Claim Missing Document
Check
Articles

Found 2 Documents
Search

Generative AI in Secondary STEM Classrooms: Teachers’ Conditional Acceptance Go, Mary Cris J; Ajon, Helen B; Witting - Acuesa, Mary Koren; Delosa, Jovelyn; Bagongon, Rowena E; Gomez, Alven L; Genita, Anna Marie
Journal of Educational Technology and Learning Creativity Vol. 4 No. 1 (2026): June
Publisher : Cahaya Ilmu Cendekia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37251/jetlc.v4i1.2568

Abstract

perceive and engage with generative artificial intelligence (GenAI) in instructional practice and identifies the institutional conditions influencing its responsible integration in public secondary schools. The study aims to understand how teachers regulate the use of GenAI within classroom instruction and professional decision-making. Methodology: A qualitative exploratory design was employed using a focus group discussion involving thirteen secondary STEM teachers from a public secondary school. Data were collected using a semi-structured discussion guide informed by the Technology Acceptance Model (TAM). Thematic analysis following Braun and Clarke’s six-phase framework was conducted, with NVivo qualitative analysis software supporting coding and data organization. Main Findings: The findings show that teachers’ engagement with generative artificial intelligence is characterized by partial familiarity, productivity-oriented use, and strong ethical concern. GenAI is primarily used for lesson preparation and instructional planning. Concerns regarding student overreliance, academic integrity, and learning authenticity limit unrestricted use, resulting in selective and regulated integration within classroom practice. Novelty/Originality of this study: This study contributes qualitative evidence on secondary STEM teachers’ engagement with generative artificial intelligence, a context underrepresented in AI-in-education research. It introduces the concept of conditional acceptance, explaining how teachers selectively adopt GenAI through professional judgment and institutional constraints, extending technology acceptance perspectives beyond binary adoption models.
Deep Learning (Pembelajaran Mendalam) dalam Pendidikan Indonesia: Tinjauan Sistematis Teori dan Praktik Ratri, Safitri Yosita; Wagiran, Wagiran; Riyadi, Andrian; Firdaus, Fery Muhamad; Delosa, Jovelyn
Jurnal Ilmu Pendidikan dan Pembelajaran Vol. 4 No. 2 (2026): April 2026
Publisher : Mitra Edukasi dan Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58706/jipp.v4n2.p176-191

Abstract

Transformasi pendidikan Indonesia menuntut pergeseran dari pembelajaran hafalan menuju Pembelajaran Mendalam (Deep Learning) yang bermakna dan kontekstual. Tujuan penelitian ini adalah mengidentifikasi dan menganalisis penerapan pembelajaran mendalam di Indonesia, mencakup landasan teoretis, paradigma pembelajaran, strategi inovatif, implementasi lokal (kesiapan guru, infrastruktur, kurikulum), relevansi dengan Outcome-Based Education (OBE), asesmen autentik, serta pilar meaningful, mindful, dan joyful. Penelitian ini menggunakan tinjauan sistematis berbasis PRISMA terhadap 45 artikel yang dianalisis secara tematik dan menghasilkan tujuh tema utama. Hasil menunjukkan bahwa meskipun kerangka global seperti DELC dan 6Cs berkembang, implementasi di Indonesia masih menghadapi tantangan pada konsistensi kebijakan, kesiapan pedagogis guru, dan penguatan asesmen autentik. Temuan ini menegaskan bahwa keberhasilan penerapan pembelajaran mendalam di Indonesia memerlukan sinergi kebijakan, peningkatan kapasitas guru, dan sistem asesmen kontekstual berkelanjutan. Dampak penelitian ini memberi kontribusi konseptual dan praktis sebagai dasar pengembangan kebijakan, penyempurnaan Naskah Akademik, serta perancangan pembelajaran dan asesmen yang lebih kontekstual, adaptif, dan berkelanjutan.