In this article, the authors examine the history, development, and current state of K-12 online learning, challenging the assertions that COVID-19-era distance education was unprecedented. Drawing on historical examples, the authors demonstrate how e...
This study aims to capture evidence on the effectiveness of emergency remote learning mediated by educational technology according to the interaction levels of K-12 students. The study involved students from a public institution that adopted emergenc...
Education 4.0 arises to provide citizens with the technical/digital competencies and cognitive/interpersonal skills demanded by Industry 4.0. New technologies drive this change, though time-independent learning remains a challenge, because students m...
Formative assessment in K-12 education has been a notable teaching and learning focus area in schools over the last 20 years, as evidenced by numerous recent systematic reviews and meta-analyses investigating and summarizing the evidence for formativ...
After the Taiwanese government launched the Blueprint for Developing Taiwan into a Bilingual Nation by 2030, the Implementation Project of Bilingual Instruction in several domains of primary and junior high school education was promoted by the Taiwan...
The COVID-19 pandemic brought extraordinary challenges to K-12 students in using modular distance learning. According to Transactional Distance Theory (TDT), which is defined as understanding the effects of distance learning in the cognitive domain,...
With the emergence of the novel coronavirus disease 2019 (COVID-19) pandemic in 2020, educational institutions had to rapidly adapt from face-to-face to online learning to ensure continued education. Various digital learning platforms were tools for...
This study explores the impact of COVID-19 on informal learning institutions, primarily science museums, through the lens of an activity kit co-created by CELL-MET—a cross-university, engineering research center—and museum partners. While...
Artificial intelligence (AI) and machine learning (ML) are pursued in most fields of data analysis, and have already become a part of everyday applications. As AI and ML are an integral part of the Industry 4.0 era, it becomes necessary to introduce...
Design thinking is regarded as an essential way to cultivate 21st century competency and there has been a concomitant rise of needs and interest in introducing K-12 students to design thinking. This study aimed to review high-qualified empirical stud...
Educators and researchers are increasingly recognizing the potential benefits of integrated science, technology, engineering, and mathematics (STEM) education to improve students’ learning outcomes, including the learning achievements, interest...
k-nearest neighbor (kNN) is a widely used learning algorithm for supervised learning tasks. In practice, the main challenge when using kNN is its high sensitivity to its hyperparameter setting, including the number of nearest neighbors k, the distanc...
Virtual reality (VR) has emerged as a promising tool for transforming science, technology, engineering, and mathematics (STEM) education, yet its adoption in K–12 classrooms remains uneven and often limited to short-term pilots. While prior stu...
A novel k-winners-take-all (k-WTA) competitive learning (CL) hardware architecture is presented for on-chip learning in this paper. The architecture is based on an efficient pipeline allowing k-WTA competition processes associated with different trai...
With the continuous development of deep reinforcement learning in intelligent control, combining automatic curriculum learning and deep reinforcement learning can improve the training performance and efficiency of algorithms from easy to difficult. M...
In this paper, the authors present their experiences from participating in a National Science Foundation (NSF) I-Corps L training program established for business startups, using Blank’s Lean LaunchPad, Osterwalder’s Business Model Canvas...
Tacit coordination games are games in which communication between the players is not allowed or not possible. In these games, the more salient solutions, that are often perceived as more prominent, are referred to as focal points. The level-k model s...
Information and communication technology considerably impacts students’ engagement with self-regulated learning (SRL) methodologies. However, there has been a lack of any comprehensive visualization of the SRL process, making it difficult to in...
As one of the entropy-based methods, the k-Star algorithm benefits from information theory in computing the distances between data instances during the classification task. k-Star is a machine learning method with a high classification performance an...
This paper redefines picture fuzzy soft matrices (pfs-matrices) because of some of their inconsistencies resulting from Cuong’s definition of picture fuzzy sets. Then, it introduces several distance measures of pfs-matrices. Afterward, this pap...
In this study, we propose three k-nearest neighbor (k-NN) optimization techniques for a distributed, in-memory-based, high-dimensional indexing method to speed up content-based image retrieval. The proposed techniques perform distributed, in-memory,...
Professional learning communities are recognized as one of the most effective approaches for promoting the professional development of teachers. In the current complex and rapidly changing era, to facilitate the implementation of interdisciplinary cu...
Machine learning (ML) in queueing theory combines the predictive and optimization capabilities of ML with the analytical frameworks of queueing models to improve performance in systems such as telecommunications, manufacturing, and service industries...
As data-driven models gain importance in driving decisions and processes, recently, it has become increasingly important to visualize the data with both speed and accuracy. A massive volume of data is presently generated in the educational sphere fro...
The k-nearest neighbors (KNN) algorithm has been widely used for classification analysis in machine learning. However, it suffers from noise samples that reduce its classification ability and therefore prediction accuracy. This article introduces the...
