Two decades of artificial intelligence in education: Contributors, collaborations, research Topics, challenges, and future directions

Xieling CHEN; Di ZOU; Haoran XIE; Gary CHENG; Caixia LIU

Two decades of artificial intelligence in education: Contributors, collaborations, research Topics, challenges, and future directions

Xieling CHEN, Di ZOU^*, Haoran XIE, Gary CHENG, Caixia LIU

^*Corresponding author for this work

Department of Computing and Decision Sciences

Research output: Journal Publications › Journal Article (refereed) › peer-review

220 Downloads (Pure)

Abstract

With the increasing use of Artificial Intelligence (AI) technologies in education, the number of published studies in the field has increased. However, no large-scale reviews have been conducted to comprehensively investigate the various aspects of this field. Based on 4,519 publications from 2000 to 2019, we attempt to fill this gap and identify trends and topics related to AI applications in education (AIEd) using topic-based bibliometrics. Results of the review reveal an increasing interest in using AI for educational purposes from the academic community. The main research topics include intelligent tutoring systems for special education; natural language processing for language education; educational robots for AI education; educational data mining for performance prediction; discourse analysis in computer-supported collaborative learning; neural networks for teaching evaluation; affective computing for learner emotion detection; and recommender systems for personalized learning. We also discuss the challenges and future directions of AIEd.

Original language	English
Pages (from-to)	28-47
Number of pages	20
Journal	Educational Technology and Society
Volume	25
Issue number	1
Publication status	Published - Jan 2022

Bibliographical note

An abstract entitled “A Bibliometric Study on Artificial Intelligence in Education for Two Decades” from this paper was presented at the International Conference on Education and Artificial Intelligence 2020, The Education University of Hong Kong, 9-11 November 2020, Hong Kong. Haoran Xie’s work in this research is supported by the Direct Grant (DR21A5) and the Faculty Research Fund (DB21A4) at Lingnan University, Hong Kong. Gary Cheng’s work is supported by General Research Fund (No. 18601118) of Research Grants Council of Hong Kong SAR, China, and One-off Special Fund from Central and Faculty Fund in Support of Research from 2019/20 to 2021/22 (MIT02/19-20) of The Education University of Hong Kong.

Keywords

Artificial intelligence in education
Structural topic modeling
Bibliometric analysis
Research topics
Research evolution

Access to Document

25_1_03Final published version, 2.2 MBLicence: CC BY-NC-ND

Cite this

@article{dcad561115474ea48573fc00c60cff8d,

title = "Two decades of artificial intelligence in education: Contributors, collaborations, research Topics, challenges, and future directions",

abstract = "With the increasing use of Artificial Intelligence (AI) technologies in education, the number of published studies in the field has increased. However, no large-scale reviews have been conducted to comprehensively investigate the various aspects of this field. Based on 4,519 publications from 2000 to 2019, we attempt to fill this gap and identify trends and topics related to AI applications in education (AIEd) using topic-based bibliometrics. Results of the review reveal an increasing interest in using AI for educational purposes from the academic community. The main research topics include intelligent tutoring systems for special education; natural language processing for language education; educational robots for AI education; educational data mining for performance prediction; discourse analysis in computer-supported collaborative learning; neural networks for teaching evaluation; affective computing for learner emotion detection; and recommender systems for personalized learning. We also discuss the challenges and future directions of AIEd.",

keywords = "Artificial intelligence in education, Structural topic modeling, Bibliometric analysis, Research topics, Research evolution",

author = "Xieling CHEN and Di ZOU and Haoran XIE and Gary CHENG and Caixia LIU",

note = "An abstract entitled “A Bibliometric Study on Artificial Intelligence in Education for Two Decades” from this paper was presented at the International Conference on Education and Artificial Intelligence 2020, The Education University of Hong Kong, 9-11 November 2020, Hong Kong. Haoran Xie{\textquoteright}s work in this research is supported by the Direct Grant (DR21A5) and the Faculty Research Fund (DB21A4) at Lingnan University, Hong Kong. Gary Cheng{\textquoteright}s work is supported by General Research Fund (No. 18601118) of Research Grants Council of Hong Kong SAR, China, and One-off Special Fund from Central and Faculty Fund in Support of Research from 2019/20 to 2021/22 (MIT02/19-20) of The Education University of Hong Kong.",

year = "2022",

month = jan,

language = "English",

volume = "25",

pages = "28--47",

journal = "Educational Technology and Society",

issn = "1176-3647",

publisher = "National Taiwan Normal University",

number = "1",

}

TY - JOUR

T1 - Two decades of artificial intelligence in education: Contributors, collaborations, research Topics, challenges, and future directions

