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All Journal Journal on English as a Foreign Language (JEFL)
Kardi Nurhadi
Universitas Wiralodra, Indramayu, Indonesia
Languange, Linguistic, Communication & Media

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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.
Gender stereotypes in visual and verbal texts from government-distributed EFL textbook: Critical discourse analysis Rama Dwika Herdiawan; Afief Fakhruddin; Eka Nurhidayat; Kardi Nurhadi
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.v15i1.9357

Abstract

Research on gender stereotypes in educational materials has been documented. However, research exploring gender stereotype constructions within visual and verbal materials of English as a foreign language (EFL) textbooks remains limited. This study investigates gender stereotype constructions within visual and verbal materials of the Indonesian government-distributed EFL textbook to shape learners' perceptions of gender roles. This study employed critical discourse analysis (CDA) to explore how textbooks construct stereotypical roles through visual depictions, dialogue patterns (verbal), and linguistic characteristics as data sources and verbal ones. The visual and verbal texts were documented in dialogues and analyzed considering theories of gender stereotypes using CDA. The results reveal that males are assigned lucrative and out-of-the-home jobs, like farmers (Beni's father) and teachers (Dayu's dad). In contrast, women are tied to household responsibilities, such as Lisa's mom being a housewife, which confirms the notion that women play a primary role in providing care. This study highlights the significance of employing gender-sensitive teaching strategies to enable EFL students to critically analyze stereotypes and form more expansive understandings of gender roles.
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 Afief Fakhruddin Agunawan Agunawan Eka Nurhidayat Nunung Suryati Rama Dwika Herdiawan Utami Widiati