Search results for: educational data mining

Authors: Nestor C. Nabe, Melvie F. Bayog

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The cultural competence of police officers can lead to effective law enforcement and gain respect to their organization. This study evaluated the level of cultural competence of Philippine National Police Personnel in Midsayap, Cotabato, Philippines. Descriptive survey research design was used in this study. The survey utilized an adapted questionnaire to measure the level of cultural competence of the respondents. Questionnaires were administered to 305 ethnic minorities coming from the four major ethnic tribes in Midsayap, Cotabato, Philippines. The data gathered were treated using Percentage, Mean, T-test and Analysis of Variance (ANOVA). The findings are as follows: the level of cultural competence of police personnel is moderate; and, there is no significant difference in the cultural competence of the police personnel when analyzed by age, gender, civil status and, occupation while there is a significant difference analyzed by educational attainment and ethnic tribe. Based on the findings, the following conclusions were drawn: the level of cultural competence of police personnel is only manifested sometimes; and, civil status, and occupation has no significant difference in the cultural competence of police personnel while educational attainment and ethnic tribe has a significant difference.

Keywords: competence, cultural, Philippines, police

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Authors: Melissa C. Ingram

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This literature review sought to explore the dimensions of diversity that can affect classroom learning. This review is significant as it can aid educators in reaching more of their diverse student population and creating supportive classrooms for teachers and students. For this study, peer-reviewed articles were found and compiled using Google Scholar. Key terms used in the search include student individuality, classroom equality, student development, teacher development, and teacher individuality. Relevant educational standards such as Common Core and Partnership for the 21st Century were also included as part of this review. Student and teacher individuality and equality is discussed as well as methods to grow both within educational settings. Embracing student and teacher individuality was found to be key as it may affect how each person interacts with given information. One method to grow individuality and equality in educational settings included drafting and employing revised teaching standards which include various Common Core and U.S. State standards. Another was to use educational theories such as constructivism, cognitive learning, and Experiential Learning Theory. However, barriers to growing individuality, such as not acknowledging differences in a population’s dimensions of diversity, still exist. Studies found preserving the dimensions of diversity owned by both teachers and students yielded more positive and beneficial classroom experiences.

Keywords: classroom equality, student development, student individuality, teacher development, teacher individuality

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Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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Authors: Ebtisam Alqahtani

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

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

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Authors: Lama Bendak

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Parents and teachers face major problems dealing with attention deficit hyperactivity students. One solution is by changing the school to a less restrictive one or leaving school for good. The purpose of this study is to highlight the importance and role of individual educational plans (IEP) in helping cycle one ages six to nine attention deficit hyperactivity disorder (ADHD) students on the behavioral level. We have adopted the qualitative approach experimental where the total number of the students in our field of study was 66 from four schools. We have limited our study to cycle one students; that is grades 1, 2 and 3, whose ages range from 5.5 to 8.5. We divided the students into two groups where the controlled group was 36 students, and the experimental group was 30 students. The measuring instrument or tool that we used in our study is The SNAP-IV Teacher and Parents Rating Scale and was filled by class teachers. We did the pretest during the first trimester of the school year. Then we applied the Individual Educational Plans IEP's for two trimesters. Then we did the posttest and submitted the results for analysis, where we used the ANCOVA. The results of this study showed that the IEP's efficacy in helping ADHD students on the behavioral aspect showed statistical differences and varied depending on the initial level of difficulty of the student.

Keywords: attention deficit hyperactivity disorder, individual educational plans, behavioral charts, SNAP-IV teacher and parents rating scale

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Authors: S. P. Akinbogun, P. Oloruntoyin

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One of the millennium development goals is the reduction of illiteracy. The state of user friendliness of the educational buildings is expected to play a significant role in the quest, particularly among the physically challenged. This study considers the state of access of educational buildings to disabled on wheel chair and crutches. It draws context from one of the federal universities in Nigeria. The study is basically qualitative; data were collected through structured interview and observation to assess compliance with the prescribed accessibility standard of academic buildings in the Federal University of Technology Akure. The study found that narrow entrances and routes of buildings, raised steps at entrances of the buildings, and ramps were absent. This implies exclusion as it renders most of the buildings inaccessible to wheelchair users. Perhaps, it accounts for low enrolment of wheelchair users in the institution despite many of them in the city. The implication is a challenge in the achievement of the millennium development goal concerning the reduction in the level of illiteracy in the country. The study suggests that government should strictly ensure that public buildings should satisfy or retrofitted to meet disabled access before development approval. This should be followed with the issuance of certificate of compliance upon completion.

