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Informatics education requires instructional designs that connect conceptual understanding with procedural application and contextual problem-solving. This study aimed to develop an Artificial Intelligence (AI)-integrated course based on Problem-Based Learning (PBL) to support these two competencies among junior high school students. The product was developed using the Moodle platform by combining digital learning materials, problem-based activities, and AI support in the form of explanations and learning-material summaries. The needs analysis involved 113 students, while the learning-outcome evaluation employed an experimental group and a control group, each consisting of 34 students, using pretests and posttests. The needs analysis revealed percentages of 23% for decomposition, 50% for pattern recognition, 35% for abstraction, and 44% for algorithms. In procedural application of computational thinking, the experimental group's mean score increased from 58.40 to 82.60, whereas the control group's mean score increased from 57.90 to 70.30. For contextual problem-solving, the experimental group's mean score increased from 56.80 to 83.10, while the control group's mean score rose from 57.20 to 71.40. Descriptively, the experimental group demonstrated greater improvement in both measured competencies. These findings indicate the potential of the developed AI-integrated PBL course to support Informatics learning; however, its statistical effectiveness must be confirmed through inferential testing. ABSTRAK Pembelajaran Informatika membutuhkan rancangan pembelajaran yang mampu menghubungkan pemahaman konsep dengan penerapan prosedur dan penyelesaian masalah kontekstual. Penelitian ini bertujuan mengembangkan course terintegrasi Artificial Intelligence (AI) berbasis Problem-Based Learning (PBL) untuk mendukung kedua kemampuan tersebut pada siswa SMP. Produk dikembangkan melalui platform Moodle dengan memadukan materi digital, aktivitas pemecahan masalah, serta dukungan AI berupa penjelasan dan rangkuman materi. Analisis kebutuhan melibatkan 113 siswa, sedangkan evaluasi hasil belajar menggunakan kelompok eksperimen dan kelompok kontrol, masing-masing terdiri atas 34 siswa, dengan pengukuran pretest dan posttest. Hasil analisis kebutuhan menunjukkan persentase kemampuan dekomposisi sebesar 23%, pengenalan pola 50%, abstraksi 35%, dan algoritma 44%. Pada kemampuan penerapan prosedur berpikir komputasional, rata-rata kelompok eksperimen meningkat dari 58,40 menjadi 82,60, sedangkan kelompok kontrol meningkat dari 57,90 menjadi 70,30. Pada kemampuan pemecahan masalah kontekstual, rata-rata kelompok eksperimen meningkat dari 56,80 menjadi 83,10, sementara kelompok kontrol meningkat dari 57,20 menjadi 71,40. Secara deskriptif, kelompok eksperimen menunjukkan peningkatan lebih besar pada kedua kemampuan yang diukur. Hasil ini mengindikasikan potensi course yang dikembangkan dalam mendukung pembelajaran Informatika, tetapi efektivitas statistiknya masih perlu dipastikan melalui pengujian inferensial.
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Cahyasari et al. (2026) studied this question.
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