A learning environment’s quality has crucial influence on a student’s engagement. In this study, we utilized a structural equation modeling approach to explore the structural relationships between students’ perceptions of an online...
While prior work has explored learner behavior using learning management systems (LMS) data, few studies provide week-level clustering validated against external engagement labels. To understand and assist students in online learning platforms and en...
This paper proposes a simple yet effective method for improving the efficiency of sparse coding dictionary learning (DL) with an implication of enhancing the ultimate usefulness of compressive sensing (CS) technology for practical applications, such...
Collecting and analyzing log data can provide students with individualized learning to maintain their motivation and engagement in learning activities and reduce dropout in Massive Open Online Courses (MOOCs). As online learning becomes more and more...
The black-box nature of deep machine learning hinders the extraction of knowledge in science. To address this issue, a proposal for a neural network (k-net) based on the Kolmogorov–Arnold Representation Theorem is presented, pursuing to be an a...
Dynamic and smart Internet of Things (IoT) infrastructures allow the development of smart healthcare systems, which are equipped with mobile health and embedded healthcare sensors to enable a broad range of healthcare applications. These IoT applicat...
Business organizations experience cut-throat competition in the e-commerce era, where a smart organization needs to come up with faster innovative ideas to enjoy competitive advantages. A smart user decides from the review information of an online pr...
Machine learning algorithms can learn mechanisms of antimicrobial resistance from the data of DNA sequence without any a priori information. Interpreting a trained machine learning algorithm can be exploited for validating the model and obtaining new...
The rise in internet users has brought with it the impending threat of cybercrime as the Internet of Things (IoT) increases and the introduction of 5G technologies continues to transform our digital world. It is now essential to protect communication...
Background: The prognosis of diffuse midline glioma (DMG) patients with H3K27M (H3K27M-DMG) alterations is poor; however, a model that encourages accurate prediction of prognosis for such lesions on an individual basis remains elusive. We aimed to co...
This study explored the effect of parental involvement in K-12 distance learning activities on their perceived technostress and behaviours of support toward their children’s learning in Saudi Arabia. Partial least squares structural equation mo...
Despite the growing adoption of technology-integrated project-based learning (PjBL) in K-12 education, little research has systematically examined its implementation. To address this gap, we conducted a systematic literature review, guided by PRISMA...
In this study, statistical assessment was performed on student engagement in online learning using the k-means clustering algorithm, and their differences in attendance, assignment completion, discussion participation and perceived learning outcome w...
During the manufacturing process of the lithium-ion battery, metal foreign matter is likely to be mixed into the battery, which seriously influences the safety performance of the battery. In order to reduce the outflow of such foreign matter defect c...
With the increasing complexity of patrol tasks, the use of deep reinforcement learning for collaborative coverage path planning (CPP) of multi-mobile robots has become a new hotspot. Taking into account the complexity of environmental factors and ope...
Alzheimer’s disease is the most common form of neurodegenerative disease, and increasing evidence shows that insulin signaling has crucial roles in AD initiation and progression. In this study, we explored the effect and underlying mechanism of...
Magnetic Resonance Imaging (MRI) is an essential medical imaging modality that provides excellent soft-tissue contrast and high-resolution images of the human body, allowing us to understand detailed information on morphology, structural integrity, a...
This paper proposes a learning-based adaptive imputation method (LAI) for imputing missing power data in an energy system. This method estimates the missing power data by using the pattern that appears in the collected data. Here, in order to capture...
Background: the Skill, Rule, and Knowledge (S-R-K) model is a framework used to describe and analyze human behaviour and decision-making in complex environments based on the nature of the task and kind of cognitive control required. The S-R-K model i...
Pistachio is a nut originating from the Middle East, and the main varieties grown and exported in Turkey are Kirmizi and Siirt pistachios. Due to their strategic importance in the agricultural economy, they need to be classified correctly. This study...
Deep learning struggles with unsupervised tasks like community detection in networks. This work proposes the Enhanced Community Detection with Structural Information VGAE (VGAE-ECF) method, a method that enhances variational graph autoencoders (VGAEs...
Traditional supervisory control methods for the nonblocking control of discrete event systems often suffer from exponential computational complexity. Reinforcement learning-based approaches mitigate state explosion by sampling many random sequences i...
This study incorporates the comprehensively observed proxies of in situ geotechnical, geophysical, petrophysical, and lithological datasets to estimate groundwater presence. Two machine-learning approaches, random forest regression (RFR) and deep neu...
Currently, one of the topical areas of application of machine learning methods in the construction industry is the prediction of the mechanical properties of various building materials. In the future, algorithms with elements of artificial intelligen...
COVID-19 has become the largest pandemic in recent history to sweep the world. This study is devoted to developing and investigating three models of the COVID-19 epidemic process based on statistical machine learning and the evaluation of the results...
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