2 · i? · review · r2

Meso-level cluster tracking across temporal KCNs. The article reports that keywords with high in-group degrees in the early educational data mining cluster — such as 'student modelling' (2014-15), 'teachable agent' (2018-19), and 'machine learning' (2018-19) — develop into representative keywords of separate clusters, showing "the evolving interests and specializations of research around educational data mining."

"'educational data mining' represents a knowledge cluster during 2010-13, but is integrates into newly emerging clusters and is not the representative label of the new clusters."

Discussion¶

Related Claims¶

• The AIED keyword co-occurrence network has a hierarchical structure with a few widely studied hub keywords bridging diverse research topics — related
• AIED research centers on two sustained themes: intelligent tutoring systems (2010–19) and massive open online courses (since 2014) — related
• New AIED knowledge clusters — 'eye tracking' and 'deep learning' — emerge only in the most recent period (2018–19) — related
• Of the student models surveyed from 2013-2014 AIED, EDM and ITS conferences, 53% have low or mid portability restrictions. — related