In this study, the magnetocaloric effect and transition temperature of bulk metallic glass, an amorphous material, were predicted through machine learning based on the composition features. From the Python module ‘Matminer’, 174 compositional features were obtained, and prediction performance was compared while reducing the composition features to prevent overfitting. After optimization using RandomForest, an ensemble model, changes in prediction performance were analyzed according to the number of compositional features. The R2 score was used as a performance metric in the regression prediction, and the best prediction performance was found using only 90 features predicting transition temperature, and 20 features predicting magnetocaloric effects. The most important feature when predicting magnetocaloric effects was the ‘Fe’ compositional ratio. The feature importance method provided by ‘scikit-learn’ was applied to sort compositional features. The feature importance method was found to be appropriate by comparing the prediction performance of the Fe-contained dataset with the full dataset.

오늘날 교육 분야에서 인공지능 기술이 빠르게 발전하면서 AI 한국어 학습 앱은 혁신적인 학습 도구로 많은 주목을 받고 있다. 본 연구는 AI 한국어 학습 앱의 사용자를 연구 대상으로 삼아 기술준비도(TRI), 기술수 용모델(TAM), 정보기술성공 모형을 기반으로 양적 데이터를 분석했다. 본 연구 결과를 바탕으로 향후 한국어 학습 앱의 개발과 한국어 해외 교 육 연구를 위한 이론적 근거와 활용 방안을 제공하고 해외 한국어 교육 의 발전을 촉진하길 바란다. 연구 결과에 따르면 낙관성, 혁신성, 시스템 품질, 학습 내용, 지각된 유용성, 지각된 용이성이 사용자의 사용 태도와 사용의도에 정(+)적인 영향을 미친다. 반면에 불편함과 불확신은 사용자 의 지각된 용이성과 유용성에 부(-)적인 영향을 미친다. 특히, 사용자의 사용의도는 지각된 유용성으로부터 가장 큰 영향을 받았다. 이상의 연구 결론을 바탕으로 AI 한국어 학습 앱의 개선 대책 및 제언을 제시했다.

Existing reinforced concrete (RC) building frames constructed before the seismic design was applied have seismically deficient structural details, and buildings with such structural details show brittle behavior that is destroyed early due to low shear performance. Various reinforcement systems, such as fiber-reinforced polymer (FRP) jacketing systems, are being studied to reinforce the seismically deficient RC frames. Due to the step-by-step modeling and interpretation process, existing seismic performance assessment and reinforcement design of buildings consume an enormous amount of workforce and time. Various machine learning (ML) models were developed using input and output datasets for seismic loads and reinforcement details built through the finite element (FE) model developed in previous studies to overcome these shortcomings. To assess the performance of the seismic performance prediction models developed in this study, the mean squared error (MSE), R-square (R2), and residual of each model were compared. Overall, the applied ML was found to rapidly and effectively predict the seismic performance of buildings according to changes in load and reinforcement details without overfitting. In addition, the best-fit model for each seismic performance class was selected by analyzing the performance by class of the ML models.

본 연구는 성인 학습자의 대학동아리 활동 만족도와 지속 요인이 학업 스트레스 간 관계에서 자아존중감의 매개효과를 검증하여, 성인 학습자의 동아리활동과 학교생활에 더욱 만족할 수 있는 방안을 제시하고자 하였다. 대구·경북 지역 25세 이상 성인학습자 250명을 대상으로 2020년 9월 25 일부터 2020년 11월 24일까지 직접 방문 및 구글을 활용한 설문조사를 실시하였다. 회수된 설문지는 215부로 이중 불성실한 응답을 한 4부의 설 문지는 제외하고 총 211부를 최종분석에 활용하였다. 분석 결과, 성인 학 습자의 대학동아리 활동 만족도는 자아존중감과 학업 스트레스에 영향을 미 치지 않은 것으로 확인되었다. 다만 성인 학습자의 동아리 활동 지속 요인 은 자아존중감, 학업 스트레스에 통계적으로 유의하게 나타났다. 그리고 성 인학습자의 대학동아리 활동 지속 요인이 학업 스트레스 간 관계에서 자아 존중감의 완전 매개효과를 검증하였다. 이러한 연구 결과를 통해 대학동아 리 활동이 성인 학습자의 자아존중감을 향상 시키고 학업 스트레스를 완화 함을 시사한다.

