Pelatihan Adaptif Berbasis Artificial Intelligence (AI) untuk Meningkatkan Hasil Belajar di Sekolah Menengah Kejuruan


  • Muhammad Syahrizal * Mail Politekni Cendana, Medan, Indonesia
  • (*) Corresponding Author
Keywords: Adaptive Training; Artificial Intelligence; Learning Outcomes; Vocational High Schools; Technology-Based Education

Abstract

This study aims to analyze the effectiveness of Artificial Intelligence (AI)-based adaptive training in improving student learning outcomes in Vocational High Schools (SMK). AI-based adaptive training is designed to provide a personalized learning experience by adjusting the level of difficulty and content of the material based on the individual needs of students. The research method used is a quasi-experiment with a pretest-posttest control group design. Data were collected through learning outcome tests, student perception questionnaires, and in-depth interviews. Participants consisted of vocational high school students majoring in engineering, who were divided into experimental and control groups. The results showed that students who took AI-based training experienced a significant increase in learning outcomes compared to the control group using conventional training methods. Specifically, the experimental group showed improvements in cognitive aspects, applications, and learning motivation. In addition, students responded positively to the implementation of AI technology, noting that this approach increased their understanding and engagement in learning. However, this study also identified challenges such as limited technological infrastructure in some schools and initial resistance to the use of new technologies. Therefore, this study recommends increasing technological literacy, developing technology-based education policies, and long-term evaluation of the effectiveness of AI-based training. The results of this study contribute to educational innovation in vocational schools to prepare students to face the challenges of the ever-evolving world of work.

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Article History
Submitted: 2025-01-27
Published: 2024-07-30
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