Keywords: public building, accessibility, physically challenged, education

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Authors: Adrian Ionita, Ana-Maria Ghimes

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The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

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Authors: Maturos Chongchaikit, Sitthikorn Sumalee, Nopphawan Chimroylarp, Nongluck Manowaluilou, Thapanee Thammetha

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The 2015 Kasetsart University Research Plan, which was funded by the National Research Institutes: TRF – NRCT, comprises four sub-research projects on the development of three OER websites and on their usage study by students in international programs. The goals were to develop the open educational resources (OER) in the form of websites that will promote three key skills of quality learning and achievement: Academic English, Educational Research, and ICT Literacy, to graduate students in international programs of Thailand. The statistics from the Office of Higher Education showed that the number of foreign students who come to study in international higher education of Thailand has increased respectively by 25 percent per year, proving that the international education system and institutes of Thailand have been already recognized regionally and globally as meeting the standards. The output of the plan: the OER websites and their materials, and the outcome: students’ learning improvement due to lecturers’ readiness for open educational media, will ultimately lead the country to higher business capabilities for international education services in ASEAN Community in the future. The OER innovation is aimed at sharing quality knowledge to the world, with the adoption of Creative Commons Licenses that makes sharing be able to do freely (5Rs openness), without charge and leading to self and life-long learning. The research has brought the problems on the low usage of existing OER in the English language to develop the OER on three specific skills and try them out with the sample of 100 students randomly selected from the international graduate programs of top 10 Thai universities, according to QS Asia University Rankings 2014. The R&D process was used for product evaluation in 2 stages: the development stage and the usage study stage. The research tools were the questionnaires for content and OER experts, the questionnaires for the sample group and the open-ended interviews for the focus group discussions. The data were analyzed using frequency, percentage, mean and SD. The findings revealed that the developed websites were fully qualified as OERs by the experts. The students’ opinions and satisfaction were at the highest levels for both the content and the technology used for presentation. The usage manual and self-assessment guide were finalized during the focus group discussions. The direct participation according to the concept of 5Rs Openness Activities through the provided tools of OER models like MERLOT and OER COMMONS, as well as the development of usage manual and self-assessment guide, were revealed as a key approach to further extend the output widely and sustainably to the network of users in various higher education institutions.

Keywords: open educational resources, international education services business, academic English, educational research, ICT literacy, international graduate program, OER

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Thomas F. Ducey, Kristin M. Trippe, James A. Ippolito, Jeffrey M. Novak, Mark G. Johnson, Gilbert C. Sigua

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The Oronogo-Duenweg mining belt –approximately 20 square miles around the Joplin, Missouri area– is a designated United States Environmental Protection Agency Superfund site due to lead-contaminated soil and groundwater by former mining and smelting operations. Over almost a century of mining (from 1848 to the late 1960’s), an estimated ten million tons of cadmium, lead, and zinc containing material have been deposited on approximately 9,000 acres. Sites that have undergone remediation, in which the O, A, and B horizons have been removed along with the lead contamination, the exposed C horizon remains incalcitrant to revegetation efforts. These sites also suffer from poor soil microbial activity, as measured by soil extracellular enzymatic assays, though 16S ribosomal ribonucleic acid (rRNA) indicates that microbial diversity is equal to sites that have avoided mine-related contamination. Soil analysis reveals low soil organic carbon, along with high levels of bio-available zinc, that reflect the poor soil fertility conditions and low microbial activity. Our study looked at the use of several materials to restore and remediate these sites, with the goal of improving soil health. The following materials, and their purposes for incorporation into the study, were as follows: manure-based biochar for the binding of zinc and other heavy metals responsible for phytotoxicity, locally sourced biosolids and compost to incorporate organic carbon into the depleted soils, effective microorganisms harvested from nearby pristine sites to provide a stable community for nutrient cycling in the newly composited 'soil material'. Our results indicate that all four materials used in conjunction result in the greatest benefit to these mine-impacted soils, based on above ground biomass, microbial biomass, and soil enzymatic activities.

