The research on mobile learning in science lacks in-depth investigation of the learning process. In this paper, we describe the implementation of a mobile technology-supported science curriculum developed by design-based approach. The long-term data collection and trace of learning process enable the exploration of students' participation and identifying potential factors in mobile learning. Employing mixed research methods, the study presents the differences of students' engagement in mobile activity. It was found out that the participation of students in doing the mobile activities varied regarding the types of mobile tools, topics, class levels, and teacher feedback. The findings unfolded the factors affecting student activity participation behavior in mobile science learning and the problems encountered by the mobile science curriculum implementation. The results could potentially inform curriculum design and implementation supported by mobile technology, as well as support professional development of science teachers.
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http://dx.doi.org/10.1186/s41039-016-0040-6 | DOI Listing |
Sensors (Basel)
December 2024
School of Mechanical Engineering and Automation, Foshan University, Foshan 528225, China.
Inspection robots, which improve hazard identification and enhance safety management, play a vital role in the examination of high-risk environments in many fields, such as power distribution, petrochemical, and new energy battery factories. Currently, the position precision of the robots is a major barrier to their broad application. Exact kinematic model and control system of the robots is required to improve their location accuracy during movement on the unstructured surfaces.
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December 2024
Department of Mobile Systems Engineering, Dankook University, Yongin 16890, Republic of Korea.
As proximity-aware services among devices such as sensors, IoT devices, and user equipment are expected to facilitate a wide range of new applications in the beyond 5G and 6G era, managing heterogeneous environments with diverse node capabilities becomes essential. This paper analytically models and characterizes the performance of heterogeneous random access-based wireless mutual broadcast (RA-WMB) with distinct transmit (Tx) power levels, leveraging a marked Poisson point process to account for nodes' various Tx power. In particular, this study enables the performance of RA-WMB with heterogeneous Tx power to be represented in terms of the performance of RA-WMB with a common Tx power by deriving an equivalent Tx power based on the probability distribution of heterogeneous Tx power and the path loss exponent.
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December 2024
Department of Computer Science and Engineering, Indian Institute of Technology Indore, Indore 453552, India.
The widespread reliance on paper-based currency poses significant drawbacks, such as counterfeiting, lack of transparency, and environmental impacts. While Central Bank Digital Currencies (CBDCs) address many of these issues, their dependence on continuous internet connectivity limits their usability in scenarios with poor or no network access. To overcome such limitations, this paper introduces ElasticPay, a novel Peer-to-Peer (P2P) Offline Digital Payment System that leverages advanced hardware security measures realised through Trusted Platform Modules (TPMs), Trusted Execution Environments (TEEs), and Secure Elements (SEs).
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December 2024
School of Computer Science and Engineering, Northeastern University, Shenyang 110000, China.
Natural disasters cause significant losses. Unmanned aerial vehicles (UAVs) are valuable in rescue missions but need to offload tasks to edge servers due to their limited computing power and battery life. This study proposes a task offloading decision algorithm called the multi-agent deep deterministic policy gradient with cooperation and experience replay (CER-MADDPG), which is based on multi-agent reinforcement learning for UAV computation offloading.
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December 2024
Psychology Department, Middle Tennessee State University, Murfreesboro, TN 37132, USA.
Consumer-grade EEG devices, such as the InteraXon Muse 2 headband, present a promising opportunity to enhance the accessibility and inclusivity of neuroscience research. However, their effectiveness in capturing language-related ERP components, such as the N400, remains underexplored. This study thus aimed to investigate the feasibility of using the Muse 2 to measure the N400 effect in a semantic relatedness judgment task.
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