This paper presents the results of research on the use of smartphone sensors (namely, GPS and accelerometers), geospatial information (points of interest, such as bus stops and train stations) and machine learning (ML) to sense mobility contexts. Our...
Reflective thinking is a key skill for constructing meaning in university. Its development requires appropriate learning contexts which can function as spaces for reflection, along with approaches, conditions and methods which can boost students&rsqu...
Indigenous science is comprised of the science-related knowledge and associated practices of indigenous cultures. Indigenous science provides rich contexts that can contribute to understanding the relationship of sociocultural life and environmental...
Children’s career exploration is a critical aspect of career development. Through it, children explore the interplay between their different life roles, including those related to work (in a broad sense), learning, and education. Through career explo...
Previous research has shown that changes in the scenarios in which something is learned and recalled, respectively, may result in a subpar performance in memory recollection. The current study aimed to evaluate how changes in the visuo-perceptual env...
This paper mainly formulates the problem of predicting context-aware smartphone apps usage based on machine learning techniques. In the real world, people use various kinds of smartphone apps differently in different contexts that include both the us...
Vocabulary acquisition and retention is an essential part of learning a foreign language and many learners use flashcard applications to repetitively increase vocabulary retention. However, it can be difficult for learners to remember new words and p...
Research shows that various contextual factors can have an impact on learning. Some of these factors can originate from the physical learning environment (PLE) in this regard. When learning from home, learners have to organize their PLE by themselves...
This paper presents the results of the analysis of the personal learning environments (PLE) used individually and in groups by fifth grade primary education students. The main objective was to determine if the use of mobile technologies in the studen...
Despite the widespread adoption of project-based learning in higher education, few empirical studies have explored its impact on situating learners within real-world contexts and enhancing student engagement. This study situates undergraduates in a t...
This study investigates the effects of gender and the learning context on learners’ perceptions of Arabic consonant contrasts. To this end, 60 intermediate Arabic learners, half of which were males and half of which were females, were recruited...
Testing as an assessment technique has been widely used at all levels of education—from primary to higher school. The main purpose of the paper is to evaluate the effect of context-based testing in teaching and learning of analytical chemistry in a R...
The age of pervasive computing has initiated a boom in the development of adaptive context-aware learning environments (ACALEs), i.e., systems that are capable of detecting a learner’s context and providing adaptive learning services based on t...
Hand tracking in video is an increasingly popular research field due to the rise of novel human-computer interaction methods. However, robust and real-time hand tracking in unconstrained environments remains a challenging task due to the high number...
Since the development of information and communication technology ‘learning media’ have been recognized as increasingly important courses by educators to assist students training to be professional teachers to understand the process of de...
An integrated navigation system is a promising solution to improve positioning performance by complementing estimated positioning in each sensor, such as a global positioning system (GPS), an inertial measurement unit (IMU), and an odometer sensor. H...
Language learning involves linguistic and societal factors that interact to facilitate or hinder second language learning. Different contextual factors provide an opportunity to examine and understand the similarities and differences that occur among...
A context-aware recommender system can make recommendations to users by considering contextual information such as time and place, not only the scores assigned to items by users. However, as a user preferences matrix is expanded in a multidimensional...
Existing point-of-interest (POI) recommendation methods often fail to capture complex contextual dependencies and suffer from severe data sparsity in location-based social networks (LBSNs). To address these limitations, this study proposes a Context-...
With the proliferation of mobile internet and location-based services, location-based social networks (LBSNs) have accumulated extensive user check-in data, driving the advancement of next Point-of-Interest (POI) recommendation systems. Although exis...
The changes observed in the school context demand new practices and impose new challenges to the operational assistants that, due to their relevant role in the educational environment, must be prepared and endowed with knowledge and skills to conduct...
Smart environments play a key role in improving user comfort, energy efficiency, and sustainability through intelligent automation. Nevertheless, real-world deployments still face major challenges, including network instability, delayed responsivenes...
The e-learning environment should support the handwriting of mathematical expressions and accurately recognize inputted handwritten mathematical expressions. To this end, expression-related information should be fully utilized in e-learning environme...
In this paper, we propose a novel congested crowd counting network for crowd density estimation, i.e., the Adaptive Multi-scale Context Aggregation Network (MSCANet). MSCANet efficiently leverages the spatial context information to accomplish crowd d...
The evolution of communication technology has driven the demand for intelligent power grids and data analysis in power systems. However, obtaining and annotating electrical data from intelligent terminals is time-consuming and challenging. We propose...
