Search results for: language acquisition and learning

Authors: Shwadhin Sharma

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As there has been increasing focus on the shorter attention span of the millennials students, there is a relative absence of instructional tools on behavioral assessments in learning information technology skills within the information systems field and textbooks. This study uses project-based learning in which students gain knowledge and skills related to information technology by working on an extended project that allows students to find a real business problem design information systems based on information collected from the company and develop an information system that solves the problem of the company. Eighty students from two sections of the same course engage in the project from the first week of the class till the sixteenth week of the class to deliver a small business information system that allows them to employ all the skills and knowledge that they learned in the class into the systems they are creating. Computer Information Systems related courses are often difficult to understand and process especially for the Under Representative Minorities students who have limited computer or information systems related (academic) experiences. Project-based learning demands constant attention of the students and forces them to apply knowledge learned in the class to a project that helps retaining knowledge. To make sure our assumption is correct, we started with a pre-test and post-test to test the students learning (of skills) based on the project. Our test showed that almost 90% of the students from the two sections scored higher in post-test as compared to pre-test. Based on this premise, we conducted a further survey that measured student’s job-search preparation, knowledge of data analysis, involved with the course, satisfaction with the course, student’s overall reaction the course and students' ability to meet the traditional learning goals related to the course.

Keywords: project-based learning, job-search preparation, satisfaction with course, traditional learning goals

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Authors: Liliana O. Martínez, Juan E. González, Manuel Ramírez-Aranda, Ana Cervantes-Herrera

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In this work, the use of a collection of mathematical challenges and puzzles aimed at students who are starting in algebra is proposed. The selected challenges and puzzles are intended to arouse students' interest in this area of mathematics, in addition to facilitating the teaching-learning process through challenges such as riddles, crossword puzzles, and board games, all in everyday situations that allow them to build themselves the learning. For this, it is proposed to carry out a "Math Rally: algebra" divided into four sections: mathematical reasoning, a hierarchy of operations, fractions, and algebraic equations.

Keywords: algebra, algebraic challenge, algebraic puzzle, math rally

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Authors: Amir Taghizadeh Vahed, Adithya Thaduri

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Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

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Authors: J. Miranda, D. Chavarría-Barrientos, M. Ramírez-Cadena, M. E. Macías, P. Ponce, J. Noguez, R. Pérez-Rodríguez, P. K. Wright, A. Molina

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Higher education methods need to evolve because the new generations of students are learning in different ways. One way is by adopting emergent technologies, new learning methods and promoting the maker movement. As a result, Tecnologico de Monterrey is developing Open Innovation Laboratories as an immediate response to educational challenges of the world. This paper presents an Open Innovation Laboratory for Rapid Realization of Sensing, Smart and Sustainable Products (S³ Products). The Open Innovation Laboratory is composed of a set of specific resources where students and teachers use them to provide solutions to current problems of priority sectors through the development of a new generation of products. This new generation of products considers the concepts Sensing, Smart, and Sustainable. The Open Innovation Laboratory has been implemented in different courses in the context of New Product Development (NPD) and Integrated Manufacturing Systems (IMS) at Tecnologico de Monterrey. The implementation consists of adapting this Open Innovation Laboratory within the course’s syllabus in combination with the implementation of specific methodologies for product development, learning methods (Active Learning and Blended Learning using Massive Open Online Courses MOOCs) and rapid product realization platforms. Using the concepts proposed it is possible to demonstrate that students can propose innovative and sustainable products, and demonstrate how the learning process could be improved using technological resources applied in the higher educational sector. Finally, examples of innovative S³ products developed at Tecnologico de Monterrey are presented.

