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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Wohllebe, Atilla</text>
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                <text>Hübner, Dirk-Siegfried</text>
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                <text>Radtke, Uwe</text>
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                <text>Wohllebe, Arabel</text>
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                <text>2021-06-18</text>
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                <text>With digitization and the spread of smartphones in many areas of life, mobile devices have also become increasingly relevant in education. While comprehensive research exists especially for smartphone use among teenagers and students, the findings for elementary school students are limited. Based on a survey, this case study provides exploratory insights into the smartphone usage behavior of elementary school students in a rural region in northern Germany. The responses of 33 students in grades 3 and 4 (ages 8 to 10) show that many students already own a smartphone at this age and use it daily, sometimes for several hours, especially for gaming and media consumption. The influence of owning an own smartphone on usage and leisure activities is reviewed. School use is of little relevance among the elementary school students surveyed.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/22565</text>
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                <text>10.3991/ijim.v15i12.22565</text>
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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/22565/9433</text>
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                <text>Copyright (c) 2021 Atilla Wohllebe, Arabel Wohllebe, Dirk-Siegfried Hübner, Uwe Radtke</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 12 (2021); pp. 184-192</text>
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                <text>1865-7923</text>
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                <text>Elementary School</text>
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                <text>Smartphones</text>
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                <text>Smartphones and Mobile Apps: Case Study on Usage Behavior of Elementary School Students – Insights from a Rural Area in Northern Germany</text>
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              <name>Title</name>
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                <elementText elementTextId="15984">
                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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      <name>Dataset</name>
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                <text>Nuanmeesri, Sumitra</text>
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            <name>Date</name>
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                <text>2022-03-08</text>
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                <text>This research aims to analyze the patterns of data errors in order to fulfill the data required for household big data development at the sub-district level in Thailand. Feature Selection and Multi-Layer Perceptron Neural Network were applied, while the data imbalance was solved by the SMOTE method and the comparison between the CFS feature selection method and Information Gain (IG) feature selection method. Afterward, the datasets were classified the data errors by the Multi-Layer Perceptron Neural Network. Each model’s effectiveness was measured by the 10-fold cross-validation method. The research results revealed that the suitable data size after being adjusted data imbalanced was 400%. Once the data had been processed for developing the model, it was found that after being adjusted data size towards the application of the SMOTE, CFS feature selection technique, and classified data errors by the Multi-Layer Perceptron Neural Network, the model provided the highest level of effectiveness in data errors classification with an accuracy of 98.29 %. Moreover, the application could effectively classify data errors and display the household big data at the highest level. The application evaluation results given by the experts and the users had an average mean of 4.69 and higher, a standard deviation of 0.47 and lower, which has the level of effectiveness of 93.78% and higher, while interquartile range values not over 1, a quartile deviation of no more than 0.5.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/22523</text>
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                <text>10.3991/ijim.v16i05.22523</text>
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            <description>A language of the resource</description>
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              <elementText elementTextId="42520">
                <text>eng</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="42521">
                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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            <description>A related resource</description>
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                <text>https://online-journals.org/index.php/i-jim/article/view/22523/10891</text>
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            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="42523">
                <text>Copyright (c) 2022 Sumitra Nuanmeesri</text>
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                <text>https://creativecommons.org/licenses/by/4.0</text>
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              <elementText elementTextId="42525">
                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 05 (2022); pp. 121-138</text>
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              <elementText elementTextId="42526">
                <text>1865-7923</text>
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            <name>Title</name>
