Implementation of an Artificial Intelligence–Based Learning System for the Personalization of Learning Materials at the Secondary School Level
DOI:
https://doi.org/10.35870/ijecs.v5i1.3994Keywords:
Artificial Intelligence, Adaptive Learning, Personalization, Student Engagement, Secondary EducationAbstract
The growing trend of artificial intelligence in secondary teaching has made schools rethink the conventional pedagogies that often overlook students’ diverse readiness levels, speeds, and learning preferences. This paper evaluated the effects of an AI-based learning system on achievement, engagement, and independent learning at three Indonesian secondary schools. It used a mixed-method design that combined quasi-experimental procedures with qualitative observations, interviews, and analysis of system-generated learning data. One hundred fifty students participated over one semester. The results revealed that adaptive features of the system contributed significantly to improvements in learning outcomes; average academic scores increased by 27% due to real-time feedback enabling students to fix mistakes faster than conventional lessons ever could. Participation rates increased by 35%, indicating more interactive systems keep attention better than teacher-centered instruction ever could. The platform further encouraged self-directed learning as shown by an increase in the ability to complete tasks without direct guidance from teachers—this rose by 42%. AI-generated classifications showed tendencies among learners which allowed the platform to recommend materials and pathways aligned with students' preferred formats and performance patterns. Teachers noted that it simplified progress monitoring and reduced manual differentiation work; students appreciated clarity and flexibility from personalized activities. However, challenges were noted: differences in tech readiness sometimes disrupted use of the system across schools and teachers need ongoing support to understand AI-generated insights so they can use them meaningfully in classroom routines. These findings speak both to potentiality as well as limitations about AI-supported instruction when it is realized within secondary education's practicalities. In sum, this study suggests that AI systems might reinforce personalization, engagement, and academic growth if sufficient infrastructure, continuous training, and careful alignment with curricular expectations support their implementation.
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