Search results for: virtual learning environments

Authors: Yi-Hsiang Pan, Ching-Hsiang Chen, Wei-Ting Hsu

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The purpose of this study was to compare the learning effects of the sports education model (SEM) to those of the traditional teaching model (TTM) in physical education classes in terms of students learning motivation, action control, learning strategies, and learning performance. A quasi-experimental design was utilized in this study, and participants included two physical educators and four classes with a total of 94 students in grades 5 and 6 of elementary schools. Two classes implemented the SEM (n=47, male=24, female=23; age=11.89, SD=0.78) and two classes implemented the TTM (n=47, male=25, female=22, age=11.77; SD=0.66). Data were collected from these participants using a self-report questionnaire (including a learning motivation scale, action control scale, and learning strategy scale) and a game performance assessment instrument, and multivariate analysis of covariance was used to conduct statistical analysis. The findings of the study revealed that the SEM was significantly better than the TTM in promoting students learning motivation, action control, learning strategies, and game performance. It was concluded that the SEM could promote the mechanics of students self-regulated learning process, and thereby improve students movement performance.

Keywords: self-regulated learning theory, learning process, curriculum model, physical education

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Authors: Leena Ahmad Khaleel Alfarani, Maggie McPherson, Neil Morris

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Over the last decade, m-learning has been widely accepted and utilized by many western universities. However, Saudi universities face many challenges in utilizing such technology, a central one being to encourage teachers to use such technology. Although there are several factors that affect faculty members’ participation in the adoption of m-learning, this paper focuses merely on two factors, the usefulness and ease of using m-learning. A sample of 279 faculty members in one Saudi university has responded to the online survey. The results of the study have revealed that there is a statistically significant relationship (at the 0.05 level) between both usefulness and ease of using m-learning factors and the intention of teachers to use m-learning currently and in the future.

Keywords: mobile learning, diffusion of innovation theory, technology acceptance, faculty adoption

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Authors: Panita Wannapiroon, Noppadon Phumeechanya, Sitthichai Laisema

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This study is the research and development which is intended to: 1) design the ubiquitous cloud learning management system and: 2) assess the suitability of the design of the ubiquitous cloud learning management system. Its methods are divided into 2 phases. Phase 1 is the design of the ubiquitous cloud learning management system, phase 2 is the assessment of the suitability of the design the samples used in this study are work done by 25 professionals in the field of Ubiquitous cloud learning management systems and information and communication technology in education selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. The results showed that the ubiquitous cloud learning management system consists of 2 main components which are: 1) the ubiquitous cloud learning management system server (u-Cloud LMS Server) including: cloud repository, cloud information resources, social cloud network, cloud context awareness, cloud communication, cloud collaborative tools, and: 2) the mobile client. The result of the system suitability assessment from the professionals is in the highest range.

Keywords: learning management system, cloud computing, ubiquitous learning, ubiquitous learning management system

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Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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Authors: Badiossadat Hassanpour, Reza Sirjani, Nangkuala Utaberta

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The avant-garde educational systems are striving to find a life long learning methods. Different fields and majors have test variety of proposed models, and found their difficulties and strengths. Architecture as a critical stage of education due to its characteristics which are learning by doing and critique based education and evaluation is out of this study procedure. Learning contracts is a new alternative form of evaluation of students’ achievements, while it acts as agreement about learning goals. Obtained results from studies in different fields which confirm its positive impact on students' learning in those fields and positively affected students' motivation and confidence in meeting their own learning needs, prompted us to implement this model in architecture design studio. In this implemented contract to the studio, students were asked to use the existing possibility of contract to have self assessment and examine their professional development to identify whether they are deficient or they would like to develop more expertise. The evidences of this research as well indicate that students feel positive about the learning contract and see it accommodating their individual learning needs.

