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This research investigates the post-internship phase for cadets at the Sekolah Tinggi Ilmu Pelayaran Jakarta with a focus on curriculum effectiveness, vocational training impact, language proficiency challenges, technology integration preferences, and the intricate influence of geographical diversity. Results reveal the integrative curriculum's success in transitioning theoretical knowledge to practical application, emphasizing the critical role of vocational training. Language proficiency nuances and a desire for balanced technology integration emerge, while geographical diversity affects cultural adaptation. Implications include refining maritime education, fostering inclusivity, and aligning educational practices with industry demands. Recognizing limitations, the study advocates for broader institutional research and targeted language proficiency investigations in future studies.

Adapting the Technology Acceptance Model (TAM) framework, this study investigates English teachers' perspectives on the intention to adopt and integrate ChatGPT in their classrooms. This study utilizes quantitative cross-sectional research with 114 respondents answering the online questionnaire. The Structural Equation Modeling (SEM) statistical analysis through SmartPLS 3.0 was employed to analyze the collected data. The result indicates that the proposed TAM model in this study can predict ChatGPT acceptance in English language teaching. Additionally, the structural model showed that perceived usefulness, ease of use, and attitude toward using significantly and positively influenced behavioral intention. Furthermore, attitude toward using and behavioral intention significantly and positively impacted actual system use. Teachers' perspectives on ChatGPT uptake and integration into English language learning are critical to technological innovation. This paper could assist teachers in Indonesia and comparable regions in understanding and adopting ChatGPT in English language teaching.

The teacher has an important role in making pupils skilled in inquiry, viz guiding them to carry out inquiry steps in science learning. However, there are obstacles to applying online learning at primary school level, especially inquiry-based science. The purpose of this research is to analyse the application of inquiry in science learning, analyse the effectiveness of e-learning based on the 2020 at the Indonesian Ministry of Education and Culture guidelines, and identify obstacles to implementing e-inquiry science learning at the primary level. This study employed a descriptive qualitative approach. Sources of data were resource persons from 6 educational institutions including trainers, school supervisors, principals, teachers, Grade VI pupils, and their parents. The result showed the only a small number of teachers implemented on-line science-based inquiry learning and the effect of the learning was the utmost significance on student's achievement. However, most of primary school teachers have not applied inquiry-based methods in science learning. Several obstacles to implementing e-inquiry learning at the primary level were identified. These obstacles include the teachers did not understand how to develop an online inquiry model learning scenario, had low skills in using ICT, lack of support for ICT facilities and of e-learning inquiry learning guide, and had limited time.

This small-scale pilot study was developed to examine the perceived occupational balance of graduate occupational therapy students and implement an education and coaching intervention to promote occupational balance for those who have difficulty achieving and maintaining it. Although literature provides many examples of interventions to facilitate stress relief in graduate students, this is the first to address the promotion of occupational balance in this effort, which has been identified as a student-reported need. A sequential explanatory mixed-methods approach was used to obtain quantitative and qualitative data on occupational therapy students' satisfaction with their balance of activity in all areas of occupation. The impact of that balance on stress levels and occupational satisfaction was examined utilizing an investigator developed scaled survey and The Canadian Occupational Performance Measure. Participants (N=22) were MSOT and OTD students from all academic years of their program. A six-week group education program was implemented. One additional 30-minute individual coaching session was held virtually with each student and the primary investigator to target individual goals. Survey data collected before the start of the educational series and again at its conclusion indicate an aggregate decrease in students' perceived stress (-0.85); an increase in perceived occupational performance (mean +1.26); and an increase in perceived occupational satisfaction (mean +2.10). The desired outcome of the intervention was to provide students with strategies to increase lifestyle balance to help manage some of the stresses of graduate academia, and ultimately increase students' health and wellness to promote retention and successful completion of graduate education.

Fresh graduates often face significant uncertainty due to the intangible complexities of employment, a lack of adequate service orientation, and delayed realization of long-term benefits. This study investigates the relationship between the quality of experiential value and its impact on the loyalty of young workers. The research was conducted on fresh graduates participating in a non-wage employment program in Medan City. A sample of 250 participants was selected using the quota sampling method. SmartPLS 3.0 was utilized for statistical analysis. The findings demonstrate that the benefits received positively and significantly influence the experiential value for young workers. Moreover, the study confirms that these benefits indirectly enhance loyalty through improvements in the perceived quality of the experience. The results highlight the importance of targeted training methods to foster the value, commitment, and long-term engagement of youths entering the workforce.

