Search results for: learning Maltese as a second language

Authors: Pedro A. Medina-Rios, Marly Yolie Quintana-Daza

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Having the opportunity to communicate in a social, academic and work context is very relevant for any individual and more for a deaf person when oral language is not their natural language, and written language is their second language. Currently, in Colombia, there is not a specialized dictionary for our best knowledge in sign language archiving. Archival is one of the areas that the deaf community has a greater chance of performing. Nourishing new signs in dictionaries for deaf people extends the possibility that they have the appropriate signs to communicate and improve their performance. The aim of this work was to illustrate the importance of designing pedagogical and technological strategies of knowledge management, for the academic inclusion of deaf people through proposals of lexicon in Colombian sign language (LSC) in the area of archival. As a method, the analytical study was used to identify relevant words in the technical area of the archival and its counterpart with the LSC, 30 deaf people, apprentices - students of the Servicio Nacional de Aprendizaje (SENA) in Documentary or Archival Management programs, were evaluated through direct interviews in LSC. For the analysis tools were maintained to evaluate correlation patterns and linguistic methods of visual, gestural analysis and corpus; besides, methods of linear regression were used. Among the results, significant data were found among the variables socioeconomic stratum, academic level, labor location. The need to generate new signals on the subject of the file to improve communication between the deaf person, listener and the sign language interpreter. It is concluded that the generation of new signs to nourish the LSC dictionary in archival subjects is necessary to improve the labor inclusion of deaf people in Colombia.

Keywords: archival, inclusion, deaf, thesaurus

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Authors: Hector Barrios-Piña, Georgia García-Arellano, Salvador García-Rodríguez, Gerardo Bocanegra-García, Shashi Kant

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This work shows the methodology of application and the effectiveness of the Flipped Learning technique for Civil Engineering laboratory classes. It was experimented by some of the professors of the Department of Civil Engineering at Tecnológico de Monterrey while teaching their laboratory classes. A total of 28 videos were created. The videos primarily demonstrate instructions of the experimental practices other than the usage of tools and materials. The technique allowed the students to prepare for their classes in advance. A survey was conducted on the participating professors and students (semester of August-December 2019) to quantify the effectiveness of the Flipped Learning technique. The students reported it as an excellent way of improving their learning aptitude, including self-learning whereas, the professors felt it as an efficient technique for optimizing their class session, which also provided an extra slot for class-interaction. A comparison of grades was analyzed between the students of the traditional classes and with Flipped Learning. It did not distinguish the benefits of Flipped Learning. However, the positive responses from the students and the professors provide an impetus for continuing and promoting the Flipped Learning technique in future classes.

Keywords: flipped learning, laboratory classes, civil engineering, competences development

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Authors: Chinfen Chen

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This paper aims to focus on the challenges and doubts encountered in the implementation of ‘bilingual teaching in some fields of courses’, and propose implementation principles and strategies from the four areas of curriculum design, teaching strategies, teaching language application, and bilingual teaching implementation and operation, as a school The administrative team considers when planning bilingual teaching and also clarifies teachers' doubts about the implementation of bilingual teaching to enhance their willingness and confidence to participate in bilingual teaching.

Keywords: bilingual education policy, language immersion, partial bilingual education, content knowledge and target language acquisition, inquiry-based teaching.

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: deep learning, generative, knowledge, response generation, retrieval

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Authors: Fani Firmahandari

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The development learning module physics based on guided inquiry approach on model cooperative learning type STAD (Student Team Achievement Division) in the main subject of temperature and heat. The research development aimed to produce physics learning module based on guided cooperative learning type STAD (Student Team Achievement Division) in the main subject of temperature and heat to the student in X class. The research method used Research and Development approach. The development procedure of this module includes potential problems, data collection to meet the need, product design, and feasibility of this module. The impact of learning can be seen or observed clearly when the learning process takes place, the teachers or the students already implemented measures cooperative learning model type STAD, so that the learning process goes well, the interaction of teachers and students, students with student looks good, besides that students can interact and work together in group.

