Applications of Explainable AI (XAI) in Education

Qianhui Liu; Juan D. Pinto; Luc Paquette

doi:10.1007/978-3-031-64487-0_5

Applications of Explainable AI (XAI) in Education

Qianhui Liu, Juan D. Pinto, Luc Paquette

Curriculum and Instruction

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

As one of the emerging methods for increasing trust in Artificial Intelligence (AI) systems, explainable AI promotes the use of methods that produce transparent explanations and reasons for decisions made by AI. In this chapter, we present an overview of applications of explainable AI in education with examples of empirical studies.

Original language	English (US)
Title of host publication	Trust and Inclusion in AI-Mediated Education
Subtitle of host publication	Where Human Learning Meets Learning Machines
Editors	Dora Kourkoulou, Anastasia Olga Tzirides, Bill Cope, Mary Kalantzis
Publisher	Springer
Pages	93-109
Number of pages	17
ISBN (Electronic)	9783031644870
ISBN (Print)	9783031644863, 9783031644894
DOIs	https://doi.org/10.1007/978-3-031-64487-0_5
State	Published - Sep 28 2024

Publication series

Name	Postdigital Science and Education
Volume	Part F3835
ISSN (Print)	2662-5326
ISSN (Electronic)	2662-5334

Keywords

AI interpretability
Explainable AI (XAI)
Learning analytics
Pedagogical implications
Technological transparency

ASJC Scopus subject areas

Arts and Humanities (miscellaneous)
Philosophy
Social Sciences (miscellaneous)
Education

Online availability

10.1007/978-3-031-64487-0_5

Library availability

Discover UIUC Full Text

Cite this

Liu, Q., Pinto, J. D., & Paquette, L. (2024). Applications of Explainable AI (XAI) in Education. In D. Kourkoulou, A. O. Tzirides, B. Cope, & M. Kalantzis (Eds.), Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines (pp. 93-109). (Postdigital Science and Education; Vol. Part F3835). Springer. https://doi.org/10.1007/978-3-031-64487-0_5

Applications of Explainable AI (XAI) in Education. / Liu, Qianhui; Pinto, Juan D.; Paquette, Luc.
Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines. ed. / Dora Kourkoulou; Anastasia Olga Tzirides; Bill Cope; Mary Kalantzis. Springer, 2024. p. 93-109 (Postdigital Science and Education; Vol. Part F3835).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

@inbook{075e915f36a54350aaf7f66864b6aedf,

title = "Applications of Explainable AI (XAI) in Education",

abstract = "As one of the emerging methods for increasing trust in Artificial Intelligence (AI) systems, explainable AI promotes the use of methods that produce transparent explanations and reasons for decisions made by AI. In this chapter, we present an overview of applications of explainable AI in education with examples of empirical studies.",

keywords = "AI interpretability, Explainable AI (XAI), Learning analytics, Pedagogical implications, Technological transparency",

author = "Qianhui Liu and Pinto, {Juan D.} and Luc Paquette",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.",

year = "2024",

month = sep,

day = "28",

doi = "10.1007/978-3-031-64487-0_5",

language = "English (US)",

isbn = "9783031644863",

series = "Postdigital Science and Education",

publisher = "Springer",

pages = "93--109",

editor = "Dora Kourkoulou and Tzirides, {Anastasia Olga} and Bill Cope and Mary Kalantzis",

booktitle = "Trust and Inclusion in AI-Mediated Education",

address = "Germany",

}

TY - CHAP

T1 - Applications of Explainable AI (XAI) in Education

AU - Liu, Qianhui

AU - Pinto, Juan D.

AU - Paquette, Luc

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024/9/28

Y1 - 2024/9/28

N2 - As one of the emerging methods for increasing trust in Artificial Intelligence (AI) systems, explainable AI promotes the use of methods that produce transparent explanations and reasons for decisions made by AI. In this chapter, we present an overview of applications of explainable AI in education with examples of empirical studies.

AB - As one of the emerging methods for increasing trust in Artificial Intelligence (AI) systems, explainable AI promotes the use of methods that produce transparent explanations and reasons for decisions made by AI. In this chapter, we present an overview of applications of explainable AI in education with examples of empirical studies.

KW - AI interpretability

KW - Explainable AI (XAI)

KW - Learning analytics

KW - Pedagogical implications

KW - Technological transparency

UR - http://www.scopus.com/inward/record.url?scp=85208540556&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85208540556&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-64487-0_5

DO - 10.1007/978-3-031-64487-0_5

M3 - Chapter

AN - SCOPUS:85208540556

SN - 9783031644863

SN - 9783031644894

T3 - Postdigital Science and Education

SP - 93

EP - 109

BT - Trust and Inclusion in AI-Mediated Education

A2 - Kourkoulou, Dora

A2 - Tzirides, Anastasia Olga

A2 - Cope, Bill

A2 - Kalantzis, Mary

PB - Springer

ER -

Applications of Explainable AI (XAI) in Education

Abstract

Publication series

Keywords

ASJC Scopus subject areas

Online availability

Library availability

Related links

Fingerprint

Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines

Cite this