Keywords: locally effective microorganisms, biochar, remediation, reclamation

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Authors: Agostinho Antunes

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The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: comparative genomics, adaptive evolution, bioinformatics, phylogenetics, genome mining

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Authors: Adam Chlapecka, Anna Kagstrom, Pavla Cermakova

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Background: Increasing educational attainment (EA) could decrease the occurrence of depression. We investigated the relationship between EA and depressive symptoms in older individuals across four European regions. Methods: We studied 108 315 Europeans (54 % women, median age 63 years old) from the Survey on Health, Ageing and Retirement in Europe assessing EA (7 educational levels based on ISCED classification); and depressive symptoms (≥ 4 points on EURO-D scale). Logistic regression estimated the association between EA and depressive symptoms, adjusting for sociodemographic and health-related factors; testing for sex/age/region and education interactions. Results: Higher EA was associated with lower odds of depressive symptoms, independent of sociodemographic and health-related factors. A threshold of the lowest odds of depressive symptoms was detected at the first stage of tertiary education (OR 0.60; 95% CI 0.55-0.65; p<0.001; relative to no education). Central and Eastern Europe showed the strongest association (OR for high vs. low education 0.37; 95% CI 0.33-0.40; p<0.001) and Scandinavia the weakest (OR for high vs. low education 0.69; 95% CI 0.60-0.80; p<0.001). The association was strongest amongst younger individuals. There was a sex and education interaction only within Central and Eastern Europe. Conclusion: The level of EA is reflected in later-life depressive symptoms, suggesting that supporting individuals in achieving EA, and considering those with lower EA at increased risk for depression, could lead to the decreased burden of depression across the life course. Further educational support in Central and Eastern Europe may decrease the higher burden of depressive symptoms in women.

Keywords: depression, education, epidemiology, Europe

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Authors: Rosa Buxeda, Lorenzo Saliceti-Piazza, Rodolfo J. Romañach, Luis Ríos, Sandra L. Maldonado-Ramírez

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Biopharmaceuticals manufacturing is one of the major economic activities worldwide. Ninety-three percent of the workforce in a biomanufacturing environment concentrates in production-related areas. As a result, strategic collaborations between industry and academia are crucial to ensure the availability of knowledgeable workforce needed in an economic region to become competitive in biomanufacturing. In the past decade, our institution has been a key strategic partner with multinational biotechnology companies in supplying science and engineering graduates in the field of industrial biotechnology. Initiatives addressing all levels of the educational pipeline, from K-12 to college to continued education for company employees have been established along a ten-year span. The Amgen BioTalents Program was designed to provide undergraduate science and engineering students with training in biomanufacturing. The areas targeted by this educational program enhance their academic development, since these topics are not part of their traditional science and engineering curricula. The educational curriculum involved the process of producing a biomolecule from the genetic engineering of cells to the production of an especially targeted polypeptide, protein expression and purification, to quality control, and validation. This paper will report and describe the implementation details and outcomes of the first sessions of the program.

Keywords: biomanufacturing curriculum, interdisciplinary learning, workforce development, industry-academia partnering

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Authors: David Pham, Yongfeng Zhang

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Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

