Al-Hijr: Journal of Adulearn World

Personalized Learning through ChatGPT: A Quasi-Experimental Study on Adaptive Curriculum in High School Settings

Muhammad Muhammad, Zain Nizam, Faisal Razak — Mon, 18 Aug 2025 00:00:00 +0700

The challenge of catering to diverse learning paces and styles in traditional high school classrooms often limits student potential. The emergence of advanced AI, such as ChatGPT, presents a novel opportunity to create adaptive learning environments that personalize educational content in real-time. This study aimed to investigate the effectiveness of a ChatGPT-driven adaptive curriculum on student academic performance and engagement compared to conventional, non-adaptive teaching methods. A quasi-experimental, pre-test/post-test design was conducted with 110 high school students. The intervention group (n=55) utilized an adaptive curriculum where content was dynamically adjusted by ChatGPT based on performance, while the control group (n=55) received standard instruction. Academic performance was measured via subject-specific tests, and engagement was assessed using the Student Engagement Instrument (SEI). The intervention group demonstrated a statistically significant improvement in academic performance (p < .01) and higher engagement scores (p < .05) compared to the control group. The adaptive curriculum effectively addressed individual learning gaps and maintained student interest. Integrating ChatGPT to facilitate personalized, adaptive curricula is a highly effective strategy for enhancing both academic achievement and student engagement in high school settings. This approach offers a scalable solution to individualized instruction.

AI-Driven Feedback Systems for Formative Assessment: Toward Personalized and Real-Time Pedagogy

Reza Oktiana Abar, Ming Pong, Rit Som — Mon, 18 Aug 2025 00:00:00 +0700

The provision of timely and personalized formative feedback is a cornerstone of effective pedagogy, yet it remains a significant challenge in conventional classroom settings due to large class sizes and time constraints. AI-driven feedback systems offer a scalable solution to this long-standing pedagogical problem. This study aimed to evaluate the impact of a real-time, AI-driven feedback system on students’ academic performance, error correction, and development of self-regulation skills during formative assessment tasks. A quasi-experimental study was conducted with 90 undergraduate students. The intervention group (n=45) received instant, personalized feedback from an AI system on their assignments, while the control group (n=45) received traditional, delayed feedback from instructors. Performance was measured by assignment scores and error reduction rates. The intervention group demonstrated significantly higher improvement in assignment scores and a faster rate of error correction compared to the control group. Furthermore, qualitative analysis of student reflections indicated enhanced self-regulation and metacognitive awareness among students using the AI system. AI-driven feedback systems are powerful tools that enhance formative assessment by providing personalized, real-time pedagogical support. This approach not only improves academic performance but also fosters crucial self-regulation skills for lifelong learning.

The Ethics of AI in Education: An Empirical Study on Students’ and Teachers’ Attitudes toward Responsible AI Use

Nofirman Nofirman, Rithy Vann, Levy Sefrizal, Ravi Dara — Mon, 18 Aug 2025 00:00:00 +0700

The rapid integration of artificial intelligence (AI) into educational settings has outpaced the development of clear ethical guidelines, creating significant challenges related to academic integrity, data privacy, and algorithmic bias. Understanding stakeholder attitudes is crucial for developing effective policies for responsible AI use. This study aimed to empirically investigate and compare the attitudes of high school students and teachers regarding the ethical challenges and responsible use of AI in education. A mixed-methods approach was employed, using a quantitative survey administered to 250 students and 50 teachers to gauge attitudes toward AI ethics. This was supplemented by qualitative data from semi-structured focus groups to explore the reasoning behind these attitudes. The findings revealed a significant divergence in attitudes, with teachers expressing greater concern for academic integrity and data privacy, while students were more focused on AI as a tool for efficiency. Both groups, however, demonstrated a shared desire for clear, explicit ethical guidelines. A notable gap exists between student and teacher perspectives on AI ethics in education. To foster a culture of responsible AI use, educational institutions must implement comprehensive training and develop clear policies that address the distinct concerns of both stakeholder groups.

Digital Storytelling with Generative AI: Impact on Creativity and Engagement in Middle School Learners

Fauzi Aldina, Raul Gomez, Livia Alves — Mon, 18 Aug 2025 00:00:00 +0700

Digital storytelling is a proven pedagogy for fostering student expression, but its potential is being redefined by generative artificial intelligence (AI). While AI offers unprecedented tools for creating visual and narrative assets, its specific impact on the creativity and engagement of middle school learners requires empirical investigation. This study aimed to evaluate the impact of integrating generative AI into digital storytelling projects on the creativity and engagement levels of middle school students compared to traditional digital methods. A quasi-experimental, pre-test/post-test design was conducted with 120 middle school students. The intervention group used generative AI tools to create story assets, while the control group used standard digital tools. Creativity was assessed using a standardized rubric, and engagement was measured with the Student Engagement Instrument (SEI). The intervention group showed statistically significant gains in creativity metrics, particularly in originality and elaboration (p < .01). This group also reported significantly higher levels of cognitive and behavioral engagement compared to the control group (p < .05). Integrating generative AI into digital storytelling projects serves as a powerful catalyst, enhancing both the creative output and the active engagement of middle school learners. The technology acts as a creative partner, enabling students to realize more ambitious narrative visions.