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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Elazhary, Hanan</text>
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                <text>In spite of the ultimate importance of procedural technical skills for most disciplines, there is shortage in the number of corresponding Intelligent Tutoring Systems (ITSs). This paper proposes a cloud-based context-aware mobile ITS of Technical computer Skills (TS-ITS). TITS is developed as a mobile application to be ubiquitously providing a valuable learning tool. Due to the nature of technical skills, they require more complex ITSs relative to typical ones requiring, for example demonstration videos that need considerable storage space. Accordingly, TS-ITS is developed using mobile cloud computing to benefit from the cloud resources and make up for limited mobile resources. On the other hand, effective multiple choice, true and false and short-answer questions can be delivered to the mobile. This also has the advantage of facilitating maintenance of the data stores on the cloud. TS-ITS is context-aware delivering training material relevant to the topic the student is studying, the skill the student is trying to acquire or the task the student is trying to accomplish. Each skill is accompanied by a short demonstration video and to facilitate searching for a relevant one, keyword search is adopted. Personalized questions are delivered based on the skills of interest and the assessed student knowledge. TS-ITS can be adopted to other domains and extended to include advanced types of training material such as Virtual reality (VR) immersive environments and interactive questions as they become available. Empirical evaluation of a prototype implementation of TS-ITS shows its tutoring effectiveness</text>
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                <text>Copyright (c) 2017 Hanan Elazhary</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 11 No. 4 (2017); pp. 170-185</text>
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                <text>1865-7923</text>
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                <text>computer skills</text>
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                <text>Cloud-based Context-aware Mobile Intelligent Tutoring System of Technical Computer Skills</text>
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                <text>Ghazali, Osman</text>
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                <text>Yang Leow, Chun</text>
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                <text>Qaiser, Shahzad</text>
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                <text>Customer disposition to data, nature of the information on site, protection concerns, trust, security concerns, and the notoriety of organization efficaciously affect the trust of Internet shoppers in the site. Two noteworthy and basic issues for e-commerce sites and consumers are trust as well as security. A belief that someone is good and honest and will not harm you, or something is safe and reliable is called trust; while security is an attempt to safeguard the data from unauthorized access. Information security is a vital management as well as technical requirement over the internet for effective and secure payment transaction activities. The safety of e-commerce resources from use, destruction, unauthorized access and alteration is known as E-commerce security so there is an urgent need to study its dimensions such as authenticity, integrity, availability, privacy, confidentiality and non-repudiation. This paper reports a review of four popular online marketplaces which are Alibaba, Amazon, eBay andTaoBao as case study on two main criteria namely building trust among users and ensuring security on the platform. Furthermore, we discuss the methods being used by each online marketplace to build trust and their unique way ofimproving the security. Finally, different ways of building trust and technique to ensure the security is presented in a tabular form for each online marketplace.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/10523</text>
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                <text>Copyright (c) 2019 Osman Ghazali</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 13 No. 04 (2019); pp. 96-116</text>
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                <text>1865-7923</text>
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                <text>Building trust</text>
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                <text>marketplaces</text>
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                <text>Cloud-Based Global Online Marketplaces Review on Trust and Security</text>
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                <text>Seno, Mohammed E.</text>
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                <text>Mohammad, Omer K. Jasim</text>
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                <text>Dhannoon, Ban N.</text>
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                <text>The cloud paradigm has swiftly developed, and it is now well known as one of the emerging technologies that will have a significant influence on technology and society in the next few years. Cloud computing also has several benefits, including lower operating costs, server consolidation, flexible system setup, and elastic resource supply. However, there are still technological hurdles to overcome, particularly with real-time applications by providing resources. Resources allocation management most charming part of cloud computing; therefore, several authors have worked in the area of resource usage. This study introduces an innovative cloud machine learning framework-based linear regression approach called cloud linear regression (CLR), which entails both cloud technology and machine learning concept. CLR using machine learning yielded good prediction results for resource allocation management, as appeared with many researching, and still seek, research to raise optimal solutions to the resources' allocation problem as the aim of this study.&amp;nbsp;&amp;nbsp; This study discusses the relation between cloud resource allocation management and machine learning techniques by illustrating the role of linear regression methods, resource distribution, and task scheduling. The analytical analysis shows that the CLR promises to present an effective solution for resources (scheduling, provisioning, allocation, and availability).</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/35791</text>