Keywords: contract (LC), architecture design studio, education, student-centered learning

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Authors: Maggie Mosher, Adam Carreon, Sean Smith

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A systematic literature review was conducted to explore the evidence base on the use of augmented reality (AR), virtual reality (VR), mixed reality (MR), and extended reality (XR) to present social skill instruction to school-age students with autism spectrum disorder (ASD). Specifically, the systematic review focus was on a. the participants and intervention agents using AR, VR, MR, and XR for social skill acquisition b. the social skills taught through these mediums and c. the social validity measures (i.e., goals, procedures, and outcomes) reported in these studies. Forty-one articles met the inclusion criteria. Researchers in six studies taught social skills to students through AR, in 27 studies through non-immersive VR, and in 10 studies through immersive VR. No studies used MR or XR. The primary targeted social skills were relationship skills, emotion recognition, social awareness, cooperation, and executive functioning. An intervention to improve many social skills was implemented by 73% of researchers, 17% taught a single skill, and 10% did not clearly state the targeted skill. The intervention was considered effective in 26 of the 41 studies (63%), not effective in four studies (10%), and 11 studies (27%) reported mixed results. No researchers reported information for all 17 social validity indicators. The social validity indicators reported by researchers ranged from two to 14. Social validity measures on the feelings toward and use of the technology were provided in 22 studies (54%). Findings indicated both AR and VR are promising platforms for providing social skill instruction to students with ASD. Studies utilizing this technology show a number of social validity indicators. However, the limited information provided on the various interventions, participant characteristics, and validity measures, offers insufficient evidence of the impact of these technologies in teaching social skills to students with ASD. Future research should develop a protocol for training treatment agents to assess the role of different variables (i.e., whether agents are customizing content, monitoring student learning, using intervention specific vocabulary in their day to day instruction). Sustainability may be increased by providing training in the technology to both treatment agents and participants. Providing scripts of instruction occurring within the intervention would provide the needed information to determine the primary method of teaching within the intervention. These variables play a role in maintenance and generalization of the social skills. Understanding the type of feedback provided would help researchers determine if students were able to feel rewarded for progressing through the scenarios or if students require rewarding aspects within the intervention (i.e., badges, trophies). AR has the potential to generalize instruction and VR has the potential for providing a practice environment for performance deficits. Combining these two technologies into a mixed reality intervention may provide a more cohesive and effective intervention.

Keywords: autism, augmented reality, social and emotional learning, social skills, virtual reality

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Cristina Galván-Fernández

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Students differentiate the different contexts of their lives as well as employment, hobbies or studies. In higher education is needed to transfer the experiential knowledge to theory and viceversa. However, is difficult to achieve than students use their personal experiences and social readings for get the learning evidences. In an experience with 178 education students from Chile and Spain we have used an e-portfolio system and a methodology for 4 years with the aims of help them to: 1) self-regulate their learning process and 2) use social networks and professional experiences for make the learning evidences. These two objectives have been controlled by interviews to the same students in different moments and two questionnaires. The results of this study show that students recognize the ownership of their learning and progress in planning and reflection of their own learning.

Keywords: competences, e-portfolio, higher education, self-regulation

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Authors: C. P. Autry, A. W. Roscoe, Mykhailo Magal

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We discuss the theoretical model underlying 2BPA (two-band peer authentication), a practical alternative to conventional authentication of entities and data in IoT. In essence, this involves assembling a virtual map of authentication assets in the network, typically leading to many paths of confirmation between any pair of entities. This map is continuously updated, confirmed, and evaluated. The value of authentication along multiple disjoint paths becomes very clear, and we require analogues of triangulation to extend authentication along extended paths and deliver it along all possible paths. We discover that if an attacker wants to make an honest node falsely believe she has authenticated another, then the length of the authentication paths is of little importance. This is because optimal attack strategies correspond to minimal cuts in the authentication graph and do not contain multiple edges on the same path. The authentication provided by disjoint paths normally is additive (in entropy).

Keywords: authentication, edge computing, industrial IoT, post-quantum resistance

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Authors: Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh

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The goal of this research is to explore the evolution of the concept of “blended learning” over a twenty-year period, to see whether or not the conceptualization has remained consistent or if it has become either more specific or more general. To achieve this goal, the term “blended learning” (and variations) was searched for in various bibliographical repositories for each year 2003-2022 to locate a highly cited paper that is not behind a paywall, to locate unique definitions that would be freely available to all academics each year. Each of the twenty unique definitions is explored to identify how they categorize both the Classroom Component and the Computer Component of blended learning, as well as identify which discipline each definition originates from and which country it comes from to see if there are any significant geographical variations. Based on this analysis, trends that appear in the definitions are noted, as well as an overall interpretation of the notion of “Blended Learning.”

