Academic Journal
Blended Pedagogy for Computer Programming Language
| Τίτλος: | Blended Pedagogy for Computer Programming Language |
|---|---|
| Γλώσσα: | English |
| Συγγραφείς: | Ling Zhang (ORCID |
| Πηγή: | Pedagogical Research. 2024 9(3). |
| Διαθεσιμότητα: | Modestum. 1 Windrush Road, DE65 5LB, Hilton, Derbyshire, UK. Tel: +44-783-473-4063; e-mail: info@modestum.org; Web site: https://www.pedagogicalresearch.com/ |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Ημερομηνία έκδοσης: | 2024 |
| Τύπος εγγράφου: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | COVID-19, Pandemics, Blended Learning, Programming Languages, Programming, Teaching Methods, In Person Learning, Electronic Learning, Student Projects, Learner Engagement, Program Effectiveness, Student Satisfaction, Student Centered Learning, College Students, Foreign Countries |
| Γεωγραφικοί όροι: | China |
| ISSN: | 2468-1989 2468-4929 |
| Περίληψη: | In the face of the challenges posed by the COVID-19 pandemic, the hybrid teaching model has garnered significant attention for its combination of the depth of traditional education with the convenience of distance learning. Focusing on the domain of computer programming language instruction, this study innovatively designs a hybrid teaching strategy aimed at fully exploiting the flexibility of its teaching design and the variety of pedagogical approaches. The strategy integrates face-to-face teaching with online autonomous learning, incorporating project-based teaching methodologies and immediate feedback mechanisms to facilitate active student engagement and deep learning. Through a year-long practice in a C++ programming course, encompassing 68 students, the study empirically validates the effectiveness of the hybrid teaching approach. It not only demonstrates remarkable educational outcomes, enhancing the quality of programming instruction and student satisfaction with their learning experience, but also employs Bayesian analysis to delve into the relationship between learning trajectories and students' sense of self-efficacy. By focusing on key indicators during the learning process, such as the timeliness and quality of online learning, laboratory work, and project assignments, the study then utilizes Bayesian models to directly assess the impact of these learning behavior metrics on students' perceived self-efficacy. The findings reveal that students with outstanding academic achievements exhibit higher levels of self-efficacy, confirming that academic performance can reasonably reflect teaching effectiveness and provide a quantifiable basis for assessing individual learning progress. Consequently, this research not only contributes a novel strategy to computer programming education practice but also offers a valuable reference for the application of hybrid teaching models in other disciplines. Furthermore, it promotes in-depth contemplation on post-pandemic innovations in teaching modes and issues of educational equity, laying a solid foundation for constructing a more adaptive and inclusive future education system. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| Αριθμός Καταχώρησης: | EJ1445019 |
| Βάση Δεδομένων: | ERIC |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1445019 Name: ERIC Full Text Category: fullText Text: Full Text from ERIC |
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| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Blended Pedagogy for Computer Programming Language – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ling+Zhang%22">Ling Zhang</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1619-3444">0000-0003-1619-3444</externalLink>) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Pedagogical+Research%22"><i>Pedagogical Research</i></searchLink>. 2024 9(3). – Name: Avail Label: Availability Group: Avail Data: Modestum. 1 Windrush Road, DE65 5LB, Hilton, Derbyshire, UK. Tel: +44-783-473-4063; e-mail: info@modestum.org; Web site: https://www.pedagogicalresearch.com/ – 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: 2024 – 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="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Pandemics%22">Pandemics</searchLink><br /><searchLink fieldCode="DE" term="%22Blended+Learning%22">Blended Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Programming+Languages%22">Programming Languages</searchLink><br /><searchLink fieldCode="DE" term="%22Programming%22">Programming</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22In+Person+Learning%22">In Person Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Projects%22">Student Projects</searchLink><br /><searchLink fieldCode="DE" term="%22Learner+Engagement%22">Learner Engagement</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Effectiveness%22">Program Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Satisfaction%22">Student Satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Centered+Learning%22">Student Centered Learning</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: ISSN Label: ISSN Group: ISSN Data: 2468-1989<br />2468-4929 – Name: Abstract Label: Abstract Group: Ab Data: In the face of the challenges posed by the COVID-19 pandemic, the hybrid teaching model has garnered significant attention for its combination of the depth of traditional education with the convenience of distance learning. Focusing on the domain of computer programming language instruction, this study innovatively designs a hybrid teaching strategy aimed at fully exploiting the flexibility of its teaching design and the variety of pedagogical approaches. The strategy integrates face-to-face teaching with online autonomous learning, incorporating project-based teaching methodologies and immediate feedback mechanisms to facilitate active student engagement and deep learning. Through a year-long practice in a C++ programming course, encompassing 68 students, the study empirically validates the effectiveness of the hybrid teaching approach. It not only demonstrates remarkable educational outcomes, enhancing the quality of programming instruction and student satisfaction with their learning experience, but also employs Bayesian analysis to delve into the relationship between learning trajectories and students' sense of self-efficacy. By focusing on key indicators during the learning process, such as the timeliness and quality of online learning, laboratory work, and project assignments, the study then utilizes Bayesian models to directly assess the impact of these learning behavior metrics on students' perceived self-efficacy. The findings reveal that students with outstanding academic achievements exhibit higher levels of self-efficacy, confirming that academic performance can reasonably reflect teaching effectiveness and provide a quantifiable basis for assessing individual learning progress. Consequently, this research not only contributes a novel strategy to computer programming education practice but also offers a valuable reference for the application of hybrid teaching models in other disciplines. Furthermore, it promotes in-depth contemplation on post-pandemic innovations in teaching modes and issues of educational equity, laying a solid foundation for constructing a more adaptive and inclusive future education system. – 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: EJ1445019 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1445019 |
| RecordInfo | BibRecord: BibEntity: Languages: – Text: English PhysicalDescription: Pagination: PageCount: 10 Subjects: – SubjectFull: COVID-19 Type: general – SubjectFull: Pandemics Type: general – SubjectFull: Blended Learning Type: general – SubjectFull: Programming Languages Type: general – SubjectFull: Programming Type: general – SubjectFull: Teaching Methods Type: general – SubjectFull: In Person Learning Type: general – SubjectFull: Electronic Learning Type: general – SubjectFull: Student Projects Type: general – SubjectFull: Learner Engagement Type: general – SubjectFull: Program Effectiveness Type: general – SubjectFull: Student Satisfaction Type: general – SubjectFull: Student Centered Learning Type: general – SubjectFull: College Students Type: general – SubjectFull: Foreign Countries Type: general – SubjectFull: China Type: general Titles: – TitleFull: Blended Pedagogy for Computer Programming Language Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ling Zhang IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 2468-1989 – Type: issn-electronic Value: 2468-4929 Numbering: – Type: volume Value: 9 – Type: issue Value: 3 Titles: – TitleFull: Pedagogical Research Type: main |
| ResultId | 1 |