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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.
Pelatihan Pembuatan Worksheet AUD Bermuatan Kearifan Lokal Papua Berbantukan Canva di TK Pertiwi XI Hajra Yansa; Wa Ode Siti Hamsinah Day; Diah Harmawati; Retno Wuri Sulistyowati; Asri Cahyaningdian; Aser Parera
Jurnal Transformasi Pendidikan Indonesia Vol. 4 No. 2 (2026): JTPI April
Publisher : Yayasan Perguruan Kampus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65474/5mjhds58

Abstract

Penggunaan worksheet sebagai media pembelajaran pada Pendidikan Anak Usia Dini (PAUD) perlu dirancang secara kontekstual agar sesuai dengan karakteristik dan lingkungan peserta didik. Namun, hasil observasi di TK Pertiwi XI menunjukkan bahwa sebagian besar worksheet yang digunakan belum mengintegrasikan kearifan lokal Papua. Selain itu, guru membutuhkan kemampuan penggunaan Canva dalam membuat worksheet secara mandiri. Kegiatan ini bertujuan untuk meningkatkan pemahaman dan keterampilan guru dalam membuat worksheet AUD bermuatan kearifan lokal Papua berbantukan Canva. Metode yang digunakan adalah pelatihan partisipatif yang dipadukan dengan pendampingan praktik. Kegiatan dilaksanakan melalui tahapan analisis kebutuhan, penyampaian materi, demonstrasi, praktik pembuatan worksheet, dan pendampingan. Peserta kegiatan berjumlah 10 guru TK Pertiwi XI. Hasil kegiatan menunjukkan adanya peningkatan pemahaman guru mengenai pentingnya integrasi kearifan lokal Papua dalam pembelajaran serta peningkatan keterampilan dalam memanfaatkan Canva sebagai media desain pembelajaran. Seluruh peserta berhasil menghasilkan minimal satu worksheet yang memuat unsur budaya Papua, seperti pangan lokal, rumah adat, alat musik tradisional, serta fauna endemik Papua. Produk yang dihasilkan memiliki tampilan visual yang lebih menarik, kontekstual, dan sesuai dengan karakteristik anak usia dini. Dengan demikian, pelatihan ini berhasil meningkatkan kompetensi guru dalam mengembangkan media pembelajaran berbasis budaya lokal sekaligus mendukung penguatan identitas budaya dan pelestarian kearifan lokal Papua melalui PAUD.
Tren Global Penelitian Artificial Inteligence dalam Pembelajaran Matematika Anak Usia Dini: Studi Bibliometrik Hajra Yansa; Aser Parera; Dite Umbara Alfansuri; Yuliana Olga Siba Sabon; Ratu Bulkis Ramli
PEDAGOGIC: Indonesian Journal of Science Education and Technology Vol. 6 No. 3 (2026): PEDAGOGIC: Indonesian Journal of Science Education and Technology
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/ijset.v6i3.5686

Abstract

This study aims to analyze global research trends on Artificial Intelligence (AI) in early childhood mathematics learning through a bibliometric approach. The research data were obtained from the Scopus database within the 2016–2026 period. A total of 41 documents were analyzed using the Bibliometrix package in the R programming language. The analysis was conducted through performance analysis and science mapping, including publication trends, author and institutional productivity, research collaboration, and thematic analysis based on co-occurrence keywords and thematic maps. The results revealed that research on AI in early childhood mathematics learning has increased significantly, with an annual growth rate of 19.58%. The United States was identified as the country with the highest publication contribution, while University of Aveiro was the most productive institution. The dominant research themes included artificial intelligence, mathematics education, numeracy, machine learning, and early childhood education. The thematic map analysis indicated that mathematics education and AI-based learning systems have become rapidly developing core themes, while adaptive learning and machine learning still provide substantial opportunities for further research. This study confirms that AI has considerable potential to support early childhood mathematics learning, particularly in learning personalization and numeracy skill development This study is limited to Scopus-indexed publications and bibliometric analysis, therefore future research is recommended to explore empirical implementation and pedagogical efectiveness of AI in earlu childhood mathematics learning across diverse educational contexts