Search results for: Dunn and Dunn learning style

Authors: Peter Akayuure

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One key determinant of the quality of mathematics learning is the teacher’s ability to assess students adequately and effectively and make assessment an integral part of the instructional practices. If the mathematics teacher lacks the required literacy to perform classroom assessment roles, the true trajectory of learning success and attainment of curriculum expectations might be indeterminate. It is therefore important that educators and policymakers understand and seek ways to improve the literacy level of mathematics teachers to implement classroom assessments that would meet curriculum demands. This study employed a descriptive survey design to explore perceived levels of assessment literacy of mathematics teachers to implement classroom assessment with the school based assessment framework in Ghana. A 25-item classroom assessment inventory on teachers’ assessment scenarios was adopted, modified, and administered to a purposive sample of 48 mathematics teachers from eleven Senior High Schools. Seven other items were included to further collect data on their self-efficacy towards assessment literacy. Data were analyzed using descriptive and bivariate correlation statistics. The result shows that, on average, 48.6% of the mathematics teachers attained standard levels of assessment literacy. Specifically, 50.0% met standard one in choosing appropriate assessment methods, 68.3% reached standard two in developing appropriate assessment tasks, 36.6% reached standard three in administering, scoring, and interpreting assessment results, 58.3% reached standard four in making appropriate assessment decisions, 41.7% reached standard five in developing valid grading procedures, 45.8% reached standard six in communicating assessment results, and 36.2 % reached standard seven by identifying unethical, illegal and inappropriate use of assessment results. Participants rated their self-efficacy belief in performing assessments high, making the relationships between participants’ assessment literacy scores and self-efficacy scores weak and statistically insignificant. The study recommends that institutions training mathematics teachers or providing professional developments should accentuate assessment literacy development to ensure standard assessment practices and quality instruction in mathematics education at senior high schools.

Keywords: assessment literacy, mathematics teacher, senior high schools, Ghana

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Authors: Athira Sanjeev

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The portrayal of lesbianism in cinema has undergone significant transformations. This study explores the evolving portrayal of lesbianism in the films of French director Céline Sciamma, focusing on how her works have redefined the representation of queer women in contemporary cinema. Through an analysis of Water Lilies (2007), Tomboy (2011), and Portrait of a Lady on Fire (2019), the study investigates the ways in which Sciamma’s films diverge from traditional depictions of lesbianism in film, which often relied on either fetishization or tragedy. Instead, Sciamma adopts a quiet, minimalist style that foregrounds emotional intimacy, offering a more nuanced and authentic portrayal of lesbian relationships. Through a comparative analysis of these films, this research explores the thematic and stylistic progression of Sciamma’s portrayal of lesbianism, highlighting her commitment to centering queer female experiences. The research highlights Sciamma's commitment to focusing on the complexities of desire, identity formation, and the female gaze, particularly through her use of visual storytelling, character development, and narrative silence. Her films emphasize the fluidity of gender and sexuality, portraying lesbianism not as a fixed identity but as part of a broader spectrum of human desire. Sciamma’s nuanced approach resists the traditional marginalization of lesbian characters, allowing them to exist as individuals rather than as plot devices or objects of spectacle. This study draws from queer theory and feminist film criticism to examine how Sciamma challenges conventional heteronormative narratives, prioritizes the female gaze, and subverts traditional cinematic representations of lesbian desire. It also explores how her work contributes to a broader conversation on the representation of queerness in contemporary French cinema, challenging heteronormative paradigms and offering new possibilities for depicting female relationships on screen. By tracing the evolution of her films, this research contributes to broader discussions on LGBTQ+ visibility in cinema and the cultural significance of lesbian representation in contemporary cinema.

Keywords: female gaze, feminist film criticism, lesbianism in cinema, queer theory

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Authors: Essam Almuhsin, Ben Soh, Alice Li, Azmat Ullah

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It is widely accepted that university students must acquire new knowledge, skills, awareness, and understanding to increase opportunities for professional and personal growth. The study reveals a significant increase in users engaging in e-coaching activities and a growing need for it during the COVID-19 pandemic. The paper proposes an e-coaching methodology for higher education in Saudi Arabia to address the need for effective coaching in the current online learning environment.

