The study of metaphor has a long history, and it has gradually been taken seriously from the very beginning of Aristotle of ancient Greek. In 1980, American scholars George Lakoff and Mark Johnson published the book Metaphor We Lived By jointly, from which metaphor began to be known as a way of cognition. The differences in languages and cultures, together with the complicated working mechanism of metaphor, post a great challenge in translating metaphor in literary work. This paper analyzes example sentences taken from Chinese classical works. By comparing these sentences with their English translations, we can have a glimpse of the translation strategies often used in rendering metaphor.
Personal data privacy regulation and mitigation are critical in implementing financial technology (fintech). Problems with fintech users’ data might result from data breaches, improper usage, and trade. Issues with personal data will result in financial losses, crimes, and violations of personal information. This legal research used three approaches: conceptual, comparative, and statute-based. In order to implement the statutory method, all laws and regulations pertaining to the legal concerns of information technology, fintech, personal data security, and protection are reviewed. Due to the nature of the sources of data, this study mainly used literature study and document observation to collect the data. Then, legal interpretation, legal reasoning, and legal argumentation are all included in the qualitative juridical analysis. This article recommends two strategies that Indonesia should take to provide personal data protection, including: 1) establishing the Personal Data Protection Commission (PDPC); and 2) improving the financial literacy of consumers.
This study aims to examine the pathways through which the user experience (UX) of ChatGPT, a representative of generative artificial intelligence, affects user loyalty. Additionally, it seeks to verify whether ChatGPT’s UX varies according to a user’s need for cognition (NFC). This research proposed and examined how ChatGPT’ UX affect user engagement and loyalty and used mediation analysis using PROCESS Macro Model 6 to test the impact of UX on web-based ChatGPT loyalty. Data were collected by an online marketing research company. 200 respondents were selected from a panel of individuals who had used ChatGPT within the previous month. Prior to the survey, the study objective was explained to the respondents, who were instructed to answer questions based on their experiences with ChatGPT during the previous month. The usefulness of ChatGPT was found to have a significant impact on interactivity, engagement, and intention to reuse. Second, it was revealed that evaluations of ChatGPT may vary according to users’ cognitive needs. Users with a high NFC, who seek to solve complex problems and pursue new experiences, perceived ChatGPT’s usefulness, interactivity, engagement, and reuse intentions more positively than those with a lower NFC. These results have several academic implications. First, this study validated the role of the UX in ChatGPT. Second, it validated the role of users’ need for cognition levels in their experience with ChatGPT.
This study aims to explore the link and match policy through industrial classes and its impact on the competence and employability of Vocational High School (VHS) graduates. The importance of this research is to address the gap between education and industry by assessing the effectiveness of industrial classes in improving the skills and employability of VHS graduates. Horison Industrial Class (HIC) in 4 schools, namely: (1) SMKN 57 Jakarta, 2 batches of Hospitality expertise programs; (2) SMKN 6 Yogyakarta, there are 3 batches of Hospitality expertise programs; (3) SMKN 6 Semarang, there are 2 batches of Hospitality expertise programs; (4) SMKN 2 Semarang. This research emphasizes the important role of industry involvement and commitment in aligning the curriculum with industry needs. The field findings show that the implementation of the link and match policy through industrial classes significantly affects the quality of learning in VHS. The study also highlights the influence of government support and industry associations in ensuring the successful implementation of industrial classes. Student participation in industry classes directly enriches their learning experiences by allowing them to engage in direct practice in a real work environment. These findings can contribute to the implementation of policies and regulations in the field of education, especially in the context of vocational education. The findings of this study can also be applied to vocational students to improve the quality of graduates in order to meet the qualification standards of employees in companies or industries.
Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.
UAVs, also known as unmanned aerial vehicles, have emerged as an efficient and flexible system for offering a rapid and cost-effective solution. In recent years, large-scale mapping using UAV photogrammetry has gained significant popularity and has been widely adopted in academia as well as the private sector. This study aims to investigate the technical aspects of this field, provide insights into the procedural steps involved, and present a case study conducted in Cesme, Izmir. The findings derived from the case study are thoroughly discussed, and the potential applications of UAV photogrammetry in large-scale mapping are examined. The study area is divided into 12 blocks. The flight plans and the distribution of ground control point (GCP) locations were determined based on these blocks. As a result of the data processing procedure, average GCP positional errors ranging from 1 to 18 cm have been obtained for the blocks.
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