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Amplifying Student and Administrator Perspectives on Equity and Bias in Learning Analytics: Alone Together in Higher Education

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Title: Amplifying Student and Administrator Perspectives on Equity and Bias in Learning Analytics: Alone Together in Higher Education
Language: English
Authors: Heiser, Rebecca E. (ORCID 0000-0002-1188-0459), Stritto, Mary Ellen Dello (ORCID 0000-0002-2046-2849), Brown, Allen S. (ORCID 0000-0002-7241-2288), Croft, Benjamin (ORCID 0000-0002-2823-4816)
Source: Journal of Learning Analytics. 2023 10(1):8-23.
Availability: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
Peer Reviewed: Y
Page Count: 16
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Student Attitudes, Administrator Attitudes, Equal Education, Bias, Higher Education, Inclusion, Stakeholders, Learning Analytics, Information Literacy, Professional Development, College Students, Diversity
ISSN: 1929-7750
Abstract: When higher education institutions (HEIs) have the potential to collect large amounts of learner data, it is important to consider the spectrum of stakeholders involved with and impacted by the use of learning analytics. This qualitative research study aims to understand the degree of concern with issues of bias and equity in the uses of learner data as perceived by students, diversity and inclusion leaders, and senior administrative leaders in HEIs. An interview study was designed to investigate stakeholder voices that generate, collect, and utilize learning analytics from eight HEIs in the United States. A phased inductive coding analysis revealed similarities and differences in the three stakeholder groups regarding concerns about bias and equity in the uses of learner data. The study findings suggest that stakeholders have varying degrees of data literacy, thus creating conditions of inequality and bias in learning data. By centring the values of these critical stakeholder groups and acknowledging that intersections and hierarchies of power are critical to authentic inclusion, this study provides additional insight into proactive measures that institutions could take to improve equity, transparency, and accountability in their responsible learning analytics efforts.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1387172
Database: ERIC
FullText Text:
  Availability: 0
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  Data: Amplifying Student and Administrator Perspectives on Equity and Bias in Learning Analytics: Alone Together in Higher Education
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  Data: <searchLink fieldCode="AR" term="%22Heiser%2C+Rebecca+E%2E%22">Heiser, Rebecca E.</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1188-0459">0000-0002-1188-0459</externalLink>)<br /><searchLink fieldCode="AR" term="%22Stritto%2C+Mary+Ellen+Dello%22">Stritto, Mary Ellen Dello</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2046-2849">0000-0002-2046-2849</externalLink>)<br /><searchLink fieldCode="AR" term="%22Brown%2C+Allen+S%2E%22">Brown, Allen S.</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-7241-2288">0000-0002-7241-2288</externalLink>)<br /><searchLink fieldCode="AR" term="%22Croft%2C+Benjamin%22">Croft, Benjamin</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2823-4816">0000-0002-2823-4816</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Learning+Analytics%22"><i>Journal of Learning Analytics</i></searchLink>. 2023 10(1):8-23.
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  Data: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
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  Data: <searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Administrator+Attitudes%22">Administrator Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Equal+Education%22">Equal Education</searchLink><br /><searchLink fieldCode="DE" term="%22Bias%22">Bias</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Inclusion%22">Inclusion</searchLink><br /><searchLink fieldCode="DE" term="%22Stakeholders%22">Stakeholders</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Analytics%22">Learning Analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Literacy%22">Information Literacy</searchLink><br /><searchLink fieldCode="DE" term="%22Professional+Development%22">Professional Development</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Diversity%22">Diversity</searchLink>
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  Data: 1929-7750
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  Data: When higher education institutions (HEIs) have the potential to collect large amounts of learner data, it is important to consider the spectrum of stakeholders involved with and impacted by the use of learning analytics. This qualitative research study aims to understand the degree of concern with issues of bias and equity in the uses of learner data as perceived by students, diversity and inclusion leaders, and senior administrative leaders in HEIs. An interview study was designed to investigate stakeholder voices that generate, collect, and utilize learning analytics from eight HEIs in the United States. A phased inductive coding analysis revealed similarities and differences in the three stakeholder groups regarding concerns about bias and equity in the uses of learner data. The study findings suggest that stakeholders have varying degrees of data literacy, thus creating conditions of inequality and bias in learning data. By centring the values of these critical stakeholder groups and acknowledging that intersections and hierarchies of power are critical to authentic inclusion, this study provides additional insight into proactive measures that institutions could take to improve equity, transparency, and accountability in their responsible learning analytics efforts.
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    Languages:
      – Text: English
    PhysicalDescription:
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        PageCount: 16
        StartPage: 8
    Subjects:
      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Administrator Attitudes
        Type: general
      – SubjectFull: Equal Education
        Type: general
      – SubjectFull: Bias
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      – SubjectFull: Higher Education
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      – SubjectFull: Inclusion
        Type: general
      – SubjectFull: Stakeholders
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      – SubjectFull: Learning Analytics
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      – SubjectFull: Information Literacy
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      – SubjectFull: Professional Development
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      – SubjectFull: College Students
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      – SubjectFull: Diversity
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      – TitleFull: Amplifying Student and Administrator Perspectives on Equity and Bias in Learning Analytics: Alone Together in Higher Education
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