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Authors: Dominique Parrish

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Globally, higher education institutions are responsible for the quality assurance and accreditation of their educational programmes (Courses). The primary purpose of these activities is to ensure that the educational standards of the governing higher education authority are met and the quality of the education provided to students is assured. Despite policies and frameworks being established in many countries, to improve the veracity and accountability of quality assurance and accreditation processes, there are reportedly still mistakes, gaps and deficiencies in these processes. An analysis of Australian universities’ quality assurance and accreditation processes noted that significant improvements were needed in managing these processes and ensuring that review recommendations were implemented. It has also been suggested that the following principles are critical for higher education quality assurance and accreditation to be effective and sustainable: academic standards and performance outcomes must be defined, attainable and monitored; those involved in providing the higher education must assume responsibility for the associated quality assurance and accreditation; potential academic risks must be identified and management solutions developed; and the expectations of the public, governments and students should be considered and incorporated into Course enhancements. This phenomenological study, which was conducted in a Faculty of Science, Medicine and Health in an Australian university, sought to systematically and iteratively develop an effective quality assurance and accreditation process that integrated the evidence-based principles of success and promoted meaningful and sustainable change. Qualitative evaluative feedback was gathered, over a period of eleven months (January - November 2014), from faculty staff engaged in the quality assurance and accreditation of forty-eight undergraduate and postgraduate Courses. Reflexive analysis was used to analyse the data and inform ongoing modifications and developments to the assurance and accreditation process as well as the associated supporting resources. The study resulted in the development of a formal quality assurance and accreditation process together with a suite of targeted resources that were identified as critical for success. The research findings also provided some insights into the institutional enablers that were antecedents to successful quality assurance and accreditation processes as well as meaningful change in the educational practices of academics. While longitudinal data will be collected to further assess the value of the assurance and accreditation process on educational quality, early indicators are that there has been a change in the pedagogical perspectives and activities of academic staff and growing momentum to explore opportunities to further enhance and develop Courses. This presentation will explain the formal quality assurance and accreditation process as well as the component parts, which resulted from this study. The targeted resources that were developed will be described, the pertinent factors that contributed to the success of the process will be discussed and early indicators of sustainable academic change as well as suggestions for future research will be outlined.

Keywords: academic standards, quality assurance and accreditation, phenomenological study, process, resources

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Authors: Shabnam

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The purpose of this study was to see importance of successful intelligence in education which can enhance achievement. There are a number of researches which have tried to apply psychological theories of education and many researches emphasized the role of thinking and intelligence. While going through the various researches, it was found that many students could learn more effectively than they do, if they were taught in a way that better matched their patterns of abilities. Attempts to apply psychological theories to education can falter on the translation of the theory into educational practice. Often, this translation is not clear. Therefore, when a program does not succeed, it is not clear whether the lack of success was due to the inadequacy of the theory or the inadequacy of the implementation of the theory. A set of basic principles for translating a theory into practice can help clarify just what an educational implementation should (and should not) look like. Sternberg’s theory of successful intelligence; analytical, creative and practical intelligence provides a way to create such a match. The results suggest that theory of successful intelligence provides successful interventions in classrooms and provides a proven model for gifted education. This article presents principles for translating a triarchic theory of successful intelligence into educational practice.

Keywords: successful intelligence, analytical, creative and practical intelligence, achievement, success, resilience

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Authors: Oluwaponmile D. Alao

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In this paper, two models have been developed to ascertain the best network needed for diagnosis of breast cancer. Breast cancer has been a disease that required the attention of the medical practitioner. Experience has shown that misdiagnose of the disease has been a major challenge in the medical field. Therefore, designing a system with adequate performance for will help in making diagnosis of the disease faster and accurate. In this paper, two models: backpropagation neural network and support vector machine has been developed. The performance obtained is also compared with other previously obtained algorithms to ascertain the best algorithms.

Keywords: breast cancer, data mining, neural network, support vector machine

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Authors: Pastraporn Thipayasothorn, Vipawan Tadapratheep, Jintana Nokyoo

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A physical realization of good environmental governance about an environmental principle, educational psychology and architecture in the three King Mongkut's Institutes of Technology, is generated for researching physical environmental factors which related to the good environmental governance, communication between the good environmental governance and a physical environmental, and a physical environmental design policy. Moreover, we collected data by a survey, observation and questionnaire that participants are students of the three King Mongkut's Institutes of Technology, and analyzed a relationship between a building utilization and the good environmental governance awareness. We found that, from the data analysis, a balance and creativity participation which played as the project users and communities of the good governance environmental promotion in the institutes helps the good governance and environmental development in the future.

