Optimizing the Effectiveness of High School Student Learning through the Utilization of Artificial Intelligence (AI) Tools
Abstract
The rapid development of Artificial Intelligence (AI) technology has brought significant transformations in various sectors, including high school education. In the modern educational landscape, AI is no longer merely a futuristic discourse, but a practical instrument that has penetrated classrooms. However, the use of AI among high school students is often limited to superficial uses and is vulnerable to academic ethics violations such as plagiarism. This Community Service (PkM) activity aims to provide high school students with understanding and practical skills in optimizing learning effectiveness through the wise and systematic use of various Artificial Intelligence tools. The implementation method used in this activity is a participatory education method that includes four main stages: the needs identification stage, Socialization regarding ethics and concepts, a hands-on workshop on the use of AI productivity tools, and Evaluation. Through this activity, students are given an understanding of prompt engineering techniques to be able to produce relevant and accurate AI output to support research and the preparation of school presentation materials. The results of this PkM activity are expected to improve students' digital literacy. Furthermore, this PkM aims to shift students' paradigms to position AI as a cognitive assistant that supports critical thinking, rather than as a quick-fix tool to replace original work. The findings of this activity demonstrate that integrating AI into the informal school curriculum can create a more efficient, adaptive, and innovative learning ecosystem for students in the digital age.
Fields of Study & Subjects
Technology-Enhanced Education Studies
Educational Curriculum and Learning Methods
Blockchain Technology in Education and Learning
Publication details
- Journal / source
- Jurnal Pemberdayaan Komunitas MH Thamrin
- Volume
- 7
- Issue
- 2
- Pages
- 538–547
- Publication date
- 9 January 2026