Assessing Disciplinary Teachers'Pedagogical and Content Knowledge in Computational Thinking.
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| Title: | Assessing Disciplinary Teachers'Pedagogical and Content Knowledge in Computational Thinking. |
|---|---|
| Authors: | Espinal, Alejandro1 (AUTHOR) espinal@uninorte.edu.co, Vieira, Camilo1 (AUTHOR), Magana, Alejandra J.2 (AUTHOR) |
| Source: | TechTrends: Linking Research & Practice to Improve Learning. Sep2025, Vol. 69 Issue 5, p883-899. 17p. |
| Subject Terms: | *Pedagogical content knowledge, *Lesson planning, *Evaluation methodology, *Educators, *Interdisciplinary education, *Teacher training, *Problem solving, *Teacher education |
| Abstract: | Promoting computational thinking (CT) integration in curricula requires well-prepared teachers with pedagogical content knowledge (PCK). Existing research often uses pretest/posttest instruments or teacher reflections to assess outcomes of professional development programs (PDP). Still, this approach is limited and can be misaligned with other learning outcomes. This study characterizes teachers'PCK through a PDP, focusing on how they enact it in designing lesson plans (n = 21) in a professional development program for K- 12 teachers. We adapted the Use-Modify-Create progression commonly used to support student learning in computer programming, and used it for teachers to learn about designing CT learning activities. Participants submitted a lesson plan integrating CT into their courses. Our results suggest that while teachers'lesson plans included both CT and disciplinary outcomes, their assessment strategies were not always well aligned. Participants used various pedagogical approaches and tools to integrate CT into disciplinary classrooms. This paper contributes to the body of work in PDP for CT by proposing an approach to assess teacher PCK beyond pretest/posttest designs and highlighting areas requiring support when integrating CT into disciplinary courses. [ABSTRACT FROM AUTHOR] |
| Copyright of TechTrends: Linking Research & Practice to Improve Learning is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 188902468 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Assessing Disciplinary Teachers'Pedagogical and Content Knowledge in Computational Thinking. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Espinal%2C+Alejandro%22">Espinal, Alejandro</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> espinal@uninorte.edu.co</i><br /><searchLink fieldCode="AR" term="%22Vieira%2C+Camilo%22">Vieira, Camilo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Magana%2C+Alejandra+J%2E%22">Magana, Alejandra J.</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22TechTrends%3A+Linking+Research+%26+Practice+to+Improve+Learning%22">TechTrends: Linking Research & Practice to Improve Learning</searchLink>. Sep2025, Vol. 69 Issue 5, p883-899. 17p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Pedagogical+content+knowledge%22">Pedagogical content knowledge</searchLink><br />*<searchLink fieldCode="DE" term="%22Lesson+planning%22">Lesson planning</searchLink><br />*<searchLink fieldCode="DE" term="%22Evaluation+methodology%22">Evaluation methodology</searchLink><br />*<searchLink fieldCode="DE" term="%22Educators%22">Educators</searchLink><br />*<searchLink fieldCode="DE" term="%22Interdisciplinary+education%22">Interdisciplinary education</searchLink><br />*<searchLink fieldCode="DE" term="%22Teacher+training%22">Teacher training</searchLink><br />*<searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink><br />*<searchLink fieldCode="DE" term="%22Teacher+education%22">Teacher education</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Promoting computational thinking (CT) integration in curricula requires well-prepared teachers with pedagogical content knowledge (PCK). Existing research often uses pretest/posttest instruments or teacher reflections to assess outcomes of professional development programs (PDP). Still, this approach is limited and can be misaligned with other learning outcomes. This study characterizes teachers'PCK through a PDP, focusing on how they enact it in designing lesson plans (n = 21) in a professional development program for K- 12 teachers. We adapted the Use-Modify-Create progression commonly used to support student learning in computer programming, and used it for teachers to learn about designing CT learning activities. Participants submitted a lesson plan integrating CT into their courses. Our results suggest that while teachers'lesson plans included both CT and disciplinary outcomes, their assessment strategies were not always well aligned. Participants used various pedagogical approaches and tools to integrate CT into disciplinary classrooms. This paper contributes to the body of work in PDP for CT by proposing an approach to assess teacher PCK beyond pretest/posttest designs and highlighting areas requiring support when integrating CT into disciplinary courses. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of TechTrends: Linking Research & Practice to Improve Learning is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=188902468 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11528-025-01072-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 883 Subjects: – SubjectFull: Pedagogical content knowledge Type: general – SubjectFull: Lesson planning Type: general – SubjectFull: Evaluation methodology Type: general – SubjectFull: Educators Type: general – SubjectFull: Interdisciplinary education Type: general – SubjectFull: Teacher training Type: general – SubjectFull: Problem solving Type: general – SubjectFull: Teacher education Type: general Titles: – TitleFull: Assessing Disciplinary Teachers'Pedagogical and Content Knowledge in Computational Thinking. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Espinal, Alejandro – PersonEntity: Name: NameFull: Vieira, Camilo – PersonEntity: Name: NameFull: Magana, Alejandra J. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 87563894 Numbering: – Type: volume Value: 69 – Type: issue Value: 5 Titles: – TitleFull: TechTrends: Linking Research & Practice to Improve Learning Type: main |
| ResultId | 1 |
