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Script Journal: Journal of Linguistic and English Teaching
Published by Universitas Widya Gama Mahakam Samarinda
ISSN : -     EISSN : -     DOI : -
Core Subject : Education,
Languange, Linguistic, Communication & Media
Script Journal: Journal of Linguistic and English Teaching published by the Department of English Language Education. The Faculty of Teacher Training and Education, Widya Gama Mahakam Samarinda University, which is published three times yearly, in April, August, and December. The Journal ISSN Number for printed version is 2477-1880 and 2502-6623 for Online ISSN, it contains articles of research or study of literature in the field of Teaching and Learning, English Language Teaching, Language and Linguistics, and English Literature. Articles are written in English
Arjuna Subject : -
Articles 226 Documents
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Domain-Specific Platform Alignment Predicts EFL Proficiency at an Indonesian University Nofvia De Vega; Jhoni Eppendi; Syarifa Rafiqa
Script Journal: Journal of Linguistics and English Teaching Vol. 11 No. 2 (2026): August
Publisher : Teacher Training and Education Faculty, Widya Gama Mahakam Samarinda University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/sj.v11i2.2267

Abstract

Background:  This study examines how four mobile-cloud platforms, BeL (reading), FlipGrid (speaking), Padlet (writing), and VoiceThread (listening), were integrated into EFL instruction through a domain-platform alignment model at a 3T-region Indonesian university. The study compares domain-level contributions to composite proficiency and does not claim to isolate platform-specific causal effects. Methodology:  A quasi-experimental pre-test and post-test design was employed with 55 university students in advanced language courses. Stratified random sampling ensured proficiency-level representation. A 12-week structured intervention assigned each platform to one skill domain. Four participants were excluded for completing fewer than 80% of tasks, yielding a final sample of 51. Multiple linear regression was applied following verification of classical assumptions. Findings:  The regression model was statistically significant (R = 0.960, R² = 0.921, F = 146.27, p < .001), with all four domain scores significant at p < .001. The R² value is largely expected given that the Total Language Proficiency Score is mathematically derived from the same four domain predictors, reflecting a compositional rather than independent predictive relationship. Standardized coefficients indicated reading as the strongest contributor (β = .433), followed by listening (β = .371), writing (β = .367), and speaking (β = .356). Post-intervention score improvements are reported as descriptive observations only, as no separate inferential pre-test to post-test analysis per domain pairing was conducted. Conclusion:  These findings offer preliminary descriptive support for domain-differentiated platform use in 3T-region EFL higher education. Model explanatory power should be interpreted cautiously given the compositional constraint, and platform-specific causal claims require further experimental evidence. Originality:  This study introduces a structured domain-platform alignment model enabling principled, domain-level comparison of platform integration within a single EFL study design.
Visual Communication in Prehistoric Public Spaces: A Linguistic Landscape Study of Liangkabori Cave Risman Iye; Dian B; Nur Haizah Aopmonaim; Fithriyah Indah Nur Abida; Susiati
Script Journal: Journal of Linguistics and English Teaching Vol. 11 No. 2 (2026): August
Publisher : Teacher Training and Education Faculty, Widya Gama Mahakam Samarinda University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/sj.v11i2.2360

Abstract

Background: Linguistic landscape studies have predominantly focused on written texts in contemporary public spaces. This study extends the concept of Semiotic Landscapes to pre-literate contexts by examining the pictograms of Liangkabori Cave in Muna as a form of prehistoric public communication. This study aims to analyze how the pictograms in Liangkabori Cave function as elements of a prehistoric semiotic landscape that convey visual communication and social meaning. Methodology: This qualitative study applies a visual semiotics approach integrated with archaeological analysis. Data were obtained from hematite-based pictograms, supported by 3D scanning and spectroscopic analysis to examine painting techniques on karst surfaces. Findings: The pictograms appear to serve both informational and symbolic functions. Hunting and boat motifs suggest representations of subsistence strategies and maritime orientation. The kite motif may indicate an understanding of basic aerodynamic principles and communal practices, while the sun symbol can be interpreted as reflecting cosmological beliefs. These findings are interpretive and do not directly represent verifiable historical intentions. Conclusion:  Liangkabori Cave can be understood as a form of prehistoric visual communication system. The findings suggest that visual representations were likely used to convey ecological knowledge, maritime practices, and belief systems. However, these interpretations remain tentative and highlight the importance of further interdisciplinary research and conservation efforts. Originality:  This study contributes to linguistic landscape research by extending its scope to prehistoric contexts and proposing rock art as a form of semiotic landscape in pre-literate societies.
Technology Integration for Promoting Deep Learning in EFL Contexts Ramli Ramli; Woro Kusmaryani
Script Journal: Journal of Linguistics and English Teaching Vol. 11 No. 2 (2026): August
Publisher : Teacher Training and Education Faculty, Widya Gama Mahakam Samarinda University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/sj.v11i2.2370

