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All Journal Belitung Nursing Journal Lingeduca: Journal of Language and Education Studies Journal Neosantara Hybrid Learning
Fang, Wang
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Computer Science & IT Education Languange, Linguistic, Communication & Media Nursing Social Sciences Other

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Analysis of Effectiveness in Distance Learning in Tahfidz Lessons Martin, Jayshree; Fang, Wang; Brunel, Benjamin
Journal Neosantara Hybrid Learning Vol. 1 No. 1 (2023)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jnhl.v1i1.80

Abstract

For those who adhere firmly to Al Quran, Allah will reward them and their status will be increased by Allah SWT. This research aims to discuss the effectiveness of tahfidz learning over long distances at Musholla Nurul Huda, Indudur nagari, Subdistrict IX, Koto Sungai Lasi, Solok Regency. This research aims to find out whether tahfidz suadah lessons are effective or not. The method used by researchers in this research is a qualitative research method with a descriptive approach. With researchers using this qualitative method, researchers can obtain accurate data. The method of data collection that the researcher uses is observation, interviews, and documentation. For the basis of the data, the triangulation technique is used which is one of the approaches used to dig and perform qualitative data processing techniques. The tahfidz learning system at Musholla Nurul Huda has not been effective because there are obstacles that make distance learning not run optimally. The lack of facilities and infrastructure in distance learning which is not yet adequate, and the large amount of money spent to buy internet quota, and the network which is difficult to guess is sometimes high and then weak due to being in the countryside. So that the learning given by the teacher is not 100% smooth or effective.
Increase Elementary School Students' Interest in Learning During Covid-19 with Teaching Materials Using E-Books Brunel, Benjamin; Martin, Jayshree; Fang, Wang
Lingeduca: Journal of Language and Education Studies Vol. 2 No. 1 (2023)
Publisher : Yayasan Pedidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (352.692 KB) | DOI: 10.55849/lingeduca.v1i2.47

Abstract

The purpose of this research is to increase students' interest in learning in elementary schools during Covid-19 with e-book teaching materials by utilizing technology in learning media, especially using digital books (e-books) through computer intermediaries, laptops or smartphones. Since the existence of Covid-19, the level of interest in learning from students has been very minimal, because educators are less creative in using technology when carrying out the learning process, so that students are less interested in doing learning, by utilizing technology published in digital form can be used by students to facilitate students in learning and increase student interest in learning during the Covid-19 pandemic by displaying information in the form of text, images, audio, video, animation, narration, music, and other multimedia. The method used in this study is a quantitative research method, in which this method researchers can collect data by means of in-depth interviews using the Google form. Because of that, with the e-book media, researchers hope that students' interest in learning can increase even though learning is still done online
Characterizing potential subtypes and influencing factors of self-directed learning competence among clinical nurses in China by latent profile analysis Zhisheng, Zhang; Mingju, Cai; Ruichu, Zhang; Fang, Wang; Shaona, Liao; Anliu, Nie; Xiangfen, Su
Belitung Nursing Journal Vol. 11 No. 6 (2025): November - December
Publisher : Belitung Raya Publisher - Belitung Raya Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33546/bnj.4144

Abstract

Background: Nurses demonstrate varying levels of self-directed learning competence, which is influenced by multiple individual and contextual factors. Identifying profiles with varying levels of self-directed learning is essential for providing targeted support and training. However, there is limited research exploring the potential profiles of self-directed learning competence among nurses. Objectives: This study aimed to identify distinct latent profiles of self-directed learning competence among nurses and analyze the influencing factors. Methods: A cross-sectional study design was used. Nurses were recruited using a convenience sampling from four tertiary hospitals in Guangzhou, China, between August 2024 and February 2025. The Self-Directed Learning Competence Scale for Nurses was used to assess the self-directed learning Competence of nurses. Latent profile analysis was performed to identify different potential profiles. Pearson’s chi-square test and multinomial logistic regression were used to explore the factors influencing self-directed learning competence. Results: A total of 740 nurses participated. Three latent profiles of self-directed learning competence were identified: low (n = 356, 48.1%), medium (n = 291, 39.3%), and high (n = 93, 12.5%). The self-directed learning competence of nurses was influenced by various factors, including Junior college and below (OR = 0.555, p= 0.043); Monthly number of night shifts = 3~4 (OR = 2.859, p = 0.029); Learning atmosphere = neutral (OR = 0.342, p  = 0.018) and good (OR = 0.412, p = 0.038); Learning willingness (OR = 1.425, p  <0.001), Difficulty of title promotion = difficult (OR = 2.628, p = 0.029) and Job stress (OR = 0.981, p  <0.001). Conclusion: The study revealed diverse profiles of self-directed learning competence among nurses. Nursing managers should design differentiated strategies based on these profiles. Enhancing organizational support and stimulating learning motivation can help improve nurses’ self-directed learning competence, thereby promoting their professional development and improving the overall quality of clinical nursing care.
Co-Authors Anliu, Nie Brunel, Benjamin Martin, Jayshree Mingju, Cai Ruichu, Zhang Shaona, Liao Xiangfen, Su Zhisheng, Zhang