Effects of Augmented Reality on Student Achievement and Self-Efficacy in Vocational Education and Training

This study aimed to test the impact of augmented reality (AR) use on student achievement and self-efficacy in vocational education and training. For this purpose, a marker-based AR application, called HardwareAR, was developed. HardwareAR provides information about characteristics of hardware components, ports and assembly. The research design was quasi experimental with pre-test post-test that included a control group. The study was conducted with 46 undergraduate students in the Computer Hardware Course. Computer hardware course achievement test, motherboard assembly self-efficacy questionnaire and unstructured observation form were used in the study for data collection purposes. The control group learned the theoretical and applied information about motherboard assembly by using their textbooks (print material) while students in the experimental group used HardwareAR application for the same purpose. It was found that the use of AR had a positive impact on student achievement in motherboard assembly whereas it had no impact on students’ self-efficacy related to theoretical knowledge and assembly skills. On the other hand use of AR helped learners to complete the assembly process in a shorter time with less support. It is concluded that compared to control group students, experimental group students were more successful in computer hardware courses. This result shows that AR application can be effective in increasing achievement. It was concluded that AR application had no effect on students’ motherboard assembly theoretical knowledge self-efficacy and motherboard assembly skills self-efficacy. This result may have been affected from the fact that students had high levels of theoretical knowledge and assembly skills before the implementation. Observations showed that AR application enabled students to assemble motherboard in a shorter time with less support. It is thought that simultaneous interaction between virtual objects and real world provided by the AR application is effective in reducing assembly time. The students who were able to see the process steps and instructions directly with the help of HardwareAR application could complete the assembly by getting less help. Considering these results, it can be argued that, thanks to simultaneous interaction it provides, AR offers an important alternative for topics that need learner application and practice

Comparative study of AR versus video tutorials for minor maintenance operations

[EN] Augmented Reality (AR) has become a mainstream technology in the development of solutions for repair and maintenance operations. Although most of the AR solutions are still limited to specific contexts in industry, some consumer electronics companies have started to offer pre-packaged AR solutions as alternative to video-based tutorials (VT) for minor maintenance operations. In this paper, we present a comparative study of the acquired knowledge and user perception achieved with AR and VT solutions in some maintenance tasks of IT equipment. The results indicate that both systems help users to acquire knowledge in various aspects of equipment maintenance. Although no statistically significant differences were found between AR and VT solutions, users scored higher on the AR version in all cases. Moreover, the users explicitly preferred the AR version when evaluating three different usability and satisfaction criteria. 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An evaluation of the Microsoft HoloLens for a manufacturing-guided assembly task

Many studies have confirmed the benefits of using Augmented Reality (AR) work instructions over traditional digital or paper instructions, but few have compared the effects of different AR hardware for complex assembly tasks. For this research, previously published data using Desktop Model Based Instructions (MBI), Tablet MBI, and Tablet AR instructions were compared to new assembly data collected using AR instructions on the Microsoft HoloLens Head Mounted Display (HMD). Participants completed a mock wing assembly task, and measures like completion time, error count, Net Promoter Score, and qualitative feedback were recorded. The HoloLens condition yielded faster completion times than all other conditions. HoloLens users also had lower error rates than those who used the non-AR conditions. Despite the performance benefits of the HoloLens AR instructions, users of this condition reported lower net promoter scores than users of the Tablet AR instructions. The qualitative data showed that some users thought the HoloLens device was uncomfortable and that the tracking was not always exact. Although the user feedback favored the Tablet AR condition, the HoloLens condition resulted in significantly faster assembly times. As a result, it is recommended to use the HoloLens for complex guided assembly instructions with minor changes, such as allowing the user to toggle the AR instructions on and off at will. The results of this paper can help manufacturing stakeholders better understand the benefits of different AR technology for manual assembly tasks

