Search results for: L2 language learning

Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: Aroona Hashmi

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An economic recession can lead people to feel more insecure about their financial situation. The series of events leading into a recession can be especially distressing for Educated Youth. One of the most salient factors linking economic recession to psychological distress is unemployment. It is proved that a large number of educated young people are facing higher unemployment rate in Pakistan. Young people are likely to get frustrated at the lack of opportunities made available to them. If the young population increases more rapidly than job opportunities, then number of unemployment is likely to increase. The aim of present study was to investigate the relationship between economic instability, growing rate of aggression and frustration among educated youth. The study aimed to find out the impact of increased economic instability on the learning abilities of the students. Data was gathered from six university students of Punjab, Pakistan. The sample of the study consisted of three hundred male and female university students. The data was analyzed by applying Chi -square test. The results of the research indicate that there is a significant relationship between low household income and growing rate of aggression among educated youth. The increasing trend of economic instability significantly influences the learning abilities of the students. The study concludes that feeling of deprivation produce frustration and could be expressed through aggression. Therefore, if factors that are responsible for youth unemployment in Pakistan are addressed, psychological effects will be reduced. The right way of tackling the youth bulge is to turn the youth into a productive workforce. There is a dire need to transform the education system to societal needs. At the same time creating demand for the young workforce is achieved through dynamic changes in the economic structure.

Keywords: psychological effects, economic recession, educated youth, environmental factors

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Authors: İsmail Seçer

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Although depression and anxiety disorders are considered to be adult disorders, the evidence obtained from several studies conducted recently shows that the roots of depression and anxiety disorders go back to childhood years. Thus, it is thought that analyzing depressive symptoms and anxiety disorders observed in the childhood is an important necessity. In the direction of the problem status of the study, the purpose of this study is to adapt anxiety and depression questionnaire for children into Turkish culture and analyze the psychometric characteristics of it on clinical and nonclinical samples separately. The study is a descriptive survey research. The study was conducted on two different sample groups, clinical and nonclinical. The clinical sample is formed of 205 individuals and the nonclinical sample is formed of 630 individuals. Through the study, anxiety and depression questionnaire for children, anxiety sensitivity index and obsessive compulsive disorder questionnaire for children were used. Experts’ opinions were asked to provide language validity of the scale. Confirmatory factor analysis and criterion-related validity to analyze construct validity and internal consistency and split-half reliability analyses were done for reliability. In the direction of experts’ opinions, construct validity of the scale was analyzed with simple confirmatory factor analysis and it was determined that the model fit of the two-factor structure of the scale gives good fit on both the clinical and nonclinical samples after determining that the language validity of the scale is provided. In criterion-related validity, it was determined that there are positive and significant relations between anxiety and depression questionnaire for children and anxiety sensitivity and obsessive compulsive disorder. The results of internal consistency and half-split reliability analyses also show that the scale has adequate reliability value. It can be said that depression and anxiety questionnaire for children which was adapted to determine depressive symptoms and anxiety disorders observed in childhood has adequate reliability and validity values and it can be used in future studies. It can be recommended that the psychometric characteristics of the scale can be analyzed and reported on new samples in the future studies.

Keywords: scale adapting, construct validity, confirmatory factor analysis, childhood depression

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Authors: Kathaleeya Chanda

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The schools under the Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn in Nakhonnayok Educational Service Area Office are the small schools, situated in a remote and undeveloped area.Thus, the school-age youth didn’t have or have fewer opportunities to study at the higher education level which can lead to many social and economic problems. This study aims to solve these educational issues of the schools, under The Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn, Nakhonnayok Educational Service Area Office, by the development of teachers, so that teachers could develop teaching and learning system with the ultimate goal to increase students’ academic achievement, increase the educational opportunities for the youth in the area, and help them learn happily. 154 in-service teachers from 22 schools and 4 different districts in Nakhonnayok participated in this teacher training. Most teachers were satisfied with the training content and the trainer. Thereafter, the teachers were given the test to assess the skills and knowledge after training. Most of the teachers earned a score higher than 75%. Accordingly, it can be concluded that after attending the training, teachers have a clear understanding of the contents. After the training session, the teachers have to write a lesson plan that is integrated or adapted to the Sufficiency Economy Philosophy. The teachers can either adopt intradisciplinary or interdisciplinary integration according to their actual teaching conditions in the school. Two weeks after training session, the researchers went to the schools to discuss with the teachers and follow up the assigned integrated lesson plan. It was revealed that the progress of integrated lesson plan could be divided into 3 groups: 1) the teachers who have completed the integrated lesson plan, but are concerned about the accuracy and consistency, 2) teachers who almost complete the lesson plan or made a great progress but are still concerned, confused in some aspects and not fill in the details of the plan, and 3), the teachers who made few progress, are uncertain and confused in many aspects, and may had overloaded tasks from their school. However, a follow-up procedure led to the commitment of teachers to complete the lesson plan. Regarding student learning assessment, from an experiment teaching, most of the students earned a score higher than 50 %. The rate is higher than the one from actual teaching. In addition, the teacher have assessed that the student is happy, enjoys learning, and providing a good cooperates in teaching activities. The students’ interview about the new lesson plan shows that they are happy with it, willing to learn, and able to apply such knowledge in daily life. Integrated lesson plan can increases the educational opportunities for youth in the area.