AU - CHEN, Xieling

AU - ZOU, Di

AU - XIE, Haoran

AU - CHENG, Gary

AU - LIU, Caixia

N1 - An abstract entitled “A Bibliometric Study on Artificial Intelligence in Education for Two Decades” from this paper was presented at the International Conference on Education and Artificial Intelligence 2020, The Education University of Hong Kong, 9-11 November 2020, Hong Kong. Haoran Xie’s work in this research is supported by the Direct Grant (DR21A5) and the Faculty Research Fund (DB21A4) at Lingnan University, Hong Kong. Gary Cheng’s work is supported by General Research Fund (No. 18601118) of Research Grants Council of Hong Kong SAR, China, and One-off Special Fund from Central and Faculty Fund in Support of Research from 2019/20 to 2021/22 (MIT02/19-20) of The Education University of Hong Kong.

PY - 2022/1

Y1 - 2022/1

N2 - With the increasing use of Artificial Intelligence (AI) technologies in education, the number of published studies in the field has increased. However, no large-scale reviews have been conducted to comprehensively investigate the various aspects of this field. Based on 4,519 publications from 2000 to 2019, we attempt to fill this gap and identify trends and topics related to AI applications in education (AIEd) using topic-based bibliometrics. Results of the review reveal an increasing interest in using AI for educational purposes from the academic community. The main research topics include intelligent tutoring systems for special education; natural language processing for language education; educational robots for AI education; educational data mining for performance prediction; discourse analysis in computer-supported collaborative learning; neural networks for teaching evaluation; affective computing for learner emotion detection; and recommender systems for personalized learning. We also discuss the challenges and future directions of AIEd.

AB - With the increasing use of Artificial Intelligence (AI) technologies in education, the number of published studies in the field has increased. However, no large-scale reviews have been conducted to comprehensively investigate the various aspects of this field. Based on 4,519 publications from 2000 to 2019, we attempt to fill this gap and identify trends and topics related to AI applications in education (AIEd) using topic-based bibliometrics. Results of the review reveal an increasing interest in using AI for educational purposes from the academic community. The main research topics include intelligent tutoring systems for special education; natural language processing for language education; educational robots for AI education; educational data mining for performance prediction; discourse analysis in computer-supported collaborative learning; neural networks for teaching evaluation; affective computing for learner emotion detection; and recommender systems for personalized learning. We also discuss the challenges and future directions of AIEd.

KW - Artificial intelligence in education

KW - Structural topic modeling

KW - Bibliometric analysis

KW - Research topics

KW - Research evolution

UR - https://www.j-ets.net/collection/published-issues/25_1

M3 - Journal Article (refereed)

VL - 25

SP - 28

EP - 47

JO - Educational Technology and Society

JF - Educational Technology and Society

SN - 1176-3647

IS - 1

ER -

Two decades of artificial intelligence in education: Contributors, collaborations, research Topics, challenges, and future directions

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Developing Schemas with Word Emotion Distribution for Emotion Classification

Preliminary Study on Artificial Intelligence Techniques for Learning Emotions from Short Text

A bibliometric study on artificial intelligence in education for two decades

Cite this

Two decades of artificial intelligence in education: Contributors, collaborations, research Topics, challenges, and future directions

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Projects

Developing Schemas with Word Emotion Distribution for Emotion Classification

Preliminary Study on Artificial Intelligence Techniques for Learning Emotions from Short Text

Research output

A bibliometric study on artificial intelligence in education for two decades

Cite this