Ex) Article Title, Author, Keywords
pISSN 0374-4914
eISSN 2289-0041
pISSN 0374-4914
eISSN 2289-0041
Ex) Article Title, Author, Keywords
Abstract : In recent years, generative AI technology, especially large language models (LLMs), has garnered significant attention for its potential to transform education. This paper provides an overview of generative AI's development and examines its impact on education, focusing on the issue of `hallucinations' in LLMs. It explores the causes and proposes solutions such as finetuning, reasoning, iterative querying, and Retrieval-Augmented Generation (RAG). These methods aim to enhance the accuracy and reliability of AI responses. Examples of AI applications in education include real-time student query responses, personalized learning pathways, and assessment feedback. While these technologies promise to improve educational quality, they also raise concerns about biases and data privacy. This paper discusses strategies to effectively utilize generative AI in education, aiming to improve quality while minimizing negative impacts.
Abstract : This study analyzed the understanding of interval voltage in electric circuits among elementary, middle, and high school students and pre-service physics teachers. As a result only 14.7% of elementary, middle, and high school students responded scientifically to the definition of voltage before the lesson, and 81.8% of pre-service physics teachers did. Second, less than 10% of students and pre-service physics teachers correctly predicted interval voltages in electric circuits and provided scientific explanations. Third, students and pre-service physics teachers almost accurately measured interval voltages, closely matching theoretical values, using both experimental methods using experimental tools and simulation. Fourth, survey results after the lesson indicated that both students and pre-service physics teachers considered the combination of measurement activities and simulation activities the most effective teaching method for learning interval voltage in electric circuits. Based on these results, implications for the science education and curriculum, as well as teaching and learning were discussed.
Abstract : Superconductor is a substance of zero-resistance below critical temperature and it has been attracted lots of attention from many researchers due to the possibility of applications in various field such as quantum computing which is the hottest topic on recent science community. However, for these applications, it is necessary to prepare high quality superconductor films and understand the physical characteristics of films. In this study, we grew YBa2Cu3O7(YBCO) thin films and established concrete conditions to synthesize highly qualified thin films with a high critical temperature and narrow transition width. Then, we analyzed samples showing different critical temperature using X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), and Transmission Electron Microscope (TEM). Through the analysis, it is identified that there is ab twinning on YBCO film with a high critical temperature (∼93 K), which are strong evidences of tetragonal-orthorhombic phase transition.
Abstract : This study explores the use of symbolic regression (SR) in physics education, aiming to gauge its effectiveness and educational value. SR involves deriving mathematical models from empirical data by finding symbolic representations that fit the data. We evaluate two SR algorithms, AI-Feynman and Φ-SO, using position data from objects in parabolic motion and damped oscillations. Our analysis demonstrates that SR algorithms can produce concise formulas to describe object motion. Integrating SR into physics education allows students to build on their prior knowledge of physics to formulate hypothetical symbolic terms and enhance their explanations of physical phenomena. Subsequently, students iteratively derive mathematical expressions from data, thereby nurturing a process of data-driven discovery. Furthermore, students can recognize the impact of technological advancements on scientific problem-solving. However, effective pedagogical strategies are necessary to guide students beyond mere derivation of mathematical expressions, encouraging them to interpret and elucidate models in meaningful scientific inquiries.
Abstract : In the 2015 revised curriculum, students have the autonomy to choose their desired subjects through a choice-based curriculum. However, there is a continuing trend among students to avoid physics, opting for subjects where they can achieve relatively higher grades without considering their future career paths. In this study, we surveyed the motivations and tendencies of students who took integrated science courses to select Physics I and analyzed the results. The results showed that students’ preferred science subjects in the second year are Biology I, Chemistry I, Earth Science I, and Physics I, in that order. Male students cited the allure of physics content, while female students emphasized the necessity for university entrance as the reason for their interest in Physics I. Both male and female students mentioned relevance to career paths and personal interest and aptitude as reasons for selecting Physics I. Additionally, students tended to find the physics component of integrated science more challenging than other areas. Based on these results, discussions were held on strategies to enable more students to choose Physics I.