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                <text>Feature Selection for Analyzing Data Errors Toward Development of Household Big Data at the Sub-District Level Using Multi-Layer Perceptron Neural Network</text>
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                <text>Peer-reviewed Article</text>
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              <elementTextContainer>
                <elementText elementTextId="15984">
                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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      <name>Dataset</name>
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          <element elementId="39">
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              <elementText elementTextId="42492">
                <text>Fadelelmoula, Ashraf Ahmed</text>
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            <name>Date</name>
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              <elementText elementTextId="42493">
                <text>2021-08-11</text>
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          <element elementId="41">
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            <description>An account of the resource</description>
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                <text>This article presents a new comprehensive approach to realize a sufficient trade-off between the CAP properties (i.e., consistency, availability, and partition tolerance) in the large-scale pervasive information systems. To achieve these critical properties, the capabilities of both cloud computing and web services were exploited in developing the components of the proposed approach. These components include a cloud-based replication architecture for ensuring high data availability and achieving partition tolerance, a web services-based middleware for maintaining the eventual consistency, and a data caching scheme to enable the mobile computing elements to conduct  update transactions during the disconnection periods.  The evaluation of the performance aspects revealed that the proposed approach is able to achieve a load balance, lower propagation delay, and higher cache hit ratio, as compared to other baseline approaches.</text>
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                <text>application/pdf</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/22517</text>
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                <text>10.3991/ijim.v15i15.22517</text>
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            <name>Language</name>
            <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/22517/9669</text>
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          <element elementId="47">
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            <elementTextContainer>
              <elementText elementTextId="42501">
                <text>Copyright (c) 2021 Ashraf Ahmed Fadelelmoula</text>
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          <element elementId="48">
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              <elementText elementTextId="42502">
                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 15 (2021); pp. 74-102</text>
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              <elementText elementTextId="42503">
                <text>1865-7923</text>
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            <name>Subject</name>
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                <text>CAP properties</text>
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              <elementText elementTextId="42505">
                <text>cloud computing</text>
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                <text>data replication</text>
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                <text>distributed systems</text>
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                <text>pervasive information systems</text>
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                <text>web services</text>
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                <text>Exploiting Cloud Computing and Web Services to Achieve Data Consistency, Availability, and Partition Tolerance in the Large-Scale Pervasive Systems</text>
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                <elementText elementTextId="15984">
                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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      <description>Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing.</description>
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          <element elementId="39">
            <name>Creator</name>
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              <elementText elementTextId="42468">
                <text>Dina, Nasa Zata</text>
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              <elementText elementTextId="42469">
                <text>Triwastuti, Ria</text>
              </elementText>
              <elementText elementTextId="42470">
                <text>Silfiani, Mega</text>
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              <elementText elementTextId="42471">
                <text>2021-09-06</text>
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                <text>In recent years, the use of ride hailing mobile application services is increasing exponentially. Customers’ expectation of these phone services varies and change dynamically as the needs of each individual also vary. Customer reviews about mobile application are honest, voluntary opinions; and these could become essential input for mobile application providers to measure satisfaction. However, managing a large number of reviews into actionable plans could be challenging. This study combines the Term Frequency-Inverse Document Frequency (TF-IDF) and Multiple-Criteria Decision-Making (MCDM)-VIKOR approach to process 600 reviews into a meaningful insight to enhance ride hailing mobile application services. The four-phase method analysis concluded that application ease of use and affordability are the most important aspects that most contribute to customers’ satisfaction in ride hailing mobile application services.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/22509</text>
