Academic Journal
Cognitive Learning Strategies in an Introductory Computer Programming Course
| Title: | Cognitive Learning Strategies in an Introductory Computer Programming Course |
|---|---|
| Language: | English |
| Authors: | Mahatanankoon, Pruthikrai, Wolf, James |
| Source: | Information Systems Education Journal. Jun 2021 19(3):11-20. |
| Availability: | Information Systems and Computing Academic Professionals. Box 488, Wrightsville Beach, NC 28480. e-mail: publisher@isedj.org; Web site: http://isedj.org |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Publication Date: | 2021 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Cognitive Processes, Learning Strategies, Introductory Courses, Computer Science Education, Programming, Programming Languages, Factor Analysis, Undergraduate Students, Persistence, Self Efficacy |
| ISSN: | 1545-679X |
| Abstract: | Learning a computer programming language is typically one of the basic requirements of being an information technology (IT) major. While other studies previously investigate computer programming self-efficacy and grit, their relationships between "shallow" and "deep" learning (Miller et al., 1996) have not been thoroughly examined in the context of computer programming. Exploratory factor analyses using data collected from undergraduate information technology students, who just completed their first programming class shows distinct shallow and deep learning in computer programming. While shallow learning supports previous research, deep learning has three sub-scale activities: practice by examples, analytical thinking, and diagramming. The results also reveal that computer programming grit and self-efficacy have low to moderate correlations with shallow and deep learning, requiring further examination. Preliminary regression analyses also find that shallow learning positively influences computer programing grit and self-efficacy. Shallow learning strategies may be more widely employed during the initial stages of computer programming, while deep learning strategies may be more prevalent in higher-level computer programming courses. IT educators can examine this shift in strategies by observing students as they progress from introductory to advanced computer programming courses. |
| Abstractor: | As Provided |
| Entry Date: | 2021 |
| Accession Number: | EJ1301236 |
| Database: | ERIC |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1301236 Name: ERIC Full Text Category: fullText Text: Full Text from ERIC |
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| Items | – Name: Title Label: Title Group: Ti Data: Cognitive Learning Strategies in an Introductory Computer Programming Course – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mahatanankoon%2C+Pruthikrai%22">Mahatanankoon, Pruthikrai</searchLink><br /><searchLink fieldCode="AR" term="%22Wolf%2C+James%22">Wolf, James</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Information+Systems+Education+Journal%22"><i>Information Systems Education Journal</i></searchLink>. Jun 2021 19(3):11-20. – Name: Avail Label: Availability Group: Avail Data: Information Systems and Computing Academic Professionals. Box 488, Wrightsville Beach, NC 28480. e-mail: publisher@isedj.org; Web site: http://isedj.org – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 10 – Name: DatePubCY Label: Publication Date Group: Date Data: 2021 – 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="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Strategies%22">Learning Strategies</searchLink><br /><searchLink fieldCode="DE" term="%22Introductory+Courses%22">Introductory Courses</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+Education%22">Computer Science Education</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="%22Factor+Analysis%22">Factor Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Persistence%22">Persistence</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink> – Name: ISSN Label: ISSN Group: ISSN Data: 1545-679X – Name: Abstract Label: Abstract Group: Ab Data: Learning a computer programming language is typically one of the basic requirements of being an information technology (IT) major. While other studies previously investigate computer programming self-efficacy and grit, their relationships between "shallow" and "deep" learning (Miller et al., 1996) have not been thoroughly examined in the context of computer programming. Exploratory factor analyses using data collected from undergraduate information technology students, who just completed their first programming class shows distinct shallow and deep learning in computer programming. While shallow learning supports previous research, deep learning has three sub-scale activities: practice by examples, analytical thinking, and diagramming. The results also reveal that computer programming grit and self-efficacy have low to moderate correlations with shallow and deep learning, requiring further examination. Preliminary regression analyses also find that shallow learning positively influences computer programing grit and self-efficacy. Shallow learning strategies may be more widely employed during the initial stages of computer programming, while deep learning strategies may be more prevalent in higher-level computer programming courses. IT educators can examine this shift in strategies by observing students as they progress from introductory to advanced computer programming courses. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2021 – Name: AN Label: Accession Number Group: ID Data: EJ1301236 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1301236 |
| RecordInfo | BibRecord: BibEntity: Languages: – Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 11 Subjects: – SubjectFull: Cognitive Processes Type: general – SubjectFull: Learning Strategies Type: general – SubjectFull: Introductory Courses Type: general – SubjectFull: Computer Science Education Type: general – SubjectFull: Programming Type: general – SubjectFull: Programming Languages Type: general – SubjectFull: Factor Analysis Type: general – SubjectFull: Undergraduate Students Type: general – SubjectFull: Persistence Type: general – SubjectFull: Self Efficacy Type: general Titles: – TitleFull: Cognitive Learning Strategies in an Introductory Computer Programming Course Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mahatanankoon, Pruthikrai – PersonEntity: Name: NameFull: Wolf, James IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Type: published Y: 2021 Identifiers: – Type: issn-electronic Value: 1545-679X Numbering: – Type: volume Value: 19 – Type: issue Value: 3 Titles: – TitleFull: Information Systems Education Journal Type: main |
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