This study utilizes association rule learning and clustering analysis to explore the co-occurrence and relationships within ecosystems, focusing on the endangered brackish-water snail Clithon retropictum, classified as Class II endangered wildlife in Korea. The goal is to analyze co-occurrence patterns between brackish-water snails and other species to better understand their roles within the ecosystem. By examining co-occurrence patterns and relationships among species in large datasets, association rule learning aids in identifying significant relationships. Meanwhile, K-means and hierarchical clustering analyses are employed to assess ecological similarities and differences among species, facilitating their classification based on ecological characteristics. The findings reveal a significant level of relationship and co-occurrence between brackish-water snails and other species. This research underscores the importance of understanding these relationships for the conservation of endangered species like C. retropictum and for developing effective ecosystem management strategies. By emphasizing the role of a data-driven approach, this study contributes to advancing our knowledge on biodiversity conservation and ecosystem health, proposing new directions for future research in ecosystem management and conservation strategies.

The objective of this study is to examine ways to develop and design actual teaching and learning materials based on grammar consciousness-raising tasks. In our country, unlike in the field of English or Korean language education as a foreign language, in the area of Spanish education there is very little research on grammar consciousness-raising tasks and there is no research on the development of teaching and learning materials. Therefore, this study was focused on teaching Spanish as a foreign language. First of all, we looked at the concept and characteristics of the grammar consciousness-raising tasks, their pros and cons, and the expected effects of introducing these tasks into domestic Spanish education. Afterwards, we set the teaching and learning model based on the grammar consciousness-raising tasks and looked at things to be careful about when designing tasks corresponding to each stage. Based on this, we created actual teaching and learning materials. We hope that this study will serve as a reference and that research on grammar consciousness-raising tasks will be actively conducted in domestic Spanish education, and that materials will be developed with more diverse language items. El objetivo de este estudio es examinar formas de desarrollar materiales de enseñanza y aprendizaje basados en las tareas gramaticales y diseñar materiales reales. En nuestro país, a diferencia de la enseñanza del idioma inglés o coreano como lengua extranjera, existe muy poca investigación sobre las tareas gramaticales en el ámbito de la enseñanza de la lengua española, y no existe investigación sobre el desarrollo de materiales de enseñanza y aprendizaje. Por ello, este estudio se centró en la enseñanza del español como lengua extranjera. En primer lugar, analizamos el concepto y las características de las tareas gramaticales, sus ventajas y desventajas, y los efectos esperados al introducir estas tareas en la educación del español en el país. Posteriormente, configuramos el modelo de enseñanza y aprendizaje basado en las tareas gramaticales y analizamos los aspectos a tener en cuenta a la hora de diseñar las tareas correspondientes a cada etapa. Con base en esto, creamos materiales de enseñanza y aprendizaje reales. Esperamos que este estudio sirva como referencia y que se lleven a cabo activamente investigaciones sobre las tareas gramaticales en la educación del español en nuestro país, y que se desarrollen materiales con elementos lingüísticos más diversos.

The interpretations of null subjects in Korean and Chinese are considered distinct, with Korean allowing both strict and sloppy interpretations, while Chinese only allows strict readings. This study investigated whether such an interpretational difference between Korean and Chinese appeared in Chinese learners’ instantaneous processing of null subjects in Korean and among native speakers of both languages with unlimited time and full cognition. An online experiment and offline surveys were conducted using a priming paradigm with a semantic categorization task, acceptability ratings, and multiple-choice surveys. The results of the online experiment provided partial support for distinct interpretations in Korean and Chinese. Meanwhile, offline acceptability ratings and surveys revealed that Chinese native speakers chose the strict reading in most cases, while Koreans also showed a higher acceptance of the strict reading of non-negated sentences. These findings suggest that the interpretation of null subjects can be influenced by experimental methods, grammatical constraints, and/or influences from discourse, underscoring the need for a more nuanced approach to investigating subject ellipsis in Korean and Chinese.

Purpose: Improving students’ self-confidence is an important strategy in simulation learning. This study aimed to identify the factors influencing students’ self-confidence in simulation learning based on the Jeffries Simulation Framework. Method: A cross-sectional survey was conducted with 140 senior nursing students’ at a university, and data were collected through self-reported questionnaires. Data on students’ self-confidence were collected for student/ facilitator factors (satisfaction on major, overall grade average, and facilitator satisfaction), educational practice factors (active learning, collaboration, diverse ways of learning and educational goals), and simulation design characteristics factors (objectives/information, support, problem solving, feedback, and fidelity). Data were analyzed using an independent t-test, one-way ANOVA, Pearson’s correlation, and hierarchical multiple regression analysis. Results: The regression model had an adjusted R2 of .61, indicating that education goal, active learning, facilitator satisfaction, and fidelity were significant predictors of students’ self-confidence in simulation learning. Conclusion: To increase students' self-confidence with simulation learning strategies, it is necessary to design lessons that include educational goals, active learning, improved student satisfaction with the facilitator and fidelity based on the Jeffries Simulation Framework.

