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Development and Validation of EFL Speaking Strategy, Speaking Anxiety, Learning Motivation, and Learning Attitude Questionnaires
No full textEffectively assessing the speaking performance of English as a Foreign Language (EFL) students remains a major challenge for language educators, particularly in the context of Chinese universities. Speaking strategy use, speaking anxiety, learning motivation, and learning attitude are four critical constructs that significantly influence EFL learners’ speaking proficiency. While previous studies have examined these factors individually or in limited combinations, few have focused on developing a comprehensive tool that measures them collectively within the Chinese EFL context. Therefore, this pilot study aimed to develop and validate a questionnaire, designed to assess speaking strategies, speaking anxiety, learning motivation, and learning attitudes among Chinese EFL students, which consist of 45, 30, 22 and 49-items scale for each respectively. The purpose of this pilot test was to ensure the reliability and validity of the instrument before it is used in a larger-scale study. The questionnaire was assessed by surveying on 60 participants selected from 1st and 2nd year non-English major undergraduate students at a university in China, with a sample of 27 males and 33 females, along with 34 freshmen and 26 sophomores. A five-phase approach was followed: item development based on literature review, definition of constructs, expert validation by two applied linguistics scholars, and a pilot administration involving 60 first- and second-year Chinese university students. The results showed strong content validity and high internal consistency, with a reliability value of 0.787 for speaking strategies, 0.674 for speaking anxiety, 0.775 for learning motivation, and 0.796 for learning attitudes, making the questionnaire highly reliable and valid tool for future research. This study offers a valuable instrument for educators and researchers to investigate the interconnected roles of these key psychological and behavioral factors in EFL speaking development, particularly within the Chinese academic context
Impact of Targeted Educational Interventions on Robotic Exoskeleton Adoption in Malaysia's Rehabilitation Practices
Get PDFOBJECTIVES: Despite policy support, the adoption of robotic exoskeletons in Malaysia's rehabilitation practices remains limited. This study explores the impact of targeted educational interventions on facilitating robotic exoskeleton adoption among rehabilitation therapists in Malaysia.
DESIGN: The study employed an action research methodology, incorporating pre- and post-intervention surveys adapted from the Technology Acceptance Model (TAM), along with qualitative feedback. The interventions included an educational webinar on the benefits of robotic exoskeletons and training support. Data were collected from 62 rehabilitation therapists across four hospitals in Malaysia. Key variables assessed were Perceived Usefulness (PU), Perceived Ease of Use (PEOU),and Intention to Use (ITU). Quantitative analyses were conducted using paired
t-tests and Pearson correlation, while qualitative feedback was analyzed thematically.
RESULTS: Post-educational intervention, significant improvements were observed: mean PU increased from 3.88 to 4.11 (p = 0.003), mean PEOU from 3.44 to 3.90 (p < 0.001), and mean ITU from 3.83 to 4.06 (p = 0.006). PU and ITU
showed a strong positive correlation (r = 0.769, < 0.001), and similarly, PEOU and ITU (r = 0.667, p < 0.001). Qualitative feedback emphasized the need for practical training and hands-on experience.
CONCLUSIONS: Targeted educational interventions significantly enhance rehabilitation therapists' acceptance and readiness to adopt robotic exoskeletons in Malaysia. By addressing training gaps and providing practical experience, these interventions help bridge the gap between policy and practice, contributing to improved patient care and operational efficiency in clinical settings
Enhancing Child-Friendly Environments in Urban Villages Through Spatial Transformation Strategies in Foshan China
Get PDFThe rapid urbanization of Foshan, China leads to insufficient development of child-friendly environments because urban villages undergo planning deficits alongside limited spatial capabilities. The research explores spatial transformation methods to create more child-friendly environments inside Foshan urban neighborhood areas by assessing independent movement and diverse play opportunities and local resident participation. Our research involved a mixed-methods evaluation of the five villages Shiken, Nanyue, Poyang, Shiliang and Dongpo through spatial mapping, 180 hours of behavioral observations (n = 565), 98 caregiver surveys along with participatory workshops (n = 125). Shiliang emerges as most child-friendly (mean score: 3.77 standard deviation: 0.28) because of its excellent facilities