Academic Journal
View in EDS
Linked Full Text

Modeling Students' Algorithmic Thinking Growth Trajectories in Different Programming Environments: An Experimental Test of the Matthew and Compensatory Hypothesis

Bibliographic Details
Title: Modeling Students' Algorithmic Thinking Growth Trajectories in Different Programming Environments: An Experimental Test of the Matthew and Compensatory Hypothesis
Language: English
Authors: Abdullahi Yusuf (ORCID 0000-0003-2487-0564), Norah Md Noor (ORCID 0000-0003-0051-0230)
Source: Smart Learning Environments. 2024 11.
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: 33
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Students, Programming, Algorithms, Problem Solving, Logical Thinking, Learning Trajectories, Error Correction, Coding
DOI: 10.1186/s40561-024-00324-7
ISSN: 2196-7091
Abstract: In recent years, programming education has gained recognition at various educational levels due to its increasing importance. As the need for problem-solving skills becomes more vital, researchers have emphasized the significance of developing algorithmic thinking (AT) skills to help students in program development and error debugging. Despite the development of various text-based and block-based programming tools aimed at improving students' AT, emerging evidence in the literature indicates insufficient AT skills among students. This study was conducted to understand the growth trajectory of students' AT skills in different programming environments. The study utilized a multigroup experiment involving 240 programming students randomly assigned to three groups: a text-and-block-based group, a block-based-only group, and a text-based-only group. Students in the text-and-block-based group were exposed to Alice and Python; those in the block-based-only group were exposed to Alice; and those in the text-based-only group were exposed to Python. We found that participants' growth trajectory in AT skills is linear, with a significant growth rate. Although between-person variability exists across groups, we observed a compensatory effect in the text-and-block-based and block-based-only groups. Additionally, we found significant differences in AT skills across the groups, with no evidence of a gender effect. Our findings suggest that combining text-based and block-based programming environments can lead to improved and sustained intra-individual problem-solving skills, particularly in the field of programming.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1436332
Database: ERIC
FullText Links:
  – Type: other
    Url: https://resolver.ebsco.com:443/public/rma-ftfapi/ejs/direct?AccessToken=47AA972A0A98E1D789F6&Show=Object
Text:
  Availability: 0
CustomLinks:
  – Url: https://dx.doi.org/doi:10.1186/s40561-024-00324-7
    Name: EDS - Springer Nature Journals (s7799221)
    Category: fullText
    Text: View record at Springer
Header DbId: eric
DbLabel: ERIC
An: EJ1436332
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Modeling Students' Algorithmic Thinking Growth Trajectories in Different Programming Environments: An Experimental Test of the Matthew and Compensatory Hypothesis
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Abdullahi+Yusuf%22">Abdullahi Yusuf</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-2487-0564">0000-0003-2487-0564</externalLink>)<br /><searchLink fieldCode="AR" term="%22Norah+Md+Noor%22">Norah Md Noor</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-0051-0230">0000-0003-0051-0230</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Smart+Learning+Environments%22"><i>Smart Learning Environments</i></searchLink>. 2024 11.
– 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: 33
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Students%22">Students</searchLink><br /><searchLink fieldCode="DE" term="%22Programming%22">Programming</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+Solving%22">Problem Solving</searchLink><br /><searchLink fieldCode="DE" term="%22Logical+Thinking%22">Logical Thinking</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Trajectories%22">Learning Trajectories</searchLink><br /><searchLink fieldCode="DE" term="%22Error+Correction%22">Error Correction</searchLink><br /><searchLink fieldCode="DE" term="%22Coding%22">Coding</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1186/s40561-024-00324-7
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 2196-7091
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In recent years, programming education has gained recognition at various educational levels due to its increasing importance. As the need for problem-solving skills becomes more vital, researchers have emphasized the significance of developing algorithmic thinking (AT) skills to help students in program development and error debugging. Despite the development of various text-based and block-based programming tools aimed at improving students' AT, emerging evidence in the literature indicates insufficient AT skills among students. This study was conducted to understand the growth trajectory of students' AT skills in different programming environments. The study utilized a multigroup experiment involving 240 programming students randomly assigned to three groups: a text-and-block-based group, a block-based-only group, and a text-based-only group. Students in the text-and-block-based group were exposed to Alice and Python; those in the block-based-only group were exposed to Alice; and those in the text-based-only group were exposed to Python. We found that participants' growth trajectory in AT skills is linear, with a significant growth rate. Although between-person variability exists across groups, we observed a compensatory effect in the text-and-block-based and block-based-only groups. Additionally, we found significant differences in AT skills across the groups, with no evidence of a gender effect. Our findings suggest that combining text-based and block-based programming environments can lead to improved and sustained intra-individual problem-solving skills, particularly in the field of programming.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1436332
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1436332
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1186/s40561-024-00324-7
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 33
    Subjects:
      – SubjectFull: Students
        Type: general
      – SubjectFull: Programming
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Problem Solving
        Type: general
      – SubjectFull: Logical Thinking
        Type: general
      – SubjectFull: Learning Trajectories
        Type: general
      – SubjectFull: Error Correction
        Type: general
      – SubjectFull: Coding
        Type: general
    Titles:
      – TitleFull: Modeling Students' Algorithmic Thinking Growth Trajectories in Different Programming Environments: An Experimental Test of the Matthew and Compensatory Hypothesis
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Abdullahi Yusuf
      – PersonEntity:
          Name:
            NameFull: Norah Md Noor
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-electronic
              Value: 2196-7091
          Numbering:
            – Type: volume
              Value: 11
          Titles:
            – TitleFull: Smart Learning Environments
              Type: main
ResultId 1