Keywords: sufficiency, economy, philosophy, integrated education syllabus

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Authors: Rizky Oktaviana

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The main purpose of studying lies in improving students’ understanding. Teachers usually use written test to measure students’ understanding about learning material especially mathematical learning material. This common method actually has a lack point, such that in mathematics content, written test only show procedural steps to solve mathematical problems. Therefore, teachers unable to see whether students actually understand about mathematical concepts and the relation between concepts or not. One of the best tools to observe students’ understanding about the mathematical concepts is concept map. The goal of this research is to describe junior high school students understanding about mathematical concepts through Concept Maps based on the difference of mathematical ability. There were three steps in this research; the first step was choosing the research subjects by giving mathematical ability test to students. The subjects of this research are three students with difference mathematical ability, high, intermediate and low mathematical ability. The second step was giving concept mapping training to the chosen subjects. The last step was giving concept mapping task about the function to the subjects. Nodes which are the representation of concepts of function were provided in concept mapping task. The subjects had to use the nodes in concept mapping. Based on data analysis, the result of this research shows that subject with high mathematical ability has formal understanding, due to that subject could see the connection between concepts of function and arranged the concepts become concept map with valid hierarchy. Subject with intermediate mathematical ability has relational understanding, because subject could arranged all the given concepts and gave appropriate label between concepts though it did not represent the connection specifically yet. Whereas subject with low mathematical ability has poor understanding about function, it can be seen from the concept map which is only used few of the given concepts because subject could not see the connection between concepts. All subjects have instrumental understanding for the relation between linear function concept, quadratic function concept and domain, co domain, range.

Keywords: concept map, concept mapping, mathematical concepts, understanding

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Raul G. Angeles

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The Philippine government instituted major reforms in its educational system. The Department of Education pushes the K to 12 program that makes kindergarten mandatory and adds two years of senior high school to the country's basic education. In essence, the students’ stay in basic education particularly those who are supposedly going to college is extended. The majority of the students expressed that they will be taking the Academic Track of the Senior High School curriculum specifically the Science, Technology, Engineering and Mathematics (STEM) and General Academic (GA) strands. Almost certainly, instruction should match the students' styles and thus through this descriptive study a city survey was conducted to explore the teaching strategies preferences of junior high school students and teachers who will be promoted to senior high school during the Academic Year 2016-2017. This study was conducted in selected public and private secondary schools in Metro Manila. Questionnaires were distributed to students and teachers; and series of follow-up interviews were also carried out to generate additional information. Preferences of students are centered on employing innovations such as technology, cooperative and problem-based learning. While the students will still be covered by basic education their interests in science are sparking to a point where the usual teaching styles may no longer work to them and for that cause, altering the teaching methods is recommended to create a teacher-student style matching. Other effective strategies must likewise be implemented.

Keywords: curriculum development, effective teaching strategies, problem-based learning, senior high school, science education, technology

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Authors: Haozheng Luo, Ruiyang Qin

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People with visual impairments urgently need assistance, not only on the fundamental tasks such as guiding and retrieving objects but on the advanced like picturing the new environments. More than a guiding dog, they might want such devices that can provide linguistic interaction. Building on this idea, we aim to study the interaction between the robot agent and visually impaired people. In our research, we are going to develop a robot agent that will be able to analyze the test environment and answer the participants’ questions. We also will study the relevant issues regarding the interaction between human beings and the robot agents to figure out which and how the factors will affect the interaction.

Keywords: HRI, video question answering, visual question answering, natural language processing

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Authors: Brennan Lodge

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Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLM’s (Large Language Models) is exciting, such models do have their downsides. LLM’s cannot easily expand or revise their memory, and they can’t straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

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Authors: Dalila Lino

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The power of play for learning and development in early childhood education is beyond question. The main goal of this study is to analyse how three contemporary early childhood pedagogical approaches, the High Scope, the Modern School Movement (MEM) and the Pedagogy of Participation integrate play in their curriculum development. From this main goal the following objectives emerged: (i) to characterize how play is integrated in the daily routine of the pedagogical approaches under study; (ii) to analyse the teachers’ role during children’s playing situations; (iii) to identify the types of play that children are more often involved. The methodology used is the qualitative approach and is situated under the interpretative paradigm. Data is collected through semi-structured interviews to 30 preschool teachers and through observations of typical daily routines. The participants are 30 Portuguese preschool classrooms attending children from 3 to 6 years and working with the High Scope curriculum (10 classrooms), the MEM (10 classrooms) and the Pedagogy of Participation (10 classrooms). The qualitative method of content analysis was used to analyse the data. To ensure confidentiality, no information is disclosed without participants' consent, and the interviews were transcribed and sent to the participants for a final revision. The results show that there are differences how play is integrated and promoted in the three pedagogical approaches. The teachers’ role when children are at play varies according the pedagogical approach adopted, and also according to the teachers’ understanding about the meaning of play. The study highlights the key role that early childhood curriculum models have to promote opportunities for children to play, and therefore to be involved in meaningful learning.

