View in EDS

The Effect of an Intelligent Tutor on Performance on Specific Posttest Problems

Saved in:
Bibliographic Details
Title: The Effect of an Intelligent Tutor on Performance on Specific Posttest Problems
Language: English
Authors: Sales, Adam, Prihar, Ethan, Heffernan, Neil, Pane, John F.
Source: International Educational Data Mining Society. 2021.
Availability: International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: https://educationaldatamining.org/conferences/
Peer Reviewed: Y
Page Count: 10
Publication Date: 2021
Document Type: Speeches/Meeting Papers
Reports - Research
Education Level: Elementary Secondary Education
Descriptors: Intelligent Tutoring Systems, Academic Achievement, Educational Technology, Algebra, Item Response Theory, Hierarchical Linear Modeling, Program Effectiveness, Pretests Posttests, Achievement Tests, Elementary Secondary Education, Standardized Tests
Assessment and Survey Identifiers: TerraNova Multiple Assessments
Abstract: This paper drills deeper into the documented effects of the Cognitive Tutor Algebra I and ASSISTments intelligent tutoring systems by estimating their effects on specific problems. We start by describing a multilevel Rasch-type model that facilitates testing for differences in the effects between problems and precise problem-specific effect estimation without the need for multiple comparisons corrections. We find that the effects of both intelligent tutors vary between problems-- the effects are positive for some, negative for others, and undeterminable for the rest. Next we explore hypotheses explaining why effects might be larger for some problems than for others. In the case of ASSISTments, there is no evidence that problems that are more closely related to students' work in the tutor displayed larger treatment effects. [For the full proceedings, see ED615472.]
Abstractor: As Provided
Entry Date: 2021
Accession Number: ED615618
Database: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=ED615618
    Name: ERIC Full Text
    Category: fullText
    Text: Full Text from ERIC
Header DbId: eric
DbLabel: ERIC
An: ED615618
AccessLevel: 3
PubType: Conference
PubTypeId: conference
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The Effect of an Intelligent Tutor on Performance on Specific Posttest Problems
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Sales%2C+Adam%22">Sales, Adam</searchLink><br /><searchLink fieldCode="AR" term="%22Prihar%2C+Ethan%22">Prihar, Ethan</searchLink><br /><searchLink fieldCode="AR" term="%22Heffernan%2C+Neil%22">Heffernan, Neil</searchLink><br /><searchLink fieldCode="AR" term="%22Pane%2C+John+F%2E%22">Pane, John F.</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22International+Educational+Data+Mining+Society%22"><i>International Educational Data Mining Society</i></searchLink>. 2021.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: https://educationaldatamining.org/conferences/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 10
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2021
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Speeches/Meeting Papers<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Intelligent+Tutoring+Systems%22">Intelligent Tutoring Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Algebra%22">Algebra</searchLink><br /><searchLink fieldCode="DE" term="%22Item+Response+Theory%22">Item Response Theory</searchLink><br /><searchLink fieldCode="DE" term="%22Hierarchical+Linear+Modeling%22">Hierarchical Linear Modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Effectiveness%22">Program Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Pretests+Posttests%22">Pretests Posttests</searchLink><br /><searchLink fieldCode="DE" term="%22Achievement+Tests%22">Achievement Tests</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink><br /><searchLink fieldCode="DE" term="%22Standardized+Tests%22">Standardized Tests</searchLink>
– Name: SubjectThesaurus
  Label: Assessment and Survey Identifiers
  Group: Su
  Data: <searchLink fieldCode="SU" term="%22TerraNova+Multiple+Assessments%22">TerraNova Multiple Assessments</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper drills deeper into the documented effects of the Cognitive Tutor Algebra I and ASSISTments intelligent tutoring systems by estimating their effects on specific problems. We start by describing a multilevel Rasch-type model that facilitates testing for differences in the effects between problems and precise problem-specific effect estimation without the need for multiple comparisons corrections. We find that the effects of both intelligent tutors vary between problems-- the effects are positive for some, negative for others, and undeterminable for the rest. Next we explore hypotheses explaining why effects might be larger for some problems than for others. In the case of ASSISTments, there is no evidence that problems that are more closely related to students' work in the tutor displayed larger treatment effects. [For the full proceedings, see ED615472.]
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2021
– Name: AN
  Label: Accession Number
  Group: ID
  Data: ED615618
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=ED615618
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
    Subjects:
      – SubjectFull: Intelligent Tutoring Systems
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Educational Technology
        Type: general
      – SubjectFull: Algebra
        Type: general
      – SubjectFull: Item Response Theory
        Type: general
      – SubjectFull: Hierarchical Linear Modeling
        Type: general
      – SubjectFull: Program Effectiveness
        Type: general
      – SubjectFull: Pretests Posttests
        Type: general
      – SubjectFull: Achievement Tests
        Type: general
      – SubjectFull: Elementary Secondary Education
        Type: general
      – SubjectFull: Standardized Tests
        Type: general
      – SubjectFull: TerraNova Multiple Assessments
        Type: general
    Titles:
      – TitleFull: The Effect of an Intelligent Tutor on Performance on Specific Posttest Problems
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Sales, Adam
      – PersonEntity:
          Name:
            NameFull: Prihar, Ethan
      – PersonEntity:
          Name:
            NameFull: Heffernan, Neil
      – PersonEntity:
          Name:
            NameFull: Pane, John F.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2021
          Titles:
            – TitleFull: International Educational Data Mining Society
              Type: main
ResultId 1