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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Transformasi Pendidikan Indonesia
Hajra Yansa
Universitas Musamus
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Environmental Science Materials Science & Nanotechnology Physics Other

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Pelatihan Pencarian Literatur yang Kredibel Menggunakan AI dalam Penulisan Karya Ilmiah bagi Mahasiswa di Merauke Hajra Yansa; Aser Parera; Dite Umbara Alfansuri; Yulia Olga Siba Sabon; Haerul Amri; Abdullah; Muh. Rafi'y
Jurnal Transformasi Pendidikan Indonesia Vol. 3 No. 2 (2025): JTPI - April
Publisher : Yayasan Perguruan Kampus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65474/3kbvax88

Abstract

To succeed in academic writing, students must have the ability to locate and evaluate reliable scientific literature. However, many students still experience difficulties in searching for relevant reference sources. Therefore, this community service aims to improve students' academic information literacy by teaching them how to use Artificial Intelligence (AI) in searching for credible literature. An initial needs survey, guidebook preparation, hands-on implementation, and barrier analysis to evaluate the training results were used in this activity. This service involved 22 students in Merauke Regency, South Papua Province. The results showed that students were better able to use AI to find and validate scientific reference sources. The stages of service include, FGD with lecturers, surveys on students, preparation of guidebooks, training, and analysis of obstacles. Most participants who previously did not know how to distinguish credible sources can now use better search strategies by using various AI platforms, such as Scite AI combined with GPT in writing academic work. Device limitations were the main obstacle in this training.
Integrasi Teknologi dan Psikometri: Pengembangan Alat Diagnostik Berbasis Aplikasi Menggunakan Model Partial Credit untuk Mengidentifikasi Miskonsepsi Siswa Nurhasanah; Zul Hidayatullah; Hajra Yansa; Moh. Badrus Sholeh Arif; Muh Asriadi
Jurnal Penelitian Pendidikan IPA Vol 11 No 12 (2025): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i12.12305

Abstract

Misconceptions in science learning remain a major barrier to students’ conceptual understanding, while traditional assessments often fail to detect them effectively. This study aimed to develop PhyTestApp, an app-based diagnostic tool that integrates the Partial Credit Model (PCM) under Item Response Theory (IRT) to uncover student misconceptions in science. A research and development design was employed, involving expert validation, limited trials, and psychometric testing. The two-tier items were designed to capture both factual knowledge and reasoning. Findings indicated that the instrument met psychometric requirements, with items demonstrating good fit and functioning across different levels of student understanding. Usability testing also showed positive responses from students and teachers regarding clarity, content relevance, and technical operation. Overall, PhyTestApp provides a reliable and practical diagnostic tool that facilitates immediate feedback and supports more targeted science instruction. These results highlight the potential of combining psychometric modeling with mobile technology to improve the quality of science education and more effectively address misconceptions in line with 21st-century learning goals.
Co-Authors Abdullah Aser Parera Dite Umbara Alfansuri Haerul Amri Moh. Badrus Sholeh Arif Muh Asriadi Muh. Rafi'y Nurhasanah Yulia Olga Siba Sabon Zul Hidayatullah