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                <text>10.3991/ijim.v15i17.22509</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>In order to facilitate effective learning experiences for the students, mobile learning (m-learning) has evolved as a powerful component of education – learning and teaching. M-learning, as opposed to electronic learning (e-learning) which uses small and portable devices along with laptops and desktops, uses mostly small and portable technological tools. M-learning assists in imparting knowledge focusing on the need of the learner, accessibility, infrastructure, and interaction, irrespective of the place and time. With rapid advancements in Information and Communication Technologies (ICT) and mobile devices, myriad applications (apps) and innovative m-learning and e-learning services are being developed and launched at an unprecedented pace. For students representing different demographics (age, education level, class, socioeconomic status, location, etc.) and enrolled in higher education, m-learning has quickly become the modern style and preferred format of learning and accessing knowledge for its ease of integrating different modes of learning. Motivated by this novel m-learning learning movement, this study synthesizes existing research on m-learning technologies, technological platforms that cater to both synchronous and asynchronous learning/teaching modalities for students and teachers at institutions of higher education.</text>
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                <text>Copyright (c) 2021 Yuvika Gupta, Farheen Mujeeb Khan</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 12 (2021); pp. 140-157</text>
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                <text>1865-7923</text>
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                <text>M-learning</text>
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                <text>TAM</text>
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                <text>Exploring Factors Influencing Mobile Learning in Higher Education – A Systematic Review</text>
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                <text>Mahdi, Hussain</text>
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                <text>Al-Bander, Baidaa</text>
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                <text>Alwan, Mohammed Hasan</text>
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                <text>Moving is the key to modern life. Most things are in moving such as vehicles and user mobiles, so the need for high-speed wireless networks to serve the high demand of the wireless application becomes essential for any wireless network design. The use of web browsing, online gaming, and on-time data exchange like video calls as an example means that users need a high data rate and fewer error communication links. To satisfy this, increasing the bandwidth available for each network will enhance the throughput of the communication, but the bandwidth available is a limited resource which means that thinking about techniques to be used to increase the throughput of the network is very important. One of the techniques used is the spectrum sharing between the available networks, but the problem here is when there is no available channel to connect with. This encourages researchers to think about using scheduling as a technique to serve the high capacity on the network. Studying scheduling techniques depends on the Quality-of-Service (QoS) of the network, so the throughput performance is the metric of this paper. In this paper, an improved Best-CQI scheduling algorithm is proposed to enhance the throughput of the network. The proposed algorithm was compared with three user scheduling algorithms to evaluate the throughput performance which are Round Robin (RR), Proportional Fair (PF), and Best-CQI algorithms. The study is performed under Line-of-Sight (LoS) link at carrier frequency 2.6 GHz to satisfy the Vehicular Long Term Evolution (LTE-V) with the high-speed scenario. The simulation results show that the proposed algorithm outperforms the throughput performance of the other algorithms.</text>
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                <text>Copyright (c) 2021 Hussain Mahdi, Baidaa Al-Bander, Mohammed Hasan Alwan, Mohammed Salah Abood, Mustafa Maad Hamdi</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 21 (2021); pp. 52-66</text>
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                <text>1865-7923</text>
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                <text>LTE-V</text>
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                <text>Vehicular Networks Performance Evaluation Based on Downlink Scheduling Algorithms for High-Speed Long Term Evolution – Vehicle</text>
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                <text>In 2021, the COVID-19 pandemic is still not over. Thailand is the one that is facing the second wave of new coronavirus. Schools and universities were closed, and faculties need to mostly teach with Online pedagogy, including the graduate students' courses. This study proposes to focus on the Ubiquitous area of the Blended Learning model with IoT-based to solve a problem of graduate students and their advisors by the qualitative focus-group technique. The mobile application draft was synthesized and designed to track and monitor graduate students' research activities on smartphones by built-in sensors. They should stay active along while researching the advisor’s assignments on their smartphone. Non-active periods are implied when several behaviors are detected. Virtualize dashboards are processed to report the total active learning period of students for the advisor's evaluation.Moreover, students can continually monitor their self-efficacy to improve the online learning process. Besides, this study proposes to confirm the model’s quality by twelve experts with the questionnaire. The results show average scores of Propriety, Utility, Feasibility, and Accuracy standard are 4.32, 4.41, 4.37, and 4.21, respectively. Therefore, the Blended Learning model's overall qualities with IoT-based smartphones are extremely high and proper to implement.</text>