Keywords: role of e-coaching, e-coaching in higher education, Saudi higher education environment, e-coaching methodology, the importance of e-coaching

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Authors: Mohsine Jebbour

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The ultimate aim of this study was to analyze a second-year baccalaureate textbook of English to see to what extent it includes elements of critical thinking. A further purpose was to assess the extent to which the teachers’ teaching practices help students develop some degree of critical thinking. The literature on critical thinking indicated that all the writers agree that critical thinking is skilled and dispositional oriented, and most of the definitions highlight the skill and disposition to select, collect, analyze and evaluate information effectively. In this study, two instruments were used, namely content analysis and questionnaire to ensure validity and reliability. The sample of this study, on the one hand, was a second year textbook of English, namely Ticket to English. The process of collecting data was carried out through designing a checklist to analyze the textbook of English. On the other hand, high school students (second baccalaureate grade) and teachers of English constituted the second sample. Two questionnaires were administered—One was completed by 28 high school teachers (18 males and10 females), and the other was completed by 51 students (26 males and 25 females) from Fez, Morocco. The items of the questionnaire tended to elicit both qualitative and quantitative data. An attempt was made to answer two research questions. One pertained to the extent to which the textbooks of English contain critical thinking elements (Critical thinking skills and dispositions, types of questions, language learning strategies, classroom activities); the second was concerned with whether the teaching practices of teachers of English help improve students’ critical thinking. The results demonstrated that the textbooks of English include elements of critical thinking, and the teachers’ teaching practices help the students develop some degree of critical thinking. Yet, the textbooks do not include problem-solving activities and media analysis and 86% of the teacher-respondents tended to skip activities in the textbooks, mainly the units dealing with Project Work and Study Skills which are necessary for enhancing critical thinking among the students. Therefore, the textbooks need to be designed around additional activities and the teachers are required to cover the units skipped so as to make the teaching of critical thinking effective.

Keywords: critical thinking, language learning strategies, language proficiency, teaching practices

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: S. B. Tende, H. L. Abubakar

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It is acknowledged that small and medium enterprises (SMEs) may encounter different ethical issues and pressures that could affect the way in which they strategize or make decisions concerning the outcome of their business. Therefore, this research aimed at assessing entrepreneurial ethics in the business of SMEs in Nigeria. Secondary data were adopted as source of corpus for the analysis. The findings conclude that a sound entrepreneurial ethics system has a significant effect on the level of performance of SMEs in Nigeria. The Nigerian Government needs to provide both guiding and physical structures; as well as learning systems that could inculcate these entrepreneurial ethics.

Keywords: culture, entrepreneurial ethics, performance, SME

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Authors: M. Shaheed Hartley

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There has been increasing pressure on education researchers and practitioners at higher education institutions to focus on the development of South Africa’s rural and peri-urban communities and improving their quality of life. Many tertiary institutions are obliged to review their outreach interventions in schools. To ensure that the support provided to schools is still relevant, a systemic evaluation of science educator needs is central to this process. These prioritised needs will serve as guide not only for the outreach projects of tertiary institutions, but also to service providers in general so that the process of addressing educators needs become coordinated, organised and delivered in a systemic manner. This paper describes one area of a broader needs assessment exercise to collect data regarding the needs of educators in a district of 45 secondary schools in the Western Cape Province of South Africa. This research focuses on the needs and challenges faced by science educators at these schools as articulated by the relevant stakeholders. The objectives of this investigation are two-fold: (1) to create a data base that will capture the needs and challenges identified by science educators of the selected secondary schools; and (2) to develop a needs profile for each of the participating secondary schools that will serve as a strategic asset to be shared with the various service providers as part of a community of practice whose core business is to support science educators and science education at large. The data was collected by a means of a needs assessment questionnaire (NAQ) which was developed in both actual and preferred versions. An open-ended questionnaire was also administered which allowed teachers to express their views. The categories of the questionnaire were predetermined by participating researchers, educators and education department officials. Group interviews were also held with the science teachers at each of the schools. An analysis of the data revealed important trends in terms of science educator needs and identified schools that can be clustered around priority needs, logistic reasoning and educator profiles. The needs database also provides opportunity for the community of practice to strategise and coordinate their interventions.

Keywords: needs assessment, science and mathematics education, evaluation, teaching and learning, South Africa

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Authors: Asmaa Abazaid, Maram Al-Ostah, Nadeen Abu-Zahra, Ruba Bawab, Refaat Abdel-Razek

