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                <text>CLAWS Journal; Vol. 11 No. 2 (2018): Winter 2018; 125-130</text>
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                <text>Liberal Studies; Vol. 4 No. 2 (2019): July-December 2019; 249-251</text>
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                <text>The political residue embedded in the consciousness of the people who are divided by the political lines nonetheless shares an undivided common history finds a voice in the poems of Akhil Katyal. The poems, in Akhil Katyal's How Many Countries does the Indus Cross, are infused with the politics of bygone days of the Indian subcontinent which unfailingly defines our present-day politics and dictates the lives of the people. With an engaging title, the poet critiques absurdly painted borders of the surfaced nations on the map of the Indian subcontinent in the twentieth century. Every country that Indus passes through has been witnessing ongoing unrest. These countries have been engulfed in territorial conflicts, regions in the course of Indus have witnessed suffering and fought a politicized dispute over the water of Indus. In spite of all, as the poet shows, irrevocable Indus, ironical as it seems, overruns the divided lands unifying the people in their experiences. Katyal's poems, interspersed with a thematic plethora, engage the readers with the stylistic appeal.&#13;
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                <text>Liberal Studies; Vol. 4 No. 2 (2019): July-December 2019; 257-261</text>
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                <text>A model consisting of five dimensions of mobile learning preferences â?? location, level of distractions, time of day, level of motivation and available time â?? is proposed in this paper. The aim of the model is to potentially increase the learning effectiveness of individuals or groups by appropriately matching and allocating mobile learning materials/applications according to each learnerâ??s type. Examples are given. Our current research investigations relating to this model are described.</text>
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                <text>Self-regulated students are able to create and maximize opportunities they have for studying or learning. We combine this learning approach with our Mobile Context-aware and Adaptive Learning Schedule (mCALS) tool which will create and enhance opportunities for students to study or learn in different locations. The learning schedule is used for two purposes, a) to help students organize their work and facilitate time management, and b) for capturing the usersâ?? activities which can be retrieved and translated as learning contexts later by our tool. These contexts are then used as a basis for selecting appropriate learning materials for the students. Using a learning schedule to capture and retrieve contexts is a novel approach in the context-aware mobile learning field. In this paper, we present the conceptual model and preliminary architecture of our mCALS tool, as well as our research questions and methodology for evaluating it. The learning materials we intend to use for our tool will be Java for novice programmers. This is appropriate because large amounts of time and motivation are necessary to learn an object-oriented programming language such as Java, and we are currently seeking ways to facilitate this for novice programmers.</text>
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                <text>Copyright (c) 2017 Jane Yau, Mike Joy</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 2 No. 3 (2008); pp. 52-57</text>
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                <text>Context-aware pervasive learning environments consist of interconnected, embedded computing devices such as portable computers, wireless sensors, auxiliary input/output devices and servers. Until this study there has been no survey that has evaluated and presented information regarding these environments. In this paper, we conducted a survey to identify the commonly used technologies, methods and models behind these systems, and evaluated the role of mobile devices in the reviewed papers. As a result, we made five observations: (i) RFID was the most common sensor technology; (ii) several learning models were suggested, but none was validated properly; (iii) client-server architectures are prevalent in the systems and mobile devices were used most commonly to represent information; (iv) most of the systems supported multiple simultaneous users, but few facilitated virtual communication; and (v) possible roles for physical environments in pervasive learning systems are: contexts for learning, content for learning, and system resources. Evidence indicates that suitable learning models have yet to be validated, and that more roles of mobile devices could be emphasised.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 3 No. 1 (2009); 70-76</text>
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                <text>1865-7923</text>