Applying bibliometric techniques to blended learning research is still relatively uncommon. This study employs bibliometric analysis, employing data from the Scopus database and VOSviewer to show papers published between 2012 and 2022. The study's sample is made up of publications on blended learning in science that have been indexed by Scopus and were published between 2012-2022, amounting to 194 articles. Through Scopus filters, 85 irrelevant works, including editorials, comments, and book reviews, were excluded. Subsequently, 109 articles relevant to the research objectives were extracted. Citation patterns, publication trends, frequently cited articles, and author keyword analysis were examined, shedding light on the growth of research in blended learning chemistry. As a result, research in blended learning chemistry has grown steadily from year to year in publications in journals with a Scopus index. Analysis and online learning are two terms rarely used concerning blended learning in chemical education. The most often used terms were "e-learning," "online learning," "collaborative learning," and "reverse classroom." Most blended learning research is carried out in the United States and the United Kingdom. For all of the papers examined, bibliometric analysis was utilised to determine goals and key areas of chemical content. The findings contribute to a deeper understanding of the evolution and current state of blended learning in chemistry education, providing insights for future research directions and educational practices.

Education plays a very important role in improving the quality of human resources. In higher education, students need learning that is innovative and not monotonous so that learning goals can be achieved. In this research, what will be discussed further is the development of learning methods by combining 2 methods, namely Cooperative Based Learning (CBL) with Problem-Based Learning (PBL) in the Advanced Financial Management course. This research method uses Pretest - Posttest Design. The data population is 711 students collected from 17 classes taking Advanced Financial Management courses at Putra Indonesia University YPTK Padang. The sampling technique uses probability sampling. The data that will be used as a sample are observations of 117 students collected from 3 classes. The CPBL method is implemented by grouping students into groups of 4-5 people to discuss each case in the material. Data will be analyzed based on the completeness of learning outcomes and calculating N-Gain. From the data processing, the results obtained were that by combining these 2 methods, it was successful in improving student learning outcomes and the students' completeness test scores were also proven to be very successful in being upgraded. The effectiveness of the collaboration between these 2 methods reaches the high category of the N-Gain test. This is a new variation in making learning calculations that use many formulas more challenging, increasing students' enthusiasm for learning and providing satisfactory learning results. This method is worth utilizing and can be used in all courses that involve calculations and case questions.

This study identifies and analyzes the processes and differences in distance learning implementation between city and village schools in Indonesia and Malaysia. Characteristics of students and teachers, distance learning facilities, ability to use technology, and parent's role in the learning process will be analyzed in depth. This research will simultaneously hypothesize the link between these factors and student learning independence. This research is a mixed methods research that combines qualitative research that using observation and interview techniques and quantitative methods that using questionnaire technique. This research was conducted on elementary school students in Indonesia and Malaysia located in rural and urban areas, with a total sample of 240 students ranging from low to high grades. Apart from students, as many as 60 school academics consisting of principals, teachers, and staff were also interviewed to obtain more comprehensive data and data triangulation. Quantitative data were analyzed using a qualitative-quantitative descriptive method where the qualitative statements in the questionnaire were converted into quantitative data, while qualitative data were analyzed using an interactive model mentioned by Miles & Huberman (2014). The study results show that the distance learning implementation between city and village schools experiences a slight difference with the rapid development of information technology. Of the four aspects studied, there are aspects in which village schools are superior to city schools. These four aspects are also investigated for their influence on student learning independence so that further research can be carried out regarding the correlation of these aspects to student learning independence.

Background: Dementia is a cognitive decline that leads to the progressive deterioration of an individual's ability to perform daily activities independently. As a result, a considerable amount of time and resources are spent on caretaking. Early detection of dementia can significantly reduce the effort and resources needed for caretaking. Aims: This research proposes an approach for assessing cognitive decline by analysing speech data, specifically focusing on speech relevance as a crucial indicator for memory recall. Methods & Procedures: This is a cross-sectional, online, self-administered. The proposed method used deep learning architecture based on transformers, with BERT (Bidirectional Encoder Representations from Transformers) and Sentence-Transformer to derive encoded representations of speech transcripts. These representations provide contextually descriptive information that is used to analyse the relevance of sentences in their respective contexts. The encoded information is then compared using cosine similarity metrics to measure the relevance of uttered sequences of sentences. The study uses the Pitt Corpus Dementia dataset for experimentation, which consists of speech data from individuals with and without dementia. The accuracy of the proposed multi-QA-MPNet (Multi-Query Maximum Inner Product Search Pretraining) model is compared with other pretrained transformer models of Sentence-Transformer. Outcomes & Results: The results show that the proposed approach outperforms the other models in capturing context level information, particularly semantic memory. Additionally, the study explores the suitability of different similarity measures to evaluate the relevance of uttered sequences of sentences. The experimentation reveals that cosine similarity is the most appropriate measure for this task. Conclusions & Implications: This finding has significant implications for the early warning signs of dementia, as it suggests that cosine similarity metrics can effectively capture the semantic relevance of spoken language. The persistent cognitive decline over time acts as one of the indicators for prevalence of dementia. Additionally early dementia could be recognised by analysis on other modalities like speech and brain images.