Search results for: second language vocabulary learning

Authors: Vasudeva Murthy Challakere Ramaswamy

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Background: Conventionally forensic pathology is learnt through autopsy demonstrations which carry various limitations such as unavailability of cases in the mortuary, medico-legal implication and infection. Over the years forensic pathology and science has undergone significant evolution in this digital world. Forensic imaging is a technology which can be effectively utilized for overcoming the current limitations in the undergraduate learning of forensic curriculum. Materials and methods: demonstration of forensic imaging was done using a novel technology of autopsy which has been recently introduced across the globe. Three sessions were conducted in international medical university for a total of 196 medical students. The innovative educational tool was evacuated by using quantitative questionnaire with the scoring scales between 1 to 10. Results: The mean score for acceptance of new tool was 82% and about 74% of the students recommended incorporation of the forensic imaging in the regular curriculum. 82% of students were keen on collaborative research and taking further training courses in forensic imaging. Conclusion: forensic imaging can be an effective tool and also a suitable alternative for teaching undergraduate students. This feedback also supports the fact that students favour the use of contemporary technologies in learning medicine.

Keywords: forensic imaging, forensic pathology, medical students, learning tool

Procedia PDF Downloads 462

Authors: Barzan Hadi Hama Karim

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In recent years, an increasing number of faculties and colleges of basic education are established by the universities and ministry of Higher Education and Scientific Research of Iraqi Kurdistan to graduate English teachers to teach in the basic and high schools. One central consideration of this study is to what extent graduate teachers receive adequate preparation from these faculties and college of basic education. An important program which is offered in the department of English language in these colleges and faculties is Viewing and Practicing. The purpose of this research is to explore how students of basic education colleges and faculties are using the program of Viewing and Practicing to support the educational process. This study provides a general framework about educational uses of the program as a pedagogical tool to teach English Language in the basic schools and describes the different perceptions of the students at the final stage of their education. A survey is used to collect responses from a group of students to determine their expectations and perceptions about the program. The results display that the program has several aspects of strengths, such as improving English teaching and speaking proficiency, cultivating subject knowledge related to applied linguistics and promoting research engagement. The findings of the study address the following questions: Is Viewing and Practicing Program beneficial for students to experience English language for future career at schools? To what extent do the students prefer teaching English Language in the schools?

Keywords: teaching experience, viewing and practicing, perception, expectation

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Authors: Lori L. Scarlatos, Ryan Courtney

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This paper explores the impact that playing a casual game can have on a player's learning and subsequent behavior. A casual mobile game, Container Chaos, was created to teach undergraduate students about the carbon footprint of various disposable beverage containers. Learning was tested with a short quiz, and behavior was tested by observing which beverage containers players choose when offered a drink and a snack. The game was tested multiple times, under a variety of different circumstances. Findings of these tests indicate that, with extended play over time, players can learn new information and sometimes even change their behavior as a result. This has implications for how other casual games can be used to teach concepts and possibly modify behavior.

Keywords: behavior, carbon footprint, casual games, environmental impact, material sciences

Procedia PDF Downloads 139

Authors: Eny Syatriana, Ardiansyah

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The purpose of recent study was to develop a learning model on writing, based on the reading texts which will be read by the students using reflection strategy. The strategy would allow the students to read the text and then they would write back the main idea and to develop the text by using their own sentences. So, the writing practice was begun by reading an interesting text, then the students would develop the text which has been read into their writing. The problem questions are (1) what kind of learning model that can develop the students writing ability? (2) what is the achievement of the students of STKIP YPUP through reflection strategy? (3) is the using of the strategy effective to develop students competence In writing? (4) in what level are the students interest toward the using of a strategy In writing subject? This development research consisted of some steps, they are (1) need analysis (2) model design (3) implementation (4) model evaluation. The need analysis was applied through discussion among the writing lecturers to create a learning model for writing subject. To see the effectiveness of the model, an experiment would be delivered for one class. The instrument and learning material would be validated by the experts. In every steps of material development, there was a learning process, where would be validated by an expert. The research used development design. These Principles and procedures or research design and development .This study, researcher would do need analysis, creating prototype, content validation, and limited empiric experiment to the sample. In each steps, there should be an assessment and revision to the drafts before continue to the next steps. The second year, the prototype would be tested empirically to four classes in STKIP YPUP for English department. Implementing the test greatly was done through the action research and followed by evaluation and validation from the experts.