Abstract

Background This study explored how an EFL lecturer understands deep learning as a pedagogical approach, how digital and AI-supported tools are integrated into EFL speaking instruction, and what challenges emerge when these tools are used in a classroom located in the Indonesia-Malaysia border area. Methodology This study employed an interpretive qualitative case-study design at the English Education Department of Universitas Borneo Tarakan, North Kalimantan, Indonesia. The participant was one purposively selected EFL lecturer who taught a speaking class and had already used digital and AI-supported applications in classroom practice. Data were collected through a semi-structured interview, four classroom observations, field notes, and video recordings of classroom activities. Findings The findings suggested that technology-supported activities appeared to create classroom conditions associated with deep learning. Students participated in group discussions, short writing activities, spontaneous speaking, oral presentations, and communicative tasks related to familiar contexts such as tourism, travel, hotel booking, and personal experiences. The lecturer used digital and AI-supported tools, including Duolingo, Elsa Speak, Cake, Busuu, Blooket, speech-to-text tools, QuillBot, and Grammarly, to support vocabulary learning, pronunciation practice, speaking rehearsal, gamified review, language feedback, revision, and learner engagement. These tools extended classroom practice and made learning more meaningful and enjoyable. However, the findings also indicated that technology did not automatically create deep learning. Its value depended on the lecturer's pedagogical guidance and on how the tools were connected to speaking tasks, reflection, and communicative purposes. Conclusion In this observed case, technology integration appeared to support active participation, contextualized language use, learner autonomy, reflection, and positive engagement in an EFL speaking classroom. At the same time, some students tended to rely too quickly on AI tools for ready-made answers, highlighting the need for teacher mediation, digital literacy, and ethical awareness. Technology can enrich EFL learning when it is used with a clear pedagogical purpose, but it should not replace students' own thinking or the teacher's instructional role. Originality This study provided context-specific evidence from a higher-education EFL classroom in the Indonesia-Malaysia border area. It demonstrated how one lecturer interpreted and enacted technology integration to support learning conditions associated with deep learning in speaking instruction.
Utilizating Artificial Intelligence Magic School Apps and Invideo. Ai In Designing Lesson Plans Ratu Sarah Pujasari; Melisa Sri; Yuyus Saputra; Nanak Hikmatullah; Santiana Santiana
Script Journal: Journal of Linguistics and English Teaching Vol. 11 No. 2 (2026): August
Publisher : Teacher Training and Education Faculty, Widya Gama Mahakam Samarinda University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/sj.v11i2.1893

Abstract

Background: The digital era requires the realm of education to continue to develop in integrating innovative approaches, especially when designing lesson plansor learning plans. This study explored the potential of artificial intelligence, Artificial Intelligence (AI), with a focus on two main platforms, namely magic school apps and invideo.ai. The researchers investigated how the Magic School Apps and Invideo applications simplify learningdesign by producing innovative learning plans that can be adapted to learning objectives, class activities, and required assessments according to therequested promt. Methodology This study used a qualitative descriptive case study to investigate the phenomenon of using artificial intelligence at the tertiary level in TechnologyEnhanced Language Learning courses. Six Participants in this research are students        in the TELL course. In collecting data the researchers interviewed these students and collect learning process information related to the use of Magic school Ai and invideo.Ai. In analyzing the data the researchers used thematic analysis. Findings: The researchers analyzed the data and they found five themes. The themes are (1) Initial Impressions and Ease of Use, (2) Feature Utility and Variety,(3) Learning Curve and Familiarity, (4) Potential in Teaching and Learning, (5) Concerns About AI Limitations. Conclusion: Exploring the development and future direction of AI in learning plans also has limitations, such as dependence on created content, this requires lecturer supervision to ensure quality and looks to the future where AI can be integrated as an adaptive learning platform and real time assessment tool to further personalize the learning experience. Originality: The issue of the utilization of Artificial Intelligence magic School AI and Invideo.AI on classroom context.
The Quality of Scientific Papers of Undergraduate Students in Regional Language and Literature Studies Lectures Before and After Using ChatGPT as a Writing Tool Ari Wulandari; Arif Budiman; Tri Ratna Herawati; Primasari Wahyuni; Diaz Danu Setyawan
Script Journal: Journal of Linguistics and English Teaching Vol. 11 No. 2 (2026): August
Publisher : Teacher Training and Education Faculty, Widya Gama Mahakam Samarinda University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/sj.v11i2.2353