Keywords: blended learning, definitions of blended learning, e-learning, thematic searches

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Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

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The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

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Authors: Chatcai Tangsri, Onjaree Na-Takuatoong

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This paper aims to present the key factors that support the decision to use the technology and to present the knowledge transformation flow of visually impaired students after the use of virtual knowledge system as proposed as a new service innovation to universities in Thailand. Correspondents of 27 visually impaired students are involved in this research. Total of 25 students are selected from the University that mainly conducts non-classroom teaching environment; while another 2 visually impaired students are selected from classroom teaching environment. All of them are fully involved in the study along 8 weeks duration. All correspondents are classified into 5 small groups in various conditions. The research results revealed that the involvement from knowledge facilitator can push out for the behavioral actual use of the virtual knowledge system although there is no any developed intention to use behaviors. Secondly, the situations that the visually impaired students inadequate of the knowledge sources that usually provided by assistants i.e. peers, audio files etc. In this case, they will use the virtual knowledge system for both knowledge access and knowledge transfer request. With this evidence, the need of knowledge would play a stronger role than all technology acceptance factors. Finally, this paper revealed that the knowledge transfer in the normal method that students have a chance to physically meet up is still confirmed as their preference method. In term of other aspects of technology acceptance, it will be discussed together with challenges and recommendations at the end of this paper.

Keywords: knowledge system, visually impaired students, higher education, knowledge management enable technology, synchronous/asynchronous knowledge access, synchronous/asynchronous knowledge transfer

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Authors: Alyona Gencheva

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The most common way to study diagnostic results is using specialized programs at a stationary workplace. Magnetic Resonance Imaging is presented in a two-dimensional (2D) format, and Computed Tomography sometimes looks like a three-dimensional (3D) model that can be interacted with. The main idea of the research is to compare ways of displaying diagnostic results in virtual reality that can help a surgeon during or before an operation in augmented reality. During the experiment, the medical staff examined liver vessels in the abdominal area and heart boundaries. The search time and detection accuracy were measured on black-and-white and coloured scans. Usability testing in virtual reality shows convenient ways of interaction like hand input, voice activation, displaying risk to the patient, and the required number of scans. The results of the experiment will be used in the new C# program based on Magic Leap technology.

Keywords: augmented reality, computed tomography, magic leap, magnetic resonance imaging, usability testing, VTE risk

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Authors: Valeria Minucciani, Maria Maddalena Margaria

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While mathematical tools that make digital architecture possible are very sophisticated and advanced, theoretical development of digital architecture (intended as a discipline that integrates or replaces the real architecture) is not. The fashion show, that involves interiors architecture, exhibit design and scenography, has been exploiting for ten years the opportunities offered by digital technologies. To gain greater visibility and to reach a wider audience, high-level experimentations have been performed. The aim of this paper is in investigating, through the analysis of some cases of virtual fashion shows, the 'architectural' impact of the virtual conception of interior space.

Keywords: digital interiors, exhibit, fashion catwalk, architectural theory

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Authors: Kuliya Muhammed

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This paper examines the potentials of online learning and the challenges to its adoption in Nigeria’s higher institutions of learning. The research would assist in tackling the challenges of online learning adoption and enlighten institutions on the numerous benefits of online learning in Nigeria. The researcher used survey method for the study and questionnaires were used to obtain the needed data from 230 respondents cut across 20 higher institutions in the country. The findings revealed that online learning has the prospect to boost access to learning tools, assist students’ to learn from the comfort of their offices or homes, reduce the cost of learning, and enable individuals to gain self-knowledge. The major challenges in the adoption of e-learning are poor Information and Communication Technology infrastructures, poor internet connectivity where available, lack of Information and Communication Technology background, problem of power supply, lack of commitment by institutions, poor maintenance of Information and Communication Technology tools, inadequate facilities, lack of government funding and fraud. Recommendations were also made at the end of the research work.

Keywords: electronic, ICT, institution, internet, learning, technology

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Authors: Ebtisam Alqahtani

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The purpose of this study is to investigate academic staff perspectives on using Augmented Reality in teaching practice to support students learning remotely during the COVID pandemic. the study adopted the DTPB theoretical model to guide the identification of key potential factors that could motivate academic staff to use or not use AR in teaching practices. A mixing method design was adopted for a better understanding of the study problem. A survey was completed by 851 academic staff, and this was followed by interviews with 20 academic staff. Statistical analyses were used to assess the survey data, and thematic analysis was used to assess the interview data. The study finding indicates that 75% of academic staff were aware of AR as a pedagogical tool, and they agreed on the potential benefits of AR in teaching and learning practices. However, 36% of academic staff use it in teaching and learning practice, and most of them agree with most of the potential barriers to adopting AR in educational environments. In addition, the study results indicate that 91% of them are planning to use it in the future. The most important factors that motivated them to use it in the future are the COVID pandemic factor, hedonic motivation factor, and academic staff attitude factor. The perceptions of academic staff differed according to the universities they attended, the faculties they worked in, and their gender. This study offers further empirical support for the DTPB model, as well as recommendations to help higher education implement technology in its educational environment based on the findings of the study. It is unprecedented the study the necessity of the use of AR technologies in the time of Covid-19. Therefore, the contribution is both theoretical and practice

