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Listiaji, Prasetyo
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Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Journal : Journal of Environmental and Science Education

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Pre-service Teachers’ Perceptions of the New Pedagogical Deep Learning (NPDL) yeni setyowati; Rahayu, Ayu; Listiaji, Prasetyo
Journal of Environmental and Science Education Vol. 5 No. 1 (2025): Journal of Environmental and Science Education : April 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jese.v5i1.25274

Abstract

This study aimed to investigate the perceptions of pre-service Science Education teachers regarding New Pedagogical Deep Learning (NPDL) in Indonesia. Employing a descriptive survey design, the research was conducted in Central Java Province and involved a sample of 88 pre-service Science Education teachers. Data collection was performed using a questionnaire consisting of 10 items, distributed through Google Forms, complemented by follow-up interviews. Quantitative data analysis with a descriptive approach was utilized to analyze the collected data. The study yielded three primary findings. First, Science Education pre-service teachers possess a basic understanding of the Deep Learning concept, although 16% of them exhibit misconceptions by equating Deep Learning solely with artificial intelligence (AI). Second, these pre-service teachers demonstrate interest in implementing Deep Learning in the classroom; however, they require further training to deepen their understanding of what Deep Learning entails and how to effectively apply it in science education at the school level. Third, pre-service teachers are ready to implement Deep Learning and require strong ecosystem support. They express a keen interest in applying Deep Learning in the classroom.
Co-Authors Aji, Septiko Andin Irsadi Andin Vita Amalia, Andin Vita Anggita Ayu Ivanda Saputri Anggraeni, Yusida Ani Rusilowati Anisia Kholidah Ardhani, Nadia Eka Aribowo, Litasari Aldila Arif Widiyatmoko, Arif Arka Yanitama Atmaja, Bagus Dwi Ayu Rahayu Bunaya Hanif Wintribrata Daeni, Fitri Darmawan, Melissa Salma Dewi Mustikaningtyas Dewi*, Novi Ratna Dewi, Novi Ratna Erna Noor Savitri, Erna Noor Faiq Hisyam Hartanto Fidia Fibriana Hakim, M. Faris Al Heriyanti, Andhina Putri Ibnul Mubarok Ika Susilowati, Ika Iqbal Fathurrohman Ismida Rahmawati Jaya, Adi Franata Kenarni, Naina Rizki Kholidah, Anisia Kholil, Putri Alifa Kinasih, Cahyani Putri Kurniawan, Tessa Surya Latifa, Ghaniya Luthfi Hanum Saputri Martien Herna Susanti Meutia Salwa Aisy Nabilla Muhamad Taufiq Mukaromah, Riska Laila Nabilla, Meutia Salwa Aisy Nia Annisa Ferani Tanjung Nisa, Farah Fitrotun Nor Farahwahidah Abdul Rahman Novi Ratna Dewi Prihestiyani*, Rini Purwadi, Cintiya Egi Putri Ulyatun Niswah Rahman, Nor Farahwahidah Abdul Ramadhani, Nisfil Amelia Risti Ayu Widianingrum Rizki Nor Amelia Sajidi, Imam Sausan Asy Syifa Madaniah Shoba, Tafuz Mahabatis Sigit Priatmoko Sigit Saptono Sri Haryani Sri Sukaesih Stephani Diah Pamelasari, Stephani Diah Subhan Subhan Suharto Linuwih Sumalia, Rifa Suparta, Gede Bayu Syahbananto, Gilang Tiara Dwi Wulandari Tirtasari, Ni Luh Trida Ridho Fariz Wicaksono, Maulana Malik Widianingrum, Risti Ayu Wintribrata, Bunaya Hanif Wiyanto - Wulandari, Tiara Dwi Yanitama, Arka yeni setyowati Yonisa, Zahra Zahra, Arisamiya Latifa Az-