View in EDS

Evaluation of the Effect of Learning Disabilities and Accommodations on the Prediction of the Stability of Academic Behaviour of Undergraduate Engineering Students Using Decision Trees

Saved in:
Bibliographic Details
Title: Evaluation of the Effect of Learning Disabilities and Accommodations on the Prediction of the Stability of Academic Behaviour of Undergraduate Engineering Students Using Decision Trees
Language: English
Authors: Singer, Gonen, Golan, Maya, Rabin, Neta, Kleper, Dvir
Source: European Journal of Engineering Education. 2020 45(4):614-630.
Availability: Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 17
Publication Date: 2020
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Learning Disabilities, Academic Accommodations (Disabilities), Undergraduate Students, Engineering Education, Early Intervention, Decision Making, Prediction, Academic Achievement, Student Behavior, Evaluation Methods, Classification, Data Analysis
DOI: 10.1080/03043797.2019.1677560
ISSN: 0304-3797
Abstract: The purpose of this study is to evaluate how learning disabilities (LDs), in combination with accommodations, affect the performance of a decision-tree to predict the stability of academic behaviour of undergraduate engineering students. Additionally, this study presents several examples to illustrate how a college could use the resultant model to choose the appropriate accommodation to give a student with a learning disability, from among a set of possible accommodations. The findings show that: (1) The models yield superior performance in predicting the stability category for a given student when the LD and accommodation factors are included; (2) Different types of accommodation action have different effects on the stability of academic behaviour, depending on the student pattern. Such a model could be useful for engineering faculties, as it would allow them to predict the stability of academic behaviour and to provide early intervention for students who are likely to need additional support.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1260455
Database: ERIC
FullText Text:
  Availability: 0
Header DbId: eric
DbLabel: ERIC
An: EJ1260455
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Evaluation of the Effect of Learning Disabilities and Accommodations on the Prediction of the Stability of Academic Behaviour of Undergraduate Engineering Students Using Decision Trees
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Singer%2C+Gonen%22">Singer, Gonen</searchLink><br /><searchLink fieldCode="AR" term="%22Golan%2C+Maya%22">Golan, Maya</searchLink><br /><searchLink fieldCode="AR" term="%22Rabin%2C+Neta%22">Rabin, Neta</searchLink><br /><searchLink fieldCode="AR" term="%22Kleper%2C+Dvir%22">Kleper, Dvir</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22European+Journal+of+Engineering+Education%22"><i>European Journal of Engineering Education</i></searchLink>. 2020 45(4):614-630.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 17
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2020
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<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="%22Learning+Disabilities%22">Learning Disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Accommodations+%28Disabilities%29%22">Academic Accommodations (Disabilities)</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering+Education%22">Engineering Education</searchLink><br /><searchLink fieldCode="DE" term="%22Early+Intervention%22">Early Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+Making%22">Decision Making</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction%22">Prediction</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Behavior%22">Student Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+Methods%22">Evaluation Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Classification%22">Classification</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Analysis%22">Data Analysis</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/03043797.2019.1677560
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0304-3797
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The purpose of this study is to evaluate how learning disabilities (LDs), in combination with accommodations, affect the performance of a decision-tree to predict the stability of academic behaviour of undergraduate engineering students. Additionally, this study presents several examples to illustrate how a college could use the resultant model to choose the appropriate accommodation to give a student with a learning disability, from among a set of possible accommodations. The findings show that: (1) The models yield superior performance in predicting the stability category for a given student when the LD and accommodation factors are included; (2) Different types of accommodation action have different effects on the stability of academic behaviour, depending on the student pattern. Such a model could be useful for engineering faculties, as it would allow them to predict the stability of academic behaviour and to provide early intervention for students who are likely to need additional support.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2020
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1260455
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1260455
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/03043797.2019.1677560
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 614
    Subjects:
      – SubjectFull: Learning Disabilities
        Type: general
      – SubjectFull: Academic Accommodations (Disabilities)
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Engineering Education
        Type: general
      – SubjectFull: Early Intervention
        Type: general
      – SubjectFull: Decision Making
        Type: general
      – SubjectFull: Prediction
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Student Behavior
        Type: general
      – SubjectFull: Evaluation Methods
        Type: general
      – SubjectFull: Classification
        Type: general
      – SubjectFull: Data Analysis
        Type: general
    Titles:
      – TitleFull: Evaluation of the Effect of Learning Disabilities and Accommodations on the Prediction of the Stability of Academic Behaviour of Undergraduate Engineering Students Using Decision Trees
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Singer, Gonen
      – PersonEntity:
          Name:
            NameFull: Golan, Maya
      – PersonEntity:
          Name:
            NameFull: Rabin, Neta
      – PersonEntity:
          Name:
            NameFull: Kleper, Dvir
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2020
          Identifiers:
            – Type: issn-print
              Value: 0304-3797
          Numbering:
            – Type: volume
              Value: 45
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: European Journal of Engineering Education
              Type: main
ResultId 1