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Innovation audit is defined as a tool that can be used to reflect on how the innovation is managed in an organization. The aim of this study is to audit innovation in the second top Engineering Firms in the world, and one of the Small Medium Enterprises (SMEs) companies that are working in United Arab Emirates (UAE). The obtained results are then compared with four international companies from China and Brazil. The Diamond model has been used for auditing innovation in the two companies in UAE to evaluate their innovation management and to identify each company’s strengths and weaknesses from an innovation perspective. The results of the comparison between the two companies (Jacobs and Hyper General Contracting) revealed that Jacobs has support for innovation, its innovation processes are well managed, the company is committed to the development of its employees worldwide and the innovation system is flexible. Jacobs was doing best in all innovation management dimensions: strategy, process, organization, linkages and learning, while Hyper General Contracting did not score as Jacobs in any of the innovation dimensions. Furthermore, the audit results of both companies were compared with international companies to examine how well the two construction companies in UAE manage innovation relative to SABIC (Saudi company), Poly Easy and Arnious (Brazilian companies), Huagong tools and Guizohou Yibai (Chinese companies). The results revealed that Jacobs is doing best in learning and organization dimensions, while PolyEasy and Jacobs are equal in the linkage dimension. Huagong Tools scored the highest score in process dimension among all the compared companies. However, the highest score of strategy dimension was given to PolyEasy. On the other hand, Hyper General Contracting scored the lowest in all of the innovation management dimensions. It needs to improve its management of all the innovation management dimensions with special attention to be given to strategy, process, and linkage as they got scores below 4 out of 7 comparing with other dimensions. Jacobs scored the highest in three innovation management dimensions related to the six companies. However, the strategy dimension is considered low, and special attention is needed in this dimension.

Keywords: Brazil, China, innovation audit, innovation evaluation, innovation management, Saudi Arabia, United Arab Emirates

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Authors: Mane Varosyan, Diana Tumanyan, Agnesa Martirosyan

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There are many catastrophic events that end with dire consequences, and to avoid them, people should be well-armed with the necessary information about these situations. During the last years, Serious Games have increasingly gained popularity for training people for different types of emergencies. The major discussed problem is the usage of gamification in education. Moreover, it is mandatory to understand how and what kind of gamified e-learning modules promote engagement. As the theme is emergency, we also find out people’s behavior for creating the final approach. Our proposed solution is an educational video game, “EZZRA”.

Keywords: gamification, education, emergency, serious games, game design, virtual reality, digitalisation

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Authors: Kim Alvin De Lara

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The research aimed to assess the level of acceptability of the developed activity sheets in Science 5 integrating climate change adaptation of grade 5 science teachers in the District of Pililla school year 2016-2017. In this research, participants were able to recognize and understand the importance of environmental education in improving basic education and integrating them in lessons through localization and contextualization. The researcher conducted the study to develop a material to use by Science teachers in Grade 5. It served also as a self-learning resource for students. The respondents of the study were the thirteen Grade 5 teachers teaching Science 5 in the District of Pililla. Respondents were selected purposively and identified by the researcher. A descriptive method of research was utilized in the research. The main instrument was a checklist which includes items on the objectives, content, tasks, contextualization and localization of the developed activity sheets. The researcher developed a 2-week lesson in Science 5 for 4th Quarter based on the curriculum guide with integration of climate change adaptation. The findings revealed that majority of respondents are female, 31 years old and above, 10 years above in teaching science and have units in master’s degree. With regards to the level of acceptability, the study revealed developed activity sheets in science 5 is very much acceptable. In view of the findings, lessons in science 5 must be contextualized and localized to improve to make the curriculum responds, conforms, reflects, and be flexible to the needs of the learners, especially the 21st century learners who need to be holistically and skillfully developed. As revealed by the findings, it is more acceptable to localized and contextualized the learning materials for pupils. Policy formation and re-organization of the lessons and competencies in Science must be reviewed and re-evaluated. Lessons in science must also be integrated with climate change adaptation since nowadays, people are experiencing change in climate due to global warming and other factors. Through developed activity sheets, researcher strongly supports environmental education and believes this to serve as a way to instill environmental literacy to students.

Keywords: activity sheets, climate change adaptation, contextualization, localization