Keywords: curriculum models, early childhood education, pedagogy, play

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Authors: J. Congalton, K. Logan, B. Crump

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Software is a critical aspect of modern life. However it is costly to develop and industry initiatives have focused on reducing costs and improving the productivity. Increasing, software is being developed in teams, and with greater globalization and migration, the teams are becoming more ethnically diverse. This study investigated whether diversity in terms of ethnicity impacted on the productivity of software development. Project managers of software development teams were interviewed. The study found that while some issues did exist due to language problems, when project managers created an environment of trust and friendliness, diversity made a positive contribution to productivity.

Keywords: diversity, project management, software development, team work

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Authors: Michelle Bulawan, Mei-Hua Chen

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Reading comprehension is crucial for acquiring information, analyzing critically, and achieving academic proficiency. However, there is a lack of growth in reading comprehension skills beyond fourth grade. The developmental shift from "learning to read" to "reading to learn" occurs around this stage. Factual knowledge and diverse views in articles enhance reading comprehension abilities. Nevertheless, some face difficulties due to evolving textual requirements, such as expanding vocabulary and using longer, more complex terminology. Most research on reading strategies has been conducted at the tertiary and secondary levels, while few have focused on the elementary levels. Furthermore, the use of character, ask, problem, solution (CAPS) charts in teaching reading has also been hardly explored. Thus, the researcher decided to explore the facilitation of active reading strategies through the CAPS chart and address the following research questions: a) What differences existed in elementary EFL learners' reading competency among those who engaged in active reading strategies and those who did not? b) What are the learners’ metacognitive skills of those who engage in active reading strategies and those who do not, and what are their effects on their reading competency? c) For those participants who engage in active reading activities, what are their perceptions about incorporating active reading activities into their English classroom learning? Two groups of elementary EFL learners, each with 18 students of the same level of English proficiency, participated in this study. Group A served as the control group, while Group B served as the experimental group. Two teachers also participated in this research; one of them was the researcher who handled the experimental group. The treatment lasts for one whole semester or seventeen weeks. In addition to the CAPS chart, the researcher also used the metacognitive awareness of reading strategy inventory (MARSI) and a ten-item, five-point Likert scale survey.

Keywords: active reading, EFL learners, metacognitive skills, reading competency, student’s perception

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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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: Aleksandra Majewska

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The subject of this article is phrasemes with the component 'water' in Polish and Russian. The purpose of the study is to analyse the collocations from the point of view of lexis and semantics. The material for analysis was extracted from phraseological dictionaries of Polish and Russian. From the point of view of lexis, an analysis was made of the inflectional component 'water' in phrasal expressions in both languages. Then, the phrasemes were divided into their corresponding semantic groups. That division became the subject of another comparative analysis in a further step. Finally, the functioning of some phrasemes compounds in the contexts of modern Polish and Russian was shown.

Keywords: lingustic, language, phraseme, polish and Russian

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Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

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Authors: Diane M. Bender

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In design education, professional education is delivered in a studio, where students learn and understand their discipline. This learning methodology culminates in a final review, where students present their work before instructors and invited reviewers, known as jurors. These jurors are recognized experts who add a wide diversity of opinions in their feedback to students. This feedback can be provided in multiple formats, mainly a verbal critique of the work. To better understand how these expert reviewers prepare for a studio review, a survey was distributed to reviewers at a multi-disciplinary design school within the United States. Five design disciplines are involved in this case study: architecture, graphic design, industrial design, interior design, and landscape architecture. Respondents (n=122) provided information about if and how they received training on how to critique and participate in a final review. Common forms of training included mentorship, modeled behavior from other designers/past professors, workshops on critique from the instructing faculty prior to the crit session, and by being a practicing design professional. Respondents also gave feedback about how much the instructor provided course materials prior to the review in order to better prepare for student interaction. Finally, respondents indicated if they had interaction, and in what format, with students prior to the final review. Typical responses included participation in studio desk crits, a midterm jury member, meetings with students, and email or social media correspondence. While the focus of this study is the studio review, the findings are equally applicable to other disciplines. Suggestions will be provided on how to improve the preparation of guests in the learning process and how their interaction can positively influence student engagement.