Keywords: learning model, reflection, strategy, reading, writing, development

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Authors: Lam Pham, Peter Hubber, Russell Tytler

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Students’ conceptual understandings of chemistry concepts/phenomena involve capability to coordinate across the three levels of Johnston’s triangle model. This triplet model is based on reasoning about chemical phenomena across macro, sub-micro and symbolic levels. In chemistry education, there is a need for further examining inquiry-based approaches that enhance students’ conceptual learning and problem solving skills. This research adopted a directed inquiry pedagogy based on students constructing and coordinating representations, to investigate senior school students’ capabilities to flexibly move across Johnston’ levels when learning dilution and molar concentration concepts. The participants comprise 50 grade 11 and 20 grade 10 students and 4 chemistry teachers who were selected from 4 secondary schools located in metropolitan Melbourne, Victoria. This research into classroom practices used ethnographic methodology, involved teachers working collaboratively with the research team to develop representational activities and lesson sequences in the instruction of a unit on solution chemistry. The representational activities included challenges (Representational Challenges-RCs) that used ‘representational tools’ to assist students to move across Johnson’s three levels for dilution phenomena. In this report, the ‘representational tool’ called ‘cross and portion’ model was developed and used in teaching and learning the molar concentration concept. Students’ conceptual understanding and problem solving skills when learning with this model are analysed through group case studies of year 10 and 11 chemistry students. In learning dilution concepts, students in both group case studies actively conducted a practical experiment, used their own language and visualisation skills to represent dilution phenomena at macroscopic level (RC1). At the sub-microscopic level, students generated and negotiated representations of the chemical interactions between solute and solvent underpinning the dilution process. At the symbolic level, students demonstrated their understandings about dilution concepts by drawing chemical structures and performing mathematical calculations. When learning molar concentration with a ‘cross and portion’ model (RC2), students coordinated across visual and symbolic representational forms and Johnson’s levels to construct representations. The analysis showed that in RC1, Year 10 students needed more ‘scaffolding’ in inducing to representations to explicit the form and function of sub-microscopic representations. In RC2, Year 11 students showed clarity in using visual representations (drawings) to link to mathematics to solve representational challenges about molar concentration. In contrast, year 10 students struggled to get match up the two systems, symbolic system of mole per litre (‘cross and portion’) and visual representation (drawing). These conceptual problems do not lie in the students’ mathematical calculation capability but rather in students’ capability to align visual representations with the symbolic mathematical formulations. This research also found that students in both group case studies were able to coordinate representations when probed about the use of ‘cross and portion’ model (in RC2) to demonstrate molar concentration of diluted solutions (in RC1). Students mostly succeeded in constructing ‘cross and portion’ models to represent the reduction of molar concentration of the concentration gradients. In conclusion, this research demonstrated how the strategic introduction and coordination of chemical representations across modes and across the macro, sub-micro and symbolic levels, supported student reasoning and problem solving in chemistry.

Keywords: cross and portion, dilution, Johnston's triangle, molar concentration, representations

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Authors: Sarah Smail

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Algeria has been subject to countless conquests and invasions that resulted in having a diverse linguistic repertoire. The sociolinguistic situation of the country made linguistic landscape analysis pertinent. This in fact, has led to the growth of diverse linguistic landscape studies that mainly focused on identifying the sociolinguistic situation of the country through shop names analysis. The present research adds to the existing literature by offering another perspective to the analysis of signs by combining the physical and digital semiotic landscape. The powerful oil, gas and agri-food industries in Algeria make it interesting to focus on the commodification of natural resources for the sake of identifying the language and semiotic resources deployed in the Algerian public scene in addition to the identification of the visibility of linguistic inequalities and minorities in the business domain. The study discusses the semiotic landscape of three trade cities: Bejaia, Setif and Hassi-Messaoud. In addition to interviews conducted with business owners and graphic designers and questionnaires with business employees. Withal, the study relies on Gorter’s multilingual inequalities in public space (MIPS) model (2021) and Irvine and Gal’s language ideology and linguistic differentiation (2000). The preliminary results demonstrate the sociolinguistic injustice existing in the business domain, e.g., the exclusion of the official languages, the dominance of foreign languages, and the excessive use of the roman script.