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Metin Özkan

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In the last decade, Turkish higher education has been expanded dramatically. With this expansion, Turkey has come a long way in establishing an efficient system of higher education which is moving into a ‘mass’ system with institutions spanning the whole country. This expansion as a quantitative target leads to questioning the quality of higher education services. Especially, the qualities of higher education services depend on mainly quality of educators. Qualities of educators are most important in Turkish higher education system due to rapid rise in the number of universities and students. Therefore, it is seen important that reveals the portrait of ideal university teacher from the point of view student enrolled in Turkish higher education system. The purpose of this current study is to determine the portrait of ideal university teacher according to the views of Turkish Students. This research is carried out with descriptive scanning method and combined and mixed of qualitative and quantitative methodologies. Research data of qualitative section were collected at Gaziantep University with the participation of 45 students enrolled in 15 different faculties. Quantitative section was performed on 217 students. The data were obtained through semi-structured interview and “Ideal University Teacher Assessment” form developed by the researcher. The interview form consists of basically two parts. The first part of the interview was about personal information, the second part included questions about the characteristic of ideal university teacher. The questions which constitute the second part of the interview are; "what is a good university teacher like?” and “What human qualities and professional skills should a university teacher have? ". Assessment form which was created from the qualitative data obtained from interviews was used to attain scaling values for pairwise comparison and ranking judgment. According to study results, it has been found that ideal university teacher characteristics include the features like patient, tolerant, comprehensive and tolerant. Ideal university teacher, besides, implement the teaching methods like encouraging the students’ critical thinking, accepting the students’ recommendations on how to conduct the lesson and making use of the new technologies etc. Motivating and respecting the students, adopting a participative style, adopting a sincere way of manner also constitute the ideal university features relationships with students.

Keywords: faculty, higher education, ideal university teacher, teacher behavior

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Madrine King'endo

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This study dealt with the influence of spelling errors on English language performance among learners with dysgraphia in public primary schools in West Embu, Embu County, Kenya. The study purposed to investigate the influence of spelling errors on the English language performance among the class three pupils with dysgraphia in public primary schools. The objectives of the study were to identify the spelling errors that learners with dysgraphia make when writing English words and classify the spelling errors they make. Further, the study will establish how the spelling errors affect the performance of the language among the study participants, and suggest the remediation strategies that teachers could use to address the errors. The study could provide the stakeholders with relevant information in writing skills that could help in developing a responsive curriculum to accommodate the teaching and learning needs of learners with dysgraphia, and probably ensure training of teachers in teacher training colleges is tailored within the writing needs of the pupils with dysgraphia. The study was carried out in Embu county because the researcher did not find any study in related literature review concerning the influence of spelling errors on English language performance among learners with dysgraphia in public primary schools done in the area. Moreover, besides being relatively populated enough for a sample population of the study, the area was fairly cosmopolitan to allow a generalization of the study findings. The study assumed the sampled schools will had class three pupils with dysgraphia who exhibited written spelling errors. The study was guided by two spelling approaches: the connectionist stimulation of spelling process and orthographic autonomy hypothesis with a view to explain how participants with learning disabilities spell written words. Data were collected through interviews, pupils’ exercise books, and progress records, and a spelling test made by the researcher based on the spelling scope set for class three pupils by the ministry of education in the primary education syllabus. The study relied on random sampling techniques in identifying general and specific participants. Since the study used children in schools as participants, voluntary consent was sought from themselves, their teachers and the school head teachers who were their caretakers in a school setting.

Keywords: dysgraphia, writing, language, performance

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Authors: Dong Seop Lee, Byung Sik Kim

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In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

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Authors: Ahmed Makhoukh

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Quality assurance (QA) has recently become a common practice, which is endorsed by most Higher Education (HE) institutions worldwide, due to the pressure of internal and external forces. One of the aims of this quality movement is to make the contribution of university education to socio-economic development highly significant. This entails that graduates are currently required have a high-quality profile, i.e., to be competent and master the 21st-century skills needed in the labor market. This wave of change, mostly imposed by globalization, has the effect that university education should be learner-centered in order to satisfy the different needs of students and meet the expectations of other stakeholders. Such a shift of focus on the student learning outcomes has led HE institutions to reconsider their strategic planning, their mission, the curriculum, the pedagogical competence of the academic staff, among other elements. To ensure that the overall institutional performance is on the right way, a QA system should be established to assume this task of checking regularly the extent to which the set of standards of evaluation are strictly respected as expected. This operation of QA has the advantage of proving the accountability of the institution, gaining the trust of the public with transparency and enjoying an international recognition. This is the case of Doha Institute (DI) for Graduate Studies, in Qatar, the object of the present study. The significance of this contribution is to show that the conception of quality has changed in this digital age, and the need to integrate a department responsible for QA in every HE institution to ensure educational quality, enhance learners and achieve academic leadership. Thus, to undertake the issue of QA in DI for Graduate Studies, an elite university (in the academic sense) that focuses on a small and selected number of students, a qualitative method will be adopted in the description and analysis of the data (document analysis). In an attempt to investigate the extent to which QA is achieved in Doha Institute for Graduate Studies, three broad indicators will be evaluated (input, process and learning outcomes). This investigation will be carried out in line with the UK Quality Code for Higher Education represented by Quality Assurance Agency (QAA).