Augmenting Reality with Intelligent Interfaces

It is clear that our daily reality will increasingly interface with virtual inputs. We already integrate the virtual into real life through constantly evolving sensor technologies embedded into our smartphones, digital assistants, and connected devices. Simultaneously, we seek more virtual input into our reality through intelligent interfaces for the applications that these devices can run in a context rich, socially connected, and personalized way. As we progress toward a future of ubiquitous Augmented Reality (AR) interfaces, it will be important to consider how this technology can best serve the various populations that can benefit most from the addition of these intelligent interfaces. This paper proposes a new terminological framework to discuss the way AR interacts with users. An intelligent interface that combines digital objects in a real-world context can be referred to as a Pose-Interfaced Presentation (PIP): Pose refers to user location and orientation in space; Interfaced means that the program responds to a user’s intention and actions in an intelligent way; and Presentation refers to the virtual object or data being layered onto the perceptive field of the user. Finally, various benefits of AR are described and examples are provided in the areas of education, worker training, and ESL learning

real time assistance to manual assembly through depth camera and visual feedback

Abstract The current fourth industrial revolution significantly impacts on production processes. The personalized production paradigm enables customers to order unique products. The operators assemble an enormous component variety adapting their process from product to product with limited learning opportunities. Digital technologies are increasingly adopted in production processes to improve performance and quality. Considering this framework, this research proposes a hardware/software architecture to assist in real-time operators involved in manual assembly processes. A depth camera captures human motions in relation with the workstation environment whereas a visual feedback guides the operator through consecutive assembly tasks. An industrial case study validates the architecture

Are Reality, Simulation, and Augmented Reality Interchangeable?

Students often ask why they should learn or where they would use this knowledge when learning. Real-life experiences make learning more meaningful for the students. Thus, learning environments where the students could acquire real-life experiences are important. However, due to the student profile, crowded classes, inadequate course hours, technological advances, natural disasters, etc., conventional instruction methods could not meet student requirements and they could not practice. This negatively affects learning achievements and psychomotor skills of the students. Effective real-life educational experiences are required to improve learning achievements and psychomotor skills of the students. Thus, the present study aimed to investigate learning achievement and psychomotor skills levels of college students in the ICT course and substitution of augmented reality applications and simulations with real-life experiences. The study data were collected from 63 college students. Descriptive statistics, two-way ANOVA, and Wilcoxon Signed Rank Test analysis were employed to answer the research questions. The findings demonstrated that augmented reality and simulation-assisted learning environments were as effective as real-life learning environments in the improvement of the learning achievements and psychomotor skills of the students in the ICT course. Thus, it could be suggested that augmented reality or simulation applications could be employed in learning environments that lack real-life experiences

Current challenges and future research directions in augmented reality for education

The progression and adoption of innovative learning methodologies signify that a respective part of society is open to new technologies and ideas and thus is advancing. The latest innovation in teaching is the use of Augmented Reality (AR). Applications using this technology have been deployed successfully in STEM (Science, Technology, Engineering, and Mathematics) education for delivering the practical and creative parts of teaching. Since AR technology already has a large volume of published studies about education that reports advantages, limitations, effectiveness, and challenges, classifying these projects will allow for a review of the success in the different educational settings and discover current challenges and future research areas. Due to COVID-19, the landscape of technology-enhanced learning has shifted more toward blended learning, personalized learning spaces and user-centered approach with safety measures. The main findings of this paper include a review of the current literature, investigating the challenges, identifying future research areas, and finally, reporting on the development of two case studies that can highlight the first steps needed to address these research areas. The result of this research ultimately details the research gap required to facilitate real-time touchless hand interaction, kinesthetic learning, and machine learning agents with a remote learning pedagogy

Distributed Self-Deployment in Visual Sensor Networks

Autonomous decision making in a variety of wireless sensor networks, and also in visual sensor networks (VSNs), specifically, has become a highly researched field in recent years. There is a wide array of applications ranging from military operations to civilian environmental monitoring. To make VSNs highly useful in any type of setting, a number of fundamental problems must be solved, such as sensor node localization, self-deployment, target recognition, etc. This presents a plethora of challenges, as low cost, low energy consumption, and excellent scalability are desired. This thesis describes the design and implementation of a distributed self-deployment method in wireless visual sensor networks. Algorithms are developed for the imple- mentation of both centralized and distributed self-deployment schemes, given a set of randomly placed sensor nodes. In order to self-deploy these nodes, the fundamental problem of localization must first be solved. To this end, visual structured marker detection is utilized to obtain coordinate data in reference to artificial markers, which then is used to deduct the location of a node in an absolute coordinate system. Once localization is complete, the nodes in the VSN are deployed in either centralized or distributed fashion, to pre-defined target locations. As is usually the case, in cen- tralized mode there is a single processing node which makes the vast majority of decisions, and since this one node has knowledge of all events in the VSN, it is able to make optimal decisions, at the expense of time and scalability. The distributed mode, however, offers increased performance in regard to time and scalability, but the final deployment result may be considered sub-optimal. Software is developed for both modes of operations, and a GUI is provided as an easy control interface, which also allows for visualization of the VSN progress in the testing environment. The algorithms are tested on an actual testbed consisting of five custom-built Mobile Sensor Platforms (MSPs). The MSPs are configured to have a camera and an ultra-sonic range sensor. The visual marker detection uses the camera, and for obstacle avoidance during motion, the sonic ranger is used. Eight markers are placed in an area measuring 4 × 4 meters, which is surrounded by white background. Both algorithms are evaluated for speed and accuracy. Experimental results show that localization using the visual markers has an accuracy of about 96% in ideal lighting conditions, and the proposed self-deployment algorithms perform as desired. The MSPs suffer from some physical design limitations, such as lacking wheel encoders for reliable movement in straight lines. Experiments show that over 1 meter of travel the MSPs deviate from the path by an average of 7.5 cm in a lateral direction. Finally, the time needed for each algorithm to complete is recorded, and it is found that centralized and distributed modes require an average of 34.3 and 28.6 seconds, respectively, effectively meaning that distributed self-deployment is approximately 16.5% faster than centralized deployment

