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Repair Strategies in an English as a Foreign Language Online Educational Setting: A Case Study of Higher Education Studies
No full textThis study aimed to explore student performance in an online communicative practice session and how students modify the way they speak in conversation in the foreign language context. Data were collected through classroom recordings involving a native speaker instructor and seven learners, all in the A2 and A2+ levels, based on the Common European Framework of Reference for Languages. During the practice session, the students modified their speech. This was then categorized into four categories of sequences: self-initiation and self-repair, other-initiation and self-repair, self-initiation and other-repair, and the last sequence, other-initiation and other-repair. There was a total of fifty-three instances. The four sequences further derived subdivisions in language aspects, thematically divided into lexical, morphosyntactic, and phonological trouble sources. The findings demonstrate the type of repair used in the online context and the most initiated by the instructor. It further highlights the least used and discusses the reasons, which can be cultural, contextual, or social. The results highlight the implications of using such practices for second language learners and further suggest pedagogical implications on the use of repair in line with the online teaching and learning mode
Chapter 6 Big Data quality assessment in the IoT era
No full textThe Internet of Things (IoT) has shown unprecedented data generation and connectivity through disruptive applications across various domains. This data, referred to as Big Data, contains valuable information about various aspects of our lives and the physical world. As the IoT ecosystem continues to expand, ensuring the quality of the vast volumes of data it produces has become crucial. Therefore Big Data quality assessment is important in the IoT era to ensure that the data collected and analyzed is accurate, trustworthy, and usable. By performing Big Data quality assessments, organizations can make better decisions, improve their operations, and gain a competitive advantage. This chapter aims to enhance data quality assessment in IoT by providing an overview of its state-of-the-art. Big Data and IoT data properties and their new lifecycles are discussed. Moreover, selected works from the literature on IoT data quality are exhaustively reviewed. Additionally, a holistic architecture of IoT quality management model is proposed capturing key characteristics of IoT applications. Finally, open challenges and possible future research directions are discussed
Conceptualizing an Inclusive Metaverse for Enhanced Learning Among Students with Disabilities
No full textTraditional learning environments often fail to meet the diverse needs of students with disabilities due to various barriers, such as limited physical accessibility and a lack of personalized learning approaches. The emerging metaverse holds the potential to revolutionize education with its immersive and interactive capabilities, overcoming these traditional limitations. Despite research on metaverse-based inclusive learning, there is still a significant need for solutions that offer customized learning for various disabilities, comprehensive virtual support from educators and therapists, and enhanced analysis of student progress through cloud computing. Addressing this issue, our paper introduces a motivational scenario for an inclusive metaverse learning platform from which we derive the requirements for this platform. The paper identifies gaps in the existing literature, proposes an early metaverse architecture, and discusses potential research challenges. Utilizing a combination of advanced technologies, including Artificial Intelligence (AI), Federated Learning (FL), cloud computing, and blockchain, the proposed architecture aims to provide personalized educational experiences while ensuring robust data analysis, privacy, and security. Through this architecture, the study demonstrates how metaverse technologies can transform educational practices, making them more accessible and effective for students with disabilities
Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis
Full text linkLeukemia is the 11th most prevalent type of cancer worldwide, with acute myeloid leukemia (AML) being the most frequent malignant blood malignancy in adults. Microscopic blood tests are the most common methods for identifying leukemia subtypes. An automated optical image-processing system using artificial intelligence (AI) has recently been applied to facilitate clinical decision-making. To evaluate the performance of all AI-based approaches for the detection and diagnosis of acute myeloid leukemia (AML). Medical databases including PubMed, Web of Science, and Scopus were searched until December 2023. We used the “metafor” and “metagen” libraries in R to analyze the different models used in the studies. Accuracy and sensitivity were the primary outcome measures. Ten studies were included in our review and meta-analysis, conducted between 2016 and 2023. Most deep-learning models have been utilized, including convolutional neural networks (CNNs). The common- and random-effects models had accuracies of 1.0000 [0.9999; 1.0001] and 0.9557 [0.9312, and 0.9802], respectively. The common and random effects models had high sensitivity values of 1.0000 and 0.8581, respectively, indicating that the machine learning models in this study can accurately detect true-positive leukemia cases. Studies have shown substantial variations in accuracy and sensitivity, as shown by the Q values and I2 statistics. Our systematic review and meta-analysis found an overall high accuracy and sensitivity of AI models in correctly identifying true-positive AML cases. Future research should focus on unifying reporting methods and performance assessment metrics of AI-based diagnostics. https://www.crd.york.ac.uk/prospero/#recordDetails, CRD42024501980
Surveillance Digitisation, Performativity, and Teacher-Student Relationships in a Blended Learning Setting
Full text linkThis study investigates how digitized surveillance technologies impact teacher-student relationships in a blended learning environment at a UAE university. Using semi-structured faculty interviews, it examines the effects of tools such as plagiarism detection, class recordings, and learning analytics on trust and engagement. The findings reveal tensions between institutional goals of academic integrity and active participation and the unintended consequences of fostering performative behaviours and eroding relational trust. Teachers report that surveillance mechanisms promote compliance over genuine learning, reshaping their roles and interactions with students. Despite these challenges, educators employ strategies of resistance, prioritising human connection and relational pedagogy to counteract the dehumanising effects of constant monitoring. This study contributes to postdigital scholarship by exploring the complex entanglements of technology, pedagogy, and trust, emphasising the need for critical and human-centred approaches to digital education