Keywords: cooperative learning type STAD (student team achievement division), development, inquiry, interaction students

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Authors: M. H. Yee, J. Md Yunos, W. Othman, R. Hassan, T. K. Tee, M. M. Mohamad

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The generation of an idea that goes through several phases is affected by individual factors, interests, preferences and motivation. The purpose of this research was to analyze the difference in difficulties of generating ideas according to individual learning styles. A total of 375 technical students from four technical universities in Malaysia were randomly selected as samples. The Kolb Learning Styles Inventory and a set of developed questionnaires were used in this research. The results showed that the most dominant learning style is among technical students is Doer. A total of 319 (85.1%) technical students faced difficulties in solving individual assignments. Most of the problem faced by technical students is the difficulty of generating ideas for solving individual assignments. There was no significant difference in difficulties of generating ideas according to students’ learning styles. Therefore, students need to learn higher order thinking skills enabling students to generate ideas and consequently complete assignments.

Keywords: difference, difficulties, generating idea, learning styles, Kolb Learning Styles Inventory

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Authors: Amal Alshahrani, Allan Ramsay

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Paraphrasing is one of the important tasks in natural language processing; i.e. alternative ways to express the same concept by using different words or phrases. Paraphrases can be used in many natural language applications, such as Information Retrieval, Machine Translation, Question Answering, Text Summarization, or Information Extraction. To obtain pairs of sentences that are paraphrases we create a system that automatically extracts paraphrases from a corpus, which is built from different sources of news article since these are likely to contain paraphrases when they report the same event on the same day. There are existing simple standard approaches (e.g. TF-IDF vector space, cosine similarity) and alignment technique (e.g. Dynamic Time Warping (DTW)) for extracting paraphrase which have been applied to the English. However, the performance of these approaches could be affected when they are applied to another language, for instance Arabic language, due to the presence of phenomena which are not present in English, such as Free Word Order, Zero copula, and Pro-dropping. These phenomena will affect the performance of these algorithms. Thus, if we can analysis how the existing algorithms for English fail for Arabic then we can find a solution for Arabic. The results are promising.

Keywords: natural language processing, TF-IDF, cosine similarity, dynamic time warping (DTW)

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Authors: C. Maphosa, Ndileleni Mudzielwana, Lufuno Phillip Netshifhefhe

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In line with established mission and vision, a university articulates its focus and purpose of existence. The conduct of business in a university should be for the furtherance of the mission and vision. Teaching and learning should play a pivotal role in driving the purpose of a university. In this paper, the researchers examine how service learning could be significant in driving the purpose of a rural-based university whose focus is to promote rural development. The importance of institutions’ vision and mission statement is explored and the vision and mission of the said university examined closely. The concept rural development and the contribution of a university in its promotion is discussed. Service learning as a teaching and learning approach is examined and its significance in driving the purpose of a rural-based university explained.

Keywords: relevance, differentiation, purpose, teaching, learning

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Authors: Jacqueline Eleonora Ek, Michael Spiteri, Chris Giordimaina, Pierre Agius

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Background: Malta is known for being a key player as a frontline country with regard to irregular immigration from Africa to Europe. Every year the island experiences an influx of migrants as boat movement across the Mediterranean continues to be a humanitarian challenge. Irregular immigration and applying for asylum is both a lengthy and mentally demanding process. Those doing so are often faced with multiple challenges, which can adversely affect their mental health. Between January and August 2020, Malta disembarked 2 162 people rescued at sea, 463 of them between July & August. Given the small size of the Maltese islands, this regulation places a disproportionately large burden on the country, creating a backlog in the processing of asylum applications resulting in increased time periods of detention. These delays reverberate throughout multiple management pathways resulting in prolonged periods of detention and challenging access to health services. Objectives: To better understand the spatial dimensions of this humanitarian crisis, this study aims to assess disparities in the acute medical management of migrants presenting to the emergency department (ED) with acute mental health presentations as compared to that of local and non-local residents. Method: In this retrospective study, 17795 consecutive ED attendances were reviewed to look for acute mental health presentations. These were further evaluated to assess discrepancies in transportation routes to hospital, nature of presenting complaint, effects of language barriers, use of CT brain, treatment given at ED, availability of psychiatric reviews, and final admission/discharge plans. Results: Of the ED attendances, 92.3% were local residents, and 7.7% were non-locals. Of the non-locals, 13.8% were migrants, and 86.2% were other-non-locals. Acute mental health presentations were seen in 1% of local residents; this increased to 20.6% in migrants. 56.4% of migrants attended with deliberate self-harm; this was lower in local residents, 28.9%. Contrastingly, in local residents, the most common presenting complaint was suicidal thought/ low mood 37.3%, the incidence was similar in migrants at 33.3%. The main differences included 12.8% of migrants presenting with refused oral intake while only 0.6% of local residents presented with the same complaints. 7.7% of migrants presented with a reduced level of consciousness, no local residents presented with this same issue. Physicians documented a language barrier in 74.4% of migrants. 25.6% were noted to be completely uncommunicative. Further investigations included the use of a CT scan in 12% of local residents and in 35.9% of migrants. The most common treatment administered to migrants was supportive fluids 15.4%, the most common in local residents was benzodiazepines 15.1%. Voluntary psychiatric admissions were seen in 33.3% of migrants and 24.7% of locals. Involuntary admissions were seen in 23% of migrants and 13.3% of locals. Conclusion: Results showed multiple disparities in health management. A meeting was held between entities responsible for migrant health in Malta, including the emergency department, primary health care, migrant detention services, and Malta Red Cross. Currently, national quality-improvement initiatives are underway to form new pathways to improve patient-centered care. These include an interpreter unit, centralized handover sheets, and a dedicated migrant health service.

