Jurnal Inovasi Fisika dan Edukasi (Journal of Physics Innovation and Education) is a scientific journal published by the Institute of Educational, Research, and Community Service (inercys). This journal aims to serve as an academic platform for the publication of research articles, literature reviews, theoretical studies, and innovative developments in the fields of physics and physics education. Its primary focus includes the advancement of concepts, approaches, and technologies in physics learning, as well as other scientific contributions intended to improve the quality of physics education at various educational levels. The journal welcomes submissions from researchers, lecturers, teachers, students, and education practitioners who are interested in innovations in physics and physics education. Jurnal Inovasi Fisika dan Edukasi is published twice a year, in June and December, and has been in publication since 2025. All submitted articles undergo a rigorous peer-review process to ensure their scientific quality and academic contribution.
INERCYS: Institute of Educational, Research, and Community Service
EXPLORATION OF AN ANDROID-BASED MYOPIA DETECTION AND PREVENTION SYSTEM IN CHILDREN USING THE EXTREME LEARNING MACHINE METHOD WITH A RISK FACTOR ANALYSIS AND EYE EXERCISE THERAPY APPROACH
Myopia, or nearsightedness, is a visual impairment whose prevalence continues to increase, particularly among children. This condition is influenced by both genetic and environmental factors, such as excessive use of digital devices and insufficient outdoor activities. These challenges highlight the need for solutions that not only enable early detection but also provide effective preventive measures. This study aims to explore an Android-based system for the detection and prevention of myopia in children using the Extreme Learning Machine (ELM) method, combined with a risk factor analysis approach and eye exercise therapy. The research employs a qualitative method with a library research approach, utilizing various relevant scientific sources, including journals, books, and conference proceedings. Data were collected through systematic searches in academic databases using keywords aligned with the research variables, followed by a selection process based on relevance and source credibility. Data analysis was conducted using content analysis techniques, which involved stages of data reduction, categorization, synthesis, and inductive conclusion drawing. The findings indicate that the Extreme Learning Machine method demonstrates high accuracy and efficient processing speed in detecting myopia, while the Android platform offers accessibility and ease of use for users. The primary risk factors identified include excessive screen time and limited outdoor activity. Furthermore, eye exercise therapy has been shown to improve visual acuity and reduce eye strain. The integration of these components results in a comprehensive system that functions not only as a detection tool but also as an educational and preventive medium. This study contributes to the field of education by providing a technology-based health education tool and to the scientific community through the advancement of artificial intelligence applications in healthcare. Future research is recommended to extend this study through experimental approaches or direct system implementation to empirically evaluate its effectiveness in real-world settings.
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THE EFFECT OF STEM-BASED PHYSICS LEARNING ON STUDENT CREATIVITY AND PROBLEM SOLVING
STEM (Science, Technology, Engineering, and Mathematics)-based learning constitutes a critical aspect of physics education as it enables the holistic integration of multiple disciplines to foster 21st-century competencies. However, the low levels of students’ creativity and problem-solving skills in physics learning remain fundamental issues that require immediate attention. This challenge underscores the need for further investigation into the effectiveness of STEM-based learning in enhancing students’ creativity and problem-solving abilities. This study aims to analyze the effect of STEM-based physics learning on the creativity and problem-solving skills of senior high school students. The research employed a quasi-experimental method with a pretest–posttest control group design. Data were collected using a creativity assessment rubric and problem-solving ability tests validated by two expert lecturers. The collected data were analyzed using the Independent t-test and N-Gain test. The findings reveal a significant difference between the experimental and control groups in terms of creativity (sig. = 0.001; t = 5.41) and problem-solving skills (sig. = 0.002; t = 4.87). The N-Gain scores in the experimental group reached 0.54 for creativity and 0.49 for problem-solving skills, both categorized as moderate, whereas the control group only achieved low categories. These results indicate that STEM-based learning is effective in enhancing students’ competencies. This study provides a significant contribution to the advancement of physics education at both national and international levels through the reinforcement of innovative STEM-based instructional models. Furthermore, the findings are expected to serve as a reference for future research, particularly in the development of instructional strategies aimed at improving creativity and problem-solving skills, as well as to encourage more in-depth and applicable follow-up studies.