Keywords: active learning, blended learning, maker movement, new product development, open innovation laboratory

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Brwa Abdulrahman Abubaker

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Recently, there has been a lot of interest in the difficult task of applying reinforcement learning to autonomous mobile robots. Conventional reinforcement learning (TRL) techniques have many drawbacks, such as lengthy computation times, intricate control frameworks, a great deal of trial and error searching, and sluggish convergence. In this paper, a modified Spiking Neural Network (SNN) is used to offer a distinct method for autonomous mobile robot learning and control in unexpected surroundings. As a learning algorithm, the suggested model combines dopamine modulation with spike-timing-dependent plasticity (STDP). In order to create more computationally efficient, biologically inspired control systems that are adaptable to changing settings, this work uses the effective and physiologically credible Izhikevich neuron model. This study is primarily focused on creating an algorithm for target tracking in the presence of obstacles. Results show that the SNN trained with three obstacles yielded an impressive 96% success rate for our proposal, with collisions happening in about 4% of the 214 simulated seconds.

Keywords: spiking neural network, spike-timing-dependent plasticity, dopamine modulation, reinforcement learning

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Fetoon K. Algarawi, Wejdan A. Alslamah, Ahlam A. Alhabib, Afnan S. Alfehaid, Dina M. Ibrahim

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Over the past 20 years, technology was rapidly developed and no one expected what will come next. Advancements in technology open new opportunities for immersive learning environments. There is a need to transmit education to a level that makes it more effective for the student. Augmented reality is one of the most popular technologies these days. This paper is an experience of applying Augmented Reality (AR) technology using a marker-based approach in E-learning system to transmitting virtual objects into the real-world scenes. We present a marker-based approach for transmitting virtual objects into real-world scenes to explain information in a better way after we developed a mobile phone application. The mobile phone application was then tested on students to determine the extent to which it encouraged them to learn and understand the subjects. In this paper, we talk about how the beginnings of AR, the fields using AR, how AR is effective in education, the spread of AR these days and the architecture of our work. Therefore, the aim of this paper is to prove how creating an interactive e-learning system using AR technology will encourage students to learn more.

Keywords: augmented reality, e-learning, marker-based, monitor-based

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Authors: Abdulmutallib U. Baraya, Aishatu M. Chadi, Zainab A. Aliyu, Agatha Samson

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Learning Resources is the field of study that investigates the process of analyzing, designing, developing, implementing, and evaluating learning materials, learners, and the learning process in order to improve teaching and learning in university-level education essential for empowering students and various sectors of Nigeria’s economy to succeed in a fast-changing global economy. Innovation in the information age of the 21st century is the use of educational technologies in the classroom for instructional delivery, it involves the use of appropriate educational technologies like smart boards, computers, projectors and other projected materials to facilitate learning and improve performance. The study examined learning resources as determinants for improving the teaching and learning process in Abubakar Tafawa Balewa University (ATBU), Bauchi, Bauchi state of Nigeria. Three objectives, three research questions and three null hypotheses guided the study. The study adopted a Survey research design. The population of the study was 880 lecturers. A sample of 260 was obtained using the research advisor table for determining sampling, and 250 from the sample was proportionately selected from the seven faculties. The instrument used for data collection was a structured questionnaire. The instrument was subjected to validation by two experts. The reliability of the instrument stood at 0.81, which is reliable. The researchers, assisted by six research assistants, distributed and collected the questionnaire with a 75% return rate. Data were analyzed using mean and standard deviation to answer the research questions, whereas simple linear regression was used to test the null hypotheses at a 0.05 level of significance. The findings revealed that physical facilities and digital technology tools significantly improved the teaching and learning process. Also, consumables, supplies and equipment do not significantly improve the teaching and learning process in the faculties. It was recommended that lecturers in the various faculties should strengthen and sustain the use of digital technology tools, and there is a need to strive and continue to properly maintain the available physical facilities. Also, the university management should, as a matter of priority, continue to adequately fund and upgrade equipment, consumables and supplies frequently to enhance the effectiveness of the teaching and learning process.

