Learning Using Comics and Artificial Intelligence in Physics Subjects : A Review

Along with the development of technology, the use of information and communication technology (ICT) in the world of education is increasingly inevitable. One form of ICT utilization that is currently developing rapidly is the use of artificial intelligence (AI) in the learning process. AI technology has great potential in supporting the teaching and learning process, both in terms of delivering materials, interacting with students, and in terms of assessment and evaluation. In junior high schools, especially at SMPN 3 Taman, learning Indonesian still faces challenges in developing students' writing skills, especially in narrative learning materials, such as making short stories. Learning short stories requires creativity, understanding of text structure, and good language skills. However, this learning process is often hampered by limited teaching resources and less innovative teaching techniques. This study analyzes the effectiveness of using AI media in learning to write short stories at Taman 3 State Junior High School, Sidoarjo Regency. This study uses a qualitative approach with a case study method in several secondary schools that have implemented AI in Indonesian language learning, By using a case study method involving observation, interviews, and document analysis, the results of the study show that AI contributes to increasing student creativity, helping to compile a more systematic storyline, and increasing student confidence in writing. However, the use of AI in learning to write short stories still requires teacher guidance so that it remains in line with educational goals and does not reduce students' natural creativity.

Continual learning in medical devices: FDA's action plan and beyond

Understanding physics concepts often faces difficulties due to the lack of resources that can encourage students in learning and improve their understanding. One solution is to use Proteus software as physics learning media. The purpose of this meta-analysis is to evaluate the effect of using Proteus software media in physics learning. This meta-analysis research method involves several stages, such as formulating the research problem, collecting data from various studies, coding the data, and analyzing and interpreting the data. In the journal search, 36 articles were found that discussed the application of Proteus software media in physics learning. There are 6 articles that are relevant to the research conducted. In this article shows that there is a strong influence of the application of proteus software media in learning physics. in this study revealed that the results of the calculation of the effect size of the application of proteus software media in learning physics is 1.55 which is classified as high at 94%. This shows that proteus software media has a high influence in learning physics, especially at the SMA / SMK / MA education level.

As the popularity and accessibility of artificial intelligence (AI) in learning continue to rise, online education has increasingly incorporated AI. It is imperative to investigate how AI in the scholarly community supports the learning of autonomous students. This scoping review investigated articles that employed AI in discussion forums. The objective of this study is to develop a summary that denotes the effective integration of AI in discussion forums, thereby characterizing the overall learning experience. In accordance with the search, appraisal, synthesis, and analysis (SALSA) framework, the preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram was employed to design the article screening and selection process. Scopus was utilized for the literature search, resulting in the identification of twelve articles that met the predetermined inclusion and exclusion criteria. The extracted articles covered the following six applications: intelligent tutoring systems, AI-assisted apps, chatbots, automatic formative assessment, AI teaching assistants, and AI-assisted lifelong learning assistants. Three types of man-machine partnerships related to the activities are discussed: student-AI partnerships, student-AI-student partnerships, and student-AI-teacher partnerships, the latter being the most commonly observed. The generated content was frequently processed through teacher adjustments and checks. Components of community of inquiry theory were adapted as indicators. Cognitive presence was observed to be more predominant than social presence, with a particular emphasis on individual learning achievements. Three distinct perspectives regarding the role of AI in learning were identified. The first perspective posited that AI functioned as a virtual teacher, supplementing the teaching functions of human teachers and delivering information to students. In the second perspective, AI facilitated students in collecting information by enabling interactions with messages or peers. In the third perspective, the significance of the automatic evaluation function, which assessed learning activities and provided feedback to enhance the system while simultaneously implementing immediate changes in the learning process, was acknowledged. Regarding the role of communication, teachers clearly intended for students to acquire knowledge through it. Despite the focus on assisting individual learners, each article encompassed references from a wide range of fields and exhibited substantial diversity overall. Consequently, the domain of discussion forums with AI was depicted through the complex interplay between technology, pedagogy, and the learning environment. This context is known as entangled pedagogies, which emphasize understanding the interconnections among these elements and their reciprocal influences. In summary, AI was predominantly utilized in the form of chatbots and GenAI in discussion forums. Emerging AI roles included virtual teachers, peer/message matching, and automated evaluation. Aggregated information was presented in a manner that supported student learning. AI also served as a conduit between students and teachers.

In the learning process, using interesting media can improve the quality of learning, especially in understanding concepts. PhET simulation media is one of the learning media that can be used. This research is one type of research to know how high the effect of learning by using PhET simulation media using meta-analysis to improve understanding of concepts in physics learning is. Meta-analysis, used as a research method, consists of formulating problems, collecting, coding, analyzing, and interpreting data. The population and sample were used as research material in scientific articles published nationally discussing the effect of PhET simulation media to improve understanding of concepts in physics learning in 2017–2022. Based on the research conducted, an effect size value of 1.48 was obtained, and the interpretation of the effect size value of the effect of PhET simulation media with the dependent variable, namely understanding of concepts in physics learning, was 92% so that the research conducted was classified in the high category. This means that the PhET simulation media have a strong effect on increasing the effectiveness of students' understanding of concepts in physics learning, especially at the SMA, SMK, or MA education level. Thus, PhET is one of the learning media in the form of interactive simulations that can be utilized in education because it presents complex data about processes and concepts so that students can more easily understand the subjects taught in detail.