efficient recreational facilities (park coverage exceeds 85% within a 400m radius) combined with high safety ratings (mean score: 3.4) whereas Nanyue stands out as least child-friendly (mean score: 2.42 standard deviation: 0.32) because of its high traffic risks (vehicle density of 12 vehicles per 100 meters of distance). The strength of relationship between park facilities availability and actual usage was 0.77 at a significance level p < 0.01 and vehicle density showed a negative correlation of -0.69 with park safety at p < 0.01. We suggest establishing a complete framework which combines physical space redesign such as larger sidewalks with play areas of different kinds and active involvement of children together with their caregivers for ownership development. The research enhances child-friendly urban planning through an investigation that unites physical and social aspects while presenting applicable guidelines for worldwide urban villages
Utilization of Generative Artificial Intelligence Technologies as Learning Tools among University Students : A Cross-Sectional Study
Get PDFABSTRACT
Artificial intelligence (AI) technologies have the potential to revolutionize the higher-education landscape by offering personalized and adaptive learning experiences. This study aimed to investigate the utilization of AI technologies as a learning tool among university students and identify the factors influencing it. This study utilized a cross-sectional design and collected data through a self-administered questionnaire developed based on the technology acceptance model and Theory of Planned Behavior (TPB). Data from 581 respondents were analyzed using SPSS version 29, employing descriptive statistics and multivariate hierarchical multiple linear regression analysis. The study found that AI technologies were widely utilized by students for various academic tasks, with clarifying understanding (76.1%), paraphrasing (71.6%), and academic translations (71%) being the most common. ChatGPT (91.4%), QuillBot (82.8%), and Grammarly (79.7%) emerged as the most popular AI tools among the participants. A hierarchica1l multiple regression analysis revealed that motivation (β = .17, p = .002), subjective norms (β = .14,
p < .001), and intention to use (β = .49, p < .001) were significant predictors of AI technology use among students. This study highlights the widespread adoption of AI technologies for academic tasks among university students. Higher education institutions foster an environment that enhances students’ motivation, addresses subjective norms, and cultivates a positive intention
towards AI technology adoption to facilitate its effective integ ration into the learning process.
KEYWORDS
Artificial intelligence (AI) technologies, learning tools, Sarawa
Hydrodynamics of Steam-Water Two-Phase Flows ThroughGrooved Walled Passages
Get PDFIn this study, we investigated the flow hydrodynamics of mixture of steam and water through a pipe that has groovedwalls. The walls were roughened using collars that has circular and squared shapes throughout the inner walls of the flowchannel. Our findings indicate that the factors related to the friction of the walls have been associated with wall roughness ranged from0.6to 0.63. The velocity deficit near the wall was slightly greater above the smooth walls compared to the rough walls, reflectingtheimpact of the friction factor. However, the profiles used to quantify the Reynolds normal stresses showed a distinct contrast. Inthe grooved surface channel, pressure-induced drag dominated, leaving little room for viscous effects and resulting in lower peaks. These stresses were heavily influenced by wall geometry. Notably, in channels with squared grooves, flowprofiles wereshows a slight decrease compared to those observed over smooth and rough walls
Obsessive–compulsive symptoms as a unique presentation of complex posttraumatic stress disorder in Southeast Asia : a case report
Get PDFBackground Posttraumatic stress disorder is a mental health condition outlining psychological sequelae experienced after encountering a traumatic event. Complex posttraumatic stress disorder, however, is increasingly recognized as being distinct from posttraumatic stress disorder. This is due to an observed variation from what is traditionally defned as a traumatic event, as well as greater heterogeneity in its presentation. Cultural factors may also infuence defnitions of traumatic events and heterogeneity in presentation.
Case presentation In this case, a 27-year-old Malay male presented with a 9-year history of obsessive–compulsive
symptoms of predominantly sexual content. Although initially treated as obsessive–compulsive disorder, persistent negative self-image and features of complex posttraumatic stress disorder surfaced in the course of therapy,
stemming from a culturally-related punitive upbringing as well as bullying by peers. He responded markedly well
to trauma-based psychotherapy and remains well at time of writing.