Keywords: education, facilities, learning-resources, technology-tools

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Authors: Liu Yi Hui

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The COVID-19 pandemic in 2020 has globally affected all aspects of life, with social distancing and quarantine orders causing turmoil and learning in community colleges being temporarily paused. In fact, this is the first time that adult education has faced such a severe challenge. It forces researchers to reflect on the impact of pandemics on adult education and ways to respond. Distance learning appears to be one of the pedagogical tools capable of dealing with interpersonal isolation and social distancing caused by the pandemic. This research aims to examine whether the impact of social distancing during COVID-19 will lead to increased acceptance of technology and, subsequently, an increase in adults ’ willingness to participate in distance learning. The hypothesis that social distancing and the desire to participate in distance learning affects learners’ tendency to accept technology is investigated. Teachers ’ participation in distance education and acceptance of technology are used as adjustment variables with the relationship to “social distancing,” “participation in distance learning,” and “acceptance of technology” of learners. A questionnaire survey was conducted over a period of twelve months for teachers and learners at all community colleges in Taiwan who enrolled in a basic unit course. Community colleges were separated using multi-stage cluster sampling, with their locations being metropolitan, non-urban, south, and east as criteria. Using the G*power software, 660 samples were selected and analyzed. The results show that through appropriate pedagogical strategies or teachers ’ own acceptance of technology, adult learners’ willingness to participate in distance learning could be influenced. A diverse model of participation can be developed, improving adult education institutions’ ability to plan curricula to be flexible to avoid the risk associated with epidemic diseases.

Keywords: social distancing, adult learning, community colleges, technology acceptance model

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Authors: Ronit German, Alexandra Beytenbrat

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Although English seems to be prevalent in every sphere of Israeli daily life, not many Israeli students have a sufficient level of writing and speaking in English which is necessary for academic studies. The inadequate level of English among Israeli students is because the sole focus is on teaching reading comprehension, and the need to adapt to the trends of the professional worldwide demands triggered a reform that requires implementing Common European Framework of Reference (CEFR) and English as a Medium of Instruction (EMI) courses in the Israeli academic institutions. However, it will be argued that this reform is challenging to implement. The fact that modern Hebrew is a revived language, and that English is L3 for more than 30% of the population, the diverse social and cultural students’ background, and psychological factors stand in the way of the new reform.

Keywords: CEFR, cultural diversity, EMI courses, English in Israel, reform

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Yasaswi Palagummi, Sareh Rowlands

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Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work of ours, to solve the GZSL problem, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GSZL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets -AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: generalised, zero-shot learning, inductive learning, shifted-window attention, Swin transformer, vision transformer

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Authors: Ehi E. Aimiuwu

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As of 2017, many online learning professionals, institutions, and journals are still wondering how instructors can keep student engaged in the online learning environment to facilitate active learning effectively. The purpose of this qualitative single-case and narrative research is to explore whether online professors understand their role as mentors and facilitators of students’ academic success by keeping students engaged in active learning based on personalized experience in the field. Data collection tools that were used in the study included an NVivo 12 Plus qualitative software, an interview protocol, a digital audiotape, an observation sheet, and a transcription. Seven online professors in the United States from LinkedIn and residencies were interviewed for this study. Eleven online teaching techniques from previous research were used as the study framework. Data analysis process, member checking, and key themes were used to achieve saturation. About 85.7% of professors agreed on rubric as the preferred online grading technique. About 57.1% agreed on professors logging in daily, students logging in about 2-5 times weekly, knowing students to increase accountability, email as preferred communication tool, and computer access for adequate online learning. About 42.9% agreed on syllabus for clear class expectations, participation to show what has been learned, and energizing students for creativity.

