“…From the application of technology readiness models (TRMs) to measure physical education teachers’ perspectives on WBT, it is possible to identify conditions in infrastructure that better accommodate the use of technological innovations that improve physical education and performance [ 125 ]. Another study shows that teachers report benefits in the incorporation of WBT in teaching by receiving real-time feedback on students’ cognitive states and representing tools for the implementation of more dynamic studying sessions; however, students stated that they experience several challenges related to the affordability, technical infrastructure, distractibility, security, ethics, and privacy of these technologies [ 126 ]. Providing insights into the perspectives of the main stakeholders of these technologies would allow for their seamless adoption and implementation and would offer better performance results.…”
Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012–2022), highlighting the evolution of this field to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, this review sheds light on the potential implications of WBT on the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with the PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation, with EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.
“…From the application of technology readiness models (TRMs) to measure physical education teachers’ perspectives on WBT, it is possible to identify conditions in infrastructure that better accommodate the use of technological innovations that improve physical education and performance [ 125 ]. Another study shows that teachers report benefits in the incorporation of WBT in teaching by receiving real-time feedback on students’ cognitive states and representing tools for the implementation of more dynamic studying sessions; however, students stated that they experience several challenges related to the affordability, technical infrastructure, distractibility, security, ethics, and privacy of these technologies [ 126 ]. Providing insights into the perspectives of the main stakeholders of these technologies would allow for their seamless adoption and implementation and would offer better performance results.…”
Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012–2022), highlighting the evolution of this field to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, this review sheds light on the potential implications of WBT on the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with the PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation, with EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.
“…While some papers aspire both, for example, researchers have constructed different models to explore and discuss current mainstream technologies (Hernandez et al, 2014; Chen et al, 2017; Giannakos et al, 2020). A few papers (6%) reviewed other papers or presented a framework that laid the groundwork for data analysis (Henrie et al, 2015; Demir & Demir, 2018; Motti, 2019; de Arriba-Pérez et al, 2019). Figure 6 shows the reviewed literatures categorized according to their research objectives.Figure 6.Number of publications by research objectives.…”
Wearable devices are an emerging technological tool in the field of learning analytics. With the help of wearable technologies, an increasing number of scholars have a strong interest in studying the associations between student data and learning outcomes in different learning environments. This systematic review examines 120 articles published between 2011 and 2021, exploring current research on learning analytics based on wearable devices in detail from both descriptive and content analysis. The descriptive analysis reviewed the included literature in five dimensions: publication times of the reviewed literature, wearable devices and data types used in studies, stakeholders, objectives, and methods involved in the analysis procedure. The content analysis aims to examine the literature covered in terms of three categorical domains of educational objectives: cognitive, affective, and behavioral, to investigate the practical applications and potential issues of learning analytics based on wearable devices. After that, based on the overall research content of the reviewed literature, a framework for learning analytics based on wearable devices is present, and its application process is summarized and analyzed for the reference of related researchers. At last, we summarize the limitations of existing studies and present several recommendations to further promote research and development in this field.
“…According to an IDC report, global shipments of wearable devices grew by 9.9% in the third quarter of 2021 [1]. Additionally, empirical data shows that wearable technology is thriving in consumer markets and gaining traction in the commercial sector [41]、 [42]. Wearable IoT technology has been widely used in various applications, such as healthcare, security, location tracking, wellness, fitness, sports, gaming, and fashion [43].…”
The advent of the Internet of Things (IoT) era has propelled the development of wearable technology. Wearable devices are widely used in medical, healthcare, sports, and safety applications, bringing more convenience to the living environment. Wearable devices can be worn on the body, collect body data using sensors, and process the collected data to obtain valuable information. IoT enables devices to connect and exchange and transmit data. Wearable devices in IoT can collect data for analysis and automatically adjust wearable device functions by connecting the obtained information to other devices. In this paper, we collect and organize articles on wearable devices used in IoT from 2017 to 2022 in terms of their applications, advantages, and disadvantages. We evaluate articles to identify wearable device application areas and evaluation criteria. Finally, we discussed the open issues of wearable devices and clarified how to face the future development and efforts of wearable devices in IoT.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
