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Implementasi Pendekatan PDIA dalam Meningkatkan Motivasi Belajar dan Kemampuan Berpikir Komputasional Siswa SMK Kelas X pada Mata Pelajaran Koding dan Kecerdasan Artifisial Laela Muliana; Tri Rijanto; Luthfiyah Nurlaela; I Gusti Putu Asto Buditjahjanto; Rommy Mochamad Ramdhani
DIAJAR: Jurnal Pendidikan dan Pembelajaran Vol. 5 No. 2 (2026): April 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/diajar.v5i2.6499

Abstract

This study aims to enhance the learning motivation and computational thinking skills of grade X SMK (Vocational High School) students in the subjects of Coding and Artificial Intelligence through the implementation of the Problem Driven Iterative Adaptation (PDIA) approach. Conducted as a Classroom Action Research (PTK) at SMKN 1 Penajam Paser Utara during the 2025/2026 academic year with 36 student participants, the study utilized the Kemmis and McTaggart action research model, which consists of planning based on identifying real-world problems, implementing contextual problem-solving activities, observation using instruments, questionnaires, and computational thinking tests, as well as in-depth reflection to evaluate and refine subsequent actions, carried out over two cycles. Data collection techniques included observation, learning motivation questionnaires, and computational thinking ability tests. The results indicate that the application of the PDIA approach significantly improved students' learning motivation and computational thinking skills. Student learning mastery increased from 50% in the pre-action phase to 63.89% in Cycle I, and further rose to 91.67% in Cycle II, with the class average score reaching 82.58. Additionally, student learning motivation showed improvement, marked by increased activity, enthusiasm, and engagement in the learning process. Therefore, it can be concluded that the PDIA approach is effective in enhancing both learning motivation and computational thinking skills among students in the subjects of Coding and Artificial Intelligence.