Pelatihan Pengembangan LKPD Berbasis Keterampilan Proses Sains Berbantuan ChatGPT Bagi Calon Guru Fisika
DOI:
https://doi.org/10.36312/linov.v10i2.3005Keywords:
LKPD, Keterampilan Proses Sains, ChatGPT, Pelatihan Calon Guru FisikaAbstract
Pelatihan pengembangan Lembar Kerja Peserta Didik (LKPD) berbasis Keterampilan Proses Sains (KPS) dengan bantuan teknologi ChatGPT dilaksanakan untuk meningkatkan kompetensi calon guru fisika dalam menyusun perangkat pembelajaran yang inovatif. Pelatihan ini menggunakan metode workshop yang dilakukan secara hybrid, melibatkan sesi daring dan luring dengan lima narasumber yang berkompeten. Mitra kegiatan adalah mahasiswa semester 7 Program Studi Fisika Universitas Pendidikan Mandalika. Hasil evaluasi menunjukkan peningkatan signifikan dalam pemahaman peserta, dengan rata-rata nilai pre-test sebesar 36,7 meningkat menjadi 80,1 pada post-test, serta rata-rata N-Gain sebesar 0,66 (kategori sedang). Mayoritas peserta memberikan tanggapan positif terhadap pelatihan, dengan 40% berada pada kategori Sangat Baik dan 60% pada kategori Baik. Kesimpulan menunjukkan bahwa pelatihan ini efektif dalam meningkatkan pemahaman konseptual dan keterampilan teknis peserta. Direkomendasikan untuk menyertakan pendalaman fitur teknologi AI seperti ChatGPT dan simulasi praktis untuk pelatihan berikutnya.
Science Process Skills-Based LKPD Development Training Assisted by ChatGPT for Prospective Physics Teachers
Abstract
The training for developing Student Worksheets (LKPD) based on Science Process Skills (SPS) assisted by ChatGPT technology was conducted to enhance the competence of prospective physics teachers in designing innovative learning tools. The training employed a workshop method conducted in a hybrid format, combining online and offline sessions with five expert instructors. The participants were 7th-semester students from the Physics Education Program at Universitas Pendidikan Mandalika. The evaluation results showed a significant improvement in participants' understanding, with the average pre-test score increasing from 36.7 to 80.1 in the post-test, and an average N-Gain of 0.66 (moderate category). Most participants provided positive feedback, with 40% rating the training as Excellent and 60% as Good. The findings concluded that this training effectively improved conceptual understanding and technical skills. Future recommendations include integrating advanced AI features such as ChatGPT and practical simulations to further enhance training effectiveness.
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Copyright (c) 2025 Irham Azmi, H. Hunaepi, Muhammad Asy’ari, Taufik Samsuri, Saiful Prayogi, Muhali Muhali, Agus Muliadi, Ni Putu Widiarini, I Gusti Ayu Ngurah Kade Sukiastini, Ketut Sri Kusuma Wardani
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