Enhancing Teachers’ AI Competencies through Artificial Intelligence of Things Professional Development Training

The rapid increase in new challenges of the combination of the Internet of Things (IoT) and artificial intelligence (AI), which are emerging technologies, can play a compelling role in prompting the development of artificial intelligence Internet of Things (AIoT). Therefore, the demand for AI competencies for everyone will increase. Educational institutes focus on encouraging AI education because the demand for AI-literate workers will increase in the industrial sector. However, teachers’ lack of AI knowledge is a significant barrier to AI education. Thus, developing the teacher’s AI competencies and educating them about how to use and teach students is critical. In this study, we proposed artificial intelligence of things professional development (AIoT-PD) training to prepare the AI competencies of teachers ready to teach. A quasi-experimental design with a two-day training workshop was conducted among 13 teachers to examine its impact on AI competencies, including AI knowledge, AI skill, and AI attitude. The quantitative data were collected via a pretest and posttest after the training activity, while qualitative data were collected via interviews. This study showed that teachers’ AI knowledge significantly improved. These findings revealed the AIoT training workshop’s effectiveness in enhancing teachers’ AI competencies, which can help them effectively teach students in AI education

A New WRR Algorithm for an Efficient Load Balancing System in IoT Networks under SDN

The Internet of Things (IoT) connects various smart objects and manages a vast network using diverse technologies, which present numerous challenges. Software-defined networking (SDN) is a system that addresses the challenges of traditional networks and ensures the centralized configuration of network entities to manage network integrity. Furthermore, the uneven distribution of IoT network load results in the depletion of IoT device resources. To address this issue, traffic must be distributed equally, requiring efficient load balancing to be ensured. This requires the development of an efficient architecture for IoT networks. The main goal of this paper is to propose a novel architecture that leverages the potential of SDN, the clustering technique, and a new weighted round-robin (N-WRR) protocol. The objective of this architecture is to achieve load balancing, which is a crucial aspect in the development of IoT networks as it ensures the network’s efficiency. Furthermore, to prevent network congestion and ensure efficient data flow by redistributing traffic from overloaded paths to less burdened ones. The simulation results demonstrate that our N-WRR algorithm achieves highly efficient load balancing compared to the simple weighted round-robin (WRR), and without the application of any load balancing method. Furthermore, our proposed approach enhances throughput, data transfer, and bandwidth availability. This results in an increase in processed requests

A Visual Computing Unified Application Using Deep Learning and Computer Vision Techniques

Vision Studio aims to utilize a diverse range of modern deep learning and computer vision principles and techniques to provide a broad array of functionalities in image and video processing. Deep learning is a distinct class of machine learning algorithms that utilize multiple layers to gradually extract more advanced features from raw input. This is beneficial when using a matrix as input for pixels in a photo or frames in a video. Computer vision is a field of artificial intelligence that teaches computers to interpret and comprehend the visual domain. The main functions implemented include deepfake creation, digital ageing (de-ageing), image animation, and deepfake detection. Deepfake creation allows users to utilize deep learning methods, particularly autoencoders, to overlay source images onto a target video. This creates a video of the source person imitating or saying things that the target person does. Digital aging utilizes generative adversarial networks (GANs) to digitally simulate the aging process of an individual. Image animation utilizes first-order motion models to create highly realistic animations from a source image and driving video. Deepfake detection is achieved by using advanced and highly efficient convolutional neural networks (CNNs), primarily employing the EfficientNet family of models

Teachers' Perspectives on Using Technology to Facilitate Pupil Participation

In the current digital era, technology plays a crucial role in facilitating diverse interactions that are essential for pupil engagement in the learning process. This article delves into the perspectives of secondary school teachers regarding the active participation of pupils in school activities through the utilization of digital technologies. The concept of participation is approached from two dimensions: passive presence and active involvement, with a specific focus on the latter, emphasizing active engagement. The study centers on the application of digital resources in Swedish grades 7–9 to promote pupil participation and enhance the learning experience. We examine the use, effectiveness, and areas requiring improvement of existing digital resources. Drawing from prior workshops involving teachers, we aim to elucidate educators’ viewpoints on the role of technology in enhancing pupil participation. Grounded in the Garrison and Andersson’s theoretical framework, the study advances the comprehension of the interactions necessary to foster an effective learning environment, as perceived by educators. The results derived from the thematic analysis yield four themes: 1) Interaction between teacher and pupil, 2) Interaction between pupil and content, 3) Interaction between pupil and pupil and 4) Extended interaction. The study concludes by outlining a set of guidelines in how digital resources can support pupil participation as the response to identified challenges

Elevating Physical Education Teacher Through Technology Integration

This paper explores how the integration of educational technology (EdTech) has been incorporated into the field of physical education (PE) and explores the difficulties encountered by Physical Education teachers (PETs) in successfully implementing technology. Through a systematic secondary literature review spanning the past decade, this paper identifies several key challenges, including unpreparedness, a trial-and-error approach, a shift in teaching priorities, and variations in teacher effectiveness. These challenges underscore the pressing need for readiness, adaptability, and preparation in the face of unforeseen disruptions, particularly in the context of online instruction. This study presents substantial recommendations to address these issues, emphasizing the pivotal role of technology-infused teacher education programs and advocating for Physical Education teachers’ education (PETE) faculty to embrace technology leadership. By implementing these recommendations, PETE programs can better equip preservice teachers and faculty members to harness technology for more effective learning experiences. Consequently, this endeavor aims to elevate the quality of PE in our increasingly digitalized era

Mobile Application to Improve the Follow-up and Control Process in Patients with Tuberculosis

