Implementasi Problem-Based Learning Dan Deep Knowledge Tracing Dalam Pembelajaran Pemrograman Dasar Untuk Meningkatkan Kompetensi Junior Programmer

Abstract

Object-Oriented Programming (OOP) learning in vocational high schools often faces challenges in improving students’ problem-solving skills and monitoring their learning progress. This study aimed to analyze the effectiveness of implementing Problem-Based Learning (PBL) supported by Deep Knowledge Tracing (DKT) in improving junior programmer competencies. A pre-experimental method with a One Group Pretest–Posttest Design was employed involving 36 tenth-grade Software Engineering students at SMKN 10 Surabaya. Learning activities were conducted through the Skill Byte Learning Management System (LMS), which facilitated PBL activities and DKT-based learning analytics. Data were collected through pretest-posttest assessments, observations, and documentation, then analyzed using descriptive statistics, the Shapiro–Wilk normality test, and the Paired Sample t-Test. The results showed that the average cognitive score increased from 50.15 to 84.44, while the statistical test indicated a significance value of 0.000 (p < 0.05). These findings demonstrate that implementing PBL supported by DKT effectively improves students’ competencies and assists teachers in monitoring learning progress through learning analytics. Therefore, this approach provides a more active, adaptive, and student-centered programming learning environment.