THE EFFECT OF USING INTERACTIVE LEARNING VIDEOS ON MOTIVATION AND PHYSICS LEARNING OUTCOMES
The use of story-based instructional video represents a crucial aspect of physics education because students often encounter difficulties in understanding abstract concepts, leading to low conceptual comprehension and suboptimal learning outcomes. This issue necessitates further investigation into the effectiveness of integrating storytelling elements within video-based learning to enhance students’ conceptual understanding. This study aims to examine the effect of story-based learning videos on students’ conceptual understanding in physics. The research employed a quantitative approach using a quasi-experimental method with a pretest–posttest control group design. Data were collected through conceptual understanding tests, supported by observation and documentation. The obtained data were analyzed using descriptive statistics and inferential analysis, including the t-test and N-gain calculation. The findings reveal that students taught using story-based instructional videos demonstrated a significant improvement in conceptual understanding, as evidenced by an increase in the mean score from 63.20 to 84.10 and an N-gain value of 0.72, categorized as high, along with a statistically significant difference between the experimental and control groups. These results indicate that the integration of storytelling in video-based learning effectively enhances students’ comprehension of abstract physics concepts and promotes more meaningful learning experiences. This study contributes significantly to the advancement of physics education at both national and international levels by providing an innovative, technology-enhanced pedagogical approach that supports interactive and engaging learning environments. Furthermore, the findings are expected to serve as a valuable reference for future research, particularly in the development of multimedia-based instructional strategies and the exploration of their long-term impact on conceptual understanding and higher-order thinking skills.
THE INFLUENCE OF STORY-BASED INSTRUCTIONAL VIDEOS ON STUDENTS' UNDERSTANDING OF PHYSICS CONCEPTS
Story-based learning videos constitute an important aspect of physics education, as many students still perceive physics as a difficult and abstract subject, leading to low levels of conceptual understanding and learning motivation. This condition highlights the need for further research focusing on the use of innovative and engaging instructional media to enhance students’ comprehension of physics concepts. This study aims to examine the effect of story-based learning videos on students’ conceptual understanding in physics. The research employed a quantitative method with an experimental approach, using a quasi-experimental design in the form of a pretest–posttest control group design. Data were collected through conceptual understanding tests, observation sheets, and documentation, and were analyzed using descriptive statistics, an independent samples t-test, and N-gain analysis. The findings reveal that students in the experimental group showed a significant improvement in conceptual understanding, with the mean score increasing from 63.20 to 84.10 and an N-gain value of 0.72 (high category), while the control group achieved an N-gain of 0.41 (medium category). Furthermore, the t-test result yielded a significance value of 0.001 < 0.05, indicating a statistically significant difference between the two groups, thereby demonstrating that story-based learning videos are effective in improving students’ conceptual understanding in physics. This study provides a significant contribution to the advancement of physics education at both national and international levels through the integration of innovative multimedia-based learning approaches that enhance student engagement, conceptual understanding, and learning outcomes. In addition, the findings offer valuable insights into the application of storytelling techniques in science education as an effective pedagogical strategy and are expected to serve as a reference for future research, particularly in the areas of technology-enhanced learning and concept mastery, while encouraging more in-depth and applied studies in related fields.
THE EFFECT OF PHET SIMULATION-BASED LEARNING ON STUDENTS’ CONCEPTUAL UNDERSTANDING IN PHYSICS
PhET simulation-based learning represents an important aspect of physics education because it addresses persistent challenges related to students’ low conceptual understanding and the abstract nature of many physics topics. This issue highlights the need for further investigation into the effectiveness of interactive digital media in improving students’ conceptual mastery. This study aims to analyze the effect of PhET simulation-based learning on students’ conceptual understanding in physics. The research employed a quantitative approach with a quasi-experimental method, using a non-equivalent control group design. Data were collected through pre-test and post-test instruments to measure students’ conceptual understanding. The collected data were analyzed using descriptive statistics, N-gain analysis, and an independent sample t-test. The results indicate that students in the experimental class experienced a significant improvement, with mean scores increasing from 61.20 to 83.45 and an N-gain value of 0.70 (high category), while the control class showed an increase from 60.75 to 71.30 with an N-gain value of 0.35 (medium category). Furthermore, the independent sample t-test yielded a significance value of 0.000 < 0.05, confirming a statistically significant difference between the two groups. These findings demonstrate that PhET simulation-based learning effectively enhances students’ conceptual understanding by facilitating interactive visualization and promoting active learning. This study contributes significantly to the advancement of physics education at both national and international levels by offering an innovative instructional strategy grounded in digital technology integration. Additionally, the findings are expected to serve as a valuable reference for future research, particularly in the areas of technology-enhanced learning and conceptual understanding in physics, and to encourage more in-depth and applied studies in related fields.
