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Virtual Laboratory: Using Electronic Workbench as Alternative Learning Physics in Covid-19 Mass Pandemic Mafudi, Innal; Handhika, Jeffry
Impulse: Journal of Research and Innovation in Physics Education Vol. 1 No. 1 (2021): Impulse: Journal of Research and Innovation in Physics Education
Publisher : Pendidikan Fisika FITK UIN Sunan Kalijaga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/impulse.2021.11-05

The purpose of this research is to describe the use of assisted virtual laboratories of Electronic Workbench (EWB) in physics experiments learning. The method in this study used (1) calibration of the results of experiments with theory and (2) analysis of user responses to EWB in practicum activities. The study concluded that: 1) EWB is easy to use for practical learning, 2) capacitive reactance values obtained from calculations and observations following the theory (close to the same), 3) the time needed for one-time trial data retrieval until the analysis phase in this practicum activity is 10 minutes means that the experiment with EWB is very efficient. Based on the results obtained indicate that EWB is feasible to use as an alternative to physics learning in the mass pandemic COVID-19.

Case Study on ChatGPT’s Performance in Assisting Students with Physics Tests Mafudi, Innal; Kuswanto, Heru; Jumadi, Jumadi; Fatmawati, Intan
Jurnal Pendidikan Fisika Vol 13, No 1 (2025): PENDIDIKAN FISIKA
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/jpf.v13i1.16624

The rapid development of artificial intelligence (AI), particularly ChatGPT, has sparked interest in its application in education. This study aims to investigate the potential of ChatGPT in helping students understand and solve physics problems, focusing on the Test of Understanding Graphs in Kinematics and the Determining and Interpreting Resistive Electric Circuit Concepts Test. The study involved 25 physics education students who completed these tests independently and with ChatGPT's assistance. The results revealed that students with a strong foundational understanding and reflective abilities interacted more effectively with ChatGPT, leading to improved answers and deeper conceptual understanding. In contrast, students with weaker prior knowledge tended to accept ChatGPT’s answers without critical reflection, perpetuating errors. Furthermore, ChatGPT showed limitations in interpreting image-based questions, reading scales, and providing consistent responses to concept-specific queries. These findings suggest that while ChatGPT has the potential to enhance learning, it requires thoughtful integration, particularly in helping students develop critical thinking and problem-solving skills. Teachers are encouraged to use ChatGPT’s limitations to design assessments that minimize the risk of cheating and foster deeper understanding. In conclusion, this study underscores the importance of combining AI tools with strong conceptual foundations and active reflection to optimize learning outcomes in physics education. Future research should focus on refining strategies for using AI in education to address its current limitations and enhance its effectiveness in complex learning scenarios.

Case Study on ChatGPT’s Performance in Assisting Students with Physics Tests Mafudi, Innal; Kuswanto, Heru; Jumadi, Jumadi; Fatmawati, Intan
Jurnal Pendidikan Fisika Vol. 13 No. 1 (2025): PENDIDIKAN FISIKA
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/jpf.v13i1.16624

The rapid development of artificial intelligence (AI), particularly ChatGPT, has sparked interest in its application in education. This study aims to investigate the potential of ChatGPT in helping students understand and solve physics problems, focusing on the Test of Understanding Graphs in Kinematics and the Determining and Interpreting Resistive Electric Circuit Concepts Test. The study involved 25 physics education students who completed these tests independently and with ChatGPT's assistance. The results revealed that students with a strong foundational understanding and reflective abilities interacted more effectively with ChatGPT, leading to improved answers and deeper conceptual understanding. In contrast, students with weaker prior knowledge tended to accept ChatGPT’s answers without critical reflection, perpetuating errors. Furthermore, ChatGPT showed limitations in interpreting image-based questions, reading scales, and providing consistent responses to concept-specific queries. These findings suggest that while ChatGPT has the potential to enhance learning, it requires thoughtful integration, particularly in helping students develop critical thinking and problem-solving skills. Teachers are encouraged to use ChatGPT’s limitations to design assessments that minimize the risk of cheating and foster deeper understanding. In conclusion, this study underscores the importance of combining AI tools with strong conceptual foundations and active reflection to optimize learning outcomes in physics education. Future research should focus on refining strategies for using AI in education to address its current limitations and enhance its effectiveness in complex learning scenarios.

Development and Validation of the Relativity Concept Inventory Test Using Item Response Theory Generalized Partial Credit Model 3PL Mafudi, Innal; Istiyono, Edi
Jurnal Pendidikan MIPA Vol 25, No 1 (2024): Jurnal Pendidikan MIPA
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract: This research aims to develop a valid and reliable Relativity Concept Inventory Test instrument. This instrument is based on relativity material, which includes Einstein's first and second postulates, time dilation, velocity addition, and length contraction. Methods for preparing instruments include 1) test design, 2) test validation, 3) test trials, and 4) test data analysis. The design of the test grid is based on Bloom's taxonomy C2 to C5 and produces 13 questions. The instrument is made in the form of multiple-choice questions and is equipped with a level of confidence. Instrument validation was carried out by 6 physics education lecturers and 1 high school teacher, with analysis using the V Aiken formula. The validated instrument was then tested on 130 students from 2 high schools in Madiun. Trial data was analyzed using the Generalized Partial Credit Model 3PL (GPCM-3PL). The development results show that: 1) 13 multiple choice Relativity Concept Inventory Test questions with a level of confidence were successfully developed, 2) expert validation showed that all question items got a score of 0.93, which is included in the valid, with instrument reliability of 0, 42 (very low category), 3) the results of the trial test showed that the relativity concept inventory was proven to be fit with the GPCM, with different power of the items of 0.407 and the level of difficulty showed that 11 items were valid with a range of -1.05 to 1.64, while 2 questions (numbers 8 and 9) are invalid with a value of more than -2. Apart from that, the question items have no potential to be guessed, as evidenced by the guessing value of 0 (zero). This Relativity Concept Inventory Test instrument meets the requirements for use in measuring students' conceptual understanding Keywords: assessment, inventory concept, relativity. DOI: http://dx.doi.org/10.23960/jpmipa/v25i1.pp142-154

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