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Case Study on How IB System of Education Supports the Gifted & Talented Students In a Primary School in Dubai
No full textThis case study investigates the effectiveness of the International Baccalaureate (IB) system in supporting gifted and talented students at a primary school in Dubai. The study explores how the IB curriculum, teaching methods, and support mechanisms address the specific needs of these students. Data were collected through interviews, classroom observations, and analysis of the school's implementation of the IB system. The findings reveal that the IB system has strengths in supporting gifted and talented students. The curriculum's emphasis on inquiry-based learning, critical thinking, and interdisciplinary approaches provides opportunities for students to explore their interests and extend their learning. The focus on differentiation and individualized instruction allows for tailored educational experiences based on students' unique abilities. This mixed method study also uncovers various support mechanisms and strategies implemented by the school. This study possesses limitations with respect to its generalizability owing to its utilization of a case study methodology.These findings contribute to the existing literature on gifted and talented education within the context of the IB system, specifically in primary schools in Dubai. Educators, administrators, and policymakers can draw insights from this research to enhance the educational experiences and outcomes of gifted and talented students. Overall, this case study provides a comprehensive examination of how the IB system supports gifted and talented students in a Dubai primary school. It sheds light on effective strategies and practices that cater to the unique needs of these students, contributing to ongoing efforts to optimize educational opportunities within the IB framework
Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models
No full textThe study of thoughts, feelings, judgments, values, attitudes, and emotions regarding goods, services, organizations, persons, tasks, occasions, titles, and their attributes is known as sentiment analysis and it involves a polarity classification task for recognizing positive, negative, or neutral text to quantify what individuals believe using textual qualitative data. The rise of social media platforms provided an excellent source for sentiment analysis data. People use these platforms for various reasons, ranging from sharing their opinions and thoughts to gaining knowledge. Twitter, Instagram, and Facebook are examples of social media platforms. As more users join social media platforms, the amount of data that is generated online continues to grow at an accelerating pace. Most of the previous research that studied sentiment analysis for the Arabic language focused on Modern Standard Arabic and Egyptian, Saudi, Algerian, Jordanian, Tunisian, and Levantine Dialects. However, to our knowledge, no study involved employing deep learning models to conduct sentiment analysis on the Emirati dialect texts. Dialects are the informal form of a language. Each country of the Arab world has its own Dialect, and each dialect may have several sub-dialects.
The main objective of this study is to develop a deep learning model that outperforms the state-of-the-art for Sentiment Analysis of the Emirati Dialect. Toward this objective, I first conducted a systematic review to identify the research gaps in the existing literature and investigate the available constructed resources for Arabic dialects and the used approaches for sentiment analysis of Arabic dialects. The systematic review focused on empirical research on the subject of Sentiment Analysis of the Arabic Dialect that was released between January 2015 and January 2021. Through the analysis, I found, with the exception of a few articles that investigated Saudi, Levantine, Jordanian, Algerian, Tunisian, and Egyptian dialects, researchers rarely specified the dialect type in their papers; instead, it was mostly mentioned (MSA and Arabic Dialects). Emirati Dialect has not been explored for Sentiment Analysis purposes. The sizes of most datasets of previous research were between 10,000 and 50,000. Moreover, the Twitter platform was the most popular online platform for constructing Arabic datasets. Most of the studies evaluated basic Machine Learning approaches for Sentiment Analysis of Arabic Dialects. My research aims to fill these identified gaps as I detail below. Since Instagram is one of the most popular social media platforms in UAE, I constructed a dataset of the Emirati dialect from the Instagram platform. My dataset consists of 216,000 posts, of which 70,000 posts were manually annotated by three human annotators. Each post is annotated into (Positive/ Negative/Neutral), and it is further annotated into (Emirati Dialect/ Arabic Dialect/ MSA). In order for the dataset to be used as a benchmark, the inter-annotator agreement (IAA) was measured using Fleiss's Kappa coefficient. The findings reveal that the overall Fleiss Kappa coefficient is = 0.93, indicating an almost-perfect agreement amongst the three annotators.
Once the dataset was constructed and validated, I then conducted a performance evaluation and comparison of various basic Machine Learning algorithms, Deep Learning models, and stacking deep learning models on different datasets of Sentiment Analysis of Arabic Dialects. For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. For deep-learning models, CNN, Bi-LSTM, Bi-GRU, as well as Hybrid deep-learning models were used for Sentiment Analysis. In order to improve performance further, I have proposed three ensemble-stacking deep-learning models with meta-learner layers of classifiers. The first stacking deep learning model combined 2 of the used deep learning models that produced the best results in terms of accuracy, the second stacking deep learning model combined 4 of the used deep learning models that produced the best results in terms of accuracy, and the final stacking deep-learning model combined all the trained deep learning models in this research. The proposed ensemble stacking model was evaluated using three datasets: the ESAAD Emirati Sentiment Analysis Annotated Dataset (which is one of this thesis contributions), and two other benchmark datasets (A Twitter-based Benchmark Arabic Sentiment Analysis Dataset ASAD and Arabic Company Reviews dataset). Experimental results show that my proposed ensemble stacking model outperformed existing deep learning models and achieved an accuracy of 95.54% for the ESAAD dataset, 96.71% for the benchmark ASAD, and 96.65% for the Arabic Company Reviews Dataset
Investigation into the extent to which mainstream schools in Dubai show readiness to integrate ‘Twice Exceptional’ children concept into practice.