Keywords: class facilitation, class management, online teaching, online education, pedagogy

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Authors: Jennifer Gallup, Joel Bocanegra, Greg Callan, Abigail Vaughn

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Students with disabilities (SWD) engaged in a distance summer program delivered over multiple virtual mediums that used gaming principles to teach and practice self-regulated learning (SRL) through the process of exploring possible jobs. Gaming quests were developed to explore jobs and teach transition skills. Students completed specially designed quests that taught and reinforced SRL and problem-solving through individual, group, and teacher-led experiences. SRL skills learned were reinforced through guided job explorations over the context of MinecraftEDU, zoom with experts in the career, collaborations with a team over Marco Polo, and Zoom. The quests were developed and laid out on an accessible web page, with active learning opportunities and feedback conducted within multiple virtual mediums including MinecraftEDU. Gaming mediums actively engage players in role-playing, problem-solving, critical thinking, and collaboration. Gaming has been used as a medium for education since the inception of formal education. Games, and specifically board games, are pre-historic, meaning we had board games before we had written language. Today, games are widely used in education, often as a reinforcer for behavior or for rewards for work completion. Games are not often used as a direct method of instruction and assessment; however, the inclusion of games as an assessment tool and as a form of instruction increases student engagement and participation. Games naturally include collaboration, problem-solving, and communication. Therefore, our summer program was developed using gaming principles and MinecraftEDU. This manuscript describes a virtual learning summer program called Virtual Academy New and Exciting Transitions (VAN) that was redesigned from a face-to-face setting to a completely online setting with a focus on SWD aged 14-21. The focus of VAN was to address transition planning needs such as problem-solving skills, self-regulation, interviewing, job exploration, and communication for transition-aged youth diagnosed with various disabilities (e.g., learning disabilities, attention-deficit hyperactivity disorder, intellectual disability, down syndrome, autism spectrum disorder).

Keywords: autism, disabilities, transition, summer program, gaming, simulations

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Authors: Festa Shabani

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This paper aims at investigating bilingual speech in the International Schools of Prishtina. More particularly, it seeks to analyze bilingual phenomena among adolescent students highly exposed to English with the latter as the language of instruction at school in naturally-occurring conversations within school environment. Adolescence was deliberately chosen since it is regarded as an age when peer influence on language choice is the greatest. Driven by daily unsystematic observation and prior research already undertaken, the hypothesis stated is that Albanian continues to be the dominant language among Prishtina international schools’ students with a lot of code-switched items from the English. Furthermore, they will also use lexical borrowings - words already adapted in the receiving language, from the language they have been in contact with, in their speech often in the lack of existing equivalents in Albanian or for other reasons. This is done owing to the fact that the language of instruction at school is English, and any topic related to the language they have been exposed to will trigger them to use English. Therefore, this needs special attention in an attempt to identify patterns of their speech; in this way, linguistic and socio-pragmatic factors will be considered when analyzing the motivations behind their language choice. Methodology for collecting data include participant systematic observation and tape-recording. While observing them in their natural conversations, the fieldworker also took notes, which helped transcribe details better. The paper starts by raising the question of whether code-switching is occurring among Prishtina International Schools’ students highly exposed to English. The data gathered from students in informal settings suggests that there are well-founded grounds for an affirmative answer. The participants in this study are observed to be code-switching, although showing differences in degree. However, a generalization cannot be made on the basis of the findings except in so far it appears that English has, in turn, became a language to which they turn when identifying with the group when discussing about particular school topics. Particularly, participants seemed to use intra-sentential CS in cases when they seem to find an English expression rather easier than an Albanian one when repeating or emphasizing a point when urged to talk about educational issues with English being their language of instruction, and inter-sentential code-switching, particularly when quoting others. Concerning the grammatical aspect of code-switching, the intrasentential CS is used more than the intersentetial one. Speaking of gender, the results show that there were really no significant differences in regards quantity between male and female participants. However, the slight tendency for men to code switch intrasententially more than women was manifested. Similarly, a slight tendency again for a difference to emerge is on intersentential switching, which contributes 21% to the total number of switches for women, but 11% to the total number of switches for men.