THE IMPACT OF THE STEM LEARNING MODEL ON STUDENTS’ SCIENCE PROCESS SKILLS AND CRITICAL THINKING SKILLS IN PHYSICS EDUCATION
The development of science process skills and critical thinking skills is a crucial aspect of physics education, as these competencies are essential for preparing students to face the challenges of 21st-century learning and to solve scientific problems effectively. This issue highlights the need for further research on the effectiveness of implementing STEM-based learning models in enhancing students’ higher-order thinking skills. This study aims to analyze the effect of the STEM learning model on students’ science process skills and critical thinking skills in physics learning. The research employed a quantitative approach using a quasi-experimental method with a pretest–posttest control group design. Data were collected through tests and observation sheets designed to measure science process skills and critical thinking skills based on higher-order thinking indicators. The collected data were analyzed using descriptive statistics, independent samples t-test, and normalized gain (N-gain) analysis. The results indicate that the implementation of the STEM learning model significantly improves students’ science process skills and critical thinking skills, as evidenced by the differences in posttest mean scores between the experimental and control groups and N-gain values in the medium to high categories. These findings suggest that STEM-based learning is effective in fostering higher-order thinking skills. This study provides a significant contribution to the development of physics education at both national and international levels through the implementation of innovative, student-centered, and interdisciplinary learning models that support the development of 21st-century skills. Furthermore, the findings are expected to serve as a reference for future research, particularly in the development of STEM-based learning models and the enhancement of higher-order thinking skills, as well as to encourage more in-depth and applicable subsequent studies.
THE EFFECT OF PHYSICS LEARNING USING FUTURE SELF DIGITAL AVATARS ON STUDENTS' MOTIVATION AND LEARNING RESILIENCE
Physics learning using future self digital avatars constitutes an important aspect of physics education because traditional instructional approaches often fail to sustain students’ motivation and resilience in facing challenging concepts and problem-solving tasks. This limitation highlights the need for further research focusing on innovative digital strategies that leverage self-representative avatars to enhance learning engagement and perseverance. This study aims to examine the effect of physics learning mediated by future self digital avatars on students’ motivation and learning resilience. The research employed a quantitative approach with an experimental method and a quasi-experimental design involving an experimental group and a control group. Data were collected using standardized motivation questionnaires, learning resilience scales, and instructional documentation. The collected data were analyzed using descriptive statistics and inferential analysis through independent samples t-tests. The results indicate that students who participated in physics learning using future self digital avatars demonstrated significantly higher motivation scores (M = 82.4; SD = 5.9) and learning resilience (M = 79.6; SD = 6.3) compared to the control group (motivation: M = 70.2; SD = 7.1; resilience: M = 68.5; SD = 7.8), with statistically significant differences (motivation: t(58) = 6.12, p < 0.001; resilience: t(58) = 5.87, p < 0.001) and strong effect sizes (Cohen’s d = 0.90 and 0.88, respectively). These findings suggest that integrating future self digital avatars into physics learning effectively strengthens students’ intrinsic motivation and their capacity to persist through challenging learning tasks. The study provides significant contributions to the advancement of physics education at both national and international levels by offering an innovative pedagogical model that combines digital self-representation, motivational scaffolding, and resilience-building strategies. Furthermore, the findings are expected to serve as a reference for future research on digital avatar–mediated learning, student motivation, and resilience in science education, as well as to encourage further development of immersive and personalized instructional approaches.
Copyright (c) 2025 Jurnal Inovasi Fisika dan Edukasi
QUANTUM STORYTELLING ARTIFICIAL INTELLIGENCE (AI) BASED PHYSICS LEARNING TO ENHANCE STUDENTS' CONCEPTUAL INTUITION ON NON-CLASSICAL PHENOMENA
Quantum storytelling artificial intelligence–based physics learning is an important aspect of physics education because conventional instructional approaches often fail to support students in developing strong conceptual intuition toward non-classical phenomena that are abstract, probabilistic, and counterintuitive, such as superposition, entanglement, and the quantum uncertainty principle. This limitation highlights the need for further research focusing on innovative instructional strategies that integrate artificial intelligence–driven narrative approaches to bridge students’ conceptual understanding of quantum phenomena. This study aims to examine the effectiveness of quantum storytelling–based physics learning supported by artificial intelligence in enhancing students’ conceptual intuition of non-classical phenomena. The research employed an experimental method with a quasi-experimental design involving an experimental group and a control group. Data were collected through quantum conceptual intuition tests, learning engagement observation sheets, and instructional documentation. The collected data were analyzed using descriptive statistics and inferential analysis through an independent samples t-test. The results indicate that students in the experimental group achieved significantly higher conceptual intuition scores (M = 83.7; SD = 6.4) than those in the control group (M = 70.9; SD = 7.6), with a statistically significant difference (t(58) = 5.61, p < 0.001) and a strong effect size (Cohen’s d = 0.86). These findings demonstrate that the integration of quantum storytelling supported by artificial intelligence effectively strengthens students’ conceptual intuition through narrative, visual, and reflective representations aligned with quantum physics principles. This study provides a significant contribution to the advancement of physics education at both national and international levels by proposing an innovative artificial intelligence–based narrative learning model for non-classical physics instruction. Furthermore, the findings are expected to serve as a reference for future research in quantum physics education, artificial intelligence–supported science learning, and studies on conceptual intuition in abstract physics domains.