코로나 팬데믹으로 언택트 교육의 중요성이 부각되었으나, 교육 분야에서의 AI 도입률은 상대적으로 낮은 상태이 며, AI 학습 로봇을 활용한 학습자 간 친밀도 연구는 부족한 상황이다. 이에 본 연구에서는 언택트 시대에 맞춰 스마트 학습 환경에서 AI 학습 로봇의 사용자 친밀도에 영향을 미치는 요인들을 분석하였다. 이를 위해 소셜 빅데 이터 분석으로 스마트 학습과 AI 학습 로봇에 대한 사회적 인식의 변화를 조사하였으며 언급량의 추이를 파악하였 다. 연구 결과, 스마트 학습에 대한 긍정적 인식이 부정적 인식보다 월등히 높게 나타났으며, 이는 기술이 교육에 가져다주는 편리함과 접근성 향상 등 긍정적인 변화를 반영한 것으로 사료된다. 그러나 스마트폰 사용에 대한 부정 적 인식도 다소 강하게 나타났는데, 이는 스마트폰 사용이 학습에 방해가 될 수 있다는 우려와 같은 기술 의존에 대한 부정적 측면을 반영한 결과로 해석된다. 이러한 결과는 스마트 학습과 AI 기술의 교육적 활용에 대한 사회적 우려와 기대가 혼재되어 있음을 보여준다. 스마트 학습 기술 중 특히 AI 학습 로봇의 효과적인 도입과 활용을 위해 서는 이러한 사회적 인식을 고려한 접근의 필요성을 시사한다. 본 연구에서는 스마트 학습 환경에서 AI 학습 로봇의 효과적인 도입과 활용을 위한 기초 자료를 제공하며, 교육 기술 개발에 있어 사용자 친밀도와 사회적 인식을 고려한 접근의 필요성을 제시한다.

The purpose of this study is to investigate the effect of ‘individual coaching’ and ‘L2 learning experiences’ on TOEIC learning among low proficiency learners. Among the 194 college students who received classroom coaching, the 23 students who scored 2 to 6 (out of 25) on Simple TOEIC 1 were given three individual coaching sessions. The effect of coaching was quantitatively proven through the independent samples t-test conducted on the scores of Simple TOEIC 1 and Simple TOEIC 2 between the individual coaching mixed group and the classroom coaching only group. The more individual coaching participants had different types of L2 learning experiences, the more their English achievement improved. In contrast, students who participated in classroom coaching only saw their academic performance decline. During individual coaching, participants who improved their English language achievement had positive learning experiences and feelings (confidence), while those who did not improve their grades experienced negative learning experiences and feelings. The clearer each participant’s learning goals (ideal L2 self) were, the more specific and continuous learning was possible, which was linked to improved English language achievement. Qualitative data from individual coaching sessions revealed the reasons for some participants’ academic success or failure.

본 연구는 뷰티 분야에서 디지털 기술 적용 및 혁신수용으로 나타나는 변화에 대한 인식개선 및 해결방안으로 뷰티관련 전공 학습자들의 신기술 수용의도를 분석하여 뷰티산업을 이끌어 갈 예비 뷰티 서비스 전문가들에게 필요한 전문적인 디지털 관련 기술 교과목을 개설하여 교육하고, 신기술을 적용할 수 있는 능력을 배양하여 디지털 기술에 대한 인식도가 높은 뷰티 전문가 배출의 가능성을 알아보고자 하였 다. 뷰티전공 학습자의 디지털 신기술 수용의도를 분석한 결과 신기술에 대한 주관적 규범, 자기효능감은 매 개변수인 용이성에 유의미한 영향을 미치는 것으로 나타났으며, 혁신의지와 자기효능감은 매개변수인 유 용성에 유의미한 영향을 미치는 것으로 나타났다. 그러나 혁신의지는 용이성에 유의미한 영향을 미치지 않는 것으로 나타났다. 또한 용이성과 유용성은 수용태도에 유의미한 영향을 미치는 것으로 나타났으며, 수용태도는 신기술 수용의도에 유의미한 영향을 미치는 것으로 나타났다. 이러한 결과를 종합하여 볼 때 뷰티전공 학습자들의 디지털 기술 관련 기초지식 수준을 분석하고, 디지털 신기술과 관련한 기초지식을 습득할 수 있도록 비교적 낮은 수준의 관련 교과목 개발 및 프로그램을 활용하여 뷰티전공 학숩자들이 디지털 신기술을 쉽게 인식할 수 있는 변화의 계기가 마련될 필요가 있다.