Keywords: emergency department, communication, health, migration

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Authors: Vidhu Mitha Goutham, Ruma Mukherjee

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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation

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Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

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Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

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Authors: Dace Aleksandraviča

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The paper presents a theoretical exploration of the emerging field of 21st-century ecolinguistics, which examines the multi-faceted relationship between language, ecology, and identity in our rapidly changing global landscape. In an era characterized by unprecedented linguistic and cultural hybridity, understanding the interplay between language and environment is paramount. This paper delves into the concept of hybrid identities, examining how individuals negotiate their linguistic and cultural affiliations within diverse ecological contexts based on relevant prior contributions in the field. Drawing upon interdisciplinary perspectives from linguistics, environmental studies, and cultural studies, the research investigates the ways in which language shapes and is shaped by environmental realities. The abstract underscores the importance of ecolinguistic approaches in fostering environmental stewardship and promoting sustainable practices. By acknowledging the intrinsic link between language, culture, and ecology, it becomes possible to cultivate a deeper appreciation for linguistic diversity and empower individuals to navigate their hybrid identities in a rapidly changing world. In line with that, the paper hopes to contribute to the growing body of literature on ecolinguistics and offer insights into how language can serve as a tool for both environmental conservation and cultural revitalization.

Keywords: ecolinguistics, hybrid identities, language, globalization

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Authors: Akiyoshi Wakatani

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This paper describes the Message Passing Interface (MPI) implementation of ADETRAN language, and its evaluation on SX-ACE supercomputers. ADETRAN language includes pdo statement that specifies the data distribution and parallel computations and pass statement that specifies the redistribution of arrays. Two methods for implementation of pass statement are discussed and the performance evaluation using Splitting-Up CG method is presented. The effectiveness of the parallelization is evaluated and the advantage of one dimensional distribution is empirically confirmed by using the results of experiments.

Keywords: iterative methods, array redistribution, translator, distributed memory

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Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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Authors: Molly Pui Man Wong

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In this study, a blended and interactive e-learning Courseware that our team developed will be introduced, and our team’s experiences on how the e-learning Courseware and the flipped classroom benefit student learning in bioethics in the medical program will be shared. This study is a continuation of the previously established study, which provides a summary of the well-developed e-learning Courseware in a blended learning approach and an update on its efficiency and efficacy. First, a collection of animated videos capturing selected topics of bioethics and related ethical issues and dilemma will be introduced. Next, a selection of problem-based learning videos (“simulated doctor-patient role play”) with pop-up questions and discussions will be further discussed. Our recent findings demonstrated that these activities launched by the Courseware strongly engaged students in bioethics education and enhanced students’ critical thinking and creativity, which were consistent with the previous data in the preliminary studies. Moreover, the educational benefits of the online art exhibition, art jamming, and competition will be discussed, through which students could express bioethics through arts and enrich their learning in medical research in an interactive, fun, and entertaining way, strengthening their interests in bioethics. Furthermore, online survey questionnaires and focus group interviews were conducted. Consistent with the preliminary studies, our results indicated that implementing the e-learning Courseware with a flipped classroom in bioethics education enhanced both active learning and student engagement. In conclusion, our Courseware not only reinforces education in art, bioethics, and medicine but also benefits students in understanding and critical thinking in socio-ethical issues and serves as a valuable learning tool in bioethics teaching and learning.

