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Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics: An Issue Brief

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Title: Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics: An Issue Brief
Language: English
Authors: Bienkowski, Marie, Feng, Mingyu, Means, Barbara, Department of Education (ED), Office of Educational Technology, SRI International
Source: Office of Educational Technology, US Department of Education. 2012.
Availability: Office of Educational Technology, US Department of Education. Available from: ED Pubs. P.O. Box 1398, Jessup, MD 20794-1398. Tel: 202-401-1444; Fax: 202-401-3941; Web site: http://www2.ed.gov/about/offices/list/os/technology/index.html
Peer Reviewed: N
Page Count: 77
Publication Date: 2012
Contract Number: ED04CO0040
Intended Audience: Policymakers; Administrators
Document Type: Reports - Evaluative
Education Level: Early Childhood Education
Elementary Education
Kindergarten
Primary Education
Elementary Secondary Education
Descriptors: Teaching Methods, Learning Processes, Data Analysis, Barriers, Outcomes of Education, Productivity, Kindergarten, Elementary Secondary Education, Educational Policy, Educational Administration, Academic Achievement, Decision Making, Online Systems, Web Sites, Privacy, Ethics, Data Use, Computer Software, Integrated Learning Systems, Student Behavior, Trend Analysis, Individualized Instruction, Profiles, Learning Activities
Abstract: As more of commerce, entertainment, communication, and learning are occurring over the Web, the amount of data online activities generate is skyrocketing. Commercial entities have led the way in developing techniques for harvesting insights from this mass of data for use in identifying likely consumers of their products, in refining their products to better fit consumer needs, and in tailoring their marketing and user experiences to the preferences of the individual. More recently, researchers and developers of online learning systems have begun to explore analogous techniques for gaining insights from learners' activities online. This issue brief describes data analytics and data mining in the commercial world and how similar techniques (learner analytics and educational data mining) are starting to be applied in education. The brief examines the challenges being encountered and the potential of such efforts for improving student outcomes and the productivity of K--12 education systems. The goal is to help education policymakers and administrators understand how data mining and analytics work and how they can be applied within online learning systems to support education-related decision making.
Abstractor: ERIC
Entry Date: 2021
Accession Number: ED611199
Database: ERIC
FullText Text:
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  Data: Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics: An Issue Brief
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  Data: Office of Educational Technology, US Department of Education. Available from: ED Pubs. P.O. Box 1398, Jessup, MD 20794-1398. Tel: 202-401-1444; Fax: 202-401-3941; Web site: http://www2.ed.gov/about/offices/list/os/technology/index.html
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  Data: 77
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  Data: Policymakers; Administrators
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  Data: <searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Processes%22">Learning Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Analysis%22">Data Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Barriers%22">Barriers</searchLink><br /><searchLink fieldCode="DE" term="%22Outcomes+of+Education%22">Outcomes of Education</searchLink><br /><searchLink fieldCode="DE" term="%22Productivity%22">Productivity</searchLink><br /><searchLink fieldCode="DE" term="%22Kindergarten%22">Kindergarten</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Policy%22">Educational Policy</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Administration%22">Educational Administration</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+Making%22">Decision Making</searchLink><br /><searchLink fieldCode="DE" term="%22Online+Systems%22">Online Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Web+Sites%22">Web Sites</searchLink><br /><searchLink fieldCode="DE" term="%22Privacy%22">Privacy</searchLink><br /><searchLink fieldCode="DE" term="%22Ethics%22">Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Use%22">Data Use</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Software%22">Computer Software</searchLink><br /><searchLink fieldCode="DE" term="%22Integrated+Learning+Systems%22">Integrated Learning Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Behavior%22">Student Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Trend+Analysis%22">Trend Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Individualized+Instruction%22">Individualized Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Profiles%22">Profiles</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Activities%22">Learning Activities</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: As more of commerce, entertainment, communication, and learning are occurring over the Web, the amount of data online activities generate is skyrocketing. Commercial entities have led the way in developing techniques for harvesting insights from this mass of data for use in identifying likely consumers of their products, in refining their products to better fit consumer needs, and in tailoring their marketing and user experiences to the preferences of the individual. More recently, researchers and developers of online learning systems have begun to explore analogous techniques for gaining insights from learners' activities online. This issue brief describes data analytics and data mining in the commercial world and how similar techniques (learner analytics and educational data mining) are starting to be applied in education. The brief examines the challenges being encountered and the potential of such efforts for improving student outcomes and the productivity of K--12 education systems. The goal is to help education policymakers and administrators understand how data mining and analytics work and how they can be applied within online learning systems to support education-related decision making.
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  Data: 2021
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  Label: Accession Number
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  Data: ED611199
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=ED611199
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      – Text: English
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      Pagination:
        PageCount: 77
    Subjects:
      – SubjectFull: Teaching Methods
        Type: general
      – SubjectFull: Learning Processes
        Type: general
      – SubjectFull: Data Analysis
        Type: general
      – SubjectFull: Barriers
        Type: general
      – SubjectFull: Outcomes of Education
        Type: general
      – SubjectFull: Productivity
        Type: general
      – SubjectFull: Kindergarten
        Type: general
      – SubjectFull: Elementary Secondary Education
        Type: general
      – SubjectFull: Educational Policy
        Type: general
      – SubjectFull: Educational Administration
        Type: general
      – SubjectFull: Academic Achievement
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      – SubjectFull: Decision Making
        Type: general
      – SubjectFull: Online Systems
        Type: general
      – SubjectFull: Web Sites
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      – SubjectFull: Privacy
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      – SubjectFull: Ethics
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      – SubjectFull: Data Use
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      – SubjectFull: Computer Software
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      – SubjectFull: Integrated Learning Systems
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      – SubjectFull: Student Behavior
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      – SubjectFull: Trend Analysis
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      – SubjectFull: Individualized Instruction
        Type: general
      – SubjectFull: Profiles
        Type: general
      – SubjectFull: Learning Activities
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      – TitleFull: Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics: An Issue Brief
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