Keywords: Albanian, code-switching contact linguistics, bilingual phenomena, lexical borrowing, English

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Authors: Isiya Shinkafi Salihu

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Open education resources (OER) are open learning materials in different formats, course content and context to support learning globally. This study investigated the level of awareness of Hospitality and Tourism OER among students in the Department of Tourism and Hotel Management in a University. Specifically, it investigated students’ awareness, use and accessibility of OER in learning. The research design method used was the quantitative approach, using an online questionnaire. The thesis research shows that respondents frequently use OER but with little knowledge of the content and context of the material. Most of the respondents’ have little knowledge about the concept even though they use it. Information and communication technologies are tools for information gathering, social networking and knowledge sharing and transfer. OER are open education materials accessible online such as curriculum, maps, course materials, and videos that users create, adapt, reuse for learning and research. Few of the respondents that used OER in learning faced some challenges such as high cost of data, poor connectivity and lack of proper guidance. The results suggest a lack of awareness of OER among students in the faculty of tourism and the need for support from the teachers in the utilization of OER. The thesis also reveals that some of the international students are accessing the internet as beginners in their studies which require guidance. The research, however, recommends that further studies should be conducted to other faculties.

Keywords: creative commons, open education resources, open licenses, information and communication technology

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Authors: A. Estaji

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The first part of the present paper studies the role of language in expressing pain. Pain is usually described as a personal and mental experience, so language has an important role in describing, expressing and measuring pain and sometimes it is believed that language is the only device for accessing this personal experience. The second part of this paper studies gender differences in expressing pain. Considering the biological, psychological and social differences between men and women, we raise this question whether men and women express their pain in the same way or differently. To answer this question, we asked 44 Farsi speaking participants to write about the most painful experience they had in the past. Qualitative analysis of the data shows that women, have expressed their pain more severely, have expressed their feelings about pain instead of describing the pain itself, have made their pain more personal and have given more details about the circumstances in which they experienced pain, while men have given a more neutral description of their pain and have given a description of their pain by distancing themselves from the painful event. Knowing these gender differences in expressing pain can help medical practitioners in assessing the pain level.

Keywords: discourse analysis, expressing pain, measuring pain, gender

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Authors: Merih Welay Welesilassie

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Language is a potent instrument that does not only serve the purpose of communication but also plays a pivotal role in shaping our cultural practices and identities. The right to choose one's language is a fundamental human right that helps to safeguard the integrity of both personal and communal identities. Language holds immense significance in Ethiopia, a nation with a diverse linguistic landscape that extends beyond mere communication to delineate administrative boundaries. Consequently, depriving Ethiopians of their linguistic rights represents a multifaceted punishment, more complex than food embargoes. In the aftermath of the civil war that shook Ethiopia in November 2020, displacing millions and resulting in the loss of hundreds of thousands of lives, concerns have been raised about the preservation of the indigenous Tigrayan language and culture. This is particularly true following the annexation of western Tigray into the Amhara region and the implementation of an Amharic-only language and culture education policy. This scholarly inquiry explores the intricacies surrounding the Amhara regional state's prohibition of Tigrayans' indigenous language and culture and the subsequent adoption of a monolingual and monocultural Amhara language and culture in western Tigray. The study adopts the linguistic genocide conceptual framework as an analytical tool to gain a deeper insight into the factors that contributed to and facilitated this significant linguistic and cultural shift. The research was conducted by interviewing ten teachers selected through a snowball sampling. Additionally, document analysis was performed to support the findings. The findings revealed that the push for linguistic and cultural assimilation was driven by various political and economic factors and the desire to promote a single language and culture policy. This process, often referred to as ‘Amharanization,’ aimed to homogenize the culture and language of the society. The Amhara authorities have enacted several measures in pursuit of their objectives, including the outlawing of the Tigrigna language, punishment for speaking Tigrigna, imposition of the Amhara language and culture, mandatory relocation, and even committing heinous acts that have inflicted immense physical and emotional suffering upon members of the Tigrayan community. Upon conducting a comprehensive analysis of the contextual factors, actions, intentions, and consequences, it has been posited that there may be instances of linguistic genocide taking place in the Western Tigray region. The present study sheds light on the severe consequences that could arise because of implementing monolingual and monocultural policies in multilingual areas. Through thoroughly scrutinizing the implications of such policies, this study provides insightful recommendations and directions for future research in this critical area.

