Activity-based learning (ABL), as a student-centered approach, has gained significant attention for improving student achievement in mathematics worldwide. However, its practical use in different mathematics classrooms remains less explored. This rev...
We propose a centralized Activity Retrieval and Detection Intelligence (ActivityRDI) solution framework, demonstrate its application performance in network threat detection in detail, and show its generalization to other domains. Network threat detec...
Destructive earthquakes are natural hazards highlighting the importance of introducing disaster preparedness from early childhood. Preschool children require developmentally appropriate educational approaches that connect scientific understanding wit...
As research progresses, integrating computational thinking (CT) and designing interdisciplinary activities to teach various disciplines have gradually emerged as new ideas and important ways to develop the CT of students. This paper introduces the co...
Project-based learning (PBL) combines student-centred learning with motor practice, but evidence on physical activity and motor performance in school physical education remains limited. This exploratory pilot study compared PBL with teacher-led instr...
Research has demonstrated the positive impact of active learning on students’ learning outcomes, particularly in science, technology, engineering and mathematics (STEM) fields. However, few studies have explored the impact of active learning vi...
Recommender systems can offer a fertile ground in e-learning software, since they can assist users by presenting them with learning material in which they can be more interested, based on their preferences. To this end, in this paper, we present a ne...
Background: Game-based learning (GBL) and active engagement strategies have shown promise in health professions education; however, their application in foundational basic science courses, which serve as critical academic gatekeepers in professional...
This article presents a case study on the way of teaching and learning the subject ‘Information Systems’ to ICT (Information and Communication Technology) engineering students, which is based on an active learning strategy implemented thr...
12 March 2026
Physically Active Learning (PAL) integrates physical activity into classroom teaching and has been shown to benefit students’ cognitive, social, and academic outcomes. Despite these advantages, PAL is not yet sustainably implemented in everyday...
Students are rapidly losing interest in STEM education due to the minimal incorporation of media into learning and the complexity of teaching methods, which ultimately results in a lack of motivation. However, despite these challenges, incorporating...
Superpixel-based classification using Active Learning (AL) has shown great potential in high spatial resolution remote sensing image classification tasks. However, in existing superpixel-based classification models using AL, the expert labeling infor...
Audiovisual content is highly employed in modern education curricula. This study aimed to identify students’ perceptions regarding the use of video in the courses they attend. Quantitative research was conducted among students of journalism and...
This article describes a problem-based learning (PBL) intervention enhanced by a smart classroom environment, which supported online interactions and class activities. The academic experience was centered on the United Nations Sustainable Development...
Numerous studies are currently being carried out on personalized services based on data analysis to find and provide valuable information about information overload. Furthermore, the number of studies on data analysis of teaching-learning activities...
Gender disparity within science, technology, engineering, and mathematics (STEM) fields is a persistent global issue, with women being consistently underrepresented. Recent research indicates that inquiry-based practices may enhance students’ i...
This manuscript presents a comprehensive exploration of an innovative active learning approach implemented in a Master’s Degree in Construction Engineering program. The pedagogical intervention involved a series of competitive battles among stu...
Sensor-based human activity recognition with wearable devices has captured the attention of researchers in the last decade. The possibility of collecting large sets of data from various sensors in different body parts, automatic feature extraction, a...
In remote sensing, active learning (AL) is considered to be an effective solution to the problem of producing sufficient classification accuracy with a limited number of training samples. Though this field has been extensively studied, most papers ex...
Chronic obstructive pulmonary disease (COPD) is a significantly concerning disease, and is ranked highest in terms of 30-day hospital readmission. Generally, physical activity (PA) of daily living reflects the health status and is proposed as a stron...
Studies on real-time PM2.5 concentrations per activity in microenvironments are gaining a lot of attention due to their considerable impact on health. These studies usually assume that information about human activity patterns in certain environments...
In object detection, annotation cost and computational efficiency are important factors in iterative model improvement under standard benchmark settings. Active learning (AL) addresses this challenge by selecting informative samples for labeling; how...
A deep learning-based quantitative structure–activity relationship analysis, namely the molecular image-based DeepSNAP–deep learning method, can successfully and automatically capture the spatial and temporal features in an image generate...
Modern technology frequently uses wearable sensors to monitor many aspects of human behavior. Since continuous records of heart rate and activity levels are typically gathered, the data generated by these devices have a lot of promise beyond counting...
Sensor-based human activity recognition (HAR) is a task to recognize human activities, and HAR has an important role in analyzing human behavior such as in the healthcare field. HAR is typically implemented using traditional machine learning methods....
Education is the road to sustainability, creating the appropriate environment for learners to socialize and acquire knowledge and skills for the 21st century. This study reviews 53 studies on Science, Technology, Engineering, and Mathematics (STEM) l...