The digital era requires teachers to have competence in utilizing technology, including artificial intelligence (AI), in the learning process. However, there are still many elementary school teachers who do not understand and implement AI optimally. Therefore, this Community Service activity aims to improve teachers' understanding and skills in using AI as a learning medium through interactive workshops. The community service method used in this activity is Participatory Action Research (PAR), which was carried out at State Elementary School Pejuang 7 Bekasi involving 31 teachers. The success evaluation is conducted through a pre-test before the training and a post-test after the training by measuring several key aspects, namely: (1) understanding of AI concepts in education, (2) technical skills in operating AI-based platforms, and (3) the ability to design AI-based learning strategies. The results of community service showed an increase in teachers' understanding of AI by 31%, which was shown through the difference in pre-test and post-test results. Before the workshop, most teachers did not understand AI in learning. Still, after the workshop, teachers were better able to integrate AI as a tool in designing more interactive and innovative learning. Optimizing the use of AI in elementary schools can contribute to improving the quality of learning that is more effective, interesting, and in accordance with current developments.

Medical imaging and radiation science students' use of artificial intelligence for learning and assessment

This research aimed to test the effect of multimedia and lecturer-student interaction on student engagement in students of the Faculty of Economics, Universitas Negeri Padang. This type of research was descriptive quantitative. The sample was taken by using the Slovin formula with 358 respondents. The measure used in the study was the likert scale. The type of data used in this study was primary data obtained through the dissemination of questionnaires to students of the Faculty of Economics, Universitas Negeri Padang. The analysis method used SEM PLS analysis using SmartPLS 3.0. The results of this study showed that: lecturer-student interaction had a significant effect on student engagement. Multimedia had a significant effect on lecturer-student interaction. Multimedia had no significant effect on student engagement. The implication of this study was that empirically in learning that online student interaction was very necessary in order to increase student involvement in learning. Then, the use of multimedia affected student involvement in learning. The future research agenda needs to study more deeply the use of multimedia on student involvement in learning.

The use of Artificial Intelligence (AI) in student learning is an increasingly relevant issue in the context of modern education. This article outlines the main issues by explaining the challenges and potential of AI in learning. The purpose of this article is to provide acomprehensive understanding of the role of AI in student learning in Indonesia. The research method used is a literature review, which includes the analysis of various sources and perspectives related to theuse of AI in higher education. The data used in this article is information from various literature sources, including research results, scientific articles, and news related to the implementation of AI in education. Examples of AI applications, such as chatbots for academic guidance, online learning systems, and automated assessments, were obtained from these sources. The results of the data analysis show thatthe use of AI in student learning has great potential to improve the quality of education, but it is necessary to pay attention to ethical challenges, the risk of dependency, and the important role of humaninteraction. Solutions such as AI ethics education, strict regulations, and the integration of AI with human interaction become integral parts of the conclusion of this article. In the era of digital transformation, adeep understanding of the role of AI in education, particularly in the context of chatbots for academic guidance, online learning systems, and automated assessments, is key to enhancing the quality of education and preparing students for a technology-driven future.

This study examines students' perceptions of the positive and negative impacts of using Artificial Intelligence (AI) in learning in the digital era. In the digital era, AI is growing rapidly and its potential is expanding in education. Understanding students' perceptions is key to implementing AI effectively and optimally. This study used a qualitative method with a descriptive approach and involved 114 students at two universities in Lampung. Data was collected through an online questionnaire. The results show that most students have a positive perception of the impact of AI in learning. AI helps them focus on learning, understand the material more easily, complete tasks faster, and make learning more interesting. However, some students also have concerns about the negative impacts of AI, such as laziness in learning, dependence on technology, and potential misuse of AI. This study concludes that AI has great potential to improve the quality of student learning. It should be understood that AI cannot replace the role of lecturers, but it can assist lecturers and students in the learning process. It is important to use AI carefully and balance it with conventional learning. The results of this research are expected to contribute to various parties in achieving better educational goals.

This study aims to show that learning physics or understanding physics concepts is not only done in the classroom, but can be done outside the classroom even at fun playgrounds. The methods used are field case studies and literature case studies. In this study, it can be concluded that learning physics or understanding physics concepts is not only done in the classroom, but can be done outside the classroom even at fun playgrounds such as the centripetal force on the Ferris wheel and merry-go-round as well as the concept of simple harmonic motion on the Kora rides. -kora. Exploration of physics concepts on game vehicles can be an innovation in learning when students are getting bored in learning physics in theory, teachers can connect physics materials and concepts with game vehicles around us or even if possible can invite students to study outside the classroom so that learning can take place. become more meaningful, fun and easy to remember by students.

