Search results for: project based learning

Authors: Lisbeth Amhag

Abstract:

The aim of the study is to describe and analyze design of mobile teaching for students collaborative learning in distance higher education with a focus on mobile technologies as online webinars (web-based seminars or conferencing) by using laptops, smart phones, or tablets. These multimedia tools can provide face-toface interactions, recorded flipped classroom videos and parallel chat communications. The data collection consists of interviews with 22 students and observations of online face-to-face webinars, as well two surveys. Theoretically, the study joins the research tradition of Computer Supported Collaborative learning, CSCL, as well as Computer Self-Efficacy, CSE concerned with individuals’ media and information literacy. Important conclusions from the study demonstrated mobile interactions increased student centered learning. As the students were appreciating the working methods, they became more engaged and motivated. The mobile technology using among student also contributes to increased flexibility between space and place, as well as media and information literacy.

Keywords: Computer self-efficacy, computer supported collaborative learning, distance and open learning, educational design and technologies, media and information literacy, mobile learning.

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Authors: Ji-Hye Lee, Jongdeok Kim

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This research investigates the use of digital technology namely interactive multimedia in effective art education provided by museum. Several multimedia experience examples created for art education are study case subjected to assistance audiences- learning within the context of existing theory in the field of interactive multimedia.

Keywords: E-learning, Fine Arts, Interactivity, Multimedia

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Authors: S. Mahmoodzadeh, J. Shahrabi, M. Pariazar, M. S. Zaeri

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In this article, by using fuzzy AHP and TOPSIS technique we propose a new method for project selection problem. After reviewing four common methods of comparing alternatives investment (net present value, rate of return, benefit cost analysis and payback period) we use them as criteria in AHP tree. In this methodology by utilizing improved Analytical Hierarchy Process by Fuzzy set theory, first we try to calculate weight of each criterion. Then by implementing TOPSIS algorithm, assessment of projects has been done. Obtained results have been tested in a numerical example.

Keywords: Fuzzy AHP, Project Selection, TOPSIS Technique.

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Authors: Norfishah Mat Rabi, Rosma Osman, Norziana Mat Rabi

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It is difficult for autistic children to mix with and be around with other people. Language difficulties are a problem that affects their social life. A lack of knowledge and ability in language are factors that greatly influence their behavior, and their ability to communicate and interact. Autistic children need to be assisted to improve their language abilities through the use of suitable learning resources. This study is conducted to identify weather graphic animation resources can help autistic children learn and use transitive verbs more effectively. The study was conducted in a rural secondary school in Penang, Malaysia. The research subject comprised of three autistic students ranging in age from 14 years to 16 years. The 14-year-old student is placed in A Class and two 16-year-old students placed in B Class. The class placement of the subjects is based on the diagnostic test results conducted by the teacher and not based on age. Data collection is done through observation and interviews for the duration of five weeks; with the researcher allocating 30 minutes for every learning activity carried out. The research finding shows that the subjects learn transitive verbs better using graphic animation compared to static pictures. It is hoped that this study will give a new perspective towards the learning processes of autistic children.

Keywords: Autistic, graphic animation, language learning, transitive verbs.

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Authors: Min Kyeong Cha, Ju Yeon Mun, Seong Baeg Kim

Abstract:

Recently, ‘play of learning’ becomes important and is  emphasized as a useful learning tool. Therefore, interest in  edutainment contents is growing. Storytelling is considered first as a  method that improves the transmission of information and learner's  interest when planning edutainment contents. In this study, we  designed edutainment contents in the form of an adventure game that  applies the storytelling method. This content provides questions and  items constituted dynamically and reorganized learning contents  through analysis of test results. It allows learners to solve various  questions through effective iterative learning. As a result, the learners  can reach mastery learning.

 

Keywords: Storytelling, edutainment, mastery learning, computer operating principle.

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Authors: Ahmed Abbas Helmy, M. R. M. Rizk, Mohamed El-Sayed

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A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.

Keywords: Adaptive control, model predictive control, dynamic matrix control, online model identification

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Authors: Sangil Lee, Kwangyeol Ryu, Kezia Amanda Kurniadi, Yongju Park

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Nowadays, many manufacturing companies try to reinforce their competitiveness or find a breakthrough by considering collaboration. In Korea, more than 900 manufacturing companies are using web-based collaboration systems developed by the government-led project, referred to as i-Manufacturing. The system supports some similar functions of Product Data Management (PDM) as well as Project Management System (PMS). A web-based collaboration system provides many useful functions for collaborative works. This system, however, does not support new linking services between buyers and suppliers. Therefore, in order to find new collaborative partners, this paper proposes a framework which creates new connections between buyers and suppliers facilitating their collaboration, referred to as Excellent Manufacturer Scouting System (EMSS). EMSS plays a role as a bridge between overseas buyers and suppliers. As a part of study on EMSS, we also propose an evaluation method of manufacturability of potential partners with six main factors. Based on the results of evaluation, buyers may get a good guideline to choose their new partners before getting into negotiation processes with them.