No full textThis research on twice-exceptional students in Dubai schools reveal several key insights into the challenges and opportunities of integrating 2e students into educational settings in mainstream schools in Dubai. The research highlights the importance of addressing misconceptions and stereotypes about twice-exceptional students, as well as providing adequate resources and support for their unique needs, and establishing well defined policies to support these students. Additionally, the research underscores the importance of collaboration and communication among educators and professionals, as well as cultural competence and sensitivity in working with diverse student populations. The main research question is to examine to what extent do mainstream schools in Dubai show readiness to integrate ‘Twice Exceptional’ policy into their system. Based on the findings, the researcher concludes that there is a need to develop a clear instructional policy for schools to include twice exceptional students, as there is no such policy yet
Issues in Formative Assessment and Feedback in EMI Classrooms
No full textIt is quite sensible to outline the definition of EMI espoused in this chapter before
we talk about formative assessment and feedback strategies in EMI classes. This
chapter adopts the definition of Macaro et al. (2018) of EMI as “The use of the
English language to teach academic subjects (other than English itself) in coun
tries or jurisdictions where the first language of the majority of the population is not
English” (p. 37). Thus, it is important to know that formative assessment and feedback
described here relate to academic subjects (called content subjects in this chapter)
conducted in the English as a Foreign Language (EFL) context. The ceaseless spread
of EMI, mainly due to “the requirement of a shared medium in the wake of globaliza
tion” (Siddiqui et al., 2021), has become an undeniable fact, has maintained a high
rate of influence and demand (Siegel, 2022) and has sparked an unprecedented need to
train teachers, lecturers and professors to run EMI classrooms effectively (Huang &
Singh, 2014). While the use of EMI in classrooms to teach content subjects has been
justified by policymakers, curriculum designers, and researchers in different parts
of the globe, it has been concomitantly acknowledged that EMI houses a number of
challenges that permeate classrooms at all levels. Siegel (2022) sums up the source
of these challenges as he states
Factors affecting buying decisions of Islamic banking products: the moderating role of religious belief
No full textPurpose–Thepurposeofthisstudyistoexaminetheimpactofthemarketingmix,customerperceptions,and
religion on the buying decision of Islamic banking products in an emerging market namely the United Arab
Emirates (UAE).
Design/methodology/approach– This study adopts a quantitative approach to analyze the data of 435
respondents collected through an online survey during January–February 2022. Data analysis of direct and
moderating relationships are done through Smart PLS (partial least squares) using structural equation
modelling (SEM) technique.
Findings– The results indicate that marketing mix (product, price, place and promotion) and customer
perceptions have a positive direct relation with the buying decision of Islamic banking products in the UAE.
However, moderation analysis shows that religion is a non-significant moderator for the above relationships.
Originality/value– This study combines potential variables from the perspectives of marketing, human
mindset, and individual beliefs. The findings of this study provide a wider understanding of consumer
behavior toward Islamic banking products. Marketers of the Islamic banking industry can utilize these
findings for effective market segmentation and well-crafted marketing strategies. This will ultimately
contribute to the sustainable growth and development of the Islamic banking industry in the UAE and other
regions
Regulating the Electronic Sea Bill of Lading in Jordanian Law: A Comparative Study of its Feasibility
No full textObjectives: The study aims to demonstrate the extent to which the provisions of the
electronic bill of lading can be regulated in Jordanian law, clarify the extent to which
the electronic bill of lading is authoritative in proof, and indicate the areas of
contradiction between the general provisions of the bill of lading in the Jordanian law
and the Hamburg Treaty.
Methods: The study adopted both inductive and comparative approaches by reviewing
and analyzing texts of international documents and related Jordanian laws and
comparing them, in addition to analyzing court rulings that examined traditional and
electronic bills of lading disputes.
Results: The study found that the Jordanian legislator did not organize provisions
related to the electronic bill of lading, and the necessity to amend Article 13 of the
Jordanian Evidence Law to grant authenticity to the electronic bill of lading. The results
also confirmed the specificity and comprehensiveness of the provisions added by the
Rotterdam Rules of 2008 by addressing the practical aspects related to the circulation of
the electronic transport record and indicating the authoritativeness of the electronic bill
of lading in proving the trading operations contained therein as per the rules of Bolero.