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                <text>Copyright (c) 2022 Haider TH.Salim ALRikabi; Mohammed E.  Seno, Omer K. Jasim  Mohammad, Ban N.  Dhannoon</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 22 (2022); pp. 157-175</text>
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                <text>1865-7923</text>
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                <text>Task scheduling, Resource Allocation, Machin Learning Algorithms, linear regression, cloud-host, VM-placement, VM-migration.</text>
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                <text>CLR: Cloud Linear Regression Environment as a More Effective Resource-Task Scheduling Environment (State-of-the-Art)</text>
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                <text>The Vehicular Ad-hoc Network (VANET) represents a new future for dynamic information dissemination between societies. VANET has a wide range of applications in a variety of aspects, including Intelligent Transportation Systems (ITS). VANET has some characteristics, like highly dynamic topology and intermittent connections. These characteristics lead to untrustworthy information transmission in VANET. Vehicle clustering is an efficient approach to improve the scalability of the network and connection reliability. The performance of the clustering is also affected by VANET characteristics. This article provides a comprehensive description of VANET clustering algorithms. The most notable clustering algorithms introduced between 1999 and 2021 are reviewed. A complete survey on clustering in VANETs is provided based upon the clustering process. The clustering process in most algorithms is explored in the aspects of CH selection metrics, cluster formation, and cluster maintenance. The clustering techniques based on some parameters like stability, convergence, overhead, and latency are compared. Some of the most common problems, as well as the approaches employed to solve them, are also discussed. Also, the performance parameters which evaluate the clustering approaches are summarized.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 10 (2022); pp. 25-48</text>
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                <text>1865-7923</text>
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                <text>VANET, Clustering Algorithms, Performance Parameters</text>
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                <text>Clustering Review in Vehicular Ad hoc Networks:  Algorithms, Comparisons, Challenges and Solutions</text>
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                <text>The daily functioning of civilization depends heavily on transportation. In most cities, a sizable section of the working class consistently attends both employment and education. There are many different things you can do when commuting, such as unwinding, eating out, and other things. The most popular means of transportation in North Cyprus, particularly in developing cities, is island transportation, which includes the usage of both private cars and commercial vehicles. The advent of edge computing, which offers the opportunity to connect potent processing servers next to the mobile device, is a significant step toward improving user experience and reducing resource use. Mobile Edge Computing is the next trustworthy approach for how mobile devices consume communications and computing. Offloading computation is a key component developing mobile edge computing, which enables devices to get around clustering techniques' limitations and get around computing, storage, and energy constraints. However, computation offloading is not always the best strategy to use; making choosing unloading is a critical step that requires consideration of numerous factors. For instance, shifting the high-resource node to an edge server and granting similar capabilities to the low-resource nodes would delegate heavy duties to the external unit inside the network. The evaluations' results were noteworthy and substantial. Problems involving the vehicles of institutions and organizations can be resolved using the suggested solution to the school bus routing issue. We also test the impact of network latency on the delivery of a particular result using an Edge Computing simulator.</text>
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                <text>Copyright (c) 2023 Dr. J. Albert Mayan, S.V. Manikanthan, Azham Hussain, S. Nithyaselvakumari, A. Vinnarasi</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 04 (2023); pp. 47-63</text>
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                <text>1865-7923</text>
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                <text>Mobile edge computing (MEC); transportation problems; save time; clustering technique; energy efficiency; resource optimization;</text>
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                <text>Clustering Technique for Mobile Edge Computing To Detect Clumps in Transportation-Related Problems</text>
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                  <text>Artha Journal of Social Sciences</text>
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                <text>The Carmalites of Mary Immaculate (CMI) has played a remarkable role in the process of the socio-economic and religious transformation in Kerala during the nineteenth and twentieth centuries. The CMI priests under the leadership of Fr. Kuriakose Elias Chavara resolved to eradicate the social evils and work for the upliftment of the downtrodden. Fr. Chavara became instrumental in establishing a series of schools and started social services for the upliftment of the poor.</text>
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                <text>Copyright (c) 2016 Artha - Journal of Social Sciences</text>
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                <text>Artha Journal of Social Sciences; Vol. 2 No. 2 (2004): Artha Journal of Social Sciences; 53-65</text>
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                <text>CMI and the Social Change in South India</text>
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                <text>Abu-Alsaad, Hiba A.</text>