Keywords: Supplier Scouting, Supplier Discovery, Collaboration, Web-based Collaboration System, Excellent Manufacturer Scouting System (EMSS)

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Authors: Izaz Ahmad, Farhatullah, Shahbaz Ali, Farhad Ali, Faiza, Hazrat Junaid, Farhan Zaid

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Current trends in remote health monitoring to monetize on the Internet of Things applications have been raised in efficient and interference free communications in Wireless Body Area Network (WBAN) scenario. Co-existence interference in WBANs have aggravates the over-congested radio bands, thereby requiring efficient Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) strategies and improve interference management. Existing solutions utilize simplistic heuristics to approach interference problems. The scope of this research article is to investigate reinforcement learning for efficient interference management under co-existing scenarios with an emphasis on homogenous interferences. The aim of this paper is to suggest a smart CSMA/CA mechanism based on reinforcement learning called QIM-MAC that effectively uses sense slots with minimal interference. Simulation results are analyzed based on scenarios which show that the proposed approach maximized Average Network Throughput and Packet Delivery Ratio and minimized Packet Loss Ratio, Energy Consumption and Average Delay.

Keywords: WBAN, IEEE 802.15.4 Standard, CAP Super-frame, Q-Learning.

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Authors: Victor Oluwaseyi Olowonisi

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The paper aimed at presenting an overview on the concept of e-learning as it relates to higher education and how it provides opportunities for students, instructors and the government in developing the educational sector. It also touched on the benefits and challenges attached to e-learning as a new medium of reaching more students especially in the Nigerian context. The opportunities attributed to e-learning in the paper includes breaking boundaries barriers, reaching a larger number of students, provision of jobs for ICT experts, etc. In contrary, poor power supply, cost of implementation, poor computer literacy, technophobia (fear of technology), computer crime and system failure were some of the challenges of e-learning discussed in the paper. The paper proffered that the government can help the people gain more from e-learning through its financing. Also, it was stated that instructors/lecturers and students need to undergo training on computer application in order for e-learning to be more effective in developing higher education in Nigeria.

Keywords: E-Learning, education, higher education, increasing literacy.

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Authors: Maurício Covolan Rosito, Daniel Antonio Callegari, Ricardo Melo Bastos

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Software organizations are constantly looking for better solutions when designing and using well-defined software processes for the development of their products and services. However, while the technical aspects are virtually easier to arrange, many software development processes lack more support on project management issues. When adopting such processes, an organization needs to apply good project management skills along with technical views provided by those models. This research proposes the definition of a new model that integrates the concepts of PMBOK and those available on the OPEN metamodel, helping not only process integration but also building the steps towards a more comprehensive and automatable model.

Keywords: OPEN metamodel, PMBOK metamodel, Project Management, Software Process

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Authors: A. A. Kudysheva, A. N. Kudyshev

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In present article the model of Blended Learning, its advantage at foreign language teaching, and also some problems that can arise during its use are considered. The Blended Learning is a special organization of learning, which allows to combine classroom work and modern technologies in electronic distance teaching environment. Nowadays a lot of European educational institutions and companies use such technology. Through this method: student gets the opportunity to learn in a group (classroom) with a teacher and additionally at home at a convenient time; student himself sets the optimal speed and intensity of the learning process; this method helps student to discipline himself and learn to work independently.

Keywords: Foreign language, information and communication technology (ICT), model of Blended Learning, virtual cool room, technophobia

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Authors: Raluca Ionela Maxim

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Designing a gender responsive Science, Technology, Engineering and Mathematics (STEM) mobile game based learning solution (mGBL) is a challenge in terms of content, gamification level and equal engagement of girls and boys. The goal of this case study was to research and create a high-fidelity prototype design of a mobile game that contains role-models as avatars that guide and expose girls and boys to STEM learning content. For this research purpose it was applied the methodology of design sprint with five-phase process that combines design thinking principles. The technique of this methodology comprises smart interviews with STEM experts, mind-map creation, sketching, prototyping and usability testing of the interactive prototype of the gender responsive STEM mGBL. The results have shown that the effect of the avatar/role model had a positive impact. Therefore, by exposing students (boys and girls) to STEM role models in an mGBL tool is helpful for the decreasing of the gender inequalities in STEM fields.

Keywords: Design thinking, design sprint, gender-responsive STEM education, mobile game based learning, role-models.