In the manufacturing industry, dispatching systems play a crucial role in enhancing production efficiency and optimizing production volume. However, in dynamic production environments, conventional static dispatching methods struggle to adapt to various environmental conditions and constraints, leading to problems such as reduced production volume, delays, and resource wastage. Therefore, there is a need for dynamic dispatching methods that can quickly adapt to changes in the environment. In this study, we aim to develop an agent-based model that considers dynamic situations through interaction between agents. Additionally, we intend to utilize the Q-learning algorithm, which possesses the characteristics of temporal difference (TD) learning, to automatically update and adapt to dynamic situations. This means that Q-learning can effectively consider dynamic environments by sensitively responding to changes in the state space and selecting optimal dispatching rules accordingly. The state space includes information such as inventory and work-in-process levels, order fulfilment status, and machine status, which are used to select the optimal dispatching rules. Furthermore, we aim to minimize total tardiness and the number of setup changes using reinforcement learning. Finally, we will develop a dynamic dispatching system using Q-learning and compare its performance with conventional static dispatching methods.

With the advent of the 4th Industrial Revolution, changes in the market environment and employment environment are accelerating due to smart technological innovation, and securing professional manpower and developing human resources for domestic small and medium-sized enterprises is becoming very important. Recently, most of the domestic small and medium-sized enterprises are experiencing hiring difficulties, and the development and training of human resources to overcome this is still lacking in systemization, despite much support from the government. This reflects the reality that it is not easy to invest training costs and time to adapt new employees to small and medium-sized businesses. Based on these problems, the work-study parallel project was introduced to cultivate practical talent in small and medium-sized businesses. Work-study parallel training is carried out in the form of mentoring between corporate field teachers and learning workers in actual workplaces, and even if the training is the same, there are differences depending on the learner's attitude, learning motivation, and training achievement. Ego state is a theory that can identify personality types and has the advantage of being able to understand and acknowledge oneself and others and intentionally improve positive factors to induce optimized interpersonal relationships. Accordingly, the purpose of this study is to analyze the attitudes of learning workers, who are the actual subjects for improving the performance of work-study parallel projects and establishing a stable settlement within the company, based on their ego status. Through this study, we aim to understand the impact of the personality type of learning workers on training performance and to suggest ways to improve training performance through work-study parallelism.

New motor development requires high-speed load testing using dynamo equipment to calculate the efficiency of the motor. Abnormal noise and vibration may occur in the test equipment rotating at high speed due to misalignment of the connecting shaft or looseness of the fixation, which may lead to safety accidents. In this study, three single-axis vibration sensors for X, Y, and Z axes were attached on the surface of the test motor to measure the vibration value of vibration. Analog data collected from these sensors was used in classification models for anomaly detection. Since the classification accuracy was around only 93%, commonly used hyperparameter optimization techniques such as Grid search, Random search, and Bayesian Optimization were applied to increase accuracy. In addition, Response Surface Method based on Design of Experiment was also used for hyperparameter optimization. However, it was found that there were limits to improving accuracy with these methods. The reason is that the sampling data from an analog signal does not reflect the patterns hidden in the signal. Therefore, in order to find pattern information of the sampling data, we obtained descriptive statistics such as mean, variance, skewness, kurtosis, and percentiles of the analog data, and applied them to the classification models. Classification models using descriptive statistics showed excellent performance improvement. The developed model can be used as a monitoring system that detects abnormal conditions of the motor test.

Purpose: Nursing students' competence in virtual simulation-based learning is a key factor in its success. This study explored the validity and reliability of a virtual-simulation-based learning competency self-evaluation tool for nursing students. Methods: Data were collected from a web-based survey. First, 11 nursing professors participated in a focus group interview, and 7 simulation education experts participated in the preliminary item content validity. The participants in these two aspects were not the same. Then, a preliminary survey was conducted with 15 fourth-year nursing students in I City. Next, based on these three efforts, a final survey comprising 20 evaluation items was developed. This survey was administered to third- and fourth-year nursing students at four nursing colleges in Korean provinces (Seoul, Gyeonggi, Gangwon, and Gyeongsan-do); 222 complete questionnaires were used for the final analysis. Further, Kirkpatrick’s evaluation model was used for four steps each of tool development and verification processes of the associated psychometric aspects, for a total of eight steps. An exploratory factor analysis was performed on the collected survey data, and verify the tool's validity and reliability. Results: Four factors comprising 15 items explained 66.59% of the variance: learning preparation and start-up (4 items), nursing assessment (3 items), data interpretation (3 items), and problem solving (5 items). The Cronbach's α of the tool was 0.74, and that of the factors ranged from 0.72 to 0.80. Conclusions: The tool's validity and reliability were demonstrated using established methodologies. This tool can be useful for evaluating Korean nursing students' virtual simulation learning competence.