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                <text>Due to the increased number of cars, outdoor parking is one of the critical problems. Moreover, the management of the parking system is also considered a difficult task. Humans, on the other hand, were acclimated to efficiently parking their automobiles by providing them with the precise location of parking in advance of their arrival. As a result of human inefficiency, it was unsuccessful and ultimately increased the compliance cost. As a result of the development of the notion of the Internet of Things. A lot of systems were installed regarding smart parking systems that are decreasing the cost but also contain a huge impact on the reduction of emissions from cars. While it is possible to integrate Internet of Things (IoT) devices into automobiles, such an approach will necessitates the deployment of additional infrastructure, which will raise the cost, and also it is not feasible within current infrastructure configurations. Then there's the fact that CCTV technology is widely available and also small enough to fit into any parking area without being noticeable. In this paper, Convolution Neural Network (CNN) based smart parking system is designed and implemented. The CNN is used to detect vacant and occupied parking spaces through CCTV cameras and provide feedback to the passengers. Furthermore, the proposed approach is using CNR and PKLot datasets for ensuring the effectiveness of the model. This was developed to solve the issues of time, cost, and accuracy with the existing systems. As a result, the proposed model provides excellent results in terms of accuracy. Moreover, it is cost-effective and saves time.</text>
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                <text>Copyright (c) 2023 Hiba Abu-Alsaad</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 11 (2023); pp. 155-170</text>
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                <text>1865-7923</text>
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                <text>The purpose of the article is to highlight how students' computational thinking, which is a critical thinking skill, can be developed through educational robotics and programming. It is a fun and engaging learning activity that encourages students to collaborate, delve into a problem, construct knowledge, and cultivate critical thinking. Educational robotics is therefore an innovative teaching tool, which contributes to the implementation of the above goal and follows the principles of building, specifically the construction of knowledge (Mikropoulos &amp;amp; Bellou, 2010). It develops students' critical thinking, strengthens their mental models, and activates known learning mechanisms leading them to a deeper level of understanding and assimilation of knowledge, which cannot be accomplished with traditional teaching methodologies. It has also been proven to be able to help students solve complex problems as well as contribute to the development of computational thinking skills (Atmatzidou &amp;amp; Demetriadis, 2014), which should characterize the entire literate population and complement the other three basic reading skills, writing, and mathematics (Mavroudis, Petrou &amp;amp; Fesakis, 2014).</text>
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            <description>A language of the resource</description>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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              </elementText>
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            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="51345">
                <text>Copyright (c) 2022 Ioanna  Moraiti, Anestis  Fotoglou, Athanasios Drigas</text>
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              <elementText elementTextId="51347">
                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 20 (2022); pp. 59-78</text>
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                <text>1865-7923</text>
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            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="51349">
                <text>STEM</text>
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                <text>STEAM</text>
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                <text>Robotics</text>
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              <elementText elementTextId="51352">
                <text>Educational Robotics</text>
              </elementText>
              <elementText elementTextId="51353">
                <text>Programming Languages</text>
              </elementText>
              <elementText elementTextId="51354">
                <text>Mobiles</text>
              </elementText>
              <elementText elementTextId="51355">
                <text>Critical Thinking</text>
              </elementText>
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                <text>Problem Solving</text>
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                <text>Block-based programming</text>
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                <text>Curriculum</text>
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                <text>Coding</text>
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            <name>Title</name>
            <description>A name given to the resource</description>
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              <elementText elementTextId="51360">
                <text>Coding with Block Programming Languages in Educational Robotics and Mobiles, Improve Problem Solving, Creativity &amp; Critical Thinking Skills</text>
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                <text>Peer-reviewed Article</text>
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                <elementText elementTextId="2304">
                  <text>Artha Journal of Social Sciences</text>
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                <text>N, Karunakaran</text>
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                <text>Coffee production in India is mostly done in Karnataka, Kerala and Tamilnadu. It is one of the important commercial crops of Keralaand is the main source of income and employment to the people of three districts in Kerala. Coffee cultivation is not an easy businessandis adversely affected by various factors at present. Small coffee growers fail to acquiretechnological improvement to compensate labour scarcity and climate change and have limited access to technologies promoted by the Coffee Board of India due to high cost and mode of payment of subsidies.This studyreveals that problems like scarcity of labour, pests and diseases, thehigh cost of production, low price for coffee, marketing difficulties and unusual climate changes often hurt coffee cultivators. However,the schemes and programmes ofthe coffee board benefited the growers. Theanalysis of the profitability of the crop shows that coffee cultivation is profitable in Kerala.</text>