Advancements in photocatalytic systems for ciprofloxacin degradation, efficiency, mechanisms, and environmental considerations
No full textIn aquatic ecosystems, the presence of ciprofloxacin (CIP) causes substantial environmental and public health risks, which require advanced water treatment procedures beyond conventional methods. This review emphasizes on the recent advances in the photocatalytic degradation of CIP, exploring the efficiency and mechanisms of various photocatalysts, covering 11 categories of metal-based, carbon-based, and hybrid nanostructures. The review underlines the major importance of photocatalyst morphology, surface area, doping, and the construction of heterojunctions in improving photocatalytic activity. Moreover, it addresses the causes of CIP pollution, the environmental repercussions of CIP, and its role in antibiotic resistance. The review offers a comprehensive overview of recent papers emphasizing the potential of photocatalysis driven by ultraviolet, visible, UV–visible, and solar light irradiation. Several studies underline the relevance of immobilizing photocatalysts for large-scale water treatment applications. The review concludes by identifying the significant obstacles and future approaches for developing more effective, sustainable, and large-scale photocatalytic systems for CIP degradation in wastewater
Unconventional Monetary Policies and Foreign Exchange Swaps: The Case of Turkey
No full textTo manage the risks from increased global liquidity after the 2008–2009 financial crisis, the Central Bank of Turkey (CBRT) heavily resorted to using the required reserve ratio, in addition to its conventional policy rate, as an active monetary policy tool. Additionally, it introduced new tools such as an asymmetric interest rate corridor and a reserve option mechanism. This study estimates a shadow interest rate to assess the CBRT’s post-crisis monetary policy stance. This shadow rate coincides with the CBRT’s weighted average funding rate (WAFC) until the end of 2016, indicating minimal impact from unconventional tools. However, from late 2016 to the end of 2017, the shadow rate is below the WAFC. We link this divergence to Turkish banks’ increasing swap exchange transactions and the resulting liquidity inflows of Turkish lira from overseas markets. Our results indicate that the transmission mechanism of monetary policy could be improved with better coordination of conventional and unconventional tools, as some of these tools exhibited isolating effects. Additionally, monitoring and managing off-balance sheet transactions can enhance the effectiveness of monetary policy
Digital echoes: Investigating the impact of online time on happiness and well-being in abu dhabi
No full textThis study examines the impact of online time on well-being among Abu Dhabi residents using data from the fourth Quality-of-Life Survey. Unlike prior studies, this research explores multiple determinants: online time, happiness, subjective health, mental health, self-perceived obesity, exercise, satisfaction with family life, and social relationships. A significant path model reveals that online time adversely affects mental health, self-perceived obesity, sleep quality, and exercise, but positively correlates with happiness and subjective health. The negative effects on mental health notably influence happiness, family life satisfaction, social relationships, subjective health, and exercise. Mental health also mediates these relationships, underscoring its importance in overall well-being. Differences in online hours and well-being determinants are found across gender, age, education, nationality, and marital status. The study underscores the need for interventions to mitigate the adverse effects of excessive online time and improve well-being across demographic groups
Salted Edges: Where the Land Sighs, Dissolving into the Ocean
No full textAlong the margins of islands, where the realms above and below water meet, the ocean spills its contents, regurgitating human refuse and warming waters spell doom for coral reefs. The Future Islands project, using field research, asks how artist’s processes such as documentation and analysis can be used to study the island edges and their aquatic habitats across the Red Sea and Indian Ocean. Field research presented in this chapter underscores the urgency for conservation and revitalization of archipelagos and cays, focusing on the critical roles of art and artists in addressing this. The focus on reefs as omens of broader ecological shifts serves as early warning systems for ocean health and impact of rising sea levels. The creation of sculptural forms from seaside debris—shells, corals, and remnants—is a meditation on nature\u27s resilience and adaptability. The artworks invite viewers to envision alternate ecosystems, symbolizing diverse possibilities for ecological resilience amid marine fragility. This allows for awareness and discussion of possible future solutions to the climate crisis. The ever-changing sea edge, retreating and returning, blurring its ancient boundaries and urging a deeper reflection on the relationship with islands and the enduring resilience of the ocean
Chapter 12 Driving change and innovation with IoT-cloud-based digital transformation
No full textThis chapter explores the Theory of Change (ToC) framework induced by the convergence of cloud and IoT technologies. The chapter reveals the societal impacts of these technologies, focusing on improved efficiency, resource optimization, and data-driven decision-making. A key theme is service-induced business model transformation through innovative service models, such as predictive maintenance as a service (PdMaaS), remote equipment monitoring as a service (REMaaS), precision agriculture as a service (PAgaaS), healthcare as a service (HCaaS), and supply chain tracking as a service (SCaaS). The chapter highlights strategies for implementing digital transformation, emphasizing the identification of change agents and overcoming resistance to change challenges. Key performance indicators (KPIs) to track progress following different change management approaches are discussed. Readiness to change is established by fostering a culture of innovation, providing training, and ensuring effective communication