Tuberculosis is a severe and life-threatening illness that affects numerous individuals worldwide every day. The key objective of this study was to create a system that could enhance the monitoring and management of tuberculosis patients. To achieve this goal, the Mobile D methodology was utilized because of its effectiveness in project management. This methodology emphasizes test-driven development, continuous integration, and optimization to enhance software processes. The outcome of this research was a prototype of a mobile application specifically designed for individuals with tuberculosis. Professionals and people affected by the disease assessed the quality of the prototype. They evaluated its effectiveness, user-friendliness, design, and functionality and gave ratings of 4.77 and 4.69 on a Likert scale, respectively. These figures indicate that the prototype meets high-quality criteria. In conclusion, this research successfully created an efficient prototype that enhances the monitoring and control of tuberculosis patients. The prototype includes features such as real-time consultations for immediate interaction between physicians and patients, clinical history visualization, and medication reminders, all of which improve the user’s experience

A ROS-Based Open Tool for Controlling an Educational Mobile Robot

Commercial educational robots provide an accessible entry point into the world of robotics. However, their programming is often limited to specific platforms, which can make it challenging to acquire the skills necessary for industry and research. In this study, we introduce an open-access tool developed using C++ and Arduino IDE that enables us to manage a commercial mobile robot through the Robot Operating System (ROS) middleware. This provides programmers with the ability to work in a powerful programming environment, such as Python. The robot used is the CrowBot BOLT, a kit based on ESP32 that enables wireless communication and includes various peripherals for application development. The mobile robot topics include robot velocities, RGB LEDs, a buzzer, a programmable button, and proximity, light, and line sensors. The proposal is assessed using two controllers: one for proximity and the other for tracking angular light. Both controllers are developed using Visual Studio Code. The experimental results demonstrated the proper functioning of the tool. Additionally, the response time was evaluated, and it was found that optimal performance is achieved at a frequency of 10 Hz. In summary, this proposal provides an accessible option for students and developers seeking to gain skills in robotics using ROS. The project’s repository is located at https://github.com/joseVarelaAldas/ROS-Crowbot

The Design of a Learning Experience Platform using xAPI with Design Thinking Learning to Promote Innovation

This research focuses on designing a learning experience platform using xAPI and incorporating design thinking principles to foster innovation. The study focused on two main areas: a) analyzing and synthesizing the conceptual framework for a learning experience platform using xAPI with design thinking learning to promote innovation; and b) evaluating the suitability of a learning management model design for the learning experience platform using xAPI with design thinking learning to promote innovation. The evaluation was conducted by nine experts and the model consists of five parts: 1) the student module, 2) the teacher module, 3) the learning module, 4) the analytical module, and 5) the portfolio module. These modules were derived from an assessment of the suitability of the learning style, which indicated the highest level. The result regarding the suitability of the components of the LEP-DT learning model was at the highest level ( x = 4.79, S.D). The value is 0.39. According to the assessment results, the model can be applied to learning management

Secondary School Teachers’ Attitudes Towards Online Learning Tools: Teachers’ Behaviour in Distance Education

Secondary school teachers’ attitudes towards online learning tools have been modified by systemic measures adopted in the school network as a result of COVID-19. This unexpected crisis situation forced schools to quickly implement digital infrastructure and look for optimal methods of online education. The aim of this study is to investigate on which factors (gender, age and subject area taught) the use of online tools for teaching activities depends. The aim is also to explore the subjective emotional experience of teachers when using online tools and the reasons of their perceived stress in distance education in the Covid era. The factors influencing the use of online tools for teaching, teachers’ subjective emotional experiences of using online tools, and the reasons for teachers’ perceived burden in distance education in the COVID era are analyzed using Welch’s ANOVA test and Games-Howell’s Post-Hoc test. The correlation values focused on teachers’ perceived feelings using online teaching tools are calculated by Pearson’s correlation coefficient. The results are directed towards the level of teachers’ emotional experience in the context of using online tools for the respective activity. Satisfaction and well-being are experienced by teachers when explaining, activating students, assigning written work, and providing information resources. The study identified a major problem in education, which is the use of online tools for oral examinations. Another problem is the integration of homework into online education. The study has practical impact on the integration of teachers’ digital competences. A holistic approach should be developed in teacher training, seeking to fully integrate digital competences, and social and health aspects should also be taken into account

Ways of Being Smart in Engineering: Beliefs, Values, and Introductory Engineering Experiences

Common discourse conveys that to be an engineer, one must be “smart.” Our individual and collective beliefs about what constitutes smart behavior are shaped by our participation in the complex cultural practice of smartness. From the literature, we know that the criteria for being considered “smart” in our educational systems are biased. The emphasis on selecting and retaining only those who are deemed “smart enough” to be engineers perpetuates inequity in undergraduate engineering education. Less is known about what undergraduate students explicitly believe are the different ways of being smart in engineering or how those different ways of being a smart engineer are valued in introductory engineering classrooms. In this study, we explored the common beliefs of undergraduate engineering students regarding what it means to be smart in engineering. We also explored how the students personally valued those ways of being smart versus what they perceived as being valued in introductory engineering classrooms. Through our multi-phase, multi-method approach, we initially qualitatively characterized their beliefs into 11 different ways to be smart in engineering, based on a sample of 36 engineering students enrolled in first-year engineering courses. We then employed quantitative methods to uncover significant differences, with a 95% confidence interval, in six of the 11 ways of being smart between the values personally held by engineering students and what they perceived to be valued in their classrooms. Additionally, we qualitatively found that 1) students described grades as central to their classroom experience, 2) students described the classroom as a context where effortless achievement is associated with being smart, and 3) students described a lack of reward in the classroom for showing initiative and for considerations of social impact or helping others. As engineering educators strive to be more inclusive, it is essential to have a clear understanding and reflect on how students value different ways of being smart in engineering as well as consider how these values are embedded into teaching praxis