Effectiveness of Integrating Deep Learning into Problem-Based Learning with PhET Simulations to Enhance Students’ Problem-Solving Skills

Problem-solving skills are widely recognized as essential competencies in physics education and central to preparing students for the demands of twenty-first-century learning. However, students often struggle to connect abstract physics concepts with real-world applications when learning is dominated by conventional approaches that emphasize rote memorization rather than critical engagement. To address this gap, this study investigated the effectiveness of integrating a deep learning approach into the Problem-Based Learning (PBL) model supported by PhET interactive simulations in enhancing students’ problem-solving skills. The research employed a pre-experimental one-group pretest–posttest design involving 15 eleventh-grade students at SMA Sultan Agung 1 Semarang. Students completed validated problem-solving assessments covering five dimensions: reading, comprehension, transformation, process skills, and encoding. The results revealed a significant increase in mean scores from 57 on the pretest to 81 on the posttest, representing an improvement of 24 points (42.1%) and yielding a normalized gain (N-Gain) of 0.63, categorized as moderate. Dimension-level analysis showed consistent improvement across all aspects, with the largest gains observed in transformation and encoding, highlighting enhanced higher-order thinking, reflective reasoning, and metacognitive awareness. The novelty of this research lies in combining deep learning strategies, PBL, and PhET simulations in a unified instructional framework, which has rarely been explored in physics education. The findings demonstrate that this integrated approach not only strengthens students’ ability to analyze and solve problems but also fosters meaningful conceptual understanding by linking theory with observable phenomena. This study contributes to the field of physics education by providing empirical evidence and a practical model that aligns with constructivist principles, offering guidance for teachers and researchers in developing innovative instructional designs to comprehensively improve problem-solving skills.

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Publication Details

Journal
Jurnal Pendidikan Fisika
Published
2025-09-30
DOI
https://doi.org/10.26618/ttrea958
Primary Topic
Technology-Enhanced Education Studies
Type
article
Field-Weighted Citation Impact
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article

Effectiveness of Integrating Deep Learning into Problem-Based Learning with PhET Simulations to Enhance Students’ Problem-Solving Skills

Sigit Ristanto, Nur Khoiri, Affandi Faisal Kurniawan, Emila Luthfia Sofa et al.
Jurnal Pendidikan Fisika
Technology-Enhanced Education Studies
article

Effectiveness of Integrating Deep Learning into Problem-Based Learning with PhET Simulations to Enhance Students’ Problem-Solving Skills

Sigit Ristanto, Nur Khoiri, Affandi Faisal Kurniawan, Emila Luthfia Sofa, Ernawati Saptanigrum
article en

Abstract

Problem-solving skills are widely recognized as essential competencies in physics education and central to preparing students for the demands of twenty-first-century learning. However, students often struggle to connect abstract physics concepts with real-world applications when learning is dominated by conventional approaches that emphasize rote memorization rather than critical engagement. To address this gap, this study investigated the effectiveness of integrating a deep learning approach into the Problem-Based Learning (PBL) model supported by PhET interactive simulations in enhancing students’ problem-solving skills. The research employed a pre-experimental one-group pretest–posttest design involving 15 eleventh-grade students at SMA Sultan Agung 1 Semarang. Students completed validated problem-solving assessments covering five dimensions: reading, comprehension, transformation, process skills, and encoding. The results revealed a significant increase in mean scores from 57 on the pretest to 81 on the posttest, representing an improvement of 24 points (42.1%) and yielding a normalized gain (N-Gain) of 0.63, categorized as moderate. Dimension-level analysis showed consistent improvement across all aspects, with the largest gains observed in transformation and encoding, highlighting enhanced higher-order thinking, reflective reasoning, and metacognitive awareness. The novelty of this research lies in combining deep learning strategies, PBL, and PhET simulations in a unified instructional framework, which has rarely been explored in physics education. The findings demonstrate that this integrated approach not only strengthens students’ ability to analyze and solve problems but also fosters meaningful conceptual understanding by linking theory with observable phenomena. This study contributes to the field of physics education by providing empirical evidence and a practical model that aligns with constructivist principles, offering guidance for teachers and researchers in developing innovative instructional designs to comprehensively improve problem-solving skills.

Jurnal Pendidikan FisikaVol. 13(3)
Universitas PGRI Semarang (ID)
Openalex Percentile: Top 69%
Technology-Enhanced Education Studies
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