Pusat Pengajian Pendidikan Jarak Jauh
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- PublicationExploring Students’ Motivation And Experience In Vlog Task-Based Language Teaching For Ielts Speaking Skills In A Chinese International School In Guangzhou(2025-02)Miaosheng, ZhanThis study investigates the motivation and experience of using vlog task-based language teaching (tblt) to enhance international english language testing system (ielts) speaking among chinese high school students. The research explores how the vlog tblt can improve students' ielts speaking based on dörnyei’s motivational theory and gibbs’ reflective cycle. A six-week vlog tblt program was implemented, during which students engaged in weekly tasks with themes of objects, animals, and sports vlogs, each lasting for two weeks. The first weeks involved a 60-minute class discussion where students introduced their vlogs, scaffolded through celebrity speaking on related topics, and, the subsequent week, produced the vlogs using video-editing applications and then shared them using media platforms.
- PublicationThe Impact Of Artificial Intelligence On Labour Productivity In China(2025-01)Zouya, LaiThis study examines the impact of artificial intelligence (ai) on labour productivity in china from 2000 to 2020, using three ai proxies: investment in fixed social assets for information transmission, computer services, and the software industry; intensity of scientific research fund investments; and ai patent applications. The study employs the diff-gmm and sys-gmm methods to investigate the effects of ai on three labor skill categories (high, medium, and low-skilled occupations). The findings reveal that scientific research fund investment increases the productivity of high-skilled workers by 41.6%, while ai patent applications increase productivity by 39.3%. However, investment in fixed social assets is not statistically significant for high-skilled workers. In contrast, it increases the productivity of medium-skilled workers by 18.5%. For low-skilled workers, both ai patent applications and fixed social asset investments boost productivity by 15.9% and 32.2%, respectively. The study also compares the impact of ai across different regions in china. In autonomous regions, investment in fixed social assets significantly enhances productivity across all worker skill categories. However, in 23 major provinces,
- PublicationDensity Functional Theory Study Of Electronic Structure And Muon Hyperfine Interaction In Guanine-Cytosine Double Strand Dna Molecule(2023-12)Jamaludin, AmmainaDeoxyribonucleic acid (DNA) is a double helical molecule that serves as a medium for an efficient electron transport process that are closely related to DNA damage and development of DNA-based devices. The complexity of understanding the electron transport within DNA molecule has intrigued researchers to perform Muon Spin Resonance (μSR) eksperiment which can provide information regarding the topology of electron transport, electron mobility, and muon hyperfine coupling constant (HFCC). However, all the information is very difficult to be interpreted because the electronic structure and muon HFCC is still unclear due to the unknown position of muonium trapping sites. Therefore, Density Functional Theory (DFT) method at B3LYP/6-31G level was employed to study the electronic structure, muonium trapping sites and muon HFCC. The aims of this study are to determine the electronic structure of pure and methylated 1, 2, and 3 base pair guanine-cytosine double strand DNA, and to predict the external applied magnetic fields in Avoided Level Crossing Muon Spin Resonance (ALC-μSR) measurements to observe any resonance dips in the spectrums. It was found that the addition of a methyl group at the C5 atom of the cytosine base does not affect the overall sizes of the studied DNA molecules.
- PublicationAssessing The Potential For Freshwater Aquaculture Development In Timor-Leste Using Gis Modeling(2025-01)Teoh, Shwu JiauTimor-leste adopted the national aquaculture development strategy (2012–2030) to enhance food security and rural livelihoods by promoting freshwater aquaculture in areas with adequate resources and favourable socioeconomic conditions. Despite the widespread use of gis in aquaculture research, its application to freshwater pond aquaculture in timor-leste remains underutilized. This study addresses this gap by developing a gis-based suitability model tailored to timor-leste’s unique biophysical and socioeconomic conditions. Biophysical and socioeconomic factors were identified through a literature review and refined via stakeholder consultations and participatory gis methods to ensure contextual relevance. The analytical hierarchy process (ahp) was used to weight criteria systematically and multi-criteria evaluation with weighted linear combination (mce-wlc) integrated these factors to assess suitability. Fuzzy logic transformations accommodated uncertainties and represented continuous suitability transitions. The gis model, validated using actual pond location data with 84% accuracy, identified 1,312 km² of highly suitable areas across three municipalities: bobonaro (588.1 km²), viqueque (373.2 km²), and lautem (350.6 km²). High-suitability areas relative to total municipality areas were most concentrated in ermera (43.1%), bobonaro (42.7%), and aileu (39.6%).
- PublicationComparison Of Parameter Estimators Of Lognormal Distribution For Predicting Pm10 And Pm2.5 Concentrations(2024-11)Omar, Muhammad UthmanPm₁₀ and pm₂.₅ are among the dominant air pollutants in malaysia and have caused severe adverse effects on human health, especially on children, pregnant mothers, and senior citizens. To better understand the distribution of pm₁₀ and pm₂.₅, statistical modelling using the lognormal distribution was used because of its positively-skewed nature and is regarded as the most appropriate distribution for particulate matter in malaysia. The lognormal distribution has two parameters namely location and scale parameters. Parameter estimation is a crucial step in getting the best prediction since the value of location and scale parameters can affect the error and accuracy of the prediction. In this study, four different estimators namely the method of moments (mom), maximum likelihood estimator (mle), probability weighted moments (pwm), and uniformly minimum variance unbiased estimator (umvue) were used to estimate the location and scale parameters. Hourly data of pm₁₀ and pm₂.₅ concentrations from 2017 to 2020 on four different classifications of monitoring stations namely jerantut as background, sungai petani as suburban, alor setar as urban, and perai as industrial were used.