Keywords: bioethics, courseware, e-learning, flipped classroom

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Authors: Rika Aoki

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The aim of this paper is to investigate whether being bilinguals facilitates or impedes the perception of a third language. The present study conducted a perception experiment in which Mandarin-Japanese bilinguals categorized a Voice-Onset-Time (VOT) continuum into English /b/ or /p/. The results show that early bilinguals were influenced by both Mandarin and Japanese, while late bilinguals behaved in a similar manner to Mandarin monolinguals Thus, it can be concluded that in the present study having two languages did not help bilinguals to perceive L3 stop contrast native-likely.

Keywords: bilinguals, perception, third language acquisition, voice-onset-time

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Authors: Ahlam Alnatour

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Background: To our knowledge, there is lack of studies that describe the experience of studying health promotion courses using an interactive approach, and compare students’ and teachers perceptions about this method of teaching. The purpose of this study is to provide a comparison between student and teacher experiences and perspectives in learning health promotion course using interactive learning. Design: A descriptive qualitative design was used to provide an in-depth description and understanding of students’ and teachers experiences and perceptions of learning health promotion courses using an interactive learning. Study Participants: About 14 fourteen students (seven male, seven female) and eight teachers at governmental university in northern Jordan participated in this study. Data Analysis: Conventional content analysis approach was used for participants’ scripts to gain an in-depth description for both students' and teacher’s experiences. Results: The main themes emerged from the data analysis describing the students’ and teachers perceptions of the interactive health promotion class: teachers’ and students positive experience in adopting interactive learning, advantages and benefits of interactive teaching, barriers to interactive teaching, and suggestions for improvement. Conclusion: Both teachers and students reflected positive attitudes toward interactive learning. Interactive learning helped to engage in learning process physically and cognitively. Interactive learning enhanced learning process, promote student attention, enhanced final performance, and satisfied teachers and students accordingly. Interactive learning approach should be adopted in teaching graduate and undergraduate courses using updated and contemporary strategies. Nursing scholars and educators should be motivated to integrate interactive learning in teaching different nursing courses.

Keywords: interactive learning, nursing, health promotion, qualitative study

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Authors: Y. Kavanagh, N. O'Hara, R. Palmer, P. Lowe, D. Rafferty

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Physical Physics is a physics education methodology for games programfmes that integrates physical activity with movement tracking and modelling. It significantly enhances the learning experience and it is effective in illustrating how physics is core in games design and programming, while allowing students to be active participants and take ownership of the learning process. It has been successfully piloted with undergraduate students studying Games Development.

Keywords: activity, enhanced learning, game development, physics

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Authors: YuLung Wu, YuTien Wu, ShuMey Yu

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Game-based learning can enhance the learning motivation of students and provide a means for them to learn through playing games. This study used augmented reality technology to develop an interactive card game as a game-based teaching aid for delivering elementary school science course content with the aim of enhancing student learning processes and outcomes. Through playing the proposed card game, students can familiarize themselves with appearance, features, and foraging behaviors of insects. The system records the actions of students, enabling teachers to determine their students’ learning progress. In this study, 37 students participated in an assessment experiment and provided feedback through questionnaires. Their responses indicated that they were significantly more motivated to learn after playing the game, and their feedback was mostly positive.