Keywords: linguistic genocide, linguistic human right, mother tongue, Western Tigray

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Authors: Jane Ebele Iloanya

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The introduction of the learning outcome approach in contemporary curriculum design and instruction, has brought student–centered education to the fore. In teacher –centered teaching and learning, the teacher transfers knowledge to the students, who are always at the receiving end. The teacher is assumed to know it all and hardly trusts the knowledge of the students. Teacher-centered education places emphasis on the supremacy of the teacher over the students who should ideally, be able to dialogue with the teacher. The paper seeks to examine the issue of democratisation of the teaching and learning process in Institutions of Higher Learning in Botswana. Botswana is a landlocked country in Southern Africa, with a total population of about two million people. In 1977, Botswana’s First National Policy on Education was unveiled. This came eleven years after the country gained independence from Great Britain. The philosophy which informed the 1977 Education Policy was “Social Harmony”. The philosophy of social harmony has four main principles: Unity, Development, Democracy and Self- Reliance. These principles were meant to permeate all aspects of lives of the people of Botswana, including, the issue of how teaching and learning is conducted in Botswana’s institutions of higher learning. This paper will examine the practicalisation of the principle of democracy in teaching and learning at higher education level in Botswana. It will in particular, discuss the issue of students’ participation and engagement in the teaching and learning process. The following questions will be addressed: 1.Are students involved in planning the curriculum? 2.How engaged are the students in the teaching and learning process? 3.How democratic are the teachers in terms of students’ rights and privileges? A mixed–method approach will be adopted in this study. Questionnaires will be distributed to the students to elicit their views on the practicalisation of the principle of democracy at the higher education level. Semi-structured interview questions will be administered in order to collect information from the lecturers on the issue of democratisation of teaching and learning at the higher education level in Botswana. In addition, relevant and related literature will be reviewed to augment collected data. The study will focus on three tertiary institutions in Gaborone, the capital city of Botswana. Currently, there are ten tertiary institutions in Gaborone; both privately and government owned. The outcome of this study will add to the existing body of knowledge on the issue of the practicalisation of democracy at the higher education level in Botswana. This research is therefore relevant in helping to find out if democratisation of teaching and learning has been realised in Botswana’s Institutions of higher learning. It is important to examine Botswana’s national policy on education in this way to ascertain if it has been effective in giving the country’s education system that democratic element, which is essential for a student-centered approach to the teaching and learning process.

Keywords: democratisation, higher education, learning, teaching

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Authors: Mariam Shalaby, Kayla Krause, Raisha Ismail, Daniel George

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Introduction: The Pennsylvania State College of Medicine Refugee Initiative is a student-run organization that works with eleven Syrian and Congolese refugee families. Since 2016, it has used grant funding to make weekly produce purchases at a local market, provide tutoring services, and develop trusting relationships. This case study explains how the Refugee Initiative shifted focus to face new challenges due to the COVID-19 pandemic in 2020. Methodology: When refugees who had previously attained stability found themselves unable to pay the bills, the organization shifted focus from food security to direct assistance such as applying for unemployment compensation since many had recently lost jobs. When refugee families additionally struggled to access hygiene supplies, funding was redirected to purchase them. Funds were also raised from the community to provide financial relief from unpaid rent and bills. Findings: Systemic challenges were encountered in navigating federal/state unemployment and social welfare systems, and there was a conspicuous absence of affordable, language-accessible assistance that could help refugees. Finally, as struggling public schools failed to maintain adequate English as a Second Language (ESL) education, the group’s tutoring services were hindered by social distancing and inconsistent access to distance-learning platforms. Conclusion: Ultimately, the pandemic highlighted that a charity-based arrangement is helpful but not sustainable, and challenges persist for refugee families. Based on the Refugee Initiative's experiences over the past year of the COVID-19 pandemic, several needs must be addressed to aid refugee families at this time, including: increased access to affordable and language-accessible social services, educational resources, and simpler options for grant-based financial assistance. Interventions to increase these resources will aid refugee families in need in Central Pennsylvania and internationally

