Science Learning Perceptions and Perceived Readiness of Preservice Early Childhood Teachers
DOI:
https://doi.org/10.61142/esj.v4i3.510Keywords:
student perceptions, teacher readiness, Science Learning Achievement, early childhood educationAbstract
Science learning in early childhood requires prospective teachers who understand its importance and are prepared to design and implement developmentally appropriate learning experiences. This study aimed to examine Pendidikan Guru Pendidikan Anak Usia Dini students’ perceptions and perceived readiness for early childhood science learning and to explore the experiences and challenges underlying these perceptions. The study employed a descriptive survey with a quantitative approach supported by qualitative data from semi-structured interviews. The survey involved 179 students, while six students were purposively selected for interviews. Quantitative data were collected using a 20-item five-point Likert-scale questionnaire and analyzed descriptively, while interview data were analyzed thematically. The results showed that students’ overall perception was categorized as high (70,82%). The highest score was found for the perceived importance of science learning (74,32%), followed by perceptions of implementation (72,11%), perceived readiness (68,32%), and understanding of early childhood science learning (67,63%). Interview findings indicated that students recognized the importance of hands-on experiences, exploration, simple experiments, and environmental resources, but still needed practical experience, examples of learning activities, and guidance. These findings indicate a descriptive gap between students’ positive perceptions of the importance of science learning and their perceived readiness to implement it. Strengthening authentic pedagogical experiences, mentoring, and opportunities to design and practice science activities is therefore important in preparing prospective early childhood teachers.
References
Ahmad, S., Wasim, S., Irfan, S., Gogoi, S., Srivastava, A., & Farheen, Z. (2019). Qualitative v/s. Quantitative Research- A Summarized Review. Journal of Evidence Based Medicine and Healthcare, 6, 2828-2832. https://doi.org/10.18410/jebmh/2019/587
Ansya, Y. A., & Salsabilla, T. (2025). Membangun Pemahaman Sains Sejak Dini. Cahya Ghani Recovery.
Ateş, H., Garzón, J., & Lampropoulos, G. (2024). Evaluating science teachers' flipped learning readiness: a GETAMEL approach test. Interactive Learning Environments, 32(10), 6283-6300. https://doi.org/10.1080/10494820.2023.2255232
Banha, F., Flores, A., & Coelho, L. S. (2022). Quantitizing qualitative data from semi-structured interviews: a methodological contribution in the context of public policy decision-making. Mathematics, 10(19), 3597. https://doi.org/10.3390/math10193597
Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE Publication. https://doi.org/10.4135/9781036232078.n9
Choiriyah, Lutfiani, N., Faturahman, A., & Nabila, E. (2021). Science Literacy in Early Childhood: Development of Learning Programs in the Classroom. Aptisi Transactions on Technopreneurship (ATT), 3, 31-36. https://doi.org/10.34306/att.v3i2.187
Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications.
Gangal, M., Çalık, M., & Ozturk, Y. (2026). Effectiveness of Early Childhood Science Activities in Promoting Scientific Literacy : A Meta Analysis Study. Science & Education, 0123456789.
https://doi.org/10.1007/s11191-026-00748-2
Haber, A. S., Leech, K. A., Benton, D. T., Dashoush, N., & Corriveau, K. H. (2021). Early Childhood Research Quarterly Questions and explanations in the classroom : Examining variation in early childhood teachers ' responses to children ' s scientific questions. 57, 121-132. https://doi.org/10.1016/j.ecresq.2021.05.008
Karatsareas, P. (2022). Semi-structured interviews. Research Methods in Language Attitudes, 99, 99. https://doi.org/10.1017/9781108867788.010
Komala, R. (2025). Membangun Karakter Dan Logika Anak Memalui Pembelajaran Sains Di Sekolah Dasar. Jurnal Ilmiah Multidisiplin Mahasiswa Dan Akademisi, 1(3), 32-43. https://doi.org/10.47134/pgsd.v1i3.562
Kotsis, K. T. (2025). Optimal STEM educators for elementary school: Students from the Primary Education vs. Science Department. EIKI Journal of Effective Teaching Methods, 3(1). https://doi.org/10.59652/jetm.v3i1.360
Larkin, K., & Lowrie, T. (2023). Teaching Approaches for STEM Integration in Pre and Primary School : a Systematic Qualitative Literature Review. International Journal of Science and Mathematics Education, 21, 11-39. https://doi.org/10.1007/s10763-023-10362-1
Majdina, N. I., Pratikno, B., & Tripena, A. (2024). Penentuan ukuran sampel menggunakan rumus Bernoulli dan Slovin: Konsep dan aplikasinya. Jurnal Ilmiah Matematika Dan Pendidikan Matematika, 16(1), 73-84. https://doi.org/10.20884/1.jmp.2024.16.1.11230
Marsetyaningrum, D. (2018). Science Learning In Early Childhood. Empowerment, 7, 98. https://doi.org/10.22460/empowerment.v7i2p98-107.944
Monteira, S. F. (2026). Creative approaches for inclusive STEM learning in early years. Early Childhood Education Journal, 54(3), 1209-1222. https://doi.org/10.1007/s10643-025-01922-x
Riduwan, M. B. A. (2022). Skala pengukuran variabel-variabel penelitian. Bandung: Alfabeta.
Romadhoni, N. A., Fitri, R., & Khotimah, N. (2024). Meningkatkan Pemahaman Sains Pada Anak Usia Dini Kelompok B dengan Pendekatan Metode PJBL Melalui Eksperimen. 5(1), 1033-1038. https://doi.org/10.62775/edukasia.v5i1.931
Santoso, A. (2023). Rumus Slovin: Panacea Masalah Ukuran Sampel? SUKSMA: Jurnal Psikologi Universitas Sanata Dharma, 4(2), 24-43.https://doi.org/10.24071/suksma.v4i2.6434
Simsar, A., & Jones, I. (2021). Field Experiences , Mentoring , and Preserv- ice Early Childhood Teachers ' Science Teaching Self-Efficacy Beliefs To cite this article : Field Experiences , Mentoring , and Preservice Early Childhood Te achers ' Science Teaching Self-Efficacy Beliefs. 3(3), 518-534. https://doi.org/10.46328/ijonses.127
Xie, T., Zhang, X., Shen, X., & Hou, J. (2026). Predicting Graduate Employment Quality in Agricultural Universities: A Machine Learning Framework Leveraging Multi-Dimensional 5-Point Likert Scale Survey Data. Sustainability, 18(4), 1998.
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