Keywords: semiotic landscaping, digital scapes, language commodification, linguistic inequalities, business signage

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Authors: Nabil El Kadhi, Minerva M. Bunagan

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The dynamism in education, particularly in the area of teaching, learning and assessment has caused Higher Education Institutions (HEIs) worldwide to seek for ways to continuously improve their educational processes. HEIs use outcomes of institutional audits, assessments and accreditations, for improvement. In this study, the published institutional audit reports of HEIs in the Sultanate of Oman were analyzed to produce features of good practice; identify challenges along Teaching, Learning Assessment (TLA); and propose a framework that puts major emphasis in having a quality-assured TLA, including a set of principles that can be used as basis in succeeding an institutional visit. The TLA framework, which shows the TLA components, characteristics of the components, related expectation, including implementation tool/ strategy and pitfalls can be used by HEIs to have an adequate understanding of the scope of audit and be able to satisfy institutional audit requirements. The scope of this study can be widened by exploring the other requirements of the Institutional Audits in the Sultanate of Oman, particularly the area on Governance and Management and Student Support Services.

Keywords: accreditation, audit, teaching, learning and assessment, quality assurance

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: Zoe Wong

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The purpose of this paper is to develop a framework for internet education. This framework uses the personalized learning approach for everyone who can freely develop their qualifications & careers. The key components of the framework includes students, teachers, assessments and infrastructure. It allows remove the challenges and limitations of the current educational system and allows learners' to cope with progressing learning materials.

Keywords: internet education, personalized approach, information technology, framework

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Authors: Arburim Iseni, Afrim Aliti, Nagri Rexhepi

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This paper focuses mainly on an important aspect of student-linguistic errors. It aims to explore the nature of Albanian intermediate level or B1 students’ language errors and mistakes and attempts to trace the possible sources or causes by classifying the error samples into both inter lingual and intra lingual errors. The hypothesis that intra lingua errors may be determined or induced somehow by the native language influence seems to be confirmed by the significant number of errors found in Albanian EFL students in the Study Program of the English Language and Literature at the State University of Tetova. Findings of this study have revealed that L1 interference first and then ignorance of the English Language grammar rules constitute the main sources or causes of errors, even though carelessness cannot be ruled out. Although we have conducted our study with 300 students of intermediate or B1 level, we believe that this hypothesis would need to be confirmed by further research, maybe with a larger number of students with different levels in order to draw more steady and accurate conclusions. The analysis of the questionnaires was done according to quantitative and qualitative research methods. This study was also conducted by taking written samples on different topics from our students and then distributing them with comments to the students and University teachers as well. These questionnaires were designed to gather information among 300 students and 48 EFL teachers, all of whom teach in the Study Program of English Language and Literature at the State University of Tetova. From the analyzed written samples of the students and face-to-face interviews, we could get useful insights into some important aspects of students’ error-making and error-correction. These different research methodologies were used in order to comprise a holistic research and the findings of the questionnaires helped us to come up with some more steady solutions in order to minimize the potential gap between students and teachers.

Keywords: L1 & L2, Linguistics, Applied linguistics, SLA, Albanian EFL students and teachers, Errors and Mistakes, Students’ Assessment and Self-Assessment

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Authors: Krishna Chandra Paudel

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This paper explores the association between the perceived classroom environment and mathematics learning and test anxiety among secondary level students in Nepal. Categorizing the students in three dominant variables- gender, ethnicity and previous schooling, and selecting sample students with respect to higher mathematics anxiety from five heterogeneous classes, the research explores disparities in student's mathematics cognition and reveals nexus between classroom environment and mathematics learning and test anxiety. This research incorporates social learning theory and social development theory as interpretive tool for analyzing themes through qualitative data. Focussing on the interviews with highly mathematics learning anxious students, the study sheds light on how mathematics anxiety among the targeted students is interlinked with multiple factors. The research basically exposes the students’ lack of mathematical passion, their association with other students and participation in classroom learning, asymmetrical content and their lack of preparedness for the tests as caustic factors behind such anxieties. The study further reveals that students’ lack of foundational knowledge and complexity of mathematical content have jointly contributed to mathematics anxiety. Admitting learning as a reciprocal experience, the study points out that the students’ gender, ethnicity and disparities in previous schooling in the context of Nepal has very insignificant impact on students’ mathematics anxiety. It finally recommends that the students who get trapped into the vicious cycle of mathematics anxiety require positive and supportive classroom environment along with inspiring comments/compliments and symmetrical course contents.

Keywords: anxiety, asymmetry, cognition, habitus, pedagogy, preparedness

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Authors: Bello Theodora O., Animola Odunayo V., Owoade Johnson T.