Keywords: COVID-19, health, pandemic, refugees

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Mohaya Farzin, Parvin Babaei, Mohammad Rostampour

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Ghrelin plays a considerable role in important neurological effects related to food intake and energy homeostasis. As was found, regular physical activity may make available significant improvements to cognitive functions in various behavioral situations. Anxiety is one of the main concerns of the modern world, affecting millions of individuals’ health. There are contradictory results regarding ghrelin's effects on anxiety-like behavior, and the plasma level of this peptide is increased during physical activity. Here we aimed to evaluate the coincident effects of exogenous ghrelin and aerobic exercise on anxiety-like behavior and passive avoidance memory in Wistar rats. Forty-five male Wistar rats (250 ± 20 g) were divided into 9 groups (n=5) and received intra-hippocampal injections of 3.0 nmol ghrelin and performed aerobic exercise training for 8 weeks. Control groups received the same volume of saline and diazepam as negative and positive control groups, respectively. Learning and memory were estimated using a shuttle box apparatus, and anxiety-like behavior was recorded by an elevated plus-maze test (EPM). Data were analyzed by ANOVA test, and p<0.05 was considered significant. Our findings showed that the combined effect of ghrelin and aerobic exercise improves the acquisition, consolidation, and retrieval of passive avoidance memory in Wistar rats. Furthermore, it is supposed that the ghrelin receiving group spent less time in open arms and fewer open arms entries compared with the control group (p<0.05). However, exercising Wistar rats spent more time in the open arm zone in comparison with the control group (p<0.05). The exercise + Ghrelin administration established reduced anxiety (p<0.05). The results of this study demonstrate that aerobic exercise contributes to an increase in the endogenous production of ghrelin, and physical activity alleviates anxiety-related behaviors induced by intra-hippocampal injection of ghrelin. In general, exercise and ghrelin can reduce anxiety and improve memory.

Keywords: anxiety, ghrelin, aerobic exercise, learning, passive avoidance memory

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Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Walter Beck

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Jharkhand is newly constituted 28th State in the eastern part of India which is known for the oldest settlement of the indigenous people. In the State of Jharkhand in which broadly three language family are found namely, Austric, Dravidian, and Indo-European. Ex-Mundari, kharia, Ho Santali come from the Austric Language family. Kurukh, Malto under Dravidian language family and Nagpuri Khorta etc. under Indo-European language family. There are 32 Indigenous Communities identified as Scheduled Tribe in the State of Jharkhand. Santhal, Munda, Kahria, Ho and Oraons are some of the major Tribe of the Jharkhand state. Jharkhand has a Rich Cultural heritage which includes Folk art, folklore, Folk Dance, Folk Music, Folk Songs for which diversity can been seen from place to place, season to season and all traditional Culture and practices. The languages as well as the songs are vulnerable to dominant culture and hence needed to be protected. The collection and documentation of these songs in their natural setting adds significant contribution to the conservation and propagation of the cultural elements. This paper reflects to bring out the Originality of the Collected Songs from remote areas of the plateau of Sothern Jharkhand as a rich intangible Cultural heritage of the Country. The research was done through participatory observation. In this research project more than 100 songs which were never documented before.