Abstract : The 87Rb nuclear magnetic resonance spectra are obtained in Rb2ZnBr4 crystals. The number of 87Rb resonance lines reflects the crystal symmetry and the crystal phases (incommensurate and paraelectric phases) of Rb2ZnBr4 crystal. The spin-lattice relaxation time of 87Rb nucleus in Rb2ZnBr4 crystal were measured on laboratory frame in the 180 to 420 K temperature range. The abrupt changes of T1 at 200 K and 347 K seem to be caused by structural phase transitions between ferroelectric and incommensurate phases and between incommensurate and paraelectric phases of Rb2ZnBr4 crystal, respectively. The temperature dependence of the 87Rb relaxation time in Rb2ZnBr4 crystal is in accordance with the Raman processes between TC1 and TC2. The chemical shift of the 87Rb NMR spectra in the sample crystal is also discussed.
Abstract : As a preliminary investigation into the effect of impurities on the properties of liquid scintillators, this study employed an infrared spectroscopy approach, focusing on the vibrational transitions of linear alkylbenzene (LAB). We analyzed the infrared spectra of various LAB isomers produced by ISU chemicals in their pure state, devoid of impurities. This analysis yielded new insights into the vibrational modes of LAB, which are expected to contribute to a deeper understanding of LAB behavior within liquid scintillators. Ultimately, this study provides fundamental data that can be utilized to enhance liquid scintillator performance and facilitate impurity analysis.
Abstract : Although heat is a phenomenon commonly observed in daily life, it is invisible and its reality is unclear. Therefore, to properly understand the concept of heat, students should understand an abstract model. Accordingly, elementary school science textbooks attempt to convey a scientific model to students by visualization of heat concepts. In this study, we analyzed how the heat concept is visualized in elementary school science textbooks and discussed how elementary school students comprehend these visualizations based on their cognitive framework. The object of analysis was to extract visualization to explain the concepts of ‘temperature & heat’ and ‘heat transfer’ in 18 elementary school science textbooks from the first curriculum to the 2015 revised curriculum. Based on the analysis results, implications were provided for ways to improve elementary school science textbook visualization considering mental models and visualization literacy of elementary school students.
Abstract : This study developed a case of utilizing artificial intelligence (AI) in school education and evaluated its educational effectiveness. The developed lesson plan applies AI to teach simple harmonic motion, a topic covered in the high school physics curriculum. Specifically, a three-session lesson plan was designed, involving the use of the Algodoo program to generate position data over time for simple harmonic motion and utilizing ChatGPT to describe mathematical functions representing an object's position over time. This lesson plan was implemented in high school classes, and a majority of students who participated in the developed lesson plan responded that ChatGPT was helpful in information gathering and analysis, understanding learning content, and solving learning tasks. These results confirm that utilizing AI directly for analyzing experimental data can enhance students' comprehension compared to traditional methods of simply providing formulas inherent in physical laws.
Abstract : In this study, we analyzed the relationship between verbal interaction and experimental design ability of gifted science students in middle school by applying an experimental design ability improvement program on the topic of light refraction and reflection. DCT individual tests were conducted before and after the program, and the revised experimental design was compared with the draft one. The entire discussion process was recorded, and transcribed, and the types of verbal interaction and their characteristics were analyzed based on the transcribed data. As a result, out of a total of four small groups, one group showed a Dominant-type, one group showed a Partial participation-type, and two groups showed All participation-type. By group, it was seen that the experimental design ability was improved in the order of Dominant-type, Partial participation-type and All participation-type. In terms of individual status within the group, it was found that the experimental design ability was usually improved in the order of prime mover, assistant mover, and out mover. So we found out that the improvement of experimental design ability was influenced by verbal interaction within the group.
Abstract : The purpose of this study was to investigate the difficulties high school students experience in learning the theory of special relativity. For this purpose, 27 College Scholastic Ability Test and mock exam questions related to the theory of special relativity were classified into five content elements: relative velocity and the principle of relativity, the principle of constancy of the speed of light, the relativity of simultaneity, time dilation, and length contraction. In the study, the operationally defined incorrect answer rates were obtained. Additionally, interviews were conducted with four high school students and five physics teachers. The main research results are as follows: First, The special relativity theory questions often combined several content elements, with the most frequent elements being the relativity of simultaneity, time dilation, and length contraction. Second, according to the difficulty analysis, the content elements students found most difficult were, in order: the relativity of simultaneity, length contraction, relative velocity and the principle of relativity, time dilation, and the principle of constancy of the speed of light. Third, there were notable differences in the content elements that students and teachers found difficult. Based on these findings, a discussion on the teaching and learning of the theory of special relativity was discussed.