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With the advent of Covid-19, online classroom instruction became a very important mode of instruction delivery during which learners were engaged in both collaborative and online interactive learning process, but along with it are challenges as well as its deliverables. This study therefore investigated the various online platform used by the students for learning among fresh undergraduate students of Obafemi Awolowo University, Ile-Ife, Osun Sate. It also assessed the student’s perception towards online learning in the university and examined the influence of collaborative learning among the students. Lastly, it examined the problems that are associated with collaborative online learning instruction in the university. These were with a view to providing empirical information on problems and prospects of online classroom instruction among fresh undergraduate physical science students of Obafemi Awolowo University, Ile-Ife. The study employed a descriptive survey research technique. The population comprised all the fresh undergraduates in physical science departments of Obafemi Awolowo University, Ile-Ife. The sample consisted two hundred freshmen in physical science departments of Obafemi Awolowo University, Ile-Ife, who were selected using simple random techniques. During the selection, a questionnaire was used to collect data from the respondents. The data were analyzed using appropriate descriptive of frequency, simple percentage, and mean. Results showed that Google Meet 149(74.5%), Telegram 120(60.0%), and Google Classroom 143(71.5%), are the prominent online classroom instruction used by the students in Obafemi Awolowo University, Ile-Ife. The results also showed that the freshmen’s perception towards online classroom instruction in Obafemi Awolowo University, Ile-Ife is low with cluster mean of 2.97. It further revealed that collaborative learning enhances the learning ability of below average learners more than that of the above average and average students (73.6%). Finally, the result showed that they are affirmative of the problems associated with online classroom instruction in Obafemi Awolowo University, Ile-Ife with cluster mean of 3.01. The result concluded that most Online platform used by the fresher’s students in Obafemi Awolowo University, Ile-Ife are Google Meet, Telegram and Google Classroom. The students have negatives perception towards online classroom instruction and the students are affirmative of the problems associated with online classroom instruction among physical science freshmen in Obafemi Awolowo University, Ile-Ife.

Keywords: online, instruction, freshmen, physical science, collaborative

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Authors: A. Karunasena, P. Bandara, J. A. T. P. Jayasuriya, P. D. Gallage, J. M. S. D. Jayasundara, L. A. P. Y. P. Nuwanjaya

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Usage of smart learning concepts has increased rapidly all over the world recently as better teaching and learning methods. Most educational institutes such as universities are experimenting those concepts with their students. Smart learning concepts are especially useful for students to learn better in large classes. In large classes, the lecture method is the most popular method of teaching. In the lecture method, the lecturer presents the content mostly using lecture slides, and the students make their own notes based on the content presented. However, some students may find difficulties with the above method due to various issues such as speed in delivery. The purpose of this research is to assist students in large classes in the following content. The research proposes a solution with four components, namely note-taker, slide matcher, reference finder, and question presenter, which are helpful for the students to obtain a summarized version of the lecture note, easily navigate to the content and find resources, and revise content using questions.

Keywords: automatic summarization, extractive text summarization, speech recognition library, sentence extraction, automatic web search, automatic question generator, sentence scoring, the term weight

Procedia PDF Downloads 129

Authors: Ana C. Sanchez

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This paper will discuss some of the bilingual practices of Heritage Spanish speakers caused by living within two cultures and two languages, Spanish, the heritage language, and English, the dominant language. When two languages remain in contact for long periods, such as the case of Spanish and English, it is common that both languages can be affected by bilingual practices such as Spanglish, code-switching, borrowing, anglicisms and calques. Examples of these translingual practices will be provided, as well as HS speaker’s linguistic dialects, and the challenges they encounter with the standard variety used in the Spanish classroom.

Keywords: heritage, practices, Spanish, speakers translingual

Procedia PDF Downloads 186

Authors: M. Khaled Abduesslam, Mohammed Ali, Basher H. Alsdai, Muhammad Nizam Inayati

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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New-England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, least squares support vector machine, learning vector quantization, voltage collapse

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Authors: Peter Adly Hamdy Fahmy

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The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

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Authors: Abdul Basit Kiani, Maryam Kiani