Keywords: cultural heritage, India, indigenous people, songs, languages

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

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Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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Authors: Eyibo Ebengeobong Eddie, Halil Zafer Alibaba

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The neglect of classroom acoustics is dominant in most educational facilities, meanwhile, hearing and listening is the learning process in this kind of facilities. A classroom should therefore be an environment that encourages listening, without an obstacles to understanding what is being taught. Although different studies have shown teachers to complain that noise is the everyday factor that causes stress in classroom, the capacity of individuals to understand speech is further affected by Echoes, Reverberation, and room modes. It is therefore necessary for classrooms to have an ideal acoustics to aid the intelligibility of students in the learning process. The influence of these acoustical parameters on learning and teaching in schools needs to be further researched upon to enhance the teaching and learning capacity of both teacher and student. For this reason, there is a strong need to provide and collect data to analyse and define the suitable quality of classrooms needed for a learning environment. Research has shown that acoustical problems are still experienced in both newer and older schools. However, recently, principle of acoustics has been analysed and room acoustics can now be measured with various technologies and sound systems to improve and solve the problem of acoustics in classrooms. These acoustic solutions, materials, construction methods and integration processes would be discussed in this paper.

Keywords: classroom, acoustics, materials, integration, speech intelligibility

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Authors: Jian Wang

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Teachers’ lesson-based discussions presume central to their effective learning to teach. Whether and to what extent such discussions offer opportunities for teachers to learn to teach effectively is worth a careful empirical examination. This study examines this assumption by drawing on lesson-based discussions and relevant curriculum materials from Chinese teachers in three urban schools. Their lesson-based discussions consistently focused on pedagogical content knowledge and offered specific and reasoned suggestions for teachers to refine their teaching practices. The mandated curriculum and their working language-mediated their lesson-based discussions.

Keywords: Chinese teachers, curriculum materials, lesson discussion, mathematics instruction

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Authors: Emmanuel Ukpe, S. M. F. D. Syed Mustapha

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Trust in an organization has been perceived as one of the key factors behind knowledge sharing, mainly in an unstructured work environment. In an informal working environment, to instill trust among individuals is a challenge and even more in the virtual environment. The study has contributed in developing the framework for building trust in an unstructured organization in performing knowledge sharing in a virtual environment. The artifact called KAPE (Knowledge Acquisition, Processing, and Exchange) was developed for knowledge sharing for the informal organization where the framework was incorporated. It applies to Cassava farmers to facilitate knowledge sharing using web-based platform. A survey was conducted; data were collected from 382 farmers from 21 farm communities. Multiple regression technique, Cronbach’s Alpha reliability test; Tukey’s Honestly significant difference (HSD) analysis; one way Analysis of Variance (ANOVA), and all trust acceptable measures (TAM) were used to test the hypothesis and to determine noteworthy relationships. The results show a significant difference when there is a trust in knowledge sharing between farmers, the ones who have high in trust acceptable factors found in the model (M = 3.66 SD = .93) and the ones who have low on trust acceptable factors (M = 2.08 SD = .28), (t (48) = 5.69, p = .00). Furthermore, when applying Cognitive Expectancy Theory, the farmers with cognitive-consonance show higher level of trust and satisfaction with knowledge and information from KAPE, as compared with a low level of cognitive-dissonance. These results imply that the adopted trust model KAPE positively improved knowledge sharing activities in an informal environment amongst rural farmers.

Keywords: trust, knowledge, sharing, knowledge acquisition, processing and exchange, KAPE

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Authors: Kunle Oparinde, Rachel Matteau-Matsha, Felix Awung

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In recent times, the issue of gender-based violence against women in South Africa is prevalent in headlines due to the high rate of attacks directed towards women. Ranging from teenagers to adults, women are continuously targeted indiscriminately in what is seemingly becoming a prolonged cycle in the country. To this end, human rights activists, organisations, and political leaders have managed to somewhat verbally condemn the atrocious acts. Further, interested people in South Africa, through walks and protests, have continued to speak against the swinging violence against women in the country. The thrust in this study is to explore and analyse how discourse (language) has been employed as a resounding voice against gender violence in the country. Through a purposive sampling of materials employed during walks and protests, collected from online sources, we examine how language is being used to combat and confront the issue of gender violence viz-a-viz how it continues to serve as a crucial tool in repelling gender violence.

Keywords: gender, violence, language, discourse, resistance

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