Keywords: built environment, good governance, environmental governance, physical environmental

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Authors: Perpetual Nwakaego Ibe

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The Millennium Development Goals (MDGs), were an integrated project formed to eradicate many unnatural situations the citizens of the third world country may found themselves in. The MDGs, to be a sustainable project for the future depends 100% on the actions of governments, multilateral institutions and civil society. This paper first looks at the political views on the MDGs and relates it to the current electoral situations around the country by underlining the drastic changes over the few months. The second part of the paper presents ICT in tertiary institutions as one of the solutions in terms of the success of the MDGs. ICT is vital in all phases of educational process and development of the cloud connectivity is an added advantage of Information and Communication Technology (ICT) for sharing a common data bank for research purposes among UNICEF, RED CROSS, NPS, INEC, NMIC, and WHO. Finally, the paper concludes with areas that needs twigging and recommendations for the tertiary institutions committed to delivering an ambitious set of goals. A combination of observation, and document materials for data gathering was employed as the methodology for carrying out this research.

Keywords: MDG, ICT, data bank, database

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Authors: Wiem Ben Khalifa, Dalila Souilem, Mahmoud Neji

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The evolutions of Social Web and Semantic Web lead us to ask ourselves about the way of supporting the personalization of learning by means of intelligent filtering of educational resources published in the digital networks. We recommend personalized courses of learning articulated around a first educational course defined upstream. Resuming the context and the stakes in the personalization, we also suggest anchoring the personalization of learning in a community of interest within a group of learners enrolled in the same training. This reflection is supported by the display of an active and semantic system of learning dedicated to the constitution of personalized to measure courses and in the due time.

Keywords: Semantic Web, semantic system, ontology, evaluation, e-learning

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Authors: Ryan Chalk, G. M. Shafiullah

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Climate change is a pertinent issue facing governments and societies around the world. The industrial revolution has resulted in a steady increase in the average global temperature. The mining and energy production industries have been significant contributors to this change prompting government to intervene by promoting low emission technology within these sectors. This paper initially reviews the energy problem in Australia and the mining sector with a focus on the energy requirements and production methods utilised in Western Australia (WA). Renewable energy in the form of utility-scale solar photovoltaics (PV) provides a solution to these problems by providing emission-free energy which can be used to supplement the existing natural gas turbines in operation at the proposed site. This research presents a custom renewable solution for the mining site considering the specific township network, local weather conditions, and seasonal load profiles. A summary of the required PV output is presented to supply slightly over 50% of the towns power requirements during the peak (summer) period, resulting in close to full coverage in the trench (winter) period. Dig Silent Power Factory Software has been used to simulate the characteristics of the existing infrastructure and produces results of integrating PV. Large scale PV penetration in the network introduce technical challenges, that includes; voltage deviation, increased harmonic distortion, increased available fault current and power factor. Results also show that cloud cover has a dramatic and unpredictable effect on the output of a PV system. The preliminary analyses conclude that mitigation strategies are needed to overcome voltage deviations, unacceptable levels of harmonics, excessive fault current and low power factor. Mitigation strategies are proposed to control these issues predominantly through the use of high quality, made for purpose inverters. Results show that use of inverters with harmonic filtering reduces the level of harmonic injections to an acceptable level according to Australian standards. Furthermore, the configuration of inverters to supply active and reactive power assist in mitigating low power factor problems. Use of FACTS devices; SVC and STATCOM also reduces the harmonics and improve the power factor of the network, and finally, energy storage helps to smooth the power supply.