Physics Physics learning media is currently starting to increase according to the times. Android-based learning applications are currently starting to develop towards augmented reality (AR) technology. This study aims to develop a product in FULAN (Fun physics learning using augmented reality) learning media as a learning medium on magnetic electricity material. This type of research is development research. The subjects involved in this study were a learning media expert and physics education expert, and physics teacher candidate students at Sultan Ageng Tirtayasa University. The data processed in this study were collected through expert validation sheets, student response questionnaires with a Likert scale. The collected data were analyzed descriptively. The model used in this study is the ADDIE model, which consists of five stages, namely assessment analysis, design, development, implementation, and evaluation. The results of this study are: the learning media made obtained a score of 81% from instructional media experts, 85% from physics education experts, and 88% from student responses. FULAN learning media using Augmented Reality technology as a creative, innovative teaching aid can increase student enthusiasm in studying magnetic electricity material. Based on these results, it can be concluded that the FULAN learning media is suitable for use in learning physics.

Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics.

Penelitian ini bertujuan untuk memahami perspektif siswa terhadap pemanfaatan media AI dalam pembelajaran bahasa Indonesia di tingkat SMA. Metode yang digunakan dalam penelitian ini adalah kuantitatif, Populasi dalam penelitian ini adalah 375 orang siswa di SMA Negeri 2 Sungai Penuh dan sampel ditentukan dengan teknik sampel acak, jumlah sampel 193 diperoleh dengan teknik Slovin. Instrumen pengumpulan data adalah kuesioner yang telah di uji validitas dan reliabilitasnya. Data dianalisis dengan teknik analisis deskriptif dengan bantuan SPSS 26. Hasil penelitian adalah mayoritas siswa menunjukkan tingkat keakraban yang tinggi dengan kecerdasan buatan (AI) dalam konteks pembelajaran Bahasa Indonesia di tingkat SMA. Mereka menunjukkan pemahaman yang baik tentang konsep AI, serta memiliki pengalaman positif dalam menggunakan aplikasi atau alat berbasis AI. Siswa juga menunjukkan optimisme yang tinggi terhadap manfaat AI dalam pembelajaran Bahasa Indonesia, percaya bahwa AI dapat meningkatkan pemahaman, efektivitas, keterlibatan, kepercayaan diri, dan pencapaian akademik mereka dalam mata pelajaran tersebut. Meskipun demikian, penggunaan AI dalam pembelajaran Bahasa Indonesia masih belum optimal, dengan adopsi teknologi ini masih rendah. Terdapat kekhawatiran yang signifikan di antara siswa terkait potensi risiko AI, seperti ketergantungan berlebihan pada teknologi, kesenjangan pendidikan, masalah privasi, dan impersonalitas dalam pembelajaran.AbstractThis study aims to understand students' perspectives on the utilization of AI media in Indonesian language learning at the high school level. The method used in this research is quantitative, the population in this study were 375 students in SMA Negeri 2 Sungai Penuh and the sample was determined by random sample technique, the sample size was 193 obtained by slovin technique. The data collection instrument is a questionnaire that has been tested for validity and reliability. Data were analyzed using descriptive analysis techniques by using SPSS 26. The result of the study is that the majority of students show a high level of familiarity with artificial intelligence (AI) in the context of Indonesian language learning at the high school level. They demonstrated a good understanding of AI concepts, as well as having positive experiences in using AI-based applications or tools. Students also show high optimism towards the benefits of AI in Indonesian language learning, believing that AI can improve their understanding, effectiveness, engagement, confidence and academic achievement in the subject. Despite this, the use of AI in Indonesian language learning is still not optimal, with adoption of this technology still low. There are significant concerns among students regarding the potential risks of AI, such as over-reliance on technology, educational gaps, privacy issues, and impersonality in learning.

The development of artificial intelligence (AI) has created new opportunities in the world of higher education, especially in supporting a more effective and efficient learning process. Nonetheless, the adoption of AI by lecturers, especially in business majors, still faces various challenges. Some lecturers doubt the advantages of AI, face difficulties in its use, feel that AI does not match the characteristics of the courses being taught, or are burdened by the cost and limitations of institutional support. Therefore, this study aims to analyze the internal and external factors that influence lecturers' intention to adopt AI in learning, focusing on the utilization of AI platforms such as OpenAI ChatGPT, Google Gemini, and Microsoft Copilot. This research combines three main theoretical frameworks, namely the Diffusion of Innovation (DoI), Technology-Organization-Environment (TOE) Framework, and Task-Technology Fit (TTF). This study uses a quantitative approach with a survey method. The data was collected through a Google Form questionnaire that was distributed to business lecturers at various universities in Indonesia. The number of respondents analyzed was 417 people. Data analysis was carried out using the Partial Least Squares - Structural Equation Modeling (PLS-SEM) method through SmartPLS software version 4. The results show that factors in the TOE framework, such as technological context, organization, and environment, have a significant effect on the perception of task-technology fit. Furthermore, TTF has a positive effect on AI adoption intentions. Additionally, the variables in DoI theory —namely, relative advantage and compatibility —have a positive effect on adoption, while complexity has a negative effect. The findings also show that gender moderates the relationship between complexity and adoption intention, as well as between compatibility and adoption intention. This means that the influence of the perception of the complexity and suitability of technology on AI adoption differs between male and female lecturers