In EDS ansehen

The Impact of GenAI-Enabled Coding Hints on Students' Programming Performance and Cognitive Load in an SRL-Based Python Course

Gespeichert in:
Bibliographische Detailangaben
Titel: The Impact of GenAI-Enabled Coding Hints on Students' Programming Performance and Cognitive Load in an SRL-Based Python Course
Sprache: English
Autoren: Anna Y. Q. Huang, Cheng-Yan Lin, Sheng-Yi Su (ORCID 0009-0000-5849-8620), Stephen J. H. Yang
Quelle: British Journal of Educational Technology. 2025 56(5):1942-1972.
Verfügbarkeit: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 31
Publikationsdatum: 2025
Publikationsart: Journal Articles
Reports - Research
Descriptors: Artificial Intelligence, Technology Uses in Education, Coding, Programming, Programming Languages, Cognitive Processes, Difficulty Level, Independent Study, Computer Science Education, Prior Learning, Scaffolding (Teaching Technique), Flow Charts, Novices, Scores, Transfer of Training, Goal Orientation, Metacognition
DOI: 10.1111/bjet.13589
ISSN: 0007-1013
1467-8535
Abstract: Programming education often imposes a high cognitive burden on novice programmers, requiring them to master syntax, logic, and problem-solving while simultaneously managing debugging tasks. Prior knowledge is a critical factor influencing programming learning performance. A lack of foundational knowledge limits students' self-regulated learning (SRL) abilities, resulting in a performance gap between students with high and low levels of prior knowledge. To address this problem, this study developed CodeFlow Assistant (CFA), a specifically developed generative artificial intelligence (GenAI) tool that provides four levels of scaffolding guidance (flowcharts, cloze coding, basic coding solutions, and advanced coding solutions) to support novice programmers in mastering skills ranging from foundational understanding to advanced application. Through a controlled experiment comparing SRL-based, teaching assistant (TA)-assisted programming (SRLP-TA) and SRL-based, CFA-assisted programming (SRLP-CFA), this study evaluated the effect of CFA on coding performance, cognitive loads, and SRL abilities among novice programming students. The results indicated that compared with the SRLP-TA group, the SRLP-CFA group achieved statistically significantly higher coding scores but showed comparable improvements in understanding programming concepts. Moreover, CFA reduced intrinsic and extraneous cognitive loads while enhancing germane load, fostering deeper knowledge integration and engagement. These findings highlight the role of CFA in enhancing coding performance, particularly in translating conceptual understanding into practice. This tool also statistically significantly improved SRL abilities, such as intrinsic goal orientation, task value, and metacognitive self-regulation.
Abstractor: As Provided
Entry Date: 2025
Dokumentencode: EJ1480021
Datenbank: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://resolver.ebscohost.com/openurl?sid=EBSCO:eric&genre=article&issn=00071013&ISBN=&volume=56&issue=5&date=20250901&spage=1942&pages=1942-1972&title=British Journal of Educational Technology&atitle=The%20Impact%20of%20GenAI-Enabled%20Coding%20Hints%20on%20Students%27%20Programming%20Performance%20and%20Cognitive%20Load%20in%20an%20SRL-Based%20Python%20Course&aulast=Anna%20Y.%20Q.%20Huang&id=DOI:10.1111/bjet.13589
    Name: Full Text Finder
    Category: fullText
    Text: Full Text Finder
    Icon: https://imageserver.ebscohost.com/branding/images/FTF.gif
    MouseOverText: Full Text Finder
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Huang%20AYQ
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: eric
DbLabel: ERIC
An: EJ1480021
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The Impact of GenAI-Enabled Coding Hints on Students' Programming Performance and Cognitive Load in an SRL-Based Python Course
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Anna+Y%2E+Q%2E+Huang%22">Anna Y. Q. Huang</searchLink><br /><searchLink fieldCode="AR" term="%22Cheng-Yan+Lin%22">Cheng-Yan Lin</searchLink><br /><searchLink fieldCode="AR" term="%22Sheng-Yi+Su%22">Sheng-Yi Su</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0000-5849-8620">0009-0000-5849-8620</externalLink>)<br /><searchLink fieldCode="AR" term="%22Stephen+J%2E+H%2E+Yang%22">Stephen J. H. Yang</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22British+Journal+of+Educational+Technology%22"><i>British Journal of Educational Technology</i></searchLink>. 2025 56(5):1942-1972.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 31
