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A Systematic Review of Literature Reviews on Artificial Intelligence in Education (AIED): A Roadmap to a Future Research Agenda

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Title: A Systematic Review of Literature Reviews on Artificial Intelligence in Education (AIED): A Roadmap to a Future Research Agenda
Language: English
Authors: Muhammad Yasir Mustafa (ORCID 0000-0002-0693-8126), Ahmed Tlili (ORCID 0000-0003-1449-7751), Georgios Lampropoulos (ORCID 0000-0002-5719-2125), Ronghuai Huang (ORCID 0000-0003-4651-5248), Petar Jandric (ORCID 0000-0002-6464-4142), Jialu Zhao, Soheil Salha (ORCID 0000-0003-2791-9925), Lin Xu, Santosh Panda, Kinshuk (ORCID 0000-0003-3923-9003), Sonsoles López-Pernas (ORCID 0000-0002-9621-1392), Mohammed Saqr (ORCID 0000-0001-5881-3109)
Source: Smart Learning Environments. 2024 11.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 33
Publication Date: 2024
Document Type: Journal Articles
Information Analyses
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Foreign Countries, Higher Education, Special Education, Teachers, Students, Administrators, Stakeholders, Educational Trends, Trend Analysis
Geographic Terms: China, United States
DOI: 10.1186/s40561-024-00350-5
ISSN: 2196-7091
Abstract: Despite the increased adoption of Artificial Intelligence in Education (AIED), several concerns are still associated with it. This has motivated researchers to conduct (systematic) reviews aiming at synthesizing the AIED findings in the literature. However, these AIED reviews are diversified in terms of focus, stakeholders, educational level and region, and so on. This has made the understanding of the overall landscape of AIED challenging. To address this research gap, this study proceeds one step forward by systematically meta-synthesizing the AIED literature reviews. Specifically, 143 literature reviews were included and analyzed according to the technology-based learning model. It is worth noting that most of the AIED research has been from China and the U.S. Additionally, when discussing AIED, strong focus was on higher education, where less attention is paid to special education. The results also reveal that AI is used mostly to support teachers and students in education with less focus on other educational stakeholders (e.g. school leaders or administrators). The study provides a possible roadmap for future research agenda on AIED, facilitating the implementation of effective and safe AIED.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1452560
Database: ERIC
FullText Text:
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PubType: Academic Journal
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IllustrationInfo
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  Data: A Systematic Review of Literature Reviews on Artificial Intelligence in Education (AIED): A Roadmap to a Future Research Agenda
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Muhammad+Yasir+Mustafa%22">Muhammad Yasir Mustafa</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-0693-8126">0000-0002-0693-8126</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ahmed+Tlili%22">Ahmed Tlili</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-1449-7751">0000-0003-1449-7751</externalLink>)<br /><searchLink fieldCode="AR" term="%22Georgios+Lampropoulos%22">Georgios Lampropoulos</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5719-2125">0000-0002-5719-2125</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ronghuai+Huang%22">Ronghuai Huang</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4651-5248">0000-0003-4651-5248</externalLink>)<br /><searchLink fieldCode="AR" term="%22Petar+Jandric%22">Petar Jandric</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6464-4142">0000-0002-6464-4142</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jialu+Zhao%22">Jialu Zhao</searchLink><br /><searchLink fieldCode="AR" term="%22Soheil+Salha%22">Soheil Salha</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2791-9925">0000-0003-2791-9925</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lin+Xu%22">Lin Xu</searchLink><br /><searchLink fieldCode="AR" term="%22Santosh+Panda%22">Santosh Panda</searchLink><br /><searchLink fieldCode="AR" term="%22Kinshuk%22">Kinshuk</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3923-9003">0000-0003-3923-9003</externalLink>)<br /><searchLink fieldCode="AR" term="%22Sonsoles+López-Pernas%22">Sonsoles López-Pernas</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9621-1392">0000-0002-9621-1392</externalLink>)<br /><searchLink fieldCode="AR" term="%22Mohammed+Saqr%22">Mohammed Saqr</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5881-3109">0000-0001-5881-3109</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Smart+Learning+Environments%22"><i>Smart Learning Environments</i></searchLink>. 2024 11.
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  Label: Availability
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
– Name: PeerReviewed
  Label: Peer Reviewed
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 33
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Information Analyses<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Special+Education%22">Special Education</searchLink><br /><searchLink fieldCode="DE" term="%22Teachers%22">Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Students%22">Students</searchLink><br /><searchLink fieldCode="DE" term="%22Administrators%22">Administrators</searchLink><br /><searchLink fieldCode="DE" term="%22Stakeholders%22">Stakeholders</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Trends%22">Educational Trends</searchLink><br /><searchLink fieldCode="DE" term="%22Trend+Analysis%22">Trend Analysis</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink><br /><searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1186/s40561-024-00350-5
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 2196-7091
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Despite the increased adoption of Artificial Intelligence in Education (AIED), several concerns are still associated with it. This has motivated researchers to conduct (systematic) reviews aiming at synthesizing the AIED findings in the literature. However, these AIED reviews are diversified in terms of focus, stakeholders, educational level and region, and so on. This has made the understanding of the overall landscape of AIED challenging. To address this research gap, this study proceeds one step forward by systematically meta-synthesizing the AIED literature reviews. Specifically, 143 literature reviews were included and analyzed according to the technology-based learning model. It is worth noting that most of the AIED research has been from China and the U.S. Additionally, when discussing AIED, strong focus was on higher education, where less attention is paid to special education. The results also reveal that AI is used mostly to support teachers and students in education with less focus on other educational stakeholders (e.g. school leaders or administrators). The study provides a possible roadmap for future research agenda on AIED, facilitating the implementation of effective and safe AIED.
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  Label: Entry Date
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  Data: 2024
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  Data: EJ1452560
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1452560
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        Value: 10.1186/s40561-024-00350-5
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      – Text: English
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      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Foreign Countries
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