Artificial Intelligence In Physics Education
A PRELIMINARY STUDY OF PHYSICS LEARNING THROUGH THE INTEGRATION OF MULTIVERSE NARRATIVE AND HYPOTHETICAL PHYSICS MODELING IN ENHANCING STUDENTS' SCIENTIFIC IMAGINATION
Physics learning through the integration of multiverse narrative and hypothetical physics modeling constitutes an important aspect of physics education because conventional instructional approaches often limit students’ scientific imagination and their ability to explore abstract, speculative, and frontier concepts in modern physics. This limitation highlights the need for further research focusing on instructional strategies that explicitly promote imaginative reasoning while preserving scientific rigor. This preliminary study aims to examine the effectiveness of integrating multiverse narratives with hypothetical physics modeling in enhancing students’ scientific imagination and learning engagement in physics. The study employed an experimental method with a quasi-experimental design involving an experimental group and a control group. Data were collected using scientific imagination assessment tests, learning engagement observation sheets, and instructional documentation, and were analyzed through descriptive statistics and inferential analysis using an independent samples t-test. The results reveal that students in the experimental group demonstrated significantly higher scientific imagination scores (M = 84.2; SD = 6.5) compared to the control group (M = 71.6; SD = 7.3), with a statistically significant difference (t(58) = 5.72, p < 0.001) and a strong effect size (Cohen’s d = 0.88). In addition, learning engagement in the experimental group was categorized as high (M = 4.21) relative to the control group (M = 3.36), indicating more active participation in exploratory discussion, conceptual speculation, and reflective reasoning. These findings illustrate that the integration of multiverse narratives with hypothetical physics modeling effectively fosters scientific imagination and cognitive engagement by providing a structured space for speculative yet theory-informed thinking. This study contributes significantly to the advancement of physics education at both national and international levels by proposing an innovative pedagogical framework that bridges narrative-based learning, theoretical modeling, and imaginative science education. Furthermore, the findings are expected to serve as a reference for future research on creative physics instruction, speculative science learning, and interdisciplinary approaches that support the development of higher-order thinking skills in 21st-century physics education.
PHYSICS LEARNING BASED ON CONCEPTUAL ERROR PREDICTION USING LARGE LANGUAGE MODEL AS A COGNITIVE ASSISTANT FOR SCHOOL STUDENTS
Physics learning based on the prediction of conceptual errors is a critical aspect of physics education, as persistent student misconceptions often hinder the development of deep conceptual understanding. This challenge highlights the need for adaptive learning approaches capable of identifying and anticipating students’ conceptual errors at an early stage. This study aims to examine the effectiveness of implementing a Large Language Model as a cognitive assistant in predicting conceptual errors and enhancing students’ conceptual understanding and learning engagement. The research employed an experimental method with a quasi-experimental design. Data were collected through conceptual understanding tests, learning engagement observation sheets, and instructional documentation, and were analyzed using descriptive statistics and inferential analysis through an independent samples t-test. The results indicate that the experimental group achieved a higher mean post-test score in conceptual understanding than the control group (M = 81.9; SD = 6.7 vs. M = 68.1; SD = 7.4), with a statistically significant difference (t(58) = 6.05, p < 0.001) and a strong effect size (Cohen’s d = 0.93). In addition, the level of conceptual errors among students in the experimental group decreased significantly, while learning engagement was classified as high (M = 4.18) compared to the control group (M = 3.34). These findings demonstrate that a Large Language Model can function effectively as a cognitive assistant by predicting patterns of conceptual errors and providing adaptive scaffolding in real time. This study makes a significant contribution to the development of artificial intelligence–based physics learning models, extends the application of constructivist theory and cognitive load theory within intelligent digital learning environments, and enriches the international literature on the use of Large Language Models in science education. Furthermore, the findings are expected to serve as a reference for the development of adaptive physics learning and for future research on integrating Large Language Models as pedagogical agents at the school level.
