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All Journal Journal on English as a Foreign Language (JEFL) ARMADA : Jurnal Penelitian Multidisiplin
Nunung Suryati
Universitas Negeri Malang, Malang, Indonesia
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ChatGPT vs. human-made argumentative essays: Which is more critical? Agunawan Agunawan; Utami Widiati; Nunung Suryati; Kardi Nurhadi
Journal on English as a Foreign Language Vol 16 No 1 (2026): Issued in March 2026
Publisher : Universitas Islam Negeri Palangka Raya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23971/jefl.v16i1.10998

Abstract

The integration of artificial intelligence (AI) into the education sector is becoming increasingly unavoidable; however, the ability of AI systems, such as ChatGPT, to generate critically argumentative texts remains insufficiently examined. This study explored whether argumentative essays authored by humans exhibit greater critical depth than those generated by ChatGPT. This study employed a sequential explanatory mixed-methods design. Ten Indonesian university students voluntarily composed two argumentative essays—on the topics of “city dumps” and “slum neighborhoods”—following an experiential learning model, resulting in 20 human-produced texts. ChatGPT was tasked with generating 20 essays on the same topics. The data were analyzed using the Holistic Critical Thinking Scoring Rubric (HCTSR) developed by Facione (2020), as follows: three blind raters assessed all 40 essays for critical thinking using standardized rubrics. Quantitative analysis (t-tests) and qualitative content inspection revealed that human essays consistently achieved higher scores for experiential breadth, perspective diversity, counterargument integration, and emotional resonance. These findings indicate that despite advancements in natural language generation, AI-produced argumentative writing still lacks the critical sophistication that human authors demonstrate. This study indicates that future AI development must move beyond surface-level fluency to better emulate the nuanced socio-contextual sophistication of human reasoning.
Improving Elementary Students’ Reading Comprehension through Guided Reading in TaRL Instruction Yuyun Dwi Suryandari; Nunung Suryati; Ahmad Heki Sujiatmoko
ARMADA : Jurnal Penelitian Multidisiplin Vol. 4 No. 7 (2026): ARMADA : Jurnal Penelitian Multidisplin, July 2026
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi 45 Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/armada.v4i7.2992

Abstract

The objective of the research was to improve elementary school students’ reading comprehension skills through the implementation of the Guided Reading strategy in TaRL instructional framework. Adopting a Classroom Action Research (CAR) design, executed through a singular cycle, of four teaching sessions incorporating all eight sequential stages of the Guided Reading approach. Participants were stratified into Group A and Group B according to baseline reading proficiency levels. Quantitative data were subjected to analysis via descriptive statistics and one-sample t-test, utilizing the Minimum Mastery Criterion (KKM) set at 85. The findings of the study reveal a notable enhancement in reading comprehension skills among both groups. In Group A, students met the Minimum Mastery Criterion increased from 0/12 in the initial test to 12/12 in Cycle I, and Group B, from 3/15. These outcomes indicate that the application of the Guided Reading methodology within the TaRL framework significantly contributes to the improvement of reading comprehension skills among students with initially stronger abilities.
Understanding university students’ perceptions of the group work-based activity to enhance collaborative problem-solving skills and its impact on academic writing performance Siti Anisah; Nunung Suryati
Journal on English as a Foreign Language Vol 15 No 1 (2025): Issued in March 2025
Publisher : Universitas Islam Negeri Palangka Raya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23971/jefl.v15i1.9653

Abstract

Group work-based activity is commonly used by teachers, primarily to improve students' learning achievement. Despite its strengths in enhancing students' abilities during language learning, yet, limited literature explores how this activity can develop students' soft skills, particularly in higher education. This study aims to explore students' perceptions of group work-based activity to enhance collaborative problem-solving skills and how group work-based activity affects their academic writing performance. Thirty-two master's students from one of the universities in Malang, Indonesia, who have been enrolled in the Writing for Publication course, are involved in this mixed-method study. The quantitative data were collected through a questionnaire and analyzed using descriptive statistics, while the results from an open-ended interview were analyzed thematically. The findings indicated that students perceive group work differently. Even though some of them stated that it was less effective, most of them agreed that this activity helped them to improve their collaborative problem-solving skills, guiding them to compose a good-quality research article. Furthermore, these findings provide new insights for teachers into how group work as a learning method can be better applied in EFL classroom practices to support 21st-century learning.
ChatGPT vs. human-made argumentative essays: Which is more critical? Agunawan Agunawan; Utami Widiati; Nunung Suryati; Kardi Nurhadi
Journal on English as a Foreign Language Vol 16 No 1 (2026): Issued in March 2026
Publisher : Universitas Islam Negeri Palangka Raya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23971/jefl.v16i1.10998

Abstract

The integration of artificial intelligence (AI) into the education sector is becoming increasingly unavoidable; however, the ability of AI systems, such as ChatGPT, to generate critically argumentative texts remains insufficiently examined. This study explored whether argumentative essays authored by humans exhibit greater critical depth than those generated by ChatGPT. This study employed a sequential explanatory mixed-methods design. Ten Indonesian university students voluntarily composed two argumentative essays—on the topics of “city dumps” and “slum neighborhoods”—following an experiential learning model, resulting in 20 human-produced texts. ChatGPT was tasked with generating 20 essays on the same topics. The data were analyzed using the Holistic Critical Thinking Scoring Rubric (HCTSR) developed by Facione (2020), as follows: three blind raters assessed all 40 essays for critical thinking using standardized rubrics. Quantitative analysis (t-tests) and qualitative content inspection revealed that human essays consistently achieved higher scores for experiential breadth, perspective diversity, counterargument integration, and emotional resonance. These findings indicate that despite advancements in natural language generation, AI-produced argumentative writing still lacks the critical sophistication that human authors demonstrate. This study indicates that future AI development must move beyond surface-level fluency to better emulate the nuanced socio-contextual sophistication of human reasoning.
Co-Authors Agunawan Agunawan Ahmad Heki Sujiatmoko Kardi Nurhadi Siti Anisah Utami Widiati Yuyun Dwi Suryandari