Keywords: accreditation, higher education, quality, quality assurance, standards

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Authors: Rossella Resi

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This paper describes a project carried out in an Italian school with English learning pupils combining three didactic tools which are attested to be relevant for the success of young learner’s language curriculum: the use of technology, the intralingual and interlingual mediation (according to CEFR) and the cultural dimension. Aim of this project was to test a technological hands-on translation activity like subtitling in a formal teaching context and to exploit its potential as motivational tool for developing listening and writing, translation and cross-cultural skills among language learners. The activities proposed involved the use of professional subtitling software called Aegisub and culture-specific films. The workshop was optional so motivation was entirely based on the pleasure of engaging in the use of a realistic subtitling program and on the challenge of meeting the constraints that a real life/work situation might involve. Twelve pupils in the age between 16 and 18 have attended the afternoon workshop. The workshop was organized in three parts: (i) An introduction where the learners were opened up to the concept and constraints of subtitling and provided with few basic rules on spotting and segmentation. During this session learners had also the time to familiarize with the main software features. (ii) The second part involved three subtitling activities in plenum or in groups. In the first activity the learners experienced the technical dimensions of subtitling. They were provided with a short video segment together with its transcription to be segmented and time-spotted. The second activity involved also oral comprehension. Learners had to understand and transcribe a video segment before subtitling it. The third activity embedded a translation activity of a provided transcription including segmentation and spotting of subtitles. (iii) The workshop ended with a small final project. At this point learners were able to master a short subtitling assignment (transcription, translation, segmenting and spotting) on their own with a similar video interview. The results of these assignments were above expectations since the learners were highly motivated by the authentic and original nature of the assignment. The subtitled videos were evaluated and watched in the regular classroom together with other students who did not take part to the workshop.

Keywords: ICT, L2, language learning, language mediation, subtitling

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Authors: Derek O Reilly, Piotr Milczarski, Shane Dowdall, Artur Hłobaż, Krzysztof Podlaski, Hiram Bollaert

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Learning through creation of contextual games is a very promising way/tool for interdisciplinary and international group projects. During 2013 and 2014 we took part and organized two intensive students projects in different conditions. The projects enrolled 68 students and 12 mentors from 5 countries. In the paper we want to share our experience how to strengthen the chances to succeed in short (12-15 days long) student projects. In our case almost all teams prepared working prototype and the results were highly appreciated by external experts.

Keywords: contextual games, mobile games, GGULIVRR, walkabout, Erasmus intensive programme

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Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Omneya Messallam, Sara S. Fouad

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The Modernist Movement initially flourished in France, Holland, Germany and the Soviet Union. Many architects and designers were inspired and followed its principles. Two of its most important architects (Gerrit Rietveld and Ludwig Mies van de Rohe) were introduced in this paper. Each did not follow the other’s principles and had their own particular rules; however, they shared the same features of the Modernist International Style, such as Anti-historicism, Abstraction, Technology, Function and Internationalism/ Universality. Key Modernist principles translated into high expectations, which sometimes did not meet the inhabitants’ aspirations of living comfortably; consequently, leading to a conflict and misunderstanding between the designer and their clients’ needs. Therefore, historical case studies (the Schroder and the Farnsworth houses) involving two Modernist pioneer architects have been chosen. This paper is an attempt to explore some of the influential factors affecting buildings design such as: needs, gender, and question concerning commonalities between both designers and their clients. The three aspects and two designers explored here have been chosen because they have been influenced the researchers to understand the impact of those factors on the design process, building’s performance, and the dweller’s satisfaction. This is a descriptive/ analytical research based on two historical comparative case studies that involve several steps such as: key evaluation questions (KEQs), observations, document analysis, etc. The methodology is based on data collation and finding validations. The research aims to state a manifest to regulate the relation between architects and their clients to reach the optimum building performance and functional interior design that suits their clients’ needs, reflects the architects’ character, and the school they belong to. At the end, through the investigation in this paper, the different needs between both the designers and the clients have been seen not only in the building itself but also it could convert the inhabitant’s life in various ways. Moreover, a successful relationship between the architect and their clients could play a significant role in the success of projects. In contrast, not every good design or celebrated building could end up with a successful relationship between the designer and their client or full-fill the inhabitant’s aspirations.