Large-scale models trained on extensive datasets have become the standard due to their strong generalizability across diverse tasks. In-context learning (ICL), widely used in natural language processing, leverages these models by providing task-speci...
Identifying stress in older adults is a crucial field of research in health and well-being. This allows us to take timely preventive measures that can help save lives. That is why a nonobtrusive way of accurate and precise stress detection is necessa...
The brain uses contextual information to uniquely resolve the interpretation of ambiguous stimuli. This paper introduces a deep learning neural network classification model that emulates this ability by integrating weighted bidirectional context into...
13 February 2020
Illumination is one of the most important environmental factors in the classroom. Researchers have discovered that lighting settings have significant impact on students’ performance. Although light-emitting diode (LED) lighting systems can prec...
Mobile Crowd Sensing (MCS) is a novel IoT paradigm where sensor data, as collected by the user’s mobile devices, are integrated with user-generated content, e.g., annotations, self-reports, or images. While providing many advantages, the human...
The proliferation of social media has made Sentiment Analysis an essential tool for understanding user opinions, particularly in underrepresented language variants such as Mexican Spanish. Recent advances in Large Language Models have made effective...
In-context learning (ICL) enables large language models (LLMs) to adapt to new tasks using only a few examples, without requiring fine-tuning. However, the new privacy and security risks brought about by this increasing capability have not received e...
An integration of deep learning and classical filtering techniques has been developed for achieving an accurate and robust positioning system. Despite significant technological advances, positioning systems often face fundamental challenges such as s...
The extensive use of large language models (LLMs), particularly in the finance sector, raises concerns about the authenticity and reliability of generated text. Developing a robust method for distinguishing between human-written and AI-generated fina...
Expert systems, a form of artificial intelligence (AI), are typically designed to solve many real-world problems by reasoning through knowledge, which is primarily represented as IF–THEN rules, with the information acquired from humans or domain expe...
Teachers are effective agents who can introduce and support students’ self-regulated learning (SRL) in classrooms. This qualitative study presents an integrative, ecological model of SRL-in-context from the teachers’ perspectives. Data were obtained...
Teacher professional learning occurs across various contexts. Previous studies on teacher learning and changes in practice have focused on either classroom contexts or learning communities outside of school, but have rarely investigated teacher learn...
Augmented reality (AR) has received increasing attention in the research literature as a fundamental pedagogical tool that can enhance learning at most educational levels. In academic contexts, this technology permits the superimposing of three-dimen...
Sensors’ existence as a key component of Cyber-Physical Systems makes it susceptible to failures due to complex environments, low-quality production, and aging. When defective, sensors either stop communicating or convey incorrect information....
Due to its capacity for temporal and spatial coverage, remote sensing has emerged as a powerful tool for mapping inundation. Many methods have been applied effectively in remote sensing flood analysis. Generally, supervised methods can achieve better...
Smart devices, such as smartphones, smartwatches, etc., are examples of promising platforms for automatic recognition of human activities. However, it is difficult to accurately monitor complex human activities on these platforms due to interclass pa...
The adoption of the active learning paradigm presents a series of challenges and uncertainties. However, its adoption may result in better academic results and a more engaging attitude towards learning. In this sense, this paper presents a case scena...
There is a strong increase in the use of devices that measure physiological arousal through electrodermal activity (EDA). Although there is a long tradition of studying emotions during learning, researchers have only recently started to use EDA to me...
This study explored a moderated mediation model, which is based on the assumption about the direct relationship between teachers’ autonomy-supportive behaviours and students’ learning strategies and via perceived classroom management as w...
This paper introduces a novel approach for enhancing fault diagnosis in industrial equipment systems through the application of sensor network-driven knowledge graph-based in-context learning (KG-ICL). By focusing on the critical role of sensor data...
Background: Several researchers have questioned the strategies necessary for effective risk management as well as of human error and its consequences, looking at both positive and negative consequences. Starting from this perspective, this study inte...
With the demand for clean energy increasing, novel research is presented in this paper on providing sustainable, clean energy for a university campus. The Internet of Things (IoT) is now a leading factor in saving energy. With added deep learning for...
Address parsing is a crucial task in natural language processing, particularly for Chinese addresses. The complex structure and semantic features of Chinese addresses present challenges due to their inherent ambiguity. Additionally, different task sc...
Cross-lingual summarization (XLS) involves generating a summary in one language from an article written in another language. XLS presents substantial hurdles due to the complex linguistic structures across languages and the challenges in transferring...
When a natural disaster occurs, humanitarian organizations need to be prompt, effective, and efficient to support people whose security is threatened. Satellite imagery offers rich and reliable information to support expert decision-making, yet its a...
of 196