Jurnal
SINTA 1
Science Learning in Answering Digital Competency Needs of Preservice Math and Science Teachers in the STEM Context
Jurnal Pendidikan IPA Indonesia
ISSN 2089-4392, 2339-1286
Published 2023-09-28
Publisher Program Studi Pendidikan IPA Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA)
Language eng
Abstract
These study purposes are to map the digital competency of pre-service math and science teachers and investigate how science learning can answer the challenge of digital competencies (DigComp) needs. This research used Rasch Model analysis to make knowledgeability mapping of the subject and analyzed using Wright map output by Winsteps 5.3.4. Data was gathered from a survey of 328 pre-service teachers of science majors, e.g., Biology, Chemistry, Geography, or Math, using the DigComp Framework-Based Questionnaire (DFBQ). The responses were based on respondents’ diverse demographic profiles (gender, region, living area, and field of study). The findings identify several differences in teacher training students’ knowledgeability of digital competencies that the Wright map in the Rasch model can map. Knowledgeability mapping is essential to determine which part of DigComp still needs to be strengthened with science education in the context of Science, Technology, Engineering, and Mathematics (STEM) implementation. The study yields two main conclusions: 1) The mapping study of pre-service math and science teachers’ knowledgeability in the DigComp framework shows Logit Value Person (0.31LVP1.11) and Logit Value Item (LVI 0.66 logits); (0 ≥ LVI ≥ 0.66) that are reflecting a middle to lower level of competency, and 2) Science learning has high potential to address this challenge through its learning strategy implementations. The findings can be recommendations for future research of knowledgeability mapping and policy development and discuss implications for digital competency framework practices.
Collaboration network of the authors
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Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/nju/index.php/jpii/oai,
first harvested 29 Okt 2026,
last seen 29 Okt 2026.
Original metadata (oai_dc)
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<dc:title xml:lang="en-US">Science Learning in Answering Digital Competency Needs of Preservice Math and Science Teachers in the STEM Context</dc:title>
<dc:creator>Hidayat, M. L.</dc:creator>
<dc:creator>Prayitno, H. J.</dc:creator>
<dc:creator>Anif, S.</dc:creator>
<dc:creator>Meccawy, M.</dc:creator>
<dc:creator>Khanzada, T. J.S.</dc:creator>
<dc:subject xml:lang="en-US">digital competency; preservice teachers; decision-making; Rasch analysis; mapping</dc:subject>
<dc:description xml:lang="en-US">These study purposes are to map the digital competency of pre-service math and science teachers and investigate how science learning can answer the challenge of digital competencies (DigComp) needs. This research used Rasch Model analysis to make knowledgeability mapping of the subject and analyzed using Wright map output by Winsteps 5.3.4. Data was gathered from a survey of 328 pre-service teachers of science majors, e.g., Biology, Chemistry, Geography, or Math, using the DigComp Framework-Based Questionnaire (DFBQ). The responses were based on respondents’ diverse demographic profiles (gender, region, living area, and field of study). The findings identify several differences in teacher training students’ knowledgeability of digital competencies that the Wright map in the Rasch model can map. Knowledgeability mapping is essential to determine which part of DigComp still needs to be strengthened with science education in the context of Science, Technology, Engineering, and Mathematics (STEM) implementation. The study yields two main conclusions: 1) The mapping study of pre-service math and science teachers’ knowledgeability in the DigComp framework shows Logit Value Person (0.31LVP1.11) and Logit Value Item (LVI 0.66 logits); (0 ≥ LVI ≥ 0.66) that are reflecting a middle to lower level of competency, and 2) Science learning has high potential to address this challenge through its learning strategy implementations. The findings can be recommendations for future research of knowledgeability mapping and policy development and discuss implications for digital competency framework practices. </dc:description>
<dc:publisher xml:lang="en-US">Program Studi Pendidikan IPA Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA)</dc:publisher>
<dc:contributor xml:lang="en-US">HIT Grant, Universitas Muhammadiyah Surakarta</dc:contributor>
<dc:date>2023-09-28</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
<dc:format>application/pdf</dc:format>
<dc:identifier>https://journal.unnes.ac.id/nju/jpii/article/view/43960</dc:identifier>
<dc:identifier>10.15294/jpii.v12i3.43960</dc:identifier>
<dc:source xml:lang="en-US">Jurnal Pendidikan IPA Indonesia; Vol 12, No 3 (2023): September 2023; 410-422</dc:source>
<dc:source>2089-4392</dc:source>
<dc:source>2339-1286</dc:source>
<dc:source>10.15294/jpii.v12i3</dc:source>
<dc:language>eng</dc:language>
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<dc:rights xml:lang="en-US">Copyright (c) 2023 Jurnal Pendidikan IPA Indonesia</dc:rights>
</oai_dc:dc>
Citations and indexing
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Cite this article
APA 7
Hidayat, M. L., Prayitno, H. J., Anif, S., Meccawy, M., & Khanzada, T. J. (2023). Science Learning in Answering Digital Competency Needs of Preservice Math and Science Teachers in the STEM Context. Jurnal Pendidikan IPA Indonesia, 12(3), 410–422. https://doi.org/10.15294/jpii.v12i3.43960
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IEEE
M. L. Hidayat, H. J. Prayitno, S. Anif, M. Meccawy, and T. J. Khanzada, “Science Learning in Answering Digital Competency Needs of Preservice Math and Science Teachers in the STEM Context,” Jurnal Pendidikan IPA Indonesia, vol. 12, no. 3, pp. 410–422, 2023, doi: 10.15294/jpii.v12i3.43960.
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