EXPLORATION OF PHYSICS LEARNING USING ADAPTIVE ARTIFICIAL INTELLIGENCE-BASED VIRTUAL UNIVERSE SIMULATION MODELS FOR SCHOOL STUDENTS
The exploration of physics learning using an adaptive artificial intelligence–based virtual universe simulation model represents an important aspect of physics education due to the limitations of conventional instruction in visualizing abstract and multiscale physical phenomena. This challenge highlights the need for experimental research that empirically examines the effectiveness of adaptive virtual simulation models in improving students’ conceptual understanding of physics. This study aims to analyze the impact of implementing an adaptive artificial intelligence–based virtual universe simulation on students’ conceptual understanding and learning engagement in school physics. The research employed an experimental method with a quasi-experimental design involving an experimental group and a control group. Data were collected through conceptual understanding tests, learning activity observation sheets, and student engagement questionnaires. The collected data were analyzed using descriptive statistics and independent samples t-tests. The results indicate that students who learned through adaptive virtual simulations achieved a statistically significant improvement in conceptual understanding scores (p < 0.05), with an average increase of more than 20% compared to the control group. These findings suggest that adaptive virtual universe simulation–based physics learning is effective in enhancing the quality of physics instruction. This study contributes to the development of intelligent technology-based physics learning models and provides empirical evidence supporting the integration of artificial intelligence in science education.
DEVELOPMENT OF ANDROID-BASED INTERACTIVE E-MODULES FOR PHYSICS LEARNING ON MECHANICAL WAVE MATERIAL
The development of digital technology drives transformation in the world of education, including in the use of mobile-based learning media. Physics learning, especially in mechanical wave material, often faces obstacles in terms of understanding concepts due to limited visualization media that support the learning process. This study was conducted to develop and test the feasibility of an Android-based interactive e-module as a physics learning media that can improve the effectiveness and quality of student learning in mechanical wave material. This study is a development research (Research and Development) using the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. The subjects in this study consisted of material experts, media experts, physics teachers, and grade XI students at one of the state high schools in Indonesia. Data collection techniques were carried out through expert validation, user response questionnaires (teachers and students), and learning outcome tests before and after using the e-module. The data collected were analyzed using quantitative descriptive analysis techniques, including validity, practicality, and effectiveness. The results showed that the interactive e-module developed was declared very valid with an average validation score of 91.25%. Teacher and student responses showed a high level of practicality with an average percentage of 89.7%. The effectiveness test produced an N-gain value of 0.72 which is included in the high category, indicating that the use of e-modules can significantly improve student understanding. It can be concluded that the Android-based interactive e-module developed in this study is suitable for use as a learning medium for mechanical wave material, and provides a positive contribution to improving the quality of physics learning in the digital era.
THE EFFECT OF USING PhET MEDIA ON UNDERSTANDING THE CONCEPT OF STRAIGHT MOTION OF HIGH SCHOOL STUDENTS
This study aims to analyze the effect of using PhET interactive simulation media on understanding the concept of straight motion of high school students. The background of this study is based on the low understanding of students of the basic concepts of physics that are abstract, especially in the topic of straight motion. The research method used is quantitative with a quasi-experimental design using the Nonequivalent Control Group Design model. The research subjects consisted of 60 grade X students who were divided into two groups, namely the experimental group using PhET media and the control group using conventional learning methods. The main instrument used was a concept understanding test in the form of validated multiple choice. Data were analyzed using N-Gain test and independent sample t-test. The results showed that the increase in concept understanding in the experimental group was in the high category with an average N-Gain of 0.72, while the control group only reached the medium category with an average N-Gain of 0.47. The t-test showed a significance value of 0.000 (p < 0.05) indicating that there was a significant difference between the two groups. This finding shows that the use of PhET media can significantly improve students' understanding of the concept of straight motion. Interactive simulations in PhET provide visual and contextual learning experiences that support students' knowledge construction of the concept of motion. This study recommends the use of PhET media as an alternative in physics learning to improve the quality of students' concept understanding, and opens up opportunities for the development of similar media on other physics materials.
