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Using Multilevel Modelling to Evaluate Science Literacy and Technology Course of the Indonesian Non-Science Students

Jurnal Pendidikan IPA Indonesia · Vol. 12 No. 1 (2023) · pp. 96–111

DOI
10.15294/jpii.v12i1.41457
ISSN
2089-4392, 2339-1286
Published
2023-03-30
Publisher
Program Studi Pendidikan IPA Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA)
Language
eng

Abstract

In this paper, a science literacy and technology course has been designed and implemented to strengthen the national initiative empowering scientifically literate Indonesian society. This paper is intended to evaluate to what degree non-science undergraduate students can perform this course. The diverse background of non-science students who participated in this study led to the challenge to evaluate their performance more comprehensively contemplating the nested structure of students’ department and faculty setting. In light of the hierarchical nature of the student data, multilevel modelling was used to conduct the analysis. The first level of analysis involved students’ performance and affective attributes measured using demonstrated science literacy assessment (SLA-D) and motivational beliefs (SLA-MB) respectively. Then, the subsequent level of analysis comprised demographic factors gathered from the institutional record. Findings demonstrated that the impact of demographic factors on the students’ performance of science literacy was not substantial. Different settings of students’ department and faculty level drove the association between affective factors and the learning process toward science literacy courses substantially. The multilevel approach controlled the equitable student assessment within the nature of students’ data structure. This paper suggests an implication of advancement regarding educational data analysis and examines the effectiveness of science literacy courses for higher institutions specifically for non-science majors.

Keywords

Collaboration network of the authors

40 authors · 149 co-authorship links · 31 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Yogyakarta State University
  • Universitas Pancasakti Tegal
  • Universitas Sulawesi Barat
  • National Central University
  • Webster University
  • National Research and Innovation Agency
  • Universitas Amikom Yogyakarta
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Sumaryanto SumaryantoYogyakarta State University2
Lantip Diat PrasojoYogyakarta State University2
Firdaus Amruzain Satiranandi WibowoAffiliation unknown2
Asma KhoirunnisaAffiliation unknown2
Angella Ananta BatubaraAffiliation unknown2
Miftah Okta BerlianAffiliation unknown2
Zulfa Safina IbrahimAffiliation unknown2
Jailani JailaniAffiliation unknown2
Purwo SusongkoUniversitas Pancasakti Tegal2
Mobinta KusumaUniversitas Pancasakti Tegal2
İnsih WilujengYogyakarta State University2
Chokchai YuenyongKhon Kaen University2
Ariyatun AriyatunAffiliation unknown2
G.D. ChenNational Central University1
M.C. WuAffiliation unknown1
Rustam AsnawiYogyakarta State University1
Nurkhamid NurkhamidYogyakarta State University1
Janu ArlinwibowoNational Research and Innovation Agency1
Bayuk NusantaraYogyakarta State University1
Samsul HadiYogyakarta State University1
Rimajon SotlikovaWebster University1
Hastari UtamaUniversitas Amikom Yogyakarta1
Nila Feby PuspitasariAffiliation unknown1
Erni SeniwatiAffiliation unknown1
Banu SantosoAffiliation unknown1
Achmad LukmanAffiliation unknown1
Sumin SuminAffiliation unknown1
Lovieanta ArrizaAffiliation unknown1
Rizki Tika AyuniAffiliation unknown1
Muhammad Lintang Damar SaktiAffiliation unknown1
Muhammad Lintang Damar SaktiAffiliation unknown1
Kana HidayatiAffiliation unknown1
Nur Hadi WaryantoAffiliation unknown1
Tri EffiyantiAffiliation unknown1
Gaffar Hafiz SagalaAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/nju/index.php/jpii/oai, first harvested 29 Oct 2026, last seen 1 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Using Multilevel Modelling to Evaluate Science Literacy and Technology Course of the Indonesian Non-Science Students</dc:title>
	<dc:creator>Setiaji, B.</dc:creator>
	<dc:creator>Santoso, P. H.</dc:creator>
	<dc:creator>Aziz, K. N.</dc:creator>
	<dc:creator>Retnawati, H.</dc:creator>
	<dc:creator>Khairudin, M.</dc:creator>
	<dc:subject xml:lang="en-US">multilevel modeling; non-science students; science literacy</dc:subject>
	<dc:description xml:lang="en-US">In this paper, a science literacy and technology course has been designed and implemented to strengthen the national initiative empowering scientifically literate Indonesian society. This paper is intended to evaluate to what degree non-science undergraduate students can perform this course. The diverse background of non-science students who participated in this study led to the challenge to evaluate their performance more comprehensively contemplating the nested structure of students’ department and faculty setting. In light of the hierarchical nature of the student data, multilevel modelling was used to conduct the analysis. The first level of analysis involved students’ performance and affective attributes measured using demonstrated science literacy assessment (SLA-D) and motivational beliefs (SLA-MB) respectively. Then, the subsequent level of analysis comprised demographic factors gathered from the institutional record. Findings demonstrated that the impact of demographic factors on the students’ performance of science literacy was not substantial. Different settings of students’ department and faculty level drove the association between affective factors and the learning process toward science literacy courses substantially. The multilevel approach controlled the equitable student assessment within the nature of students’ data structure. This paper suggests an implication of advancement regarding educational data analysis and examines the effectiveness of science literacy courses for higher institutions specifically for non-science majors.</dc:description>
	<dc:publisher xml:lang="en-US">Program Studi Pendidikan IPA Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA)</dc:publisher>
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	<dc:date>2023-03-30</dc:date>
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	<dc:identifier>https://journal.unnes.ac.id/nju/jpii/article/view/41457</dc:identifier>
	<dc:identifier>10.15294/jpii.v12i1.41457</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Pendidikan IPA Indonesia; Vol 12, No 1 (2023): March 2023; 96-111</dc:source>
	<dc:source>2089-4392</dc:source>
	<dc:source>2339-1286</dc:source>
	<dc:source>10.15294/jpii.v12i1</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>
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