Article Per Year (5 Year)
p-Index From 2020 - 2025
1.756
P-Index
This Author published in this journals
All Journal HUMANIS Parole: Journal of Linguistics and Education KAJIAN SASTRA HUMANIKA Nusa: Jurnal Ilmu Bahasa dan Sastra Jurnal Pendidikan Bahasa Inggris Jurnal Arbitrer At-Taqaddum Indonesian EFL Journal HARMONI Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming International Journal of Social Learning (IJSL) COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat
Catur Kepirianto
Unknown Affiliation
Religion Arts Humanities Automotive Engineering Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Other

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 13 Documents
Search

 1   2 
ENHANCING STUDENTS’ READING COMPREHENSION OF RECOUNT TEXT WITH MULTIMODAL DIGITAL LITERACY Mariam, Siti; Kepirianto, Catur; Fadlilah, Sayyidatul; Izza, Awwalia Fitrotin
Indonesian EFL Journal Vol. 11 No. 1 (2025)
Publisher : University of Kuningan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ieflj.v11i1.11337

Abstract

This study aims firstly to explain the use of multimodal digital literacy to boost students’ reading comprehension of recount text. Secondly, to describe students’ engagement in joining this learning model. It employed a qualitative method. Classroom action research with two cycles was used as the research design. Each cycle consisted of planning, acting, observing, and evaluating. The participants were thirty-ninth graders at the Islamic secondary school in Semarang Regency in the academic year 2024-2025. The pre-test, posttests, and observation guidelines were provided as data collection techniques. The results show that incorporating a genre-based approach and multimodal digital literacy can enhance students’ reading comprehension of recount text. Based on students’ achievement in the pretest, they reached 69, in post-test cycle 1, they achieved 75, and in post-test cycle 2, they obtained 84. Because students were intrigued by multimodal digital literacy, they were also delighted in putting this learning approach into practice. Their grasp of reading comprehension of recall texts was enhanced by the teacher. Together with their peers and the teacher, they studied the course materials. It can be concluded, this learning paradigm improves group work and interpersonal skills, raises learning motivation, and promotes active learners' involvement.Keywords: digital literacy, multimodal; reading comprehension; recount text; revolutionizing. 
DICO-JALF v.1.0: Diponegoro Corpus of Japanese Learners as a Foreign Language in Indonesia with AI Error Annotation and Human Supervision Prihantoro, Prihantoro; Ishikawa, Shin'Ichiro; Liu, Tanjun; Fadli, Zaki Ainul; Rini, Elizabeth Ika Hesti Aprilia Nindia; Kepirianto, Catur
Jurnal Arbitrer Vol. 12 No. 3 (2025)
Publisher : Masyarakat Linguistik Indonesia Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ar.12.3.274-288.2025

Abstract

There is a growing body of research in using AI for corrective feedback in foreign language teaching. However, few studies have specifically addressed the accuracy of AI analysis in learner corpus research. This study aims to create an AI-annotated corpus whose data were obtained from learners of Japanese as a Foreign Language (JFL) in Indonesia with human supervision; branded it as DICO-JALF v.1.0. The aim is to measure to what extent ChatGPT accurately annotates errors. A task was first administered to collect corpus data and metadata to build the corpus. The corpus was error-annotated using ChatGPT 4.0. Human annotators manually supervised the accuracy of AI-generated annotations. Regarding errors committed by learners, it is observed that incorrect lexical choices and forms dominate the cause of errors, while underuse and overuse are minimal. It can be concluded that ChatGPT demonstrated an average accuracy of 70% correct identification of errors. Regarding error rate, the verb is the category where errors are most frequent, which maybe driven by its conjugation, a feature absent in Indonesian, the L1 of the students. This suggests that Indonesian learners' acquisition of Japanese verbs needs greater emphasis. As compared to other similar studies, this is relatively low. However, it can be argued that one factor determining the accuracy of ChatGPT annotations, or any other LLM-based tool, is the complexity of the annotation scheme they adhere to. The corpus have been made available for download. The annotations shall be readable by a corpus query system that reads XML tags. This corpus serves as a foundational resource for future research on AI-assisted error analysis in JFL learning contexts in Indonesia.
Online Assessment of English Competence and Its Washback: Teachers’ and Students’ Voices Mariam, Siti; Fadlilah, Sayyidatul; Kepirianto, Catur
International Journal of Social Learning (IJSL) Vol. 5 No. 3 (2025): August
Publisher : Indonesian Journal Publisher in cooperation with Indonesian Social Studies Association (APRIPSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijsl.v5i3.437

Abstract

Online assessments present several challenges for teachers, particularly in EFL (English as a Foreign Language) contexts. These difficulties fall into four categories: contextual, psychological, pedagogical, and technical. This study aims to explain teachers’ and students’ voices on implementing online assessment of English competence and its washback. It employed a qualitative method and a narrative inquiry research design. Data collection techniques used semi-structured interviews and open-ended questions. Thematic analysis was used as a data analysis technique. The participants were two English teachers and five students of an Islamic secondary school in Semarang city. The results show that the biggest challenge when conducting online English assessment reflects a range of technological, emotional, and instructional challenges, namely poor internet connection, device sharing or lack of equipment, speaking anxiety, unclear instructions, difficulty with listening tests, time pressure, lack of feedback, and technical platform confusion.
Co-Authors Braheng, Syarifah Deli Nirmala Djoko Sutrisno Fahmi, Iftitah Amalia Mutiara Hersugondo Hersugondo Ishikawa, Shin'Ichiro Izza, Awwalia Fitrotin Liu, Tanjun Mualimin Muhammad Nafi Annury, Muhammad Nafi Nurhayati Nurhayati Parmadi, Alifia Rimas Pratama, Luthfi Hakim Bintang Prihantoro Prihantoro Reza Kafipour Rini, Elizabeth Ika Hesti Aprilia Nindia Sa'adah, Ardiana Alifatus Santoso, Balqis Salsabila Sayyidatul Fadlilah Siti Mariam SITI MARIAM Soepomo Poedjosoedarmo Suhandano Suhandano Zaki Ainul Fadli