APPLICATION OF GUIDED INQUIRY LEARNING MODEL TO IMPROVE STUDENTS' CRITICAL THINKING SKILLS ON NEWTON'S LAW MATERIAL IN SENIOR HIGH SCHOOL
Critical thinking skills are essential competencies in 21st century physics learning, but in practice, students often have difficulty in understanding the concept of Newton's Law in depth due to teacher-centered learning methods. This study aims to analyze the effectiveness of the guided inquiry learning model in improving students' critical thinking skills on Newton's Law material at the Senior High School level. The type of research used is quantitative with a quasi-experimental approach using a nonequivalent control group design. The research subjects consisted of two classes, namely the experimental class taught using the guided inquiry model and the control class taught with a conventional approach. Data were collected through critical thinking skills tests in the form of open-ended descriptions given before and after treatment (pretest and posttest). The instrument was validated by experts and tested for reliability using Cronbach's Alpha. Data were analyzed descriptively and inferentially using t-test of two independent samples after going through normality and homogeneity tests. The results showed that there was a significant difference between the posttest scores of the experimental group and the control group (p < 0.05), with the average score of the experimental group higher. This shows that the guided inquiry learning model is effective in improving students' critical thinking skills. Conclusion.
THE EFFECTIVENESS OF STEM-BASED LEARNING IN IMPROVING STUDENTS' SCIENCE LITERACY IN TEMPERATURE AND HEAT
Improving science literacy is one of the main focuses in 21st-century learning, especially in the context of physics learning, which requires conceptual understanding and scientific thinking skills. However, various studies show that Indonesian students' science literacy is still relatively low, particularly in the abstract subject matter of temperature and heat, which requires a contextual approach. Therefore, this study aims to determine the effectiveness of STEM-based learning (Science, Technology, Engineering, and Mathematics) in improving students' science literacy in the subject matter of temperature and heat. This study uses a quantitative approach with a quasi-experimental method and a nonequivalent control group design. The research sample consisted of two 11th grade high school classes, namely the experimental group that received STEM-based learning and the control group that received conventional learning. The instruments used were multiple-choice science literacy tests based on PISA science literacy indicators and learning implementation observation sheets. Data collection was conducted through pre-tests and post-tests on both groups. Data were analyzed descriptively and inferentially. Normality and homogeneity tests were conducted before proceeding with the independent two-sample t-test. The analysis results showed that there was a significant difference between the science literacy scores of the experimental group and the control group with a significance value (p) of 0.000 (< 0.05). The average posttest score of the experimental group was higher than that of the control group. The conclusion of this study indicates that STEM-based learning is effective in improving students' science literacy on the topic of temperature and heat. This approach integrates conceptual understanding with scientific skills through contextual and problem-solving oriented learning activities.
ANALYSIS OF STUDENTS' MISCONCEPTIONS USING A THREE-TIER DIAGNOSTIC TEST ON GEOMETRIC OPTICS MATERIAL AT THE JUNIOR HIGH SCHOOL LEVEL
Geometric optics is an important topic in junior high school physics education, but it often causes conceptual difficulties for students. Many students experience misconceptions due to limitations in understanding abstract physical phenomena such as reflection, refraction, and image formation. This study aims to analyze the form and level of students' misconceptions in geometric optics using the Three-Tier Diagnostic Test instrument. This study is a quantitative descriptive study using a survey approach. The instrument used is a three-tier diagnostic test specifically designed to identify students' conceptual understanding, consisting of 15 questions covering three aspects: multiple-choice answers, conceptual reasoning, and confidence level. Data were collected by distributing the test to 120 eighth-grade students from three junior high schools who had studied optical concepts. Data analysis techniques used classification based on the Treagust model, which distinguishes between students who understand the concept, have misconceptions, guess, have limited understanding, and do not understand. The results of the study show that 46% of students have misconceptions, 31% understand the concept correctly, 12% guess, 7% do not understand, and 4% have limited understanding. The highest misconceptions were found in the sub-topic of light refraction (62%), followed by shadows on lenses (55%) and curved mirrors (51%). Additionally, 67% of students answered with high confidence despite their incorrect answers, indicating that misconceptions are deeply rooted. It can be concluded that misconceptions remain a serious issue in geometric optics learning, and the use of the Three-Tier Diagnostic Test has proven effective in comprehensively identifying and mapping misconceptions. These findings provide a foundation for developing more targeted diagnostic-based learning strategies to enhance students' conceptual understanding.