Keywords: climate change, mitigation strategies, photovoltaic (PV), power quality

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Authors: Rusudan Chagelishvili, Nino Sulava, Tamar Beridze, Nana Rezesidze, Nikoloz Tatuashvili

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The South Caucasus is one of the most important centers of prehistoric metallurgy, known for its Colchian bronze culture. Modern Lechkhumi – historical Mountainous Colchis where the existence of prehistoric metallurgy is confirmed by the discovery of many artifacts is a part of this area. Studies focused on prehistoric smelting sites, related artefacts, and ore deposits have been conducted during last ten years in Lechkhumi. More than 20 prehistoric smelting sites and artefacts associated with metallurgical activities (ore roasting furnaces, slags, crucible, and tuyères fragments) have been identified so far. Within the framework of integrated studies was established that these sites were operating in 13-9 centuries B.C. and used for copper smelting. Palynological studies of slags revealed that chestnut (Castanea sativa) and hornbeam (Carpinus sp.) wood were used as smelting fuel. Geological exploration-analytical studies revealed that copper ore mining, processing, and smelting sites were distributed close to each other. Despite recent complex data, the signs of prehistoric mines (trenches) haven’t been found in this part of the study area so far. Since 2018 the archaeological-geological exploration has been focused on the southern part of Lechkhumi and covered the areas of villages Okureshi and Opitara. Several copper smelting sites (Okureshi 1 and 2, Opitara 1), as well as a Colchian Bronze culture settlement, have been identified here. Three mine workings have been found in the narrow gorge of the river Rtkhmelebisgele in the vicinities of the village Opitara. In order to establish a link between the Opitara-Okureshi archaeometallurgical sites, Late Bronze Age settlements, and mines, various scientific analytical methods -mineralized rock and slags petrography and atomic absorption spectrophotometry (AAS) analysis have been applied. The careful examination of Opitara mine workings revealed that there is a striking difference between the mine #1 on the right bank of the river and mines #2 and #3 on the left bank. The first one has all characteristic features of the Soviet period mine working (e. g. high portal with angular ribs and roof showing signs of blasting). In contrast, mines #2 and #3, which are located very close to each other, have round-shaped portals/entrances, low roofs, and fairly smooth ribs and are filled with thick layers of river sediments and collapsed weathered rock mass. A thorough review of the publications related to prehistoric mine workings revealed some striking similarities between mines #2 and #3 with their worldwide analogues. Apparently, the ore extraction from these mines was conducted by fire-setting applying primitive tools. It was also established that mines are cut in Jurassic mineralized volcanic rocks. Ore minerals (chalcopyrite, pyrite, galena) are related to calcite and quartz veins. The results obtained through the petrochemical and petrography studies of mineralized rock samples from Opitara mines and prehistoric slags are in complete correlation with each other, establishing the direct link between copper mining and smelting within the study area. Acknowledgment: This work was supported by the Shota Rustaveli National Science Foundation of Georgia (grant # FR-19-13022).

Keywords: archaeometallurgy, Mountainous Colchis, mining, ore minerals

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Authors: Laila Jeebodh Desai

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Storytelling as a therapeutic intervention entails the narrating of events by externalising emotions, thoughts and responses to life-changing events such as loss and grief. This creates the opportunity for clients to engage with psychologists by projecting various beliefs and challenges, such as grief, through a range of therapeutic modalities. This study conducts an inquiry into the ways in which storytelling can be utilised by educational psychologists with adolescent clients to address behavioural challenges relating to grief. This qualitative study therefore aims to facilitate an understanding of the use and benefits of storytelling as a therapeutic intervention. This has been achieved by examining interviews with four educational psychologists who have utilised storytelling as a therapeutic intervention with adolescent clients to overcome challenges with grief. The participants (educational psychologists) discussed case studies during interviews, which provided evidence of their practical administration of storytelling as a therapeutic intervention incorporating integrated theoretical approaches through the use of blended therapeutic techniques. Behavioural challenges relating to grief were also predominant in the case study information provided by the participants. The participants further confirmed that the term ‘grief’ included different types of loss that were experienced among adolescent clients. The implications and recommendations of the findings encouraged the utilisation of storytelling as a therapeutic intervention with adolescent clients in addressing behavioural challenges related to grief, based on the outcome of the case studies discussed by the participants.