Keywords: game-based learning, learning motivation, teaching aid, augmented reality

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Authors: Mairo Musa Galadima

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This paper examines the impact of Mother tongue interference on students’ performance in English Language in Bauchi State. It is observed that the students of Bauchi district share the same problem with Hausa native speakers of Kano dialect which is the standard form. It is observed that there are some phonemes which are present in English but absent in Hausa so the Hausa speakers of Bauchi district also replace these sounds with similar ones present in Hausa. Students in Bauchi district fail English language because they transfer features of their mother tongue (MT) into English. The data is obtained through unobtrusive observation of the English speech of about fifty Hausa native speakers of Bauchi district which is similar to Kano dialect from Abubakar Tatari Ali Polytechnic, Bauchi since only those who have had some good background of secondary education are used because uneducated Nigeria English of whatever geographical location is more likely to be unintelligible as cockney or uneducated African-American English. For instance /Ə:/ is absent in Hausa so the speakers find it difficult to distinguish between such pairs of words as /bƏ:d / and /bΛst/, /fa:st/ and /fƏ:st / hence /a:/ is generally used wherever /Ə:/ is present regardless of the spelling, that is why words like ‘work’, ‘first’ and ‘person’ all have / a:/. In Hausa most speakers use /P/ in place of, or in alternation with /f/, e.g. ‘few’ is pronounced as ‘pew’, or ‘pen’, as ‘fen’, /b/ for /v/, /s/ for /z/ and /z/ for /ᵹ/. Also the word vision/visn/ is pronounced as /vidzn/. Therefore, there is confusion in spellings and pronunciation of words. One solution out of the problem is having constant practice with a qualified consistent staff and making use of standard textbooks in the learning process.

Keywords: English, failure, mother tongue, interference, students

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Authors: Ashutosh Mishra, Nikhil Goyal

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A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

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Authors: Yake Zhang, Peng Xu

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The development of building energy models (BEM) required for architectural design and analysis is a time-consuming and complex process, demanding a deep understanding and proficient use of simulation software. To streamline the generation of complex building energy models, this study proposes an automated method for generating building energy models using a large language model and the BEM library aimed at improving the efficiency of model generation. This method leverages a large language model to parse user-specified requirements for target building models, extracting key features such as building location, window-to-wall ratio, and thermal performance of the building envelope. The BEM library is utilized to retrieve energy models that match the target building’s characteristics, serving as reference information for the large language model to enhance the accuracy and relevance of the generated model, allowing for the creation of a building energy model that adapts to the user’s modeling requirements. This study enables the automatic creation of building energy models based on natural language inputs, reducing the professional expertise required for model development while significantly decreasing the time and complexity of manual configuration. In summary, this study provides an efficient and intelligent solution for building energy analysis and simulation, demonstrating the potential of a large language model in the field of building simulation and performance modeling.

Keywords: artificial intelligence, building energy modelling, building simulation, large language model

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Authors: K. M. Wong

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Engineering education is crucial to technological innovation and advancement worldwide by generating young talents who are able to integrate scientific principles and design practical solutions for real-world problems. Graduates of engineering curriculums are expected to demonstrate an extensive set of learning outcomes as required in international accreditation agreements for engineering academic qualifications, such as the Washington Accord and the Sydney Accord. On the other hand, students have different learning preferences of receiving, processing and internalizing knowledge and skills. If the learning environment is advantageous to the learning styles of the students, there is a higher chance that the students can achieve the intended learning outcomes. With proper identification of the learning styles of the students, corresponding teaching strategies can then be developed for more effective learning. This research was an investigation of learning styles of tertiary students studying higher diploma programmes in Hong Kong. Data from over 200 students in engineering programmes were collected and analysed to identify the learning characteristics of students. A small-scale longitudinal study was then started to gather academic results of the students throughout their two-year engineering studies. Preliminary results suggested that the sample students were reflective, sensing, visual, and sequential learners. Observations from the analysed data not only provided valuable information for teachers to design more effective teaching strategies, but also provided data for further analysis with the students’ academic results. The results generated from the longitudinal study shed light on areas of improvement for more effective engineering curriculum design for better teaching and learning.

Keywords: learning styles, learning characteristics, engineering education, vocational education, Hong Kong

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Authors: Marvelyn F. Carolino, Charlene R. Cunanan, Gellien Faith O. Masongsong, Berlinda A. Ofrecio