Keywords: architect’s character, building’s performance, commonalities, client’s character, gender, modernist movement, needs

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Authors: Victor Abu

Abstract:

Background: Social justice ideals are considered as the foundation of nursing practice. These ideals are not always clearly integrated into nursing professional standards or curricula. This hinders concerted global nursing agendas for becoming aware of social injustice or engaging in action for social justice to improve the health of individuals and groups. Aim and objectives: The aim was to create an educational framework for empowering nursing students for social justice awareness and action. This purpose was attained by understanding the meaning of social justice, the effect of social injustice, the visibility of social justice learning, and ways of integrating social justice in nursing education and practice. Methods: Critical interpretive methodologies and constructivist grounded theory research designs guided the processes of recruiting nursing students (n = 11) and nurse educators (n = 11) at a London nursing university to participate in interviews and focus groups, which were analysed by coding systems. Findings: Firstly, social justice was described as ethical practices that enable individuals and groups to have good access to health resources. Secondly, social injustice was understood as unfair practices that caused minimal access to resources, social deprivation, and poor health. Thirdly, social justice learning was considered to be invisible in nursing education due to a lack of explicit modules, educator knowledge, and organisational support. Lastly, explicit modules, educating educators, and attracting leaders’ support were suggested as approaches for the visible integration of social justice in nursing education and practice. Discussion: This research proposes approaches for nursing awareness and action for the development of critical active nurse-learner, critical conscious nurse-educator, and servant nurse leader. The framework on Awareness for Social Justice Action (ASJA) created in this research is an approach for empowering nursing students for social justice practices. Conclusion: This research contributes to and advocates for greater nursing scholarship to raise the spotlight on social justice in the profession.

Keywords: social justice, nursing practice, nursing education, nursing curriculum, social justice awareness, social justice action, constructivist grounded theory

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Authors: C. Fortin, D. Tokmeninova, O. Ushakova

Abstract:

Among 500 Russian universities Skolkovo Institute of Science and Technology (Skoltech) is one of the youngest (established in 2011), quite small and vastly international, comprising 20 percent of international students and 70 percent of faculty with significant academic experience at top-100 universities (QS, THE). The institute has emerged from close collaboration with MIT and leading Russian universities. Skoltech is an entirely English speaking environment. Skoltech curriculum plans of ten Master programs are based on the CDIO learning outcomes model. However, despite the Institute’s unique focus on industrial innovations and startups, one of the main challenges has become an evident large proportion of nearly half of MSc graduates entering PhD programs at Skoltech or other universities rather than industry or entrepreneurship. In order to increase the share of students joining the industrial sector after graduation, Skoltech started implementing a number of unique practices with a focus on employers’ expectations incorporated into the curriculum redesign. In this sense, extended knowledge exchange with industrial partners via collaboration in learning activities, industrial projects and assessments became essential for students’ headway into industrial and entrepreneurship pathways. Current academic curriculum includes the following types of components based on extended knowledge exchange with industrial partners: innovation workshop, industrial immersion, special industrial tracks, MSc defenses. Innovation workshop is a 4 week full time diving into the Skoltech vibrant ecosystem designed to foster innovators, focuses on teamwork, group projects, and sparks entrepreneurial instincts from the very first days of study. From 2019 the number of mentors from industry and startups significantly increased to guide students across these sectors’ demands. Industrial immersion is an exclusive part of Skoltech curriculum where students after the first year of study spend 8 weeks in an industrial company carrying out an individual or team project and are guided jointly by both Skoltech and company supervisors. The aim of the industrial immersion is to familiarize students with relevant needs of Russian industry and to prepare graduates for job placement. During the immersion a company plays the role of a challenge provider for students. Skoltech has started a special industrial track comprising deep collaboration with IPG Photonics – a leading R&D company and manufacturer of high-performance fiber lasers and amplifiers for diverse applications. The track is aimed to train a new cohort of engineers and includes a variety of activities for students within the “Photonics” MSc program. It is expected to be a successful story and used as an example for similar initiatives with other Russian high-tech companies. One of the pathways of extended knowledge exchange with industrial partners is an active involvement of potential employers in MSc Defense Committees to review and assess MSc thesis projects and to participate in defense procedures. The paper will evaluate the effect and results of the above undertaken measures.

Keywords: Curriculum redesign, knowledge exchange model, learning outcomes framework, stakeholder engagement

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Authors: Camille Deprez

Abstract:

