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This is a Quantitative Study study.

October 23, 2025

AI- Assisted scaffolding: AI Implementation in English Speaking Communication

Key Points

Students using AI in Project-Based Learning achieved a significantly higher mean speaking score of 82.00 compared to 72.00 in the control group.
Data analysis employed descriptive statistics and normality testing to verify the effectiveness of AI integration.
Integration of Artificial Intelligence in Project-Based Learning promotes learner autonomy and creates engaging environments for speaking practice.
Study highlights the need for extended practice and teacher facilitation for optimal outcomes in AI-assisted learning.

Abstract

This study investigates the impact of integrating Artificial Intelligence (AI) into a Project-Based Learning (PjBL) model to enhance students’ English speaking skills. Recognizing the persistent challenges in providing sufficient speaking practice opportunities in conventional classrooms, this research employed AI-based applications, including Character AI, TikTok, and video editing tools, to create an interactive and personalized speaking environment. This study examines the integration of Artificial Intelligence (AI) into a Project-Based Learning (PjBL) model to enhance students’ English speaking skills. The research was motivated by the limited opportunities for speaking practice in conventional classrooms. AI-based applications such as Character AI, TikTok, and video editing tools were employed to create an interactive and personalized learning environment. A total of 60 students participated in the study, divided into a control group applying conventional PjBL and an experimental group applying AI-assisted PjBLThe study involved 60 students divided into two groups: a control group applying conventional PjBL and an experimental group using AI-assisted PjBL. Data were collected through pre- and post-tests and analyzed using SPSS with descriptive statistics, normality testing, and independent samples t-test. The results revealed that the AI-assisted PjBL group achieved a higher mean speaking score (M = 82.00, SD = 6.103) compared to the control group (M = 72.00, SD = 5.038), with a statistically significant difference (t = 6.922, p < 0.05). These findings indicate that integrating AI in PjBL can significantly improve students’ speaking performance by providing adaptive feedback, increasing learner autonomy, and creating more authentic speaking practice opportunities. However, the study also highlights limitations, including restricted AI platforms and a relatively short experiment duration. The findings suggest that AI-assisted PjBL is a promising approach for enhancing speaking skills in higher education, but it should be complemented with extended practice and teacher facilitation to achieve optimal outcomes.

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