Keywords: higher education, academic staff, AR technology as pedological tools, teaching and learning practice, benefits of AR, barriers of adopting AR, and motivating factors to adopt AR

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Authors: Richard Levy, Peter Dawson

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Ft. Conger, located in the Canadian Arctic was one of the most remote 19th-century scientific stations. Established in 1881 on Ellesmere Island, a wood framed structure established a permanent base from which to conduct scientific research. Under the charge of Lt. Greely, Ft. Conger was one of 14 expeditions conducted during the First International Polar Year (FIPY). Our research project “From Science to Survival: Using Virtual Exhibits to Communicate the Significance of Polar Heritage Sites in the Canadian Arctic” focused on the creation of a virtual museum website dedicated to one of the most important polar heritage site in the Canadian Arctic. This website was developed under a grant from Virtual Museum of Canada and enables visitors to explore the fort’s site from 1875 to the present, http://fortconger.org. Heritage sites are often viewed as static places. A goal of this project was to present the change that occurred over time as each new group of explorers adapted the site to their needs. The site was first visited by British explorer George Nares in 1875 – 76. Only later did the United States government select this site for the Lady Franklin Bay Expedition (1881-84) with research to be conducted under the FIPY (1882 – 83). Still later Robert Peary and Matthew Henson attempted to reach the North Pole from Ft. Conger in 1899, 1905 and 1908. A central focus of this research is on the virtual reconstruction of the Ft. Conger. In the summer of 2010, a Zoller+Fröhlich Imager 5006i and Minolta Vivid 910 laser scanner were used to scan terrain and artifacts. Once the scanning was completed, the point clouds were registered and edited to form the basis of a virtual reconstruction. A goal of this project has been to allow visitors to step back in time and explore the interior of these buildings with all of its artifacts. Links to text, historic documents, animations, panorama images, computer games and virtual labs provide explanations of how science was conducted during the 19th century. A major feature of this virtual world is the timeline. Visitors to the website can begin to explore the site when George Nares, in his ship the HMS Discovery, appeared in the harbor in 1875. With the emergence of Lt Greely’s expedition in 1881, we can track the progress made in establishing a scientific outpost. Still later in 1901, with Peary’s presence, the site is transformed again, with the huts having been built from materials salvaged from Greely’s main building. Still later in 2010, we can visit the site during its present state of deterioration and learn about the laser scanning technology which was used to document the site. The Science and Survival at Fort Conger project represents one of the first attempts to use virtual worlds to communicate the historical and scientific significance of polar heritage sites where opportunities for first-hand visitor experiences are not possible because of remote location.

Keywords: 3D imaging, multimedia, virtual reality, arctic

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Authors: Alemayehu Ambaw, Matia Mukama, Umezuruike Linus Opara

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This study introduces a comprehensive method for designing ventilated corrugated fiberboard carton for fresh fruit packaging utilising virtual prototyping. The technique efficiently assesses and analyses the mechanical and thermal capabilities of fresh fruit packing boxes prior to making production investments. Comprehensive structural, aerodynamic, and thermodynamic data from designs were collected and evaluated in comparison to real-world packaging needs. Physical prototypes of potential designs were created and evaluated afterward. The virtual prototype is created with computer-aided graphics, computational structural dynamics, and computational fluid dynamics technologies. The virtual prototyping quickly generated data on carton compression strength, airflow resistance, produce cooling rate, spatiotemporal temperature, and product quality map in the cold chain within a few hours. Six distinct designs were analysed. All the various carton designs showed similar effectiveness in preserving the quality of the goods. The innovative packaging box design is more compact, resulting in a higher freight density of 1720 kg more fruit per reefer compared to the commercial counterpart. The precooling process was improved, resulting in a 17% increase in throughput and a 30% reduction in power usage.