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                <text>https://journals.christuniversity.in/index.php/artha/article/view/1985</text>
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              <elementText elementTextId="8373">
                <text>10.12724/ajss.43.6</text>
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            <description>A language of the resource</description>
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            <name>Publisher</name>
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                <text>Centre for Publications, CHRIST (Deemed to be University), Bangalore</text>
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                <text>https://journals.christuniversity.in/index.php/artha/article/view/1985/1635</text>
              </elementText>
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          </element>
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            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8377">
                <text>Copyright (c) 2019 Artha - Journal of Social Sciences</text>
              </elementText>
              <elementText elementTextId="8378">
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                <text>Artha Journal of Social Sciences; Vol. 16 No. 4 (2017): Artha Journal of Social Sciences; 97-108</text>
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                <text>0000-0000</text>
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                <text>0975-329X</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
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                <text>Coffee cultivation</text>
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                <text>Coffee board</text>
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                <text>Profitability</text>
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                <text>Kerala</text>
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                <text>Coffee Cultivation in Kerala: Some Economic Aspects</text>
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                <elementText elementTextId="15984">
                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
                </elementText>
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      <name>Dataset</name>
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              <elementText elementTextId="51001">
                <text>Saleh, Ashraf Mousa</text>
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                <text>Enaizan, Odai</text>
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                <text>Cognitive workload has been defined as the cognitive processing amount needed by a user in using an application. Cognitive load theory has been gaining increasing levels of importance within usability evaluations for mobile applications and the user interface. The PACMAD model has proven that cognitive workload (CL) can be seen as being a primary usability evaluation attribute in relation to mobile applications. Once the tasks that have been assigned to users within the environment of the mobile application have been performed by the evaluator, he/she subjectively measures the CL. Typically, subjective measurements are taken at a point following completion of a task and so they are static. Since these methods are static in nature, they are inappropriate for assessment of dynamic changes to the cognitive loads through user interaction. Robust measurement of the cognitive load of a user within real-time is not a simple, trivial undertaking. Lots of research studies have tried to assess the CL of users through use of various subjective measurements, though it is often the case that those approaches are unsuitable for use with real-life applications because of the high degree of intrusiveness. Automated measurement is seen as being a field that is relatively unexplored, particularly if used in relation to CL for mobile applications. The COG tool (CL automated tool) is proposed in this paper since it supports the interaction logging of the user for derivation of CL metrics that are based upon both secondary and primary tasks. Several strengths are provided by the automated measurement of CL, and it fills the gaps of a static nature of its non-objective, automated (subjective) counterpart. Within this research, in order for the study aim to be satisfied, objective CL metrics have been used by the researcher, i.e., task time, task success rate, number of touches, number of errors, duration on help, help visit count, total effort percentage and reaction on help. A total of 68 participants were recruited for the experiment, with them using an AAU mobile application through performance of a task that was predefined without there being any interference of a moderator or researcher. The findings showed that the proposed tool could fulfill the expected cognitive load monitoring functions amongst user interaction, collection of cognitive metrics and the logging of CL metrics that could be analyzed further.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/33363</text>
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                <text>10.3991/ijim.v16i20.33363</text>
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            <description>A language of the resource</description>
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                <text>eng</text>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/33363/12171</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="47">
            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="51011">
                <text>Copyright (c) 2022 Ashraf Saleh, Odai Enaizan</text>
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              <elementText elementTextId="51012">
                <text>https://creativecommons.org/licenses/by/4.0</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 20 (2022); pp. 143-161</text>
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              <elementText elementTextId="51014">
                <text>1865-7923</text>
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                <text>Cognitive load theory</text>
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              <elementText elementTextId="51016">
                <text>Mobile cognitive workload</text>
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                <text>mobile application</text>
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                <text>COG Tool: An Automated Cognitive Measurement of Workload for Mobile Event Logging</text>
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