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            <description>Information about rights held in and over the resource</description>
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                <text>Copyright (c) 2021 Kobchai Siripongdee</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 11 (2021); pp. 166-182</text>
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                <text>1865-7923</text>
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                <text>Blended Learning</text>
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                <text>Mobile application.</text>
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                <text>Blended Learning Model with IoT-based by Smartphone</text>
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                <text>Abstrait-Ce travail vise à étudier comment une expérience de formation à distance de trois jours pour enseignants, programmée d'urgence, pour développer chez ces enseignants les capacités d'utilisation de la plateforme numérique, la création et la gestion de ressources numériques, ainsi que la création et la gestion d'un évaluation, afin qu'ils soient en mesure d'assurer correctement la continuité pédagogique. La mise en place de ce mode de formation a été recommandée dans un état d'urgence en raison de la pandémie de Corona Virus qui a été connue dans le monde entier et qui a provoqué la fermeture des écoles, ce qui a forcé le passage du mode présentiel à l'enseignement à distance, au cours de l'année 2020. Cette formation à distance, qui concerne les enseignants des écoles, était nécessaire pour développer leurs capacités à utiliser ce nouveau mode d'enseignement.A partir du cadre de l'évaluation de la formation professionnelle, et à travers les outils de collecte de données construits et utilisés dans cette recherche, les résultats montrent une certaine évolution dans les conceptions de ces enseignants pour revisiter les objectifs de cette formation par les enseignants-formateurs pour son déploiement éventuel.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 17 (2021); pp. 119-140</text>
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                <text>1865-7923</text>
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                <text>continuing education</text>
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                <text>This study seeks to answer the question of how effectively students can use their smartphones as tools for measuring and processing data when they perform physics experiments. The research was conducted in a local secondary school in Athens, Greece. The sample consisted of fifty-two 16-year-old students (10th grade). The students formed 26 pairs, and were asked to perform an experiment using their smartphones for measuring, processing and saving data, and then to email the data file to the researchers. During the implementation, students of each pair completed the steps on a worksheet. Two researchers monitored each pair individually and recorded scores and comments on evaluation sheets. The worksheets, the evaluation sheets, and the experimental data emailed by each pair constituted the data of the present study. The findings of the study show that the integration of students' smart mobile devices in the performance of physics experiments in the classroom or in the school lab is possible without posing particular problems. However, this integration presupposes the proper planning by the teacher and the dedication of appropriate time both for the preparation of the students for the activity, and for the installation of the necessary applications in the devices.</text>
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                <text>Copyright (c) 2021 Serafeim Tsoukos, Panagiotis Lazos, Pavlos Tzamalis, Alexandros Kateris, Athanasios Velentzas</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 14 (2021); pp. 55-71</text>
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                <text>1865-7923</text>
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                <text>Smartphone Sensors</text>
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                <text>How Effectively Can Students’ Personal Smartphones be Used as Tools in Physics Labs?</text>
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                <text>Okuboyejo, Senanu</text>
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                <text>Mobile learning applications (apps) are increasingly and widely adopted for learning purposes and educational content delivery globally, especially with the massive means of accessing the internet done majorly on mobile handheld devices. Users often submit their feedback on use, experience and general satisfaction via the reviews and ratings given in the digital distribution platforms. With this massive information given through the reviews, it presents an opportunity to derives valuable insights which can be utilized for various reasons and by different stakeholders of these mobile learning apps. This large volume of online reviews creates significant information overload which presents a time-consuming task to read through all reviews. By combining text mining techniques of topic modeling using Latent Dirichlet Algorithm (LDA) and sentiment analysis using Linguistic Inquiry Word Count (LIWC), we analyze these user reviews. These techniques identify inherent topics in the reviews and identifies variables of user satisfaction of mobile learning apps. The thematic analysis done reveals different keywords which guide classification into the topics identified. Conclusively, the topics derived are important to app stakeholders for further modifications and evolution tasks.</text>
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                <text>Copyright (c) 2021 Senanu Okuboyejo, Ooreofe Koyejo</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 15 (2021); pp. 47-58</text>
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                <text>1865-7923</text>
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