This paper proposes to present research findings of an ongoing Hong Kong government-funded project on ‘The Documentary Film in India (1948-1975)’ (GRF 1240314), for which an extensive research fieldwork has been carried out in various archives in India. This project investigates the role and significance of the Indian documentary film sector from the inauguration of the state-sponsored Films Division one year after independence in 1948 until the declaration of a ‘State of Emergency’ in 1975. The documentary film production of this first period of national independence was characterised by increasing formal experimentation and analytical social and political enquiry, and by a complex, mixed structure of state-sponsored monopoly and free-market operation. However, that production remains significantly under-researched. What were the main production, distribution and exhibition strategies over this period? What were the recurrent themes and stylistic features of the films produced? In the new context of national independence (in which the State considered film as means of mass persuasion), consolidation of the commercial film, and the emergence of television and art cinema, what role did official, professional and creative factors play in the development of the documentary film sector? What were the impact of such films and the challenges faced by the documentary film in India? Based upon the crossed-analysis of primary written research documents, interviews and relevant films, this study interweaves empirical study of the sector's financing, production, distribution and exhibition strategies, as well as the films' content and form, with the larger historical context of India over the period from 1948 to 1975. Whilst most of the films made within the sector explored social issues, they were rarely able to do so from an overtly critical perspective. However, this paper proposes to analyse the contribution of important filmmakers and producers, including Ezra Mir, Paul Zils, Jean Bhownagary, S. Sukhdev, S. N. S. Sastri, and P. Pati, to the development of the Indian documentary film sector and style within and outside the remits of Films Division. It will more specifically assess the extent to which they criticised the State, showed the inequalities in Indian society and explored film form.

Keywords: documentary film, film archives, film history, India

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Authors: Fusun Akdag

Abstract:

Today, as business becomes increasingly global, managers/leaders of multinational companies or local companies work with employees or customers from a variety of cultural backgrounds. To do this effectively, they need to develop cultural competence. Therefore, cultural intelligence (CQ) becomes a vitally important aptitude and skill, especially for leaders. The organizational success or failure depends upon the way, the kind of leadership which has been provided to its members. The culture we are born into deeply effects our values, beliefs, and behavior. Cultural intelligence (CQ) focuses on how well individuals can relate and work across cultures. CQ helps minimize conflict and maximize performance of a diverse workforce. The term 'decision,' refers to a commitment to a course of action that is intended to serve the interests and values of particular people. One dimension of culture that has received attention is individualism-collectivism or, independence-interdependence. These dimensions are associated with different conceptualizations of the 'self.' Individualistic cultures tend to value personal goal pursuit as opposed to pursuit of others’ goals. Collectivistic cultures, by contrast, view the 'self' as part of a whole. Each person is expected to work with his or her in-group toward goals, generally pursue group harmony. These differences underlie cross-cultural variation in decision-making, such as the decision modes people use, their preferences, negotiation styles, creativity, and more. The aim of this study is determining the effect of CQ on decision making styles of male and female managers in Turkey, an emergent economy framework. The survey is distributed to gather data from managers at various companies. The questionnaire consists of three parts: demographics, The Cultural Intelligence Scale (CQS) to measure the four dimensions of cultural intelligence and General Decision Making Style (GMDS) Inventory to measure the five subscales of decision making. The results will indicate the Turkish managers’ score at metacognitive, cognitive, motivational and behavioral aspects of cultural intelligence and to what extent these scores affect their rational, avoidant, dependent, intuitive and spontaneous decision making styles since business leaders make dozens of decisions every day that influence the success of the company and also having an impact on employees, customers, shareholders and the market.

Keywords: cultural intelligence, decision making, gender differences, management styles,

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Authors: Alvaro L. Ronco

Abstract:

Background and purpose: Although our country is a developing one, it has a typical Western meat-rich dietary style. Based on estimates of heme and nonheme iron contents in representative foods, we carried out the present epidemiologic study, with the aim of accurately analyzing dietary iron and its role on CRC risk. Subjects/methods: Patients (611 CRC incident cases and 2394 controls, all belonging to public hospitals of our capital city) were interviewed through a questionnaire including socio-demographic, reproductive and lifestyle variables, and a food frequency questionnaire of 64 items, which asked about food intake 5 years before the interview. The sample included 1937 men and 1068 women. Controls were matched by sex and age (± 5 years) to cases. Food-derived nutrients were calculated from available databases. Total dietary iron was calculated and classified by heme or nonheme source, following data of specific Dutch and Canadian studies, and additionally adjusted by energy. Odds Ratios (OR) and 95% confidence intervals were calculated through unconditional logistic regression, adjusting for relevant potential confounders (education, body mass index, family history of cancer, energy, infusions, and others). A heme/nonheme (H/NH) ratio was created and the interest variables were categorized into tertiles, for analysis purposes. Results: The following risk estimations correspond to the highest tertiles. Total iron intake showed no association with CRC risk neither among men (OR=0.83, ptrend =.18) nor among women (OR=1.48, ptrend =.09). Heme iron was positively associated among men (OR=1.88, ptrend < .001) and for the overall sample (OR=1.44, ptrend =.002), however, it was not associated among women (OR=0.91, ptrend =.83). Nonheme iron showed an inverse association among men (OR=0.53, ptrend < .001) and the overall sample (OR=0.78, ptrend =.04), but was not associated among women (OR=1.46, ptrend =.14). Regarding H/NH ratio, risks increased only among men (OR=2.12, ptrend < .001) but lacked of association among women (OR=0.81, ptrend =.29). Conclusions. We have observed different types of associations between CRC risk and high dietary heme, nonheme and H/NH iron ratio. Therefore, the source of the available iron might be of importance as a link to colorectal carcinogenesis, perhaps pointing to reconsider the animal/plant proportions of this vital mineral within diet. Nevertheless, the different associations observed for each sex, demand further studies in order to clarify these points.