Investigating Real-time Touchless Hand Interaction and Machine Learning Agents in Immersive Learning Environments

The recent surge in the adoption of new technologies and innovations in connectivity, interaction technology, and artificial realities can fundamentally change the digital world. eXtended Reality (XR), with its potential to bridge the virtual and real environments, creates new possibilities to develop more engaging and productive learning experiences. Evidence is emerging that thissophisticated technology offers new ways to improve the learning process for better student interaction and engagement. Recently, immersive technology has garnered much attention as an interactive technology that facilitates direct interaction with virtual objects in the real world. Furthermore, these virtual objects can be surrogates for real-world teaching resources, allowing for virtual labs. Thus XR could enable learning experiences that would not bepossible in impoverished educational systems worldwide. Interestingly, concepts such as virtual hand interaction and techniques such as machine learning are still not widely investigated in immersive learning. Hand interaction technologies in virtual environments can support the kinesthetic learning pedagogical approach, and the need for its touchless interaction nature hasincreased exceptionally in the post-COVID world. By implementing and evaluating real-time hand interaction technology for kinesthetic learning and machine learning agents for self-guided learning, this research has addressed these underutilized technologies to demonstrate the efficiency of immersive learning. This thesis has explored different hand-tracking APIs and devices to integrate real-time hand interaction techniques. These hand interaction techniques and integrated machine learning agents using reinforcement learning are evaluated with different display devices to test compatibility. The proposed approach aims to provide self-guided, more productive, and interactive learning experiences. Further, this research has investigated ethics, privacy, and security issues in XR and covered the future of immersive learning in the Metaverse.<br/

Investigating Real-time Touchless Hand Interaction and Machine Learning Agents in Immersive Learning Environments

The recent surge in the adoption of new technologies and innovations in connectivity, interaction technology, and artificial realities can fundamentally change the digital world. eXtended Reality (XR), with its potential to bridge the virtual and real environments, creates new possibilities to develop more engaging and productive learning experiences. Evidence is emerging that thissophisticated technology offers new ways to improve the learning process for better student interaction and engagement. Recently, immersive technology has garnered much attention as an interactive technology that facilitates direct interaction with virtual objects in the real world. Furthermore, these virtual objects can be surrogates for real-world teaching resources, allowing for virtual labs. Thus XR could enable learning experiences that would not bepossible in impoverished educational systems worldwide. Interestingly, concepts such as virtual hand interaction and techniques such as machine learning are still not widely investigated in immersive learning. Hand interaction technologies in virtual environments can support the kinesthetic learning pedagogical approach, and the need for its touchless interaction nature hasincreased exceptionally in the post-COVID world. By implementing and evaluating real-time hand interaction technology for kinesthetic learning and machine learning agents for self-guided learning, this research has addressed these underutilized technologies to demonstrate the efficiency of immersive learning. This thesis has explored different hand-tracking APIs and devices to integrate real-time hand interaction techniques. These hand interaction techniques and integrated machine learning agents using reinforcement learning are evaluated with different display devices to test compatibility. The proposed approach aims to provide self-guided, more productive, and interactive learning experiences. Further, this research has investigated ethics, privacy, and security issues in XR and covered the future of immersive learning in the Metaverse.<br/