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– 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="%22Coding%22">Coding</searchLink><br /><searchLink fieldCode="DE" term="%22Programming%22">Programming</searchLink><br /><searchLink fieldCode="DE" term="%22Programming+Languages%22">Programming Languages</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Difficulty+Level%22">Difficulty Level</searchLink><br /><searchLink fieldCode="DE" term="%22Independent+Study%22">Independent Study</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+Education%22">Computer Science Education</searchLink><br /><searchLink fieldCode="DE" term="%22Prior+Learning%22">Prior Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Scaffolding+%28Teaching+Technique%29%22">Scaffolding (Teaching Technique)</searchLink><br /><searchLink fieldCode="DE" term="%22Flow+Charts%22">Flow Charts</searchLink><br /><searchLink fieldCode="DE" term="%22Novices%22">Novices</searchLink><br /><searchLink fieldCode="DE" term="%22Scores%22">Scores</searchLink><br /><searchLink fieldCode="DE" term="%22Transfer+of+Training%22">Transfer of Training</searchLink><br /><searchLink fieldCode="DE" term="%22Goal+Orientation%22">Goal Orientation</searchLink><br /><searchLink fieldCode="DE" term="%22Metacognition%22">Metacognition</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/bjet.13589
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0007-1013<br />1467-8535
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Programming education often imposes a high cognitive burden on novice programmers, requiring them to master syntax, logic, and problem-solving while simultaneously managing debugging tasks. Prior knowledge is a critical factor influencing programming learning performance. A lack of foundational knowledge limits students' self-regulated learning (SRL) abilities, resulting in a performance gap between students with high and low levels of prior knowledge. To address this problem, this study developed CodeFlow Assistant (CFA), a specifically developed generative artificial intelligence (GenAI) tool that provides four levels of scaffolding guidance (flowcharts, cloze coding, basic coding solutions, and advanced coding solutions) to support novice programmers in mastering skills ranging from foundational understanding to advanced application. Through a controlled experiment comparing SRL-based, teaching assistant (TA)-assisted programming (SRLP-TA) and SRL-based, CFA-assisted programming (SRLP-CFA), this study evaluated the effect of CFA on coding performance, cognitive loads, and SRL abilities among novice programming students. The results indicated that compared with the SRLP-TA group, the SRLP-CFA group achieved statistically significantly higher coding scores but showed comparable improvements in understanding programming concepts. Moreover, CFA reduced intrinsic and extraneous cognitive loads while enhancing germane load, fostering deeper knowledge integration and engagement. These findings highlight the role of CFA in enhancing coding performance, particularly in translating conceptual understanding into practice. This tool also statistically significantly improved SRL abilities, such as intrinsic goal orientation, task value, and metacognitive self-regulation.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1480021
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1480021
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/bjet.13589
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 31
        StartPage: 1942
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Coding
        Type: general
      – SubjectFull: Programming
        Type: general
      – SubjectFull: Programming Languages
        Type: general
      – SubjectFull: Cognitive Processes
        Type: general
      – SubjectFull: Difficulty Level
        Type: general
      – SubjectFull: Independent Study
        Type: general
      – SubjectFull: Computer Science Education
        Type: general
      – SubjectFull: Prior Learning
        Type: general
      – SubjectFull: Scaffolding (Teaching Technique)
        Type: general
      – SubjectFull: Flow Charts
        Type: general
      – SubjectFull: Novices
        Type: general
      – SubjectFull: Scores
        Type: general
      – SubjectFull: Transfer of Training
        Type: general
      – SubjectFull: Goal Orientation
        Type: general
      – SubjectFull: Metacognition
        Type: general
    Titles:
      – TitleFull: The Impact of GenAI-Enabled Coding Hints on Students' Programming Performance and Cognitive Load in an SRL-Based Python Course
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Anna Y. Q. Huang
      – PersonEntity:
          Name:
            NameFull: Cheng-Yan Lin
      – PersonEntity:
          Name:
            NameFull: Sheng-Yi Su
      – PersonEntity:
          Name:
            NameFull: Stephen J. H. Yang
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 0007-1013
            – Type: issn-electronic
              Value: 1467-8535
          Numbering:
            – Type: volume
              Value: 56
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: British Journal of Educational Technology
              Type: main
ResultId 1