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                <text>Innovation in learning technologies and services is driven by demands from Higher Educational Institutions (HEIs) in order to meet their students’ needs and make knowledge delivery easier. The technology could play a pivotal role in extending the possibilities for teaching, learning, and research in educational institutions. M-learning emerged from this innovation as a result of an unprecedented explosion in the number of mobile devices due to availability and affordability of mobile phones, smartphones and tablets among students. Competition in the mobile device industry is also encouraging developers to be innovative, constantly striving to introduce new features. Consequently, newer sources of risks are being introduced in the mobile computing paradigm at manufacturing level. Similarly, many m-learning promoters and developers focus on developing and delivering learning content and infrastructure for m-learning system without adequate consideration for security of stakeholders’ data, whereas the use of these mobile technologies for learning poses a serious threat to confidentiality, integrity and privacy of those involved in teaching and learning, yet traditional security threats are also evolving. Against this backdrop, the stakeholders in education sector (i.e. education providers, educators, m-learning promoters and developers) should begin to consider the security implications of these devices in modern teaching and learning environments. The purpose of this paper is to identify the m-learning security issues that stakeholders may face, how they are being affected by the security threats,  who among is stakeholders are affected or most affected by security issues in m-learning using three Nigeria universities as case studies and what are the responsibilities of the stakeholders in ensuring risk free m-learning.</text>
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                <text>Copyright (c) 2017 Shaibu Adekunle Shonola, Mike S Joy</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 9 No. 3 (2015); pp. 64-70</text>
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                <text>1865-7923</text>
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                <text>Security of m-learning system: A collective responsibility</text>
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                <text>The purpose of this study was to (1) assess the impact of using Dynamic Geometry Software (DGS) on students’ mathematical abilities, (2) determine the differences in effectiveness based on study characteristics in order to help educators decide under what conditions the use of DGS would be suitable in improving students' mathematical abilities. This meta-analysis study investigates 57 effect sizes from 50 articles that have been published in journals, international and domestic proceedings from 2010 to 2020 using the Comprehensive Meta-Analysis (CMA) tool as a calculation tool. Meanwhile, the Hedges coefficient is applied to the calculation of the effect size at the 95% confidence level. Based on a random effect model with a standard error of 0.09, the analysis results have found an overall effect size of 1.07. This means that learning using DGS has a high positive effect on students' mathematical abilities. The effect size of 1.07 explains the average student who uses DGS exceeds 84% math ability of those in conventional classes that are initially equivalent. Analysis of the study characteristics found significant differences in terms of sample size, student to computer ratio, and education level. This research showed the DGS used was more effective under certain conditions. First, it is very effective in sample conditions less than or equal to 30. Second, it provides classrooms with a sufficient number of computers, allowing students to use them individually, which is required to achieve higher effectiveness levels. Third, DGS is effective in high schools and colleges than in junior high schools. These facts can help educators in deciding on the appropriate sample sizes, student to computer ratios, and future levels of education in using DGS.</text>
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                <text>Copyright (c) 2021 Dadang Juandi, Yaya Sukjaya Kusumah, Maximus Tamur, Krisna Satrio Perbowo, Muhammad Daut Siagian, Rini Sulastri, Habibi R. P Negara</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 02 (2021); pp. 18-37</text>
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                <text>The Effectiveness of Dynamic Geometry Software Applications in Learning Mathematics: A Meta-Analysis Study</text>
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                <text>The purpose of this study was to determine and apply (1) the Augmented Reality (AR) development process; (2) AR model design; (3) application of AR technology; and (4) the results of AR development that can be used as a support for learning methods in the Building Engineering Education Study Program for the implementation of the 2020 curriculum. Adequate teaching materials are needed so that prospective professional teachers can quickly learn learning materials using the latest learning facilities and meet the demands of 21st-century learning. The main material that must be mastered by prospective professional teachers of the Construction and Housing Engineering Expertise Program include statics, building construction, construction drawings, and construction management. The number of materials contained in each main material requires mapping of essential competencies that must be mastered by prospective professional teacher students as the basic material for learning the Construction and Housing Engineering Expertise Program. The essential competencies that have been identified are used as materials for developing 3D AR-based learning media that can be delivered online so that they can be accessed by students without being limited by the dimensions of space and time. The results of the development of learning media will make it easier for prospective professional teacher students to learn the main content.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 05 (2022); pp. 199-206</text>
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                <text>Essential Competence as a Determiner of Learning Media Development in Network-Based on 3D Augmented Reality in the Pre-Teacher Civil Engineering Education Study Program</text>
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