Keywords: postharvest, container logistics, space/volume usage, computational method, packaging technology

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Authors: Aqeel Zeid, Hasna Anees, Mohamed Adheeb, Mohamed Rifan, Kalpani Manathunga

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To achieve constructive alignment in a higher education program, a clear set of learning outcomes must be defined. Traditional learning outcome definition techniques such as Bloom’s taxonomy are not written to be utilized by the student. This might be disadvantageous for students in student-centric learning settings where the students are expected to formulate their own learning strategies. To solve the problem, we propose the learning outcome relation and aggregation (LORA) model. To achieve alignment, we developed learning outcome, assessment, and resource authoring tools which help teachers to tag learning outcomes during creation. A pilot study was conducted with an expert panel consisting of experienced professionals in the education domain to evaluate whether the LORA model and tools present an improvement over the traditional methods. The panel unanimously agreed that the model and tools are beneficial and effective. Moreover, it helped them model learning outcomes in a more student centric and descriptive way.

Keywords: learning design, constructive alignment, Bloom’s taxonomy, learning outcome modelling

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Authors: Maroonisha Maharajh

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Based on the Black Swan and Disruptive Innovation Theories, this study proposes an educational game based learning model within the context of the traditional classroom learning environment. In the proposed model, the perceived e-learning component is decomposed into accessibility, perceived quality and perceived usability within the traditional rural classroom environment. A sample of 92 respondents took part in this study. The results suggest that users’ continuance intention is determined by both economic and grassroots internet accessibility, which in turn is jointly determined by perceived usefulness, information quality, service quality, system quality, perceived ease of use and cognitive absorption of learning.

Keywords: blended learning, flipped classroom, e-learning, gaming

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Authors: Noritaka Shigei, Kazuto Matsumoto, Yoshiki Nakashima, Hiromi Miyajima

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Although Mobile Wireless Sensor Networks (MWSNs), which consist of mobile sensor nodes (MSNs), can cover a wide range of observation region by using a small number of sensor nodes, they need to construct a network to collect the sensing data on the base station by moving the MSNs. As an effective method, the network construction method based on Virtual Rails (VRs), which is referred to as VR method, has been proposed. In this paper, we propose two types of effective techniques for the VR method. They can prolong the operation time of the network, which is limited by the battery capabilities of MSNs and the energy consumption of MSNs. The first technique, an effective arrangement of VRs, almost equalizes the number of MSNs belonging to each VR. The second technique, an adaptive movement method of MSNs, takes into account the residual energy of battery. In the simulation, we demonstrate that each technique can improve the network lifetime and the combination of both techniques is the most effective.

Keywords: mobile sensor node, relay of sensing data, residual energy, virtual rail, wireless sensor network

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Authors: Randa El Bedawy

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Exchanging best practices in the scope of entrepreneurship education and the use of experiential learning approaches are growing lately at a very fast pace. Educators should be challenged to promote such a learning approach to bridge the gap between entrepreneurship students and the actual business work environment. The study aims to share best practices, experiences, and knowledge to support entrepreneurship education. The study is exploratory qualitative research based on a case study approach to demonstrate how experiential learning can be used for supporting learning effectiveness in entrepreneurship education through demonstrating a set of fourteen tasks that were used to engage practically the students who were studying a course of entrepreneurship at the American University in Cairo. The study sheds the light on the rational process of using experiential learning to endorse entrepreneurship education through the illustration of each task along with its learning outcomes. The study explores the benefits and obstacles that educators may face when implementing such an experiential approach. The results of the study confirm that developing an experiential learning approach based on constructing a set of well designed practical tasks that complement the overall intended learning outcomes has proven very effective for promoting the students’ learning of entrepreneurship education. However, good preparation for both educators and students is needed primarily to ensure the effective implementation of such an experiential learning approach.

Keywords: business education, entrepreneurship, entrepreneurship education, experiential learning

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Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram, Wenli Hu, Yang Yung

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In 3D video games, the dominance of production is unceasingly growing with a protruding level of affordability in terms of budget. Afterward, the automation of speech-lip synchronization technique is customarily onerous and has advanced a critical research subject in virtual reality based 3D video games. This paper presents one of these automatic tools, precisely riveted on the synchronization of the speech and the lip movement of the game characters. A robust and precise speech recognition segment that systematized with Algebraic Code Excited Linear Prediction method is developed which unconventionally delivers lip sync results. The Algebraic Code Excited Linear Prediction algorithm is constructed on that used in code-excited linear prediction, but Algebraic Code Excited Linear Prediction codebooks have an explicit algebraic structure levied upon them. This affords a quicker substitute to the software enactments of lip sync algorithms and thus advances the superiority of service factors abridged production cost.

