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Usability of ChatGPT in the english essay writing proficiency of the BEED students Aglibot, Karl Alvin; Tomines, Edrian Mark; Talaman, Janel; Soguilon, Janabeth; Bongolto, Rowena; Abayon, Rhona Marielle
Journal of Science and Education (JSE) Vol. 4 No. 2 (2024): Journal of Science and Education (JSE)
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56003/jse.v4i2.338

Abstract

The advancement of AI technology, especially in language processing systems like ChatGPT, creates opportunities for students to elevate their writing skills. This study aimed to explore the relationship between the usability of ChatGPT and the English essay writing proficiency of the BEED students. The study utilized a descriptive correlational design to investigate the relationship. A sample of 58 participants was selected to write an essay with the assistance of ChatGPT. Researchers developed and employed a rubric to assess the quality and ethical use of ChatGPT. Then, the participants answered the USE questionnaire to measure their perceived usability of ChatGPT. The result revealed that BEED students perceived ChatGPT as beneficial in enhancing their essays and found the system easy to use, and learn, and provided satisfying results. The participants also expressed a strong sense of contentment regarding using ChatGPT. The essay writing proficiency assessment revealed that BEED students were proficient writers. However, a Pearson correlation coefficient of 0.042 showed a statistically significant but very weak relationship observed between ChatGPT usability and English essay writing proficiency levels. It can be concluded that ChatGPT may improve students' essay writing proficiency to a minimal extent. Moreover, this study recommended further research to explore ChatGPT's use in other academic outputs, refine the rubrics to include vocabulary, grammar, and sentence structure criteria, and provide training for effective AI tool management among students. Also, policymakers should establish clear policies and guidelines to ensure the responsible and ethical use of ChatGPT, maintaining academic integrity and enhancing writing proficiency.
The future of teaching: Analyzing the interplay between AI literacy and TPACK among BEED pre-service teachers Aglibot, Karl Alvin; Rito, Chelsea Lorraine; Villalon, Larence; Gampal , Nelvin
Journal of Artificial Intelligence in Education & Learning Innovation Vol. 1 No. 1 (2025): Journal of Artificial Intelligence in Education & Learning Innovation
Publisher : CV Rezki Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56003/jaieli.v1i1.570

Abstract

Background: As artificial intelligence (AI) continues transforming the educational landscape, pre-service teachers must develop theoretical understanding and practical skills in AI integration. Objectives: This study explored the relationship between AI literacy and TPACK among 139 BEED pre-service teachers. Methods: Using descriptive statistics, Spearman's correlation, and multiple linear regression analysis, the study investigated how components of AI literacy relate to TPACK. Results: Results revealed that the pre-service teachers demonstrated high levels of AI literacy, particularly in ethical awareness and intrinsic motivation. Pre-service teachers expressed strong interest in AI's educational potential and a commitment to its responsible use. While their foundational AI knowledge was high, many reported moderate self-efficacy and lacked confidence in executing AI-related tasks. Gaps were also noted in applying AI concepts to real-world teaching scenarios and designing AI-driven solutions. Furthermore, the results showed high TPACK proficiency, with strength in pedagogical and technological knowledge, though weaknesses were observed in content areas like mathematics and technical troubleshooting. A moderate positive correlation (Spearman's ρ = 0.48, p < 0.05) between AI literacy and TPACK indicates a meaningful association. Regression analysis revealed that AI literacy components explained 25.5% of the variance in TPACK. Cognitive learning emerged as the only significant predictor. Conclusions: The findings underscore the need for teacher education programs to provide hands-on, cognitive-focused AI training. Hence, enhancing pre-service teachers' cognitive and practical skills is essential to thoroughly preparing them for AI-enhanced teaching environments' demands.