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All Journal Jurnal Elemen Suluh Abdi: Jurnal Ilmiah Pengabdian Kepada Masyarakat
Rindu Alriavindra Funny
Institut Teknologi Dirgantara Adisutjipto
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Edukasi Dan Pendampingan Penggunaan Kecerdasan Buatan (Ai) Yang Sehat Dan Etis Bagi Siswa Dan Orang Tua Di Rumah Rindu Alriavindra Funny; Yenni Astuti; Fajar Khanif Rahmawati; Maria Asumpta Deni Kusumaningrum
Suluh Abdi: Jurnal Ilmiah Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2025): Suluh Abdi
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), Universitas Muhammadiyah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32502/suluhabd.v7i2.1376

Abstract

Perkembangan pesat teknologi kecerdasan buatan (Artificial Intelligence/AI), khususnya Generative AI seperti ChatGPT dan DALL·E, telah memengaruhi cara belajar siswa namun belum diimbangi dengan literasi dan pendampingan yang memadai dari orang tua. Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan literasi AI dan kesadaran etika penggunaannya di lingkungan keluarga, khususnya bagi Ibu-Ibu PKK Kompleks TNI AU Lanud Adisutjipto, Yogyakarta. Metode pelaksanaan meliputi tiga tahap utama, yaitu workshop literasi AI, simulasi penggunaan AI dalam pembelajaran, serta diskusi kelompok antara orang tua dan anak. Kegiatan dilaksanakan dengan pendekatan partisipatif melalui kombinasi teori dan praktik langsung, disertai evaluasi pre-test dan post-test. Hasil kegiatan menunjukkan peningkatan signifikan pada pemahaman peserta tentang AI (dari skor rata-rata 3,2 menjadi 4,5), antusiasme penggunaan AI secara produktif (dari 3,1 menjadi 4,5), dan rasa percaya diri dalam mendampingi anak (dari 3,0 menjadi 4,5). Peserta juga menunjukkan kesadaran etis yang lebih baik serta inisiatif menyusun aturan keluarga terkait penggunaan AI di rumah. Kegiatan ini berhasil memperkuat peran orang tua sebagai pendamping digital anak dan mendorong budaya belajar yang sehat, etis, dan adaptif terhadap perkembangan teknologi
Mapping cognitive load profiles in realistic mathematics education: A study with aerospace engineering students Rindu Alriavindra Funny; Fajar Khanif Rahmawati
Jurnal Elemen Vol 11 No 4 (2025): October
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jel.v11i4.32104

Abstract

Although Realistic Mathematics Education (RME) promotes deeper conceptual learning, empirical evidence mapping different types of cognitive loads in university engineering mathematics is limited. This mixed-methods study profiled intrinsic, extraneous, and germane cognitive loads among 76 first-year aeronautical engineering students working on RME-based task, a contextualized double integral problems modelling aircraft wing surface. We measured load components with a CLT questionnaire that adapted from Leppink et.al and mental effort with the Paas scale, then triangulated findings with student reflections and observations. Correlations showed intrinsic and germane load related to students’ mental effort, while extraneous load was minimal, suggesting clear task design. Multiple regression analysis clarified that the germane load was the main unique predictor of mental effort, whereas intrinsic complexity and extraneous factors contributed little uniquely. Qualitative data confirmed that students used strategies such as breaking tasks into sub-steps, activating prior knowledge, and peer explanation to manage effort. We propose an RME–CLT alignment framework that scaffolds intrinsic difficulty, minimizes extraneous processing, and cultivates germane engagement through reflective context-rich tasks. The findings also inform the design of cognitively efficient engineering-mathematics curricula. Thus, it offers practical guidance for designing cognitively efficient engineering mathematics instruction and recommends future studies using longitudinal and real-time measures.
Co-Authors Maria Asumpta Deni Kusumaningrum Rahmawati, Fajar Khanif Yenni Astuti