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This study delves into the language usage differences among men, women, and individuals with other gender preferences. It specifically centers on the sociolinguistic aspects within the English majors at the College of Education of Rizal Technological University-Pasig, spanning from the first-year to fourth-year levels. The researchers employed a triangulation approach for data collection, utilizing a validated self-made questionnaire, interviews, and observations. The results revealed that language usage among different genders is influenced by a combination of cultural norms, social dynamics, and technological factors. Cultural norms significantly shape how respondents use language, as they conform to expected speech patterns based on their gender. Social factors, such as peer pressure, were found to impact language usage for individuals of all genders. This influence was viewed as constructive for personal development rather than inhibiting performance or communication. In terms of technological factors, respondents strongly agreed that the time spent on social media and educational applications influenced their language use. These platforms provided opportunities to expand and enhance their vocabulary. Additionally, the study employed hypothesis testing through the z-test formula to assess the impact of demographic profiles on language usage differences among genders. The results indicated that gender, economic status, locality, and ethnicity did not show statistically significant differences in language use. This lack of significant variation in findings was attributed to the relatively homogeneous demographic profile of respondents, primarily composed of females with low-income backgrounds and Tagalog ethnicity. This demographic similarity likely minimized the diversity of responses.

Keywords: gender, language, sociolinguistics, differences

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Authors: Jolanta Jonak, Sylvia Tolczyk

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Educational systems are tasked with preparing students for future success in academic or work environments. Schools strive to achieve this goal, but often it is challenging as conventional teaching approaches are often ineffective in increasingly diverse educational systems. In today’s ever-increasing global society, educational systems become increasingly diverse in terms of cultural and linguistic differences, learning preferences and styles, ability and disability. Through increased understanding of disabilities and improved identification processes, students having some form of disabilities tend to be identified earlier than in the past, meaning that more students with identified disabilities are being supported in our classrooms. Also, a large majority of students with disabilities are educated in general education environments. Due to cognitive makeup and life experiences, students have varying learning styles and preferences impacting how they receive and express what they are learning. Many students come from bi or multilingual households and with varying proficiencies in the English language, further impacting their learning. All these factors need to be seriously considered when developing learning opportunities for student's. Educators try to adjust their teaching practices as they discover that conventional methods are often ineffective in reaching each student’s potential. Many teachers do not have the necessary educational background or training to know how to teach students whose learning needs are more unique and may vary from the norm. This is further complicated by the fact that many classrooms lack consistent access to interventionists/coaches that are adequately trained in evidence-based approaches to meet the needs of all students, regardless of what their academic needs may be. One evidence-based way for providing successful education for all students is by incorporating cognitive approaches and strategies that tap into affective, recognition, and strategic networks in the student's brain. This can be done through Differentiated Instruction (DI). Differentiated Instruction is increasingly recognized model that is established on the basic principles of Universal Design for Learning. This form of support ensures that regardless of the students’ learning preferences and cognitive learning profiles, they have opportunities to learn through approaches that are suitable to their needs. This approach improves the educational outcomes of students with special needs and it benefits other students as it accommodates learning styles as well as the scope of unique learning needs that are evident in the typical classroom setting. Differentiated Instruction also is recognized as an evidence-based best practice in education and is highly effective when it is implemented within the tiered system of the Response to Intervention (RTI) model. Recognition of DI becomes more common; however, there is still limited understanding of the effective implementation and use of strategies that can create unique learning environments for each student within the same setting. Through employing knowledge of a variety of instructional strategies, general and special education teachers can facilitate optimal learning for all students, with and without a disability. A desired byproduct of DI is that it can eliminate inaccurate perceptions about the students’ learning abilities, unnecessary referrals for special education evaluations, and inaccurate decisions about the presence of a disability.

Keywords: differentiated instruction, universal design for learning, special education, diversity

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Authors: Alexander Huang

Abstract:

