View in EDS PDF Full Text

From Assistance to Autonomy: AI Integration in Structured Research-Based Learning for Higher Education

Saved in:
Bibliographic Details
Title: From Assistance to Autonomy: AI Integration in Structured Research-Based Learning for Higher Education
Language: English
Authors: Festiyed Festiy, Desnita Desnita, Ziola Natasya, Muhammad Aizri Fadillah, Fuja Novitra
Source: Electronic Journal of e-Learning. 2026 24(1):109-124.
Availability: Academic Conferences Limited. Curtis Farm, Kidmore End, Nr Reading, RG4 9AY, UK. Tel: +44-1189-724148; Fax: +44-1189-724691; e-mail: info@academic-conferences.org; Web site: https://academic-publishing.org/index.php/ejel/index
Peer Reviewed: Y
Page Count: 16
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Science Education, Research Skills, Student Research, Undergraduate Students, Physics, Technology Integration, Models
ISSN: 1479-4403
Abstract: Despite the growing interest in artificial intelligence (AI) for science education, little is known about its role within structured research-based learning (RBL) frameworks that balance technological assistance with developing independent research competencies. Existing studies often focus on AI as an isolated tool or a single-stage intervention, leaving a gap in understanding how AI can be systematically embedded across the research process without diminishing students' cognitive engagement. This study addresses that gap by implementing the newly developed IFTAR model, which organizes RBL into five sequential phases--Identification, Find Literature, Determine Methodology, Accommodate/Analyze/Interpret Data, and Report & Present--with AI selectively integrated into the literature search and data analysis stages. A quasi-experimental, non-equivalent control group PreTest-PostTest design was conducted with ninety undergraduate physics education students assigned to one control and two experimental groups. Cognitive outcomes were measured using a validated instrument and analyzed through classical ANCOVA, rank-based ANCOVA, and robust ANCOVA to account for assumption violations. Across all analytical approaches, both experimental groups significantly outperformed the control group, with no significant difference between the experimental conditions. These findings demonstrate that phase-specific AI integration within a transparent and scaffolded RBL framework can enhance cognitive performance while preserving methodological autonomy, offering a replicable model for purposeful AI use in STEM higher education.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1497276
Database: ERIC
FullText Links:
  – Type: pdflink
    Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwG3gE2D8be2sHVzrC4NrnojAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDG73-Fauyw_VX-BeqwIBEICBm1Hj0oK-T7sSa4AnTsJCneXtABWPpx5Q-0bG-VpR9GJ9mH99hT2ifWh9Xqpf7hAeBUwmx5bk-ZbifqZ6Nd4fqTXunUecvju0dYmTeHFCjRgqsQoxlBEFu-n8sFPYqkjRTpmAsRgkYrM53mt37AeWmisfmx_TNTM0WMGlKZx8lbeE1QOKdxQ3oaJdi6bSPqweU6QUDx8pwX5iHhCa
Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1497276
    Name: ERIC Full Text
    Category: fullText
    Text: Full Text from ERIC
Header DbId: eric
DbLabel: ERIC
An: EJ1497276
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: From Assistance to Autonomy: AI Integration in Structured Research-Based Learning for Higher Education
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Festiyed+Festiy%22">Festiyed Festiy</searchLink><br /><searchLink fieldCode="AR" term="%22Desnita+Desnita%22">Desnita Desnita</searchLink><br /><searchLink fieldCode="AR" term="%22Ziola+Natasya%22">Ziola Natasya</searchLink><br /><searchLink fieldCode="AR" term="%22Muhammad+Aizri+Fadillah%22">Muhammad Aizri Fadillah</searchLink><br /><searchLink fieldCode="AR" term="%22Fuja+Novitra%22">Fuja Novitra</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Electronic+Journal+of+e-Learning%22"><i>Electronic Journal of e-Learning</i></searchLink>. 2026 24(1):109-124.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Academic Conferences Limited. Curtis Farm, Kidmore End, Nr Reading, RG4 9AY, UK. Tel: +44-1189-724148; Fax: +44-1189-724691; e-mail: info@academic-conferences.org; Web site: https://academic-publishing.org/index.php/ejel/index
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 16
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2026
– 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="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Science+Education%22">Science Education</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Skills%22">Research Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Research%22">Student Research</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Physics%22">Physics</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Integration%22">Technology Integration</searchLink><br /><searchLink fieldCode="DE" term="%22Models%22">Models</searchLink>
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1479-4403
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Despite the growing interest in artificial intelligence (AI) for science education, little is known about its role within structured research-based learning (RBL) frameworks that balance technological assistance with developing independent research competencies. Existing studies often focus on AI as an isolated tool or a single-stage intervention, leaving a gap in understanding how AI can be systematically embedded across the research process without diminishing students' cognitive engagement. This study addresses that gap by implementing the newly developed IFTAR model, which organizes RBL into five sequential phases--Identification, Find Literature, Determine Methodology, Accommodate/Analyze/Interpret Data, and Report & Present--with AI selectively integrated into the literature search and data analysis stages. A quasi-experimental, non-equivalent control group PreTest-PostTest design was conducted with ninety undergraduate physics education students assigned to one control and two experimental groups. Cognitive outcomes were measured using a validated instrument and analyzed through classical ANCOVA, rank-based ANCOVA, and robust ANCOVA to account for assumption violations. Across all analytical approaches, both experimental groups significantly outperformed the control group, with no significant difference between the experimental conditions. These findings demonstrate that phase-specific AI integration within a transparent and scaffolded RBL framework can enhance cognitive performance while preserving methodological autonomy, offering a replicable model for purposeful AI use in STEM higher education.
– 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: EJ1497276
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1497276
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 109
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Science Education
        Type: general
      – SubjectFull: Research Skills
        Type: general
      – SubjectFull: Student Research
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Physics
        Type: general
      – SubjectFull: Technology Integration
        Type: general
      – SubjectFull: Models
        Type: general
    Titles:
      – TitleFull: From Assistance to Autonomy: AI Integration in Structured Research-Based Learning for Higher Education
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Festiyed Festiy
      – PersonEntity:
          Name:
            NameFull: Desnita Desnita
      – PersonEntity:
          Name:
            NameFull: Ziola Natasya
      – PersonEntity:
          Name:
            NameFull: Muhammad Aizri Fadillah
      – PersonEntity:
          Name:
            NameFull: Fuja Novitra
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 1479-4403
          Numbering:
            – Type: volume
              Value: 24
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Electronic Journal of e-Learning
              Type: main
ResultId 1