Abstract

Background:  This study addresses the growing use of ChatGPT in academic writing. Grounded in constructivism, the study investigates changes in the quality of scientific papers produced by undergraduate students in the Regional Language and Literature Studies course at University “A” before and after the use of ChatGPT as a writing support tool. Methodology:  A quasi-experimental pretest–posttest design using document analysis was applied. The data consisted of 30 student papers written before and after ChatGPT use. Assessment covered five aspects: ideas, organization, grammar, diction, and spelling. Findings:  The findings indicate substantial improvements in students’ scientific papers after the use of ChatGPT. The mean writing score increased from 77.9 before ChatGPT-assisted revision to 89.0 after revision, and 27 of the 30 papers improved to the excellent category. The strongest improvements were observed in organization, grammar, diction, and spelling, whereas gains in idea development were comparatively more modest. Conclusion:  The findings suggest that ChatGPT-assisted revision can enhance the technical quality of students’ scientific writing. However, lecturer guidance remains necessary to support critical thinking, independent analysis, and the responsible use of generative AI in academic writing. Originality:  This study contributes empirical evidence on changes in the quality of students’ scientific writing associated with ChatGPT-assisted revision within the context an undergraduate language and literature course.
Exploring EFL University Students’ Experiences of Engaging with ChatGPT-Generated Feedback during Academic Writing: A Qualitative Case Study Ryan Purnomo Ryan; Moh Rif'attullah Rif'attullah; Septiana Wandira Septiana; Thomas Kaufmann Thomas; Deng Zhauyue Deng; A'i Mulyani Az-Zahra Mulyani
Script Journal: Journal of Linguistics and English Teaching Vol. 11 No. 2 (2026): August
Publisher : Teacher Training and Education Faculty, Widya Gama Mahakam Samarinda University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/sj.v11i2.2397

Abstract

 Background: This study investigates how EFL university students engage with ChatGPT-generated feedback during academic writing, focusing on behavioral, cognitive, and affective dimensions. Although generative AI is  increasingly used as a feedback tool in EFL contexts, limited research has examined how students interpret, evaluate, and respond to AI-generated feedback as part of the writing process. Methodology: This qualitative case study involved five EFL university students who had experience using ChatGPT as a feedback tool during academic writing tasks. Data were collected through semi-structured interviews exploring students’ reported experiences, perceptions, and decision-making processes when interacting with ChatGPT-generated feedback. The interview data were analyzed thematically to identify perceived behavioral, cognitive, and affective dimensions of AI-mediated feedback engagement. Findings: The findings suggest that participants reported engaging with ChatGPT-generated feedback through iterative revision, evaluative judgment, and emotional regulation, reflecting behavioral, cognitive, and affective dimensions of feedback engagement. Participants also perceived several affordances of ChatGPT, including immediate responses, explanatory support, and motivational encouragement, while simultaneously reporting challenges related to feedback accuracy, contextual appropriateness, and potential overreliance. These findings indicate that the pedagogical value of AI-generated feedback is not inherent in the technology itself but may emerge through learners’ critical interpretation, evaluation, and adaptation of AI suggestions during the revision process. Originality: This study provides qualitative insights into EFL students’ engagement with AI-generated feedback by examining their self-reported experiences of interacting with ChatGPT during academic writing revision. The findings reveal how students perceived behavioral, cognitive, and affective dimensions of engagement, including their reported practices of seeking, evaluating, and applying AI-generated feedback, as well as their emotional responses toward AI-assisted writing. Rather than providing direct evidence of students’ revision processes, this study offers an in-depth understanding of how learners interpret and negotiate ChatGPT feedback within their academic writing experiences.

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