Online learning sessions have become an indispensable complement to in-classroom-learning sessions in the past two years due to the emergence of Covid-19. Due to social distance requirements, many courses and interaction-intensive sessions, ranging from music classes to debate camps, are online. However, online learning imposes a significant challenge for engaging students effectively during the learning sessions. To resolve this problem, Project PWR, a non-profit organization formed by high school students, developed an online kid-teach-kid learning environment to boost students' learning interests and further improve students’ engagement during online learning. Fundamentally, the kid-teach-kid learning model creates an affinity space to form learning groups, where like-minded peers can learn and teach their interests. The role of the teacher can also help a kid identify the instructional task and set the rules and procedures for the activities. The approach also structures initial discussions to reveal a range of ideas, similar experiences, thinking processes, language use, and lower student-to-teacher ratio, which become enriched online learning experiences for upcoming lessons. In such a manner, a kid can practice both the teacher role and the student role to accumulate experiences on how to convey ideas and questions over the online session more efficiently and effectively. In this research work, we conducted two case studies involving a 3D-Design course and a Speech and Debate course taught by high-school kids. Through Project PWR, a kid first needs to design the course syllabus based on a provided template to become a student-teacher. Then, the Project PWR academic committee evaluates the syllabus and offers comments and suggestions for changes. Upon the approval of a syllabus, an experienced and voluntarily adult mentor is assigned to interview the student-teacher and monitor the lectures' progress. Student-teachers construct a comprehensive final evaluation for their students, which they grade at the end of the course. Moreover, each course requires conducting midterm and final evaluations through a set of surveyed replies provided by students to assess the student-teacher’s performance. The uniqueness of Project PWR lies in its established kid-teach-kids affinity space. Our research results showed that Project PWR could create a closed-loop system where a student can help a teacher improve and vice versa, thus improving the overall students’ engagement. As a result, Project PWR’s approach can train teachers and students to become better online learners and give them a solid understanding of what to prepare for and what to expect from future online classes. The kid-teach-kid learning model can significantly improve students' engagement in the online courses through the Project PWR to effectively supplement the traditional teacher-centric model that the Covid-19 pandemic has impacted substantially. Project PWR enables kids to share their interests and bond with one another, making the online learning environment effective and promoting positive and effective personal online one-on-one interactions.

Keywords: kid-teach-kid, affinity space, online learning, engagement, student-teacher

Procedia PDF Downloads 143

Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

Abstract:

Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

Procedia PDF Downloads 59

Authors: Jordana Lenhardt

Abstract:

This paperwork aims to promote a reflection on the critical literacy and multiliteracies concepts in the English language teaching, under an emancipatory perspective, in the English language classroom at the Federal Institute of Mato Grosso (IFMT), Rondonópolis Campus. Some Authors place the relationship between the world conscience and the self-conscience in a direct reason, compromising one to the other, and others defend that emancipatory teaching practice must be connected in all the spheres of the social context; with this paperwork, we intend to analyze students’ interactions with the English language, in order to verify if they demonstrate critical conscience about language and the world around them. The study is still at a preliminary level and is grounded in discourse critical analysis and systemic-functional linguistics. We understand that text is irremediable, linked to a context, and that the linguistic selection made by the speaker builds social representations. This research foresees the analysis of some students’ speeches in an interview about their classes at the Federal Institute in the city of Rondonópolis and the methodology being used on them. Discourse critical analysis explains that, through the awareness of the language uses, learners can become more conscious of the coercions in their own language practices, the possibilities of risks, and the costs of the individual or collective challenges, to engage themselves in emancipatory linguistic practice. The critical language conscience contributes, on the other hand, to make students more aware of the practices in which they are involved, as producers and consumers of texts, of the social forces, ideologies, and power relations, their effects on the identities and social relations, as well as the discourse role in the social and cultural processes.

Keywords: multiliteracies, critical literacy, emancipation, social transformation

Procedia PDF Downloads 101

Authors: Gilbert Makanda, Roelf Sypkens

Abstract:

A mathematical model for knowledge acquisition in teaching and learning is proposed. In this study we adopt the mathematical model that is normally used for disease modelling into teaching and learning. We derive mathematical conditions which facilitate knowledge acquisition. This study compares the effects of dropping out of the course at early stages with later stages of learning. The study also investigates effect of individual interaction and learning from other sources to facilitate learning. The study fits actual data to a general mathematical model using Matlab ODE45 and lsqnonlin to obtain a unique mathematical model that can be used to predict knowledge acquisition. The data used in this study was obtained from the tutorial test results for mathematics 2 students from the Central University of Technology, Free State, South Africa in the department of Mathematical and Physical Sciences. The study confirms already known results that increasing dropout rates and forgetting taught concepts reduce the population of knowledgeable students. Increasing teaching contacts and access to other learning materials facilitate knowledge acquisition. The effect of increasing dropout rates is more enhanced in the later stages of learning than earlier stages. The study opens up a new direction in further investigations in teaching and learning using differential equations.

Keywords: differential equations, knowledge acquisition, least squares nonlinear, dynamical systems

Procedia PDF Downloads 364