View in EDS

Predicting Job Creation Likelihood among Corps Members in Nigeria Using Linear and Machine Learning Models

Saved in:
Bibliographic Details
Title: Predicting Job Creation Likelihood among Corps Members in Nigeria Using Linear and Machine Learning Models
Language: English
Authors: Valentine Joseph Owan, Peter Owogoga Aduma, Michael Shittu Moses, Michael Ekpenyong Asuquo
Source: Discover Education. 2026 5.
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: 23
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Foreign Countries, Prediction, Job Development, Youth Employment, Youth Programs, Job Training, Attitudes, Qualifications, Marital Status, Age, Sex, Entrepreneurship
Geographic Terms: Nigeria
DOI: 10.1007/s44217-025-01097-y
ISSN: 2731-5525
Abstract: Youth unemployment continues to pose a major challenge in Nigeria despite sustained government initiatives promoting entrepreneurship and empowerment. The National Youth Service Corps (NYSC) established the Skill Acquisition and Entrepreneurship Development (SAED) programme to provide graduates with practical skills that can stimulate job creation. Earlier studies have often examined entrepreneurial intentions rather than actual job creation after participation in SAED or the joint influence of demographic attributes and graduate attitudes on such outcomes. This study examined how age, gender, marital status, educational qualification, and graduate attitude relate to job creation among Nigerian corps members. A survey research design was used to gather data from more than nineteen thousand NYSC members who served between 2012 and 2021. Data were obtained electronically through social media platforms and analysed with descriptive statistics and logistic regression, while a machine learning model was used to assess the strength of predictive accuracy. The results showed that graduate attitude, educational qualification, and marital status were significant predictors of job creation, whereas age and gender were not. The model performed effectively, confirming the reliability of the findings. This study contributes to current understanding of graduate employment outcomes in Nigeria and provides useful evidence for improving entrepreneurship education and policy measures aimed at addressing youth unemployment.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506520
Database: ERIC
FullText Text:
  Availability: 0
Header DbId: eric
DbLabel: ERIC
An: EJ1506520
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Predicting Job Creation Likelihood among Corps Members in Nigeria Using Linear and Machine Learning Models
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Valentine+Joseph+Owan%22">Valentine Joseph Owan</searchLink><br /><searchLink fieldCode="AR" term="%22Peter+Owogoga+Aduma%22">Peter Owogoga Aduma</searchLink><br /><searchLink fieldCode="AR" term="%22Michael+Shittu+Moses%22">Michael Shittu Moses</searchLink><br /><searchLink fieldCode="AR" term="%22Michael+Ekpenyong+Asuquo%22">Michael Ekpenyong Asuquo</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Discover+Education%22"><i>Discover Education</i></searchLink>. 2026 5.
– Name: Avail
  Label: Availability
  Group: Avail
  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
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 23
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2026
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction%22">Prediction</searchLink><br /><searchLink fieldCode="DE" term="%22Job+Development%22">Job Development</searchLink><br /><searchLink fieldCode="DE" term="%22Youth+Employment%22">Youth Employment</searchLink><br /><searchLink fieldCode="DE" term="%22Youth+Programs%22">Youth Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Job+Training%22">Job Training</searchLink><br /><searchLink fieldCode="DE" term="%22Attitudes%22">Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Qualifications%22">Qualifications</searchLink><br /><searchLink fieldCode="DE" term="%22Marital+Status%22">Marital Status</searchLink><br /><searchLink fieldCode="DE" term="%22Age%22">Age</searchLink><br /><searchLink fieldCode="DE" term="%22Sex%22">Sex</searchLink><br /><searchLink fieldCode="DE" term="%22Entrepreneurship%22">Entrepreneurship</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Nigeria%22">Nigeria</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s44217-025-01097-y
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 2731-5525
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Youth unemployment continues to pose a major challenge in Nigeria despite sustained government initiatives promoting entrepreneurship and empowerment. The National Youth Service Corps (NYSC) established the Skill Acquisition and Entrepreneurship Development (SAED) programme to provide graduates with practical skills that can stimulate job creation. Earlier studies have often examined entrepreneurial intentions rather than actual job creation after participation in SAED or the joint influence of demographic attributes and graduate attitudes on such outcomes. This study examined how age, gender, marital status, educational qualification, and graduate attitude relate to job creation among Nigerian corps members. A survey research design was used to gather data from more than nineteen thousand NYSC members who served between 2012 and 2021. Data were obtained electronically through social media platforms and analysed with descriptive statistics and logistic regression, while a machine learning model was used to assess the strength of predictive accuracy. The results showed that graduate attitude, educational qualification, and marital status were significant predictors of job creation, whereas age and gender were not. The model performed effectively, confirming the reliability of the findings. This study contributes to current understanding of graduate employment outcomes in Nigeria and provides useful evidence for improving entrepreneurship education and policy measures aimed at addressing youth unemployment.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2026
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1506520
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1506520
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s44217-025-01097-y
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 23
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Prediction
        Type: general
      – SubjectFull: Job Development
        Type: general
      – SubjectFull: Youth Employment
        Type: general
      – SubjectFull: Youth Programs
        Type: general
      – SubjectFull: Job Training
        Type: general
      – SubjectFull: Attitudes
        Type: general
      – SubjectFull: Qualifications
        Type: general
      – SubjectFull: Marital Status
        Type: general
      – SubjectFull: Age
        Type: general
      – SubjectFull: Sex
        Type: general
      – SubjectFull: Entrepreneurship
        Type: general
      – SubjectFull: Nigeria
        Type: general
    Titles:
      – TitleFull: Predicting Job Creation Likelihood among Corps Members in Nigeria Using Linear and Machine Learning Models
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Valentine Joseph Owan
      – PersonEntity:
          Name:
            NameFull: Peter Owogoga Aduma
      – PersonEntity:
          Name:
            NameFull: Michael Shittu Moses
      – PersonEntity:
          Name:
            NameFull: Michael Ekpenyong Asuquo
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 2731-5525
          Numbering:
            – Type: volume
              Value: 5
          Titles:
            – TitleFull: Discover Education
              Type: main
ResultId 1