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Artificial Intelligence in Physics Education Research in Two Decades: A Bibliometric Study from Scopus Database Nurjanah, Siti; Martaputri, Nurul Aulia; Zamzami, Zamzami; Suardi, Izzul Kiram; Hulu, Hepi Kharisda
Jurnal Pendidikan Fisika Vol 12, No 2 (2024): PENDIDIKAN FISIKA
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/jpf.v12i2.14745

Abstract

There has been a substantial rise in research on utilizing Artificial Intelligence (AI) technology in physics education. This study conducts a comprehensive bibliometric analysis of this emerging field, aiming to discern trends, patterns, and future research areas. Using the PRISMA methodology, data were extracted from the Google Scholar and Scopus databases and analyzed with Biblioshiny and VOSviewer. We identified 12 main topic clusters, including chatbot applications and 3D virtual simulations, with significant growth in publications from 2020 to 2023. Key findings focused on pre-trained language models like ChatGPT, revealing strong connections between ChatGPT and topics such as linguistic quality and student perception. Future research areas can include thorough evaluations of AI models' accuracy and quality across various physics topics and educational levels, developing fair and transparent AI-driven assessment systems, and exploring blended learning approaches integrating AI-powered simulations. Encouraging interdisciplinary collaborations and conducting longitudinal studies to assess the long-term impact of AI on learning outcomes are also crucial. The use of Google Scholar and Scopus databases limits our research. Future research could benefit from incorporating other databases, such as Web of Science (WoS), and conducting a systematic literature review for a more nuanced understanding.
Evaluation of the Implementation of the International Credit Transfer Program of Makassar State University Suardi, Izzul Kiram; Arnidah, Arnidah; Haling, Abdul
Edunesia : Jurnal Ilmiah Pendidikan Vol. 5 No. 2 (2024)
Publisher : research, training and philanthropy institution Natural Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51276/edu.v5i2.883

Abstract

In 2021, Universitas Negeri Makassar (UNM) first became one of the universities participating in the International Credit Transfer Program (ICT) and made Universiti Kebangsaan Malaysia (UKM) one of the partner universities. Thus, this study aims to evaluate the implementation of ICT held online by UNM for one semester. The evaluation model used in this study is an illuminative evaluation model that focuses on qualitative data collection using observation, interview, and document review methods. The results showed that the implementation of ICT by UNM went quite well. This is evidenced by the achievement of the goals of the ICT program for universities and students. In addition, this program motivates students to take part in other international programs participated in by UNM and organized by the government. However, there are some problems encountered by UNM and students during the program. Such as communication problems of the committee and participants, to administrative problems. In conclusion, ICT is incredibly good to be followed again by UNM, seeing the magnitude of the impact and enthusiasm of the students. However, improvements to the administrative and communication systems must be completed first before returning to participate in the following years.
A SYSTEMATIC REVIEW OF FORMATIVE ASSESSMENT IN HIGH SCHOOL PHYSICS LEARNING Nurjanah, Siti; Suyanto, Slamet; Iqbal, Muhammad; Ramadhani, Shaufi; Suardi, Izzul Kiram; Seran, D’aquinaldo Stefanus Fani
EDUSAINS Vol 16, No 2 (2024): EDUSAINS
Publisher : Faculty of Education and Teacher Training, UIN (State Islamic University) Syarif Hidayatul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/es.v16i2.37785

Abstract

Implementing formative assessment (FA) in physics learning has been widely acknowledged as an effective strategy for enhancing learning process and student performance. Unfortunately, there was a dearth of thorough research on formative assessment in high school physics learning, including publication opportunities, physics topics evaluated by prior studies, and forms of formative assessment investigated by prior studies. This review mapped studies on formative assessment in physics subjects in the high school context. The research method used was a systematic review by analyzing relevant research results from the Scopus databases that published over the past decade (from 2014 to 2023). A total of 17 articles were examined in this study. This study found that Q1 ranked journals were where the most articles with FA topics in high school physics subjects were published. Mechanics was the most common physics topic investigated by previous research. Technology-based formative assessment was the most common form of FA used by previous studies. The results of this review may benefit researchers, school leaders, and policy makers when they aspire to do research or facilitate the implementation of formative assessment in physics class.
Psychometric quality of multiple-choice tests under classical test theory (CTT): AnBuso, Iteman, and R Nurjanah, Siti; Iqbal, Muhammad; Zafrullah, Zafrullah; Mahmud, Muhammad Naim; Seran, D'aquinaldo Stefanus Fani; Suardi, Izzul Kiram; Arriza, Lovieanta
Jurnal Penelitian dan Evaluasi Pendidikan Vol. 28 No. 2 (2024)
Publisher : Graduate School, Universitas Negeri Yogyakarta in cooperation with Himpunan Evaluasi Pendidikan Indonesia (HEPI) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pep.v28i2.71542

Abstract

Psychometric quality analysis of psychological instruments was important to ensure credible measurement. This study aims to compare the psychometric quality analysis of multiple-choice test items using three different applications to evaluate the advantages and disadvantages of the features provided in supporting classical test theory analysis. This study used a quantitative approach by analysing dichotomous data from 50 participants of a 30-item multiple-choice test. The data were analysed using three applications (AnBuso, Iteman, and R) to compare the statistical output of the main psychometric parameters of the classical test theory, such as difficulty index, discrimination index, and distractor effectiveness. Data analysis was conducted descriptively and quantitatively by comparing the features provided by the application in support of classical test theory analysis to evaluate the advantages and disadvantages of each application. The study found that all three applications produced similar results for the difficulty index, distractor effectiveness, and discrimination index. AnBuso proved user-friendly but limited in capacity, Iteman offered comprehensive output with restricted free functionality, and R provided flexibility but required programming expertise. The application demonstrated unique strengths that are suitable for different research needs and user proficiencies. The choice of application should consider factors such as analysis complexity, sample size, and user expertise. Further research into paid options and diverse test conditions is recommended for a more comprehensive evaluation of these applications in classical test theory analysis.
Artificial Intelligence in Physics Education Research in Two Decades: A Bibliometric Study from Scopus Database Nurjanah, Siti; Martaputri, Nurul Aulia; Zamzami, Zamzami; Suardi, Izzul Kiram; Hulu, Hepi Kharisda
Jurnal Pendidikan Fisika Vol. 12 No. 2 (2024): PENDIDIKAN FISIKA
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/jpf.v12i2.14745

Abstract

There has been a substantial rise in research on utilizing Artificial Intelligence (AI) technology in physics education. This study conducts a comprehensive bibliometric analysis of this emerging field, aiming to discern trends, patterns, and future research areas. Using the PRISMA methodology, data were extracted from the Google Scholar and Scopus databases and analyzed with Biblioshiny and VOSviewer. We identified 12 main topic clusters, including chatbot applications and 3D virtual simulations, with significant growth in publications from 2020 to 2023. Key findings focused on pre-trained language models like ChatGPT, revealing strong connections between ChatGPT and topics such as linguistic quality and student perception. Future research areas can include thorough evaluations of AI models' accuracy and quality across various physics topics and educational levels, developing fair and transparent AI-driven assessment systems, and exploring blended learning approaches integrating AI-powered simulations. Encouraging interdisciplinary collaborations and conducting longitudinal studies to assess the long-term impact of AI on learning outcomes are also crucial. The use of Google Scholar and Scopus databases limits our research. Future research could benefit from incorporating other databases, such as Web of Science (WoS), and conducting a systematic literature review for a more nuanced understanding.