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Online developers now have the tools necessary to create online apps that are not only reliable but also highly interactive, thanks to the introduction of JavaScript frameworks and APIs. The objective is to give a broad overview of the recent advances in the area. The fusion of machine learning (ML) and artificial intelligence (AI) has expanded the possibilities for web development. Modern websites now include chatbots, clever recommendation systems, and customization algorithms built in. In the rapidly evolving landscape of modern websites, it has become increasingly apparent that user engagement and personalization are key factors for success. To meet these demands, websites now incorporate a range of innovative technologies. One such technology is chatbots, which provide users with instant assistance and support, enhancing their overall browsing experience. These intelligent bots are capable of understanding natural language and can answer frequently asked questions, offer product recommendations, and even help with troubleshooting. Moreover, clever recommendation systems have emerged as a powerful tool on modern websites. By analyzing user behavior, preferences, and historical data, these systems can intelligently suggest relevant products, articles, or services tailored to each user's unique interests. This not only saves users valuable time but also increases the chances of conversions and customer satisfaction. Additionally, customization algorithms have revolutionized the way websites interact with users. By leveraging user preferences, browsing history, and demographic information, these algorithms can dynamically adjust the website's layout, content, and functionalities to suit individual user needs. This level of personalization enhances user engagement, boosts conversion rates, and ultimately leads to a more satisfying online experience. In summary, the integration of chatbots, clever recommendation systems, and customization algorithms into modern websites is transforming the way users interact with online platforms. These advanced technologies not only streamline user experiences but also contribute to increased customer satisfaction, improved conversions, and overall website success.

Keywords: Javascript, machine learning, artificial intelligence, web development

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Authors: Ripudaman S. Minhas, Pardeep K. Benipal, Aisha K. Yousafzai

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Background: Children of refugee or asylum-seeking background have multiple, complex needs (e.g. trauma, mental health concerns, separation, relocation, poverty, etc.) that places them at an increased risk for developing learning problems. Families encounter challenges accessing support during resettlement, preventing children from achieving their full developmental potential. There are very few studies in literature that examine the unique parenting challenges refugee families’ face. Providing appropriate support services and educational resources that address these distinctive concerns of refugee parents, will alleviate these challenges allowing for a better developmental outcome for children. Objective: To identify the characteristics of effective parenting interventions that address the unique needs of refugee families. Methods: English-language articles published from 1997 onwards were included if they described or evaluated programmes or interventions for parents of refugee or asylum-seeking background, globally. Data were extracted and analyzed according to Arksey and O’Malley’s descriptive analysis model for scoping reviews. Results: Seven studies met criteria and were included, primarily studying families settled in high-income countries. Refugee parents identified parenting to be a major concern, citing they experienced: alienation/unwelcoming services, language barriers, and lack of familiarity with school and early years services. Services that focused on building the resilience of parents, parent education, or provided services in the family’s native language, and offered families safe spaces to promote parent-child interactions were most successful. Home-visit and family-centered programs showed particular success, minimizing barriers such as transportation and inflexible work schedules, while allowing caregivers to receive feedback from facilitators. The vast majority of studies evaluated programs implementing existing curricula and frameworks. Interventions were designed in a prescriptive manner, without direct participation by family members and not directly addressing accessibility barriers. The studies also did not employ evaluation measures of parenting practices or the caregiving environment, or child development outcomes, primarily focusing on parental perceptions. Conclusion: There is scarce literature describing parenting interventions for refugee families. Successful interventions focused on building parenting resilience and capacity in their native language. To date, there are no studies that employ a participatory approach to program design to tailor content or accessibility, and few that employ parenting, developmental, behavioural, or environmental outcome measures.

Keywords: asylum-seekers, developmental pediatrics, parenting interventions, refugee families

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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Authors: Byung Ho Jung, Dong Hoon Lim

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Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. Logistic regression is used extensively in numerous disciplines, including the medical and social science fields. In this paper, we address the problem of estimating parameters in the logistic regression based on MapReduce framework with RHadoop that integrates R and Hadoop environment applicable to large scale data. There exist three learning algorithms for logistic regression, namely Gradient descent method, Cost minimization method and Newton-Rhapson's method. The Newton-Rhapson's method does not require a learning rate, while gradient descent and cost minimization methods need to manually pick a learning rate. The experimental results demonstrated that our learning algorithms using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also compared the performance of our Newton-Rhapson's method with gradient descent and cost minimization methods. The results showed that our newton's method appeared to be the most robust to all data tested.