Keywords: chelation, colorectal cancer, heme, iron, nonheme

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Authors: C. E. Laburu, M. A. Barros, A. F. Zompero, O. H. M. Silva

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The work presents a teaching strategy that employs syntagmatic and paradigmatic linguistic relations in order to monitor the understanding of physics students’ concepts. Syntagmatic and paradigmatic relations are theoretical elements of semiotics studies and our research circumstances and justified them within the research program of multi-modal representations. Among the multi-modal representations to learning scientific knowledge, the scope of action of syntagmatic and paradigmatic relations belongs to the discursive writing form. The use of such relations has the purpose to seek innovate didactic work with discourse representation in the write form before translate to another different representational form. The research was conducted with a sample of first year high school students. The students were asked to produce syntagmatic and paradigmatic of Newton’ first law statement. This statement was delivered in paper for each student that should individually write the relations. The student’s records were collected for analysis. It was possible observed in one student used here as example that their monemes replaced and rearrangements produced by, respectively, syntagmatic and paradigmatic relations, kept the original meaning of the law. In paradigmatic production he specified relevant significant units of the linguistic signs, the monemas, which constitute the first articulation and each word substituted kept equivalence to the original meaning of original monema. Also, it was noted a number of diverse and many monemas were chosen, with balanced combination of grammatical (grammatical monema is what changes the meaning of a word, in certain positions of the syntagma, along with a relatively small number of other monemes. It is the smallest linguistic unit that has grammatical meaning) and lexical (lexical monema is what belongs to unlimited inventories; is the monema endowed with lexical meaning) monemas. In syntagmatic production, monemas ordinations were syntactically coherent, being linked with semantic conservation and preserved number. In general, the results showed that the written representation mode based on linguistic relations paradigmatic and syntagmatic qualifies itself to be used in the classroom as a potential identifier and accompanist of meanings acquired from students in the process of scientific inquiry.

Keywords: semiotics, language, high school, physics teaching

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Authors: Nabeel Mohammed Ali

Abstract:

Background and significance of the study: This study focuses on the experiences, perspectives, and issues of the working-class Aboriginals and immigrants in Australia. In addition to dealing with their lives, struggles, and aspirations of working-class people, poetry of labor presents an insight into a neglected literary writing that goes beyond the social discourse of class distinction. In this contemporary context, it explores a broader spectrum of challenges and experiences, such as the complexities of modern labor, immigration, indigenous rights, social justice, multiculturalism, economic inequality, advocating for workers' rights and labor movements, the impact of globalization on local industries, and the evolution of labor in the digital age. Aims of the Study: The study will try to answer the following questions: What insights does poetics of labor provide to affect the literary creation of poetry at the time, as well as whether it can create a change in the social fabric of Australian diversity? What are the main themes and issues that Aboriginal and immigrant poets address in their works? How do they reflect the realities and challenges of working-class people in Australia? How do they use language, form, and style to convey their messages and emotions? How do the poets engage with and critique the dominant narratives and ideologies of Australian society and culture? How do they challenge or resist the stereotypes, prejudices, and discrimination that they face? And how do they show solidarity or empathy with others who share similar struggles or aspirations? Methodology: The study will utilize traditional Marxist paradigms to analyze the poetry of the selected poets in the context of the evolving sociopolitical landscape of the 21st century. The Neo-Marxist literary criticism is used as a theoretical tool to analyze the texts. The concept of Power dynamics to analyze the intersectionality of race, labor and class. Findings: The poetry of contemporary Australian Aboriginal and immigrant poets labor, represents a critical, yet under-explored, discussion of the intersection of labor, class, and a multicultural identity. The study will deal with the poetry of the Aboriginal poet Ali Cobby Eckermann (1963- ) and the immigrant Chinese poet Ouyang Yu ( 1955- ).

Keywords: aboriginals, immigrants, Australia, working-class, Ali eckermann, ouyang Yu

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