Conclusions: The study recommends that the Jordanian legislature address the need to
amend the texts of the Jordanian Electronic Transactions Law and clarify the provisions
of Article 12 to reduce confusion. Additionally, it recommends amending Article 13 of
the Evidence Law and Article 18 of the Electronic Transactions Law to align with the
specificity of the electronic bill of lading contained in international documents.
Keywords: E-commerce, Sea shipping, Carriage of goods by sea, electronic bill of lading
The impact of remote working on employee productivity during COVID-19 in the UAE: the moderating role of job level
No full textPurpose–Thepurpose of this study is to examine the various factors that influence the productivity (PR) of
employees who worked remotely in the United Arab Emirates (UAE) during the COVID-19 pandemic.
Design/methodology/approach– This study adopts a quantitative approach to analyze data collected
online from 110 respondents using the snowball sampling technique during the pandemic. The analysis of the
data is conducted using the structural equation modeling (SEM) technique of Smart PLS(Partial least squares)
to evaluate the direct and moderating variables.
Findings–Theresultsindicatethatdirectvariablessuch asworkload,job satisfaction, work–life balanceand
social support have a significant positive impact on employee PR in the UAE. However, the analysis of the
moderating variable indicates that job level is not a significant moderator of the above relationships. The
findings, generally, provide support for social exchange theory.
Practical implications– The findings of this study will help businesses of various domains in a variety of
industries in understanding the core factors that should be considered to enhance the overall PR of their
employees while working from home. Businesses can achieve their organizational goals by ensuring steady
growth even during uncertain times.
Originality/value–ThispaperanswersthequestionofwhetherremoteworkingaffectsemployeePRduring
the pandemicinanemergingmarket,namelytheUAE.Thecurrentstudycontributestotheexisting literature
bycombiningthevariablesinvestigatedinpreviousstudiesintoasinglestudyandbyconsideringjoblevelasa
moderator variable
Enhancing student satisfaction and academic performance through school courtyard design: a quantitative analysis
No full textTraditionally, students’ overall satisfaction with their educational
experience was typically measured using a single question or a
straightforward ‘yes’ or ‘no’ response. However, this approach might not
capture their complete assessment of other aspects of satisfaction. The
design of School Courtyard is expected to be one of these aspects, and it
will be the subject of this quantitative research. To gather the data, a
self-administered survey was made available to a sample of secondary
school students from two private schools. To investigate and validate the
connection between School Courtyard Design, Courtyard Suitability and
Courtyard Attractiveness with Students’ Satisfaction, three hypotheses
were developed. To evaluate the viability of the developed hypotheses,
software namely SPSS (Statistical Package for Science Software) was used
to carry out several tests, including regression analysis and correlation
coefficient. The results showed a high relationship significance between
the School Courtyard Design and Students’ Satisfaction with a chance of
37.5%. Student satisfaction can be predicted also by Courtyard Suitability
with a 22.9% chance. Finally, Students’ Satisfaction can be additionally
predicted by the Courtyard Attractiveness with a 24.7% chance. The
research reveals the courtyard design needs, enhancing student
satisfaction and academic performance, benefiting architects, experts,
and practitioners
THE IMPACT OF SAFETY AND HEALTH ISSUES ON THE CONSTRUCTION WORKFORCE PRODUCTIVITY IN MALAYSIA
No full textThis research aims to study the impact of safety and health of the construction
workforce productivity among workers in G3 contractors in Kuantan, Pahang, Malaysia. Previous
research found that construction companies face a lack of safety concerns due to insufficient safety
compliance and poor attitude towards safety. While poor safety measures in the working
environment and material storage cause injuries and accidents that affect work on-site. Lack of
health concerns based on physical and mental health issues affected the productivity of the
construction workers. In this study, a quantitative research is used to collect and analyze data using
the PLS-SEM model. This research has collected 152 responses from workers of G3 contractors
in Kuantan, Pahang. Hence, the result of this study could be used as a reference for future studies
among the constructions companies in improving the productivity of their workers in order to sustain
their business operation
Estimating the probability of detection of cracks in metal plates using lamb waves
No full textThis paper focusses on the development of a data-driven damage detection method to
quantify fatigue crack in metal plates using Lamb waves and its reliability using a probability of
detection (POD) technique. The guided Lamb waves are generated and sensed using an array of
direct-write (DW) polyvinylidene fluoride (PVDF) annular comb shaped transducers designed to
explicitly generate a desired guided wave mode in the test specimen. The annular comb design
helps generate a single desired wave mode in the specimen thereby suppressing the energy of other
wave modes that can be generated simultaneously. The guided wave responses are obtained
through a simulation study and are recorded at different progressions of crack. A damage index
(DI) is constructed as a function of crack size that can effectively track the change in ultrasonic
response variations and for diagnosing fatigue crack in the metallic specimens. This DI is then
further used in the POD model to estimate the crack detection probability. The POD curves can be
helpful to check the reliability of the proposed inspection system as well as identify the critical
experimental parameters that can significantly influence the crack detection results