This study aimed to investigate English as a Second Language (ESL) teachers' technology acceptance levels and to identify the factors affecting their behavioral intentions (BI) with respect to technology use in the post-COVID-19 era. A cross-sectional survey of 361 Malaysian ESL teachers was conducted. Participants were recruited via convenience sampling, and they answered an online survey questionnaire that was designed with reference to past studies. The collected data were analyzed via descriptive statistics, Pearson's correlation, and multiple regression analyses. The findings revealed that Malaysian ESL teachers generally had a high level of technology acceptance in the post-COVID-19 era. Their BIs had a significant relationship with three factors: performance expectancy (PE), effort expectancy (EE), and social influence (SI), of which EE was identified as the most significant factor influencing their BI with respect to technology use in the post-COVID-19 era. Conversely, the presence of facilitating conditions did not have a substantial connection with ESL teachers' behavioral intentions for technology use after the pandemic, despite the fact that there was weak positive relationship with each other. This study provides insights for the field of educational psychology by identifying the current trends in ESL teachers' behavioral intentions in adopting technology in the post-COVID-19-era ESL classrooms. The findings of this study may also support investigations into technology acceptance in ESL teaching, illustrating a growing need to provide adequate educational and technological tools, resources, and facilities to facilitate the delivery of lessons by ESL teachers. Future studies should conduct longitudinal research and investigate more variables from different technology acceptance models.
Education evolves and progresses globally in a technology-driven world, highlighting the integration of VUCA elements of volatility, uncertainty, complexity, and ambiguity in lessons. Learners are molded to equip themselves with the world and real-life knowledge in their readiness to adapt to the VUCA world. Global education consists of preparing learners for the VUCA world. This study aimed to investigate the current English as a Second Language (ESL) teaching practices and the ESL teachers' incorporation of VUCA elements in ESL lessons. This study was conducted quantitatively using a survey questionnaire. This study was administered to 30 ESL teachers from different secondary schools in a district in Malacca. The results from the questionnaire revealed that the ESL participants had positive perceptions toward the adaptation of VUCA in the current ESL lessons. Most of the ESL teachers agreed that they adapted VUCA elements into the activities during lessons, although some showed uncertainty about their knowledge and understanding of VUCA. From the high agreement levels in the findings, it can be concluded that the ESL teachers agreed that VUCA elements through problem-based, digital-based, collaborative, and challenging activities in English lessons are beneficial to assist students' meaningful and autonomous learning. Based on these findings, implications were made for enhancing ESL teachers' knowledge, understanding, and skills in adapting VUCA in lessons in response to global education demand.
Atherosclerosis is known as the leading factor in heart disease with the highest mortality rate among the Malaysian population. Usually, the gold standard for diagnosing atherosclerosis is by using the coronary computed tomography angiography (CCTA) technique to look for plaque within the coronary artery. However, qualitative diagnosis for noncalcified atherosclerosis is vulnerable to false-positive diagnoses, as well as inconsistent reporting between observers. In this study, we assess the reproducibility and repeatability of segmenting atherosclerotic lesions manually and semiautomatically in CCTA images to identify the most appropriate CCTA image segmentation method for radiomics analysis to quantitatively extract the atherosclerotic lesion. Thirty (30) CCTA images were taken retrospectively from the radiology image database of Hospital Canselor Tuanku Muhriz (HCTM), Kuala Lumpur, Malaysia. We extract 11,700 radiomics features which include the first-order, second-order and shape features from 180 times of image segmentation. The interest vessels were segmentized manually and semiautomatically using LIFEx (Version 7.0.15, Institut Curie, Orsay, France) software by two independent radiology experts, focusing on three main coronary blood vessels. As a result, manual segmentation with a soft-tissuewindowing setting yielded higher repeatability as compared to semiautomatic segmentation with a significant intraclass correlation coefficient (intra-CC) 0.961 for thefirst-order and shape features; intra-CC of 0.924 for thesecond-order features with p < 0.001. Meanwhile, the semiautomatic segmentation has higher reproducibility as compared to manual segmentation with significant interclass correlation coefficient (inter-CC) of 0.920 (first-order features) and a good interclass correlation coefficient of 0.839 for the second-order features with p < 0.001. The first-order, shape order and second-order features for both manual and semiautomatic segmentation have an excellent percentage of reproducibility and repeatability (intra-CC > 0.9). In conclusion, semi-automated segmentation is recommended for inter-observer study while manual segmentation with soft tissue-windowing can be used for single observer study.