Keywords: big data, logistic regression, MapReduce, RHadoop

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Authors: Supannee Pinmanee

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This article focuses on the strategies in the translation of terms of address for both referential and vocative functions from Thai to English from a cultural perspective. The discussion concerns the culture-specific ways in which Thai people use address terms that depend largely on social and conventional contexts, including pragmatic factors, for example, relationships between people, levels of formality, and attitudes. Examples used to illustrate the problems and proposed solutions were drawn from the media, the internet, the novels and the language used by Thai native speakers in expressing Thai address terms. The terms used in this area show very well not only the differences in language but also the different cultures and world views of the speakers of Thai and those of English. Thai has developed its own set of address terms, particularly kinship terms for non-relatives and the Thai royal terms. Some of Newmark’s procedures (1995) are used in the article to illustrate the task of translating Thai terms into English, a language that embodies a very different culture with its own set of address terms. However, no one strategy can be applied to serve all purposes and to translate all the intended senses. One particular term can be translated by several strategies, and which strategy to choose depends largely on one’s purposes and what requirement one needs to fulfill.

Keywords: translation, terms of address, Thai-English translation, Thai culture-specific terms of address, translation strategies

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Authors: Raquel P. F. Guiné, Daniela V. T. A. Costa, Paula M. R. Correia, Moisés Castro, Luis T. Guerra, Cristina A. Costa

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The aim of this work was to characterize a potential target group of people interested in participating into a training program in organic farming in the context of mobile-learning. The information sought addressed in particular, but not exclusively, possible contents, formats and forms of evaluation that will contribute to define the course objectives and curriculum, as well as to ensure that the course meets the needs of the learners and their preferences. The sample was selected among different European countries. The questionnaires were delivered electronically for answering online and in the end 135 consented valid questionnaires were obtained. The results allowed characterizing the target group and identifying their training needs and preferences towards m-learning formats, giving valuable tools to design the training offer.

Keywords: mobile-learning, organic farming, rural development, survey

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Authors: Jackqueline Uy, Hannah Miriam Verano, Crysler Luis Verbo, Irene Gueco

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Educational tours are part of the curriculum of the College of Tourism and Hospitality Management, De La Salle University-Dasmarinas. They are highly significant to the students, especially Tourism students. The purpose of this study was to determine how effective educational tours were as a learning tool using the Experiential Learning Theory by David Kolb. This study determined the demographic profile of the third year tourism students in terms of gender, section, educational tours joined, and monthly family income and lastly, this study determined if there is a significant difference between the demographic profile of the respondents and their assessment of educational tours as a learning tool. The researchers used a historical research design with the third-year students of the bachelor of science in tourism management as the population size and used a random sampling method. The researchers made a survey questionnaire and utilized statistical tools such as weighted mean, frequency distribution, percentage, standard deviation, T-test, and ANOVA. The result of the study answered the profile of the respondents such as the gender, section, educational tour/s joined, and family monthly income. The findings of the study showed that the 3rd year tourism management students strongly agree that educational tours are a highly effective learning tool in terms of active experimentation, concrete experience, reflective observation, and abstract conceptualisation based on the data gathered from the respondents.

Keywords: CTHM, educational tours, experiential learning theory, De La Salle University Dasmarinas, tourism

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Authors: Daniel Ecler

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This paper aims to compare the data obtained using semi-structured questionnaires and find some connections between them, which could help to understand what factors affect the perception of the advantages and disadvantages of distance learning compared to conventional education. The data collected came from respondents from Czech and Chinese university students, and expectations were such that the different cultural environments from which the two groups come would have an impact on different experiences of distance education. With the help of variation-finding comparison, it turned out that Chinese students did not have such difficulties with the transition to distance learning as students from the Czech Republic, as most of them came into contact with some form of distance education in the past. In addition, it has also been shown that Chinese students use modern technology to a much greater extent, which has also made it easier for them to become accustomed to another form of teaching. In conclusion, Chinese students have greater preconditions for easier management of distance learning, while Czech students prefer more personal contact, and thus full-time teaching. It is obvious that both approaches have their pros and cons; now, it is necessary to find out how to use them for maximum efficiency of the educational process.