Conclusion A diagnosis of complex posttraumatic stress disorder should be considered in the individual who
presents with mental health difculties, particularly if the individual’s symptoms are atypical to classical diagnostic
criteria or the individual does not respond to conventional treatment. It is important to note the role of cultural
background—this may give rise to unique presentations of complex posttraumatic stress disorder, and the triggering events may not be traditionally defned as traumatic. Cultural background may also potentially inform treatment
and future prevention strategies for complex posttraumatic stress disorder
DNA Barcoding and Morphology of the Spine Bahaba, Bahaba polykladiskos (Actinopterygii, Sciaenidae), from Thailand and Borneo, with Notes on Its Taxonomic Status
Get PDFIn this study, we examined the external morphology of croaker specimens with distinct golden body coloration collected from Thailand's Bang Pakong River, along with one specimen of the spine bahaba, Bahaba polykladiskos (Bleeker), from the Sibuti River Estuary in northern Sarawak, Borneo. These specimens differed in coloration from previous descriptions of Ba. polykladiskos, including the specimen from Borneo, but shared other morphological characteristics, particularly a longer interocular distance, that closely aligned them with Ba. polykladiskos. Phylogenetic analyses and species delimitation based on DNA analysis of the COI gene sequence confirmed that the golden colored croaker from the Bang Pakong River and Ba. polykladiskos specimens from Borneo are conspecific, forming a sister group to the Boeseman croaker, Boesemania microlepis (Bleeker). An exceptional laterodorsal enlargement of the swim bladder head in both Ba. polykladiskos and Bo. microlepis further supports their close phylogenetic affinities. This study also discusses the taxonomic status of Ba. polykladiskos, and the genera Bahaba and Boesemania
Socioeconomic and Cultural Influences on Food Security Among the Bidayuh in Padawan, Sarawak
No full textThis thesis explores the concept of food security among the Bidayuh community in Padawan, Sarawak. Food security, a critical global issue, to ensure that all people have access to sufficient, safe, and nutritious food. The study aims to understand the Bidayuh's perceptions of food security, identify the factors affecting their food security, and examine the medium- and long-term strategies they employ to ensure household food security. Utilizing an exploratory study, data were collected through interviews and surveys with members of the Bidayuh community. The findings reveal that food security in this context is influenced by socioeconomic factors, cultural practices, and access to resources. The study also highlights the community's resilience and adaptive strategies in the face of food insecurity challenges. These insights contribute to the broader discussion on food security by providing a localized understanding of how indigenous communities guide and sustain their food systems
MALAY-ENGLISH CODE-SWITCHED SOCIAL MEDIA SENTIMENT CORPUS AND SUPERVISED BENCHMARK
No full textCode-switching between Malay and English is common on social media platforms like
Twitter (currently called X) and YouTube, reflecting Malaysia's linguistically diverse
society. However, this phenomenon presents a significant challenge for sentiment analysis,
as the mixing of languages within sentences or phrases increases the likelihood of sentiment
misclassification. To address this issue, this research proposed a methodology consisting of
a corpus construction framework and a supervised benchmark for sentiment classification
on Malay-English code-switched social media data, aimed to improve sentiment
interpretation accuracy within such mixed-language content. The first part of the
methodology focused on constructing a Malay-English code-switched sentiment corpus
using social media data, referred to as MESocSentiment. This corpus consists of 78.23%
neutral, 16.33% positive, and 5.44% negative tweets. Data from MESocSentiment were used
in a supervised machine learning approach that included a bootstrapping technique for
benchmarking sentiment models. The bootstrapping technique was implemented in four
rounds, with training data from the corpus added incrementally to increase the dataset size
at each round. Subsequently, 6,000 tweets with sentiment labels from bootstrapping were
used to train six selected machine learning and deep learning models for benchmarking. The
findings showed that SVM was the best model for classifying code-switched data in terms
of accuracy and AUC-ROC metrics. It achieved 76.55% accuracy, and all its AUC values
ranged between 0.90 and 0.83. Its AUC values for the micro-average and macro-average
ROC curves were 0.90 and 0.84, respectively. Lastly, the MESocSentiment corpus and
selected experiment outputs have been published on GitHub for public use
Capital Structure and Firm Performance: Moderating Effect of Economic Conditions, Monetary Policy, and Stock Market Volatility
No full textThe relationship between capital structure and firm performance has received considerable attention, particularly in emerging markets like Malaysia. However, most existing studies either rely on outdated data, focus on specific industries, or overlook the influence of macroeconomic conditions. This study addresses these limitations by incorporating Gross Domestic Product (GDP) growth, the Overnight Policy Rate (OPR), and stock market volatility (VOL) as moderating variables to assess their role in the capital structure–performance relationship. Using data from 719 non-financial firms listed on Bursa Malaysia from 2012 to 2022, this study applies both static and dynamic panel regression techniques. Firm performance is measured using Return on Assets (ROA), while debt is assessed through total, long-term, and short-term debt ratios to assets. The two-step system Generalized Method of Moments (sys-GMM) model is employed to address statistical issues including multicollinearity, heteroscedasticity, autocorrelation, endogeneity, and dynamic panel bias. Results reveal a significant negative relationship between debt levels and firm performance, supporting the trade-off theory. However, GDP, OPR, and VOL do not significantly moderate this relationship, suggesting that internal firm factors may exert a greater influence than macroeconomic conditions. This finding has several implications. For managers, Managers must practice careful debt management in uncertain times. Policymakers should prioritize strengthening firm resilience over relying only on macro tools. Investors can expect more stable returns from less-leveraged firms, making capital structure a key factor in investment decisions