Most of the traditional supervised classification methods using full-polarimetric synthetic aperture radar (PolSAR) imagery are dependent on sufficient training samples, whereas the results of pixel-based supervised classification methods show a high...
Radar, as one of the sensors for human activity recognition (HAR), has unique characteristics such as privacy protection and contactless sensing. Radar-based HAR has been applied in many fields such as human–computer interaction, smart surveillance a...
Nanotechnology is an interdisciplinary field that promises to reshape many spheres of our lives. One core activity in nanotechnology is the synthesis of nanoparticles. Here, we introduce a research-based activity centered on the use of zein, the main...
Visual pollution (VP) is the deterioration or disruption of natural and man-made landscapes that ruins the aesthetic appeal of an area. It also refers to physical elements that limit the movability of people on public roads, such as excavation barrie...
Background: Peptides are a class of molecules that can be presented as good antimicrobials and with mechanisms that avoid resistance, and the design of peptides with good activity can be complex and laborious. The study of their quantitative structur...
Human activity recognition (HAR) is a popular and challenging research topic, driven by a variety of applications. More recently, with significant progress in the development of deep learning networks for classification tasks, many researchers have m...
Human activities are accompanied by characteristic sound events, the processing of which might provide valuable information for automated human activity recognition. This paper presents a novel approach addressing the case where one or more human act...
Deep learning techniques are being widely applied to Human Activity Recognition (HAR). This paper describes the implementation and evaluation of a HAR system for daily life activities using the accelerometer of an iPhone 6S. This system is based on a...
Automated construction monitoring assists site managers in managing safety, schedule, and productivity effectively. Existing research focuses on identifying construction sounds to determine the type of construction activity. However, there are two ma...
In recent years, Human Activity Recognition (HAR) has become one of the most important research topics in the domains of health and human-machine interaction. Many Artificial intelligence-based models are developed for activity recognition; however,...
A global pandemic caused by the SARS-CoV-2 virus that started in 2020 and has wreaked havoc on humanity still ravages up until now. As a result, the negative impact of travel restrictions and lockdowns has underscored the importance of our preparedne...
Sensor-based human activity recognition (HAR) has attracted interest both in academic and applied fields, and can be utilized in health-related areas, fitness, sports training, etc. With a view to improving the performance of sensor-based HAR and opt...
Human activity recognition (HAR) by wearable sensor devices embedded in the Internet of things (IOT) can play a significant role in remote health monitoring and emergency notification to provide healthcare of higher standards. The purpose of this stu...
Project-based learning often centers learning experiences around projects and is characterized by the application of knowledge, management of resources, and self-directed learning. In recent years, newer classroom designs have been developed to facil...
(1) Podcasts are increasingly used in undergraduate medical education. They differ from traditional learning activities and may influence exam performance. Podcasts also offer insights into learning behaviour and perceptions of family medicine (FM)....
Today’s wireless activity recognition research still needs to be practical, mainly due to the limited sensing range and weak through-wall effect of the current wireless activity recognition based on Wi-Fi, RFID (Radio Frequency Identification,...
Due to its low cost and privacy protection, Channel-State-Information (CSI)-based activity detection has gained interest recently. However, to achieve high accuracy, which is challenging in practice, a significant number of training samples are requi...
The Internet of Things (IoT) is an emerging paradigm, even though it does not receive enough attention in many academic plans. In order to introduce our students to IoT, in this paper we present the overall results of a seminar dedicated to encourage...
Several pedestrian navigation solutions have been proposed to date, and most of them are based on smartphones. Real-time recognition of pedestrian mode and smartphone posture is a key issue in navigation. Traditional ML (Machine Learning) classificat...
Biospeckle imaging enables non-destructive observation of dynamic physiological activity in plant tissues; however, the relative sensitivity of different biospeckle activity maps to water stress and their implications for data-driven classification r...
Human activity recognition (HAR) is an important research area in the fields of human perception and computer vision due to its wide range of applications. These applications include: intelligent video surveillance, ambient assisted living, human com...
Due to its capacity to gather vast, high-level data about human activity from wearable or stationary sensors, human activity recognition substantially impacts people’s day-to-day lives. Multiple people and things may be seen acting in the video...
19 December 2020
The quantitative structure-activity relationship (QSAR) approach has been used in numerous chemical compounds as in silico computational assessment for a long time. Further, owing to the high-performance modeling of QSAR, machine learning methods hav...
Automatic segmentation is essential for enhancing human activity recognition, especially given the limitations of publicly available datasets that often lack diversity in daily activities. This study introduces a novel segmentation method that utiliz...
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