Abstract : In recent years, generative AI technology, especially large language models (LLMs), has garnered significant attention for its potential to transform education. This paper provides an overview of generative AI's development and examines its impact on education, focusing on the issue of `hallucinations' in LLMs. It explores the causes and proposes solutions such as finetuning, reasoning, iterative querying, and Retrieval-Augmented Generation (RAG). These methods aim to enhance the accuracy and reliability of AI responses. Examples of AI applications in education include real-time student query responses, personalized learning pathways, and assessment feedback. While these technologies promise to improve educational quality, they also raise concerns about biases and data privacy. This paper discusses strategies to effectively utilize generative AI in education, aiming to improve quality while minimizing negative impacts.
Abstract : This study is a self-study by a teacher educator who designed and operated a one-semester PBL course using the micro:bit. As a professor of physics education who majored in both physics and science education and is currently working at a college of education, I explore the social demand for physics education that reflects informatization and digital literacy and the direction of change accordingly, and to consider subject identity. To this end, I opened a PBL course to explore the use of the micro:bit in physics education and conducted research using self-study techniques focusing on awareness and practice. Students taking the PBL course who participated in the study developed a positive perception of the usability of the micro:bit in physics education through engineering output projects and physics inquiry activity development projects. In this process, through discussions with critical colleagues, the possibility and limitations of new digital tools became more clearly recognized, and the direction and elements of the teacher education curriculum related to the use of the micro:bit were elaborated. As I began to focus on the educational potential of producing engineering outputs as new scientific inquiry activities, I came to perceive more positively the direction of innovation and its practical possibilities in converging science and engineering through educational tools such as physical computers, including the micro:bit.
Abstract : This study analyzed the understanding of interval voltage in electric circuits among elementary, middle, and high school students and pre-service physics teachers. As a result only 14.7% of elementary, middle, and high school students responded scientifically to the definition of voltage before the lesson, and 81.8% of pre-service physics teachers did. Second, less than 10% of students and pre-service physics teachers correctly predicted interval voltages in electric circuits and provided scientific explanations. Third, students and pre-service physics teachers almost accurately measured interval voltages, closely matching theoretical values, using both experimental methods using experimental tools and simulation. Fourth, survey results after the lesson indicated that both students and pre-service physics teachers considered the combination of measurement activities and simulation activities the most effective teaching method for learning interval voltage in electric circuits. Based on these results, implications for the science education and curriculum, as well as teaching and learning were discussed.
Abstract : Science teachers are expected to have high teaching expertise. However, middle school science teachers experience difficulties when teaching all subject areas of science beyond their in-field major. This study investigated the difficulties of middle school science teachers in teaching physics units which are considered to be most difficult to teach. For this purpose, difficulties related to Subject Matter Knowledge(SMK) and Pedagogical Content Knowledge(PCK) were analyzed through open-ended surveys conducted on 36 middle school science teachers with non-physics major, and difficulty factors were analyzed through in-depth interviews conducted on 7 of them. As a result, there were 13 difficulties related to SMK and PCK. In addition, abstract concepts, laws expressed in formulas, and ideal conditions appeared to be factors that caused 13 difficulties when teachers with non-physics major teach physics units. Educational implications for increasing the expertise of science teachers are proposed based on the findings.
Aekyung Shin, Donggeul Hyun, Jeongwoo Park
New Phys.: Sae Mulli 2023; 73(1): 37-43
https://doi.org/10.3938/NPSM.73.37
Geon Park, Inseo Kim, Hojung Sun, Yongjei Lee, Kimoon Lee, JungYup Yang
New Phys.: Sae Mulli 2023; 73(1): 23-28
https://doi.org/10.3938/NPSM.73.23
Bongwoo Lee*
New Phys.: Sae Mulli 2022; 72(10): 795-805
https://doi.org/10.3938/NPSM.72.795
pISSN 0374-4914