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Authors: Ahmet Ok, Banu Yücel Toy

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Promoting critical thinking (CT) in an educational setting has been appraised in order to enhance learning and intellectual skills. In this study, a pedagogical course in a vocational teacher education program in Turkey was designed by integrating CT skill-based strategies/activities into the course content and CT skills were means leading to intended course objectives. The purpose of the study was to evaluate the importance of the course objectives, the attainment of the objectives, and the effectiveness of teachinglearning strategies/activities from prospective teachers- points of view. The results revealed that although the students mostly considered the course objectives important, they did not feel competent in the attainment of all objectives especially in those related to the main topic of Learning and those requiring higher order thinking skills. On the other hand, the students considered the course activities effective for learning and for the development of thinking skills, especially, in interpreting, comparing, questioning, contrasting, and forming relationships.

Keywords: Critical thinking, critical thinking-based instruction, higher order thinking skills, teacher education

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other artificial intelligence (AI)-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: Machine learning, text classification, NLP techniques, semantic representation.

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Authors: Suzan Wedyan

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Associative classification (AC) is a data mining approach that combines association rule and classification to build classification models (classifiers). AC has attracted a significant attention from several researchers mainly because it derives accurate classifiers that contain simple yet effective rules. In the last decade, a number of associative classification algorithms have been proposed such as Classification based Association (CBA), Classification based on Multiple Association Rules (CMAR), Class based Associative Classification (CACA), and Classification based on Predicted Association Rule (CPAR). This paper surveys major AC algorithms and compares the steps and methods performed in each algorithm including: rule learning, rule sorting, rule pruning, classifier building, and class prediction.

Keywords: Associative Classification, Classification, Data Mining, Learning, Rule Ranking, Rule Pruning, Prediction.

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Authors: Jānis Zuters

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There are a lot of extensions made to the classic model of multi-layer perceptron (MLP). A notable amount of them has been designed to hasten the learning process without considering the quality of generalization. The paper proposes a new MLP extension based on exploiting topology of the input layer of the network. Experimental results show the extended model to improve upon generalization capability in certain cases. The new model requires additional computational resources to compare to the classic model, nevertheless the loss in efficiency isn-t regarded to be significant.

Keywords: Learning algorithm, multi-layer perceptron, topology.

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Authors: Anna Nedyalkova, KrassimirNedyalkov, TeodoraBakardjieva

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In the present paper, we-ll explore how social media tools provide an opportunity for new developments of the e-Learning in the context of managing personal knowledge. There will be a discussion how social media tools provide a possibility for helping knowledge workersand students to gather, organize and manage their personal information as a part of the e-learning process. At the centre of this social software driven approach to e-learning environments are the challenges of personalization and collaboration. We-ll share concepts of how organizations are using social media for e-Learning and believe that integration of these tools into traditional e-Learning is probably not a choice, but inevitability. Students- Survey of use of web technologies and social networking tools is presented. Newly developed framework for semantic blogging capable of organizing results relevant to user requirements is implemented at Varna Free University (VFU) to provide more effective navigation and search.

Keywords: Semantic blogging, social media tools, e-Learning, web 2.0, web 3.0.

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: Malaria, deep learning, DL, convolution neural network, CNN, thin blood smears.

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Authors: Carlos V. Regueiro, Jose E. Domenech, Roberto Iglesias, Jose L. Correa

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In this work a visual and reactive contour following behaviour is learned by reinforcement. With artificial vision the environment is perceived in 3D, and it is possible to avoid obstacles that are invisible to other sensors that are more common in mobile robotics. Reinforcement learning reduces the need for intervention in behaviour design, and simplifies its adjustment to the environment, the robot and the task. In order to facilitate its generalisation to other behaviours and to reduce the role of the designer, we propose a regular image-based codification of states. Even though this is much more difficult, our implementation converges and is robust. Results are presented with a Pioneer 2 AT on a Gazebo 3D simulator.

Keywords: Image-based State Codification, Mobile Robotics, ReinforcementLearning, Visual Behaviour.

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Authors: Yasser k. Ali, Hesham N. Elmahdy, Sanaa El Olla Hanfy Ahmed

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Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.

Keywords: Agent Migration, Decision Tree learning, ID3 algorithm, Naive Bayes Classifier

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Authors: Salina Budin, Nor Liawati Abu Othman, Shaira Ismail

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This study attempts to determine kinesthetic, verbal and visual intelligences among mechanical engineering undergraduate students and explores any probable relation with students’ learning styles and academic performance. The questionnaire used in this study is based on Howard Gardner’s multiple intelligences theory comprising of five elements of learning style; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering. Additional questions on students’ perception of learning styles and their academic performance are included in the questionnaire. The results show that one third of the students are strongly dominant in the kinesthetic intelligent (33%), followed by a combination of kinesthetic and visual intelligences (29%) and 21% are strongly dominant in all three types of intelligences. There is a statistically significant correlation between kinesthetic, verbal and visual intelligences and students learning styles and academic performances. The ANOVA analysis supports that there is a significant relationship between academic performances and level of kinesthetic, verbal and visual intelligences. In addition, it has also proven a remarkable relationship between academic performances and kinesthetic, verbal and visual learning styles amongst the male and female students. Thus, it can be concluded that, academic achievements can be enhanced by understanding as well as capitalizing the students’ types of intelligences and learning styles.