Keywords: storytelling, therapeutic intervention, adolescents, grief

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Authors: C. F. Jones Couto, L. C. Motlhaolwa, K. Williams

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This article explores the re-imagining of physical education teacher education in South African higher education. Utilising student reflections from a physical education practical module, valuable insights into student experiences were obtained about the current physical education pedagogical approaches and potential areas for improvement. The traditional teaching model of physical education is based on the idea of teaching students a variety of sports and physical activities. However, this model has been shown to be ineffective in promoting lifelong physical activity. The modern world demands a more holistic approach to health and wellness. Data was collected using the arts-based collage method in combination with written group reflections from 139 second-year undergraduate physical education students. This study employed thematic analysis methods to gain a comprehensive understanding of the data and extract a broader perspective on the students' experiences. The study aimed to empower student teachers to learn, think, and act creatively within the many educational models that impact their experience, contributing to the ongoing efforts of re-imagining physical education teacher education in South African higher education. This research is significant as the students' valuable insights reflected that they can think and work across disciplines. Sustainable development goals and graduate attributes are important concepts that can contribute to student preparation. Using a multi-model educational approach based on the cultural-historical theory, higher education institutions can help develop graduate attributes that will prepare students for success in the workplace and life.

Keywords: holistic education, graduate attributes, physical education, teacher education, student experiences, sustainable development goals

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Authors: Sergio Paez Moncaleano, Alvaro Mauricio Montenegro

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This paper presents a novel statistical methodology for measuring and founding constructs in Latent Regression Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations on Item Response Theory (IRT). In addition, based on the fundamentals of submodel theory and with a convergence of many ideas of IRT, we propose an algorithm not just to solve the dimensionality problem (nowadays an open discussion) but a new research field that promises more fear and realistic qualifications for examiners and a revolution on IRT and educational research. In the end, the methodology is applied to a set of real data set presenting impressive results for the coherence, speed and precision. Acknowledgments: This research was financed by Colciencias through the project: 'Multidimensional Item Response Theory Models for Practical Application in Large Test Designed to Measure Multiple Constructs' and both authors belong to SICS Research Group from Universidad Nacional de Colombia.

Keywords: item response theory, dimensionality, submodel theory, factorial analysis

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Authors: Annapureddy Srikant Reddy, Atthanti Mahendra, Samala Chinni Krishna, N. Neelima

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In our present world, we are generating a lot of data and we, need a specific device to store all these data. Generally, we store data in pen drives, hard drives, etc. Sometimes we may loss the data due to the corruption of devices. To overcome all these issues, we implemented a cloud space for storing the data, and it provides more security to the data. We can access the data with just using the internet from anywhere in the world. We implemented all these with the java using Net beans IDE. Once user uploads the data, he does not have any rights to change the data. Users uploaded files are stored in the cloud with the file name as system time and the directory will be created with some random words. Cloud accepts the data only if the size of the file is less than 2MB.

Keywords: cloud space, AES, FTP, NetBeans IDE

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Shima Nikanjam, Badiossadat Hassanpour, Adi Irfan Che Ani

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The design process in architecture education is based upon the Learning-by-Doing method, which leads students to understand how to design by practicing rather than studying. First-year design studios, as starting educational stage, provide integrated knowledge and skills of design for newly jointed architecture students. Within the basic design studio environment, students are guided to transfer their abstract thoughts into visual concrete decisions under the supervision of design educators for the first time. Therefore, introductory design studios have predominant impacts on students’ operational thinking and designing. Architectural design thinking is quite different from students’ educational backgrounds and learning habits. This educational challenge at basic design studios creates a severe need to study the reality of design education at foundation year and define appropriate educational methods with convenient project types with the intention of enhancing architecture education quality. Material for this study has been gathered through long-term direct observation at a first year second semester design studio at the faculty of architecture at EMU (known as FARC 102), fall and spring academic semester 2014-15. Distribution of a questionnaire among case study students and interviews with third and fourth design studio students who passed through the same methods of education in the past 2 years and conducting interviews with instructors are other methodologies used in this research. The results of this study reveal a risk of a mismatch between the implemented teaching method, project type and scale in this particular level and students’ learning styles. Although the existence of such risk due to varieties in students’ profiles could be expected to some extent, recommendations can support educators to reach maximum compatibility.

Keywords: architecture education, basic design studio, educational method, forms creation skill

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