Keywords: algebraic code excited linear prediction, speech-lip synchronization, video games, virtual reality

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Lucia Silveira Alda

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This research aims to analyze critically a set of studies published in the Proceedings of the International Conference on Mobile Learning of IADIS, from 2008 until 2012, which addresses the issue of foreign language learning mediated by mobile phones. The theoretical review of this study is based on the Vygotskian assumptions about tools and mediated learning and the concepts of mobile learning, CALL and MALL. In addition, the diffusion rates of the mobile phone and especially its potential are considered. Through systematic review and meta-analysis, this research intended to identify similarities and differences between the identified characteristics in the studies on the subject of language learning and mobile phone. From the analysis of the results, this study verifies that the mobile phone stands out for its mobility and portability. Furthermore, this device presented positive aspects towards student motivation in language learning. The studies were favorable to mobile phone use for learning. It was also found that the challenges in using this tool are not technical, but didactic and methodological, including the need to reflect on practical proposals. The findings of this study may direct further research in the area of language learning mediated by mobile phones.

Keywords: language learning, mobile learning, mobile phones, technology

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Authors: Sresha Yadav, Ishwar Kumar

Abstract:

Second language learning is an important area of research in the language and linguistic domains. Literature suggests that several factors impact second language learning, including age, motivation, objectives, teacher, instructional material, classroom interaction, intelligence and previous background, previous linguistic experience, other student characteristics. Previous researchers have also highlighted that classroom atmospherics has a significant impact on learning as well as on the performance of students. However, the impact of classroom atmospherics on second language learning is still not known in the existing literature. Therefore, the purpose of the present study is to explore whether classroom atmospherics has an impact on second language learning or not? And if it does, it would be worthwhile to explore the nature of such relationship. The present study aims to explore the impact of classroom atmospherics on second language learning by dwelling into the existing literature to explore factors which impact second language learning, classroom atmospherics which impact language learning and the metrics through which such learning impacts could be measured. Based on the findings of literature review, the researchers have adopted a clustering approach for categorization and positioning of various measures of second language learning. Based on the clustering approach, the researchers have approach for measuring the impact of classroom atmospherics on second language learning by drawing a student sample consisting of 80 respondents. The results of the study uncover various basic premises of second language learning, especially with regard to classroom atmospherics. The present study is important not only from the point of view of language learning but implications could be drawn with regard to the design of classroom atmospherics, environmental psychology, anthropometrics, etc as well.

Keywords: classroom atmospherics, cluster analysis, linguistics, second language learning

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

Abstract:

In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

Abstract:

In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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Authors: Gabrielle Brand, Christopher Etherton-Beer

Abstract:

The learning landscape of higher education environment is changing, with an increased focus over the past decade on how educators might begin to cultivate reflective skills in health professions students. In addition, changing professional requirements demand that health professionals are adequately prepared to practice in today’s complex Australian health care systems, including responding to changing demographics of population ageing. To counteract a widespread perception of health professions students’ disinterest in caring for older persons, the authors will report on an exploratory, mixed method research study that used photographs, narrative and small group work to enhance medical and nursing students’ reflective learning experience. An innovative photo-elicitation technique and reflective questioning prompts were used to increase engagement, and challenge students to consider new perspectives (around ageing) by constructing shared storylines in small groups. The qualitative themes revealed how photographs, narratives and small group work created learning spaces for reflection whereby students could safely explore their own personal and professional values, beliefs and perspectives around ageing. By providing the space for reflection, the students reported how they found connection and meaning in their own learning through a process of self-exploration that often challenged their assumptions of both older people and themselves as future health professionals. By integrating cognitive and affective elements into the learning process, this research demonstrates the importance of embedding visual methodologies that enhance reflection and transformative learning. The findings highlight the importance of integrating the arts into predominantly empirically driven health professional curricula and can be used as a catalyst for individual and/or collective reflection which can potentially enhance empathy, insight and understanding of the lived experiences of older patients. Based on these findings, the authors have developed ‘Depth of Field: Exploring Ageing’ an innovative, interprofessional, digital reflective learning resource that uses Prezi Inc. software (storytelling tool that presents ideas on a virtual canvas) to enhance students’ reflective capacity in the higher education environment.

Keywords: narrative, photo-elicitation, reflective learning, qualitative research

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