Keywords: Kinesthetic intelligent, verbal intelligent, visual intelligent, learning style, academic performances.

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: Gradient image, segmentation and extract, mean-shift algorithm, dictionary learning.

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

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In this contribution a newly developed e-learning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: Computational Intelligence, E-learning Environments, Intelligent Agents, User Modelling, Bayesian Networks.

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Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: Random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation.

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Authors: J. M. Breed, E. Taylor

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In this paper challenges associated with a new generation of Computer Science students are examined. The mode of education in tertiary institutes has progressed slowly while the needs of students have changed rapidly in an increasingly technological world. The major learning paradigms and learning theories within these paradigms are studied to find a suitable strategy for educating modern students. These paradigms include Behaviourism, Constructivism, Humanism and Cogntivism. Social Learning theory and Elaboration theory are two theories that are further examined and a survey is done to determine how these strategies will be received by students. The results and findings are evaluated and indicate that students are fairly receptive to a method that incorporates both Social Learning theory and Elaboration theory, but that some aspects of all paradigms need to be implemented to create a balanced and effective strategy with technology as foundation.

Keywords: Computer Science, Education, Elaboration Theory, Learning Paradigms, Social Learning Theory.

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Authors: Eulalia Torras, Andreu Bellot

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To know whether students’ achievements are the result of online interaction and not just a consequence of individual differences themselves, it seems essential to link the teaching presence and social presence to the types of knowledge built. The research aim is to analyze the social presence in relation to two types of knowledge, declarative and procedural. Qualitative methodology has been used. The analysis of the contents was based on an observation protocol that included community of enquiry indicators and procedural and declarative knowledge indicators. The research has been conducted in three phases that focused on an observational protocol and indicators, results and conclusions. Results show that the teaching-learning processes have been characterized by the patterns of presence and types of knowledge. Results also show the importance of social presence support provided by the teacher and the students, not only in regard to the nature of the instructional support but also concerning how it is presented to the student and the importance that is attributed to it in the teaching-learning process, that is, what it is that assistance is offered on. In this study, we find that the presence based on procedural guidelines and declarative reflection, the management of shared meaning on the basis of the skills and the evidence of these skills entail patterns of learning. Nevertheless, the importance that the teacher attributes to each support aspect has a bearing on the extent to which the students reflect more on the given task.

Keywords: Education, online, teaching and learning processes, knowledge.

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Authors: Carlos Ramirez, Carlos Concha, Benjamin Valdes

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Emotions are related with learning processes and physiological signals can be used to detect them for the personalization of learning resources and to control the pace of instruction. A model of relevant emotions has been developed, where specific combinations of emotions and cognition processes are connected and integrated with the concept of 'flow', in order to improve learning. The cardiac pulse is a reliable signal that carries useful information about the subject-s emotional condition; it is detected using a classroom chair adapted with non invasive EMFi sensor and an acquisition system that generates a ballistocardiogram (BCG), the signal is processed by an algorithm to obtain characteristics that match a specific emotional condition. The complete chair system is presented in this work, along with a framework for the personalization of learning resources.

Keywords: Ballistocardiogram, emotions in learning, noninvasive sensors, personalization of learning resources.

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Authors: N. Hamzah, M.A. Khoiry, I. Arshad, W.H.W. Badaruzzaman, N. M. Tawil

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Construction delay is unavoidable in developing countries including Malaysia. It is defined as time overrun or extension of time for completion of a project. The purpose of the study is to determine the causes of delay in Malaysian construction industries based on previous worldwide research. The field survey conducted includes the experienced developers, consultants and contractors in Malaysia. 34 causes of the construction delay have been determined and 24 have been selected using the Rasch model analysis. The analysis result will be used as the baseline for the next research to find the causes of delay in the Malaysian construction industry taking place in Malaysian higher learning institutions.

Keywords: Causes of construction delay, construction projects, Malaysian construction industry, Rasch model analysis.

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Adam Marks, Munir Majdalawieh, Maytha Al Ali

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While research is rich with what criteria could be included in the academic program review processes, there is rarely any mention of how this significant and complex process should be managed. This paper proposes using project management methodology in alignment with the program review criteria of the Dickeson’s Prioritizing Academic Programs model. Project management and academic program review share two distinct characteristics; one is their life cycle, and the second is the core knowledge areas they use. This aligned and structured approach offers academic administrators a step-by-step guide that can help them manage this process and effectively assess academic programs.

Keywords: Project management, academic program, program review, education, higher education institution, strategic management.

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