Keywords: Chinese college students, cultural background, Czech college students, distance learning, full-time teaching

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Andrei Nosov

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This paper discusses the development directions of dialogue systems within the digitalisation of the railway industry, where technologies based on conversational AI are already potentially applied or will be applied. Conversational AI is one of the popular natural language processing (NLP) tasks, as it has great prospects for real-world applications today. At the same time, it is a challenging task as it involves many areas of NLP based on complex computations and deep insights from linguistics and psychology. In this review, we focus on dialogue systems and their implementation in the railway domain. We comprehensively review the state-of-the-art research results on dialogue systems and analyse them from three perspectives: type of problem to be solved, type of model, and type of system. In particular, from the perspective of the type of tasks to be solved, we discuss characteristics and applications. This will help to understand how to prioritise tasks. In terms of the type of models, we give an overview that will allow researchers to become familiar with how to apply them in dialogue systems. By analysing the types of dialogue systems, we propose an unconventional approach in contrast to colleagues who traditionally contrast goal-oriented dialogue systems with open-domain systems. Our view focuses on considering retrieval and generative approaches. Furthermore, the work comprehensively presents evaluation methods and datasets for dialogue systems in the railway domain to pave the way for future research. Finally, some possible directions for future research are identified based on recent research results.

Keywords: digitalisation, railway, dialogue systems, conversational AI, natural language processing, natural language understanding, natural language generation

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Authors: Sergio Andres Rojas, Julian Benavides Franco, Juan Tomas Sayago

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An increasing amount of research demonstrates how market mood affects financial markets, but their primary goal is to demonstrate how Trump's tweets impacted US interest rate volatility. Following that lead, this work evaluates the effect that Trump's tweets had during his presidency on local and international stock markets, considering not just volatility but the direction of the movement. Three indexes for Trump's tweets were created relating his activity with movements in the S&P500 using natural language analysis and machine learning algorithms. The indexes consider Trump's tweet activity and the positive or negative market sentiment they might inspire. The first explores the relationship between tweets generating negative movements in the S&P500; the second explores positive movements, while the third explores the difference between up and down movements. A pseudo-investment strategy using the indexes produced statistically significant above-average abnormal returns. The findings also showed that the pseudo strategy generated a higher return in the local market if applied to intraday data. However, only a negative market sentiment caused this effect on daily data. These results suggest that the market reacted primarily to a negative idea reflected in the negative index. In the international market, it is not possible to identify a pervasive effect. A rolling window regression model was also performed. The result shows that the impact on the local and international markets is heterogeneous, time-changing, and differentiated for the market sentiment. However, the negative sentiment was more prone to have a significant correlation most of the time.

Keywords: market sentiment, Twitter market sentiment, machine learning, natural dialect analysis

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Authors: Zahara Abdulhussan Al-Awadai

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In recent years, serious games have started to gain an increasing interest as a tool to support learning across different educational and training fields. It began to serve as a powerful educational tool for improving learning outcomes. In this research, we discuss the potential of virtual experiences and games research outside of the games industry and explore the multifaceted impact of serious games and related technologies on various aspects of our lives. We highlight the usage of serious games as a tool to improve education and other applications with a purpose beyond the entertainment industry. One of the main contributions of this research is proposing a model that facilitates the design and development of serious games in a flexible and easy-to-use way. This is achieved by exploring different requirements to develop a model that describes a serious game structure with a focus on both aspects of serious games (educational and entertainment aspects).

Keywords: game development, requirements, serious games, serious game model

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Authors: Yesha Devi Mahadeo-Doorgakant

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The Mauritian landscape is well-known for its multilingualism with the daily interaction of the number of languages that are used in the island; namely Kreol Morisien, the European languages (English and French) and the Oriental/Asian languages (Hindi, Arabic/Urdu, Tamil, Telegu, Marathi, Mandarin, etc.). However, within Mauritius’ multilingual educational system, English is the official medium of instruction while French is taught as compulsory subject till upper secondary and oriental languages are offered as optional languages at primary level. Usually, Mauritians choose one oriental language based on their ethnic/religious identity, when they start their primary schooling as an additional language to learn. In January 2012, Kreol Morisien, which is the considered the language of daily interaction of the majority of Mauritians, was introduced as an optional subject at primary level, taught at the same time as the oriental languages. The introduction of Kreol Morisien has spurred linguistic debates about the issue of multilingualism within the curriculum. Taking this into account, researchers have started pondering on the multilingual educational system of the country and questioning whether the current language curriculum caters for the complex everyday linguistic reality of the multilingual Mauritian learner, given most learners are embedded within an environment where the different languages interact with each other daily. This paper, therefore, proposes translanguaging as being a more befitting theoretical lens through which the multilingualism and the linguistic repertoire of Mauritian learners’ can best be understood.

Keywords: multilingualism, translanguaging, multilingual learner, linguistic ethnography

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