Keywords: critique, design, education, evaluation, juror

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Authors: Aysegul Evren Yapicioglu

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The social roles and responsibilities expected from citizens are increasing due to changing global living conditions. Science education is expected to prepare conscious and sensitive students. Because today’s students are the adults of future. Precondition of this task is Teacher Education. In the past decade, one of the most important research field is socioscientific issues. This study deals with advantages and disadvantages of socioscientific issue based instruction in science classroom according to pre-service science teachers’ views. A case study approach that is one of the qualitative research design was used to explore their views. Fourteen pre-service science teachers participated to instruction process. Dolphinariums, Kyoto Protocol, genetically modified organisms, recyclable black bags’ benefits and damages, genetic tests, alternative energy sources and organ donation are examples of socioscientific issues, which were taught through activities in a special teaching course. Diaries and focus group interview were used as data collection tools. As a result of the study, the advantages of socioscientific issue based instruction in science classroom comprise of six sub-categories which are multi-skilling, social awareness development of thinking, meaningful learning, character and professional development, contribution of scientific literacy whereas disadvantages of this instruction process are challenges teachers and students, limitations of teaching and learning process in pre-service science teachers’ perspectives. Finally, this study contributes to science teachers and researchers to overcome disadvantages and benefit from the advantage of socioscientific issue based instruction in science classroom.

Keywords: science education, socioscientific issues, socioscientific issue based instruction, pre-service science teacher

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Authors: Diana Santiago, Tania Lisboa, Sophie Lee, Alexander P. Demos, Monica C. S. Vasconcelos

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Memorization has long been recognized as an arduous and anxiety-evoking task for musicians, and yet, it is an essential aspect of performance. Research shows that musicians are often not taught how to memorize. While memorization and practice strategies of professionals have been studied, little research has been done to examine how student musicians learn to practice and memorize music in different cultural settings. We present the process of developing and testing a questionnaire of music memorization and musical practice for student musicians in the UK and Brazil. A survey was developed for a cross-cultural research project aiming at examining how young orchestral musicians (aged 7–18 years) in different learning environments and cultures engage in instrumental practice and memorization. The questionnaire development included members of a UK/US/Brazil research team of music educators and performance science researchers. A pool of items was developed for each aspect of practice and memorization identified, based on literature, personal experiences, and adapted from existing questionnaires. Item development took the varying levels of cognitive and social development of the target populations into consideration. It also considered the diverse target learning environments. Items were initially grouped in accordance with a single underlying construct/behavior. The questionnaire comprised three sections: a demographics section, a section on practice (containing 29 items), and a section on memorization (containing 40 items). Next, the response process was considered and a 5-point Likert scale ranging from ‘always’ to ‘never’ with a verbal label and an image assigned to each response option was selected, following effective questionnaire design for children and youths. Finally, a pilot study was conducted with young orchestral musicians from diverse learning environments in Brazil and the United Kingdom. Data collection took place in either one-to-one or group settings to facilitate the participants. Cognitive interviews were utilized to establish response process validity by confirming the readability and accurate comprehension of the questionnaire items or highlighting the need for item revision. Internal reliability was investigated by measuring the consistency of the item groups using the statistical test Cronbach’s alpha. The pilot study successfully relied on the questionnaire to generate data about the engagement of young musicians of different levels and instruments, across different learning and cultural environments, in instrumental practice and memorization. Interaction analysis of the cognitive interviews undertaken with these participants, however, exposed the fact that certain items, and the response scale, could be interpreted in multiple ways. The questionnaire text was, therefore, revised accordingly. The low Cronbach’s Alpha scores of many item groups indicated another issue with the original questionnaire: its low level of internal reliability. Several reasons for each poor reliability can be suggested, including the issues with item interpretation revealed through interaction analysis of the cognitive interviews, the small number of participants (34), and the elusive nature of the construct in question. The revised questionnaire measures 78 specific behaviors or opinions. It can be seen to provide an efficient means of gathering information about the engagement of young musicians in practice and memorization on a large scale.

Keywords: cross-cultural, memorization, practice, questionnaire, young musicians

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Authors: Yanbin Cai

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L2 Translation, or translation out of one’s native language, is often adopted for Chinese classical literature. The purpose of this study is to investigate problems arisen in this process and the strategies different from translation by native speakers. Texts selected for this study is a Ming dynasty novel, Fengshen Yanyi, written by Xu Zhonglin and translated into English by Gu Zhizhong. Translated proper names and dialogues are analyzed, followed with a review on translator’s shifting focus on text selection. The result reveals not the problem of linguistic incompetence or cultural negligence, but translation strategies adopted for specific purposes and target readers.

Keywords: L2 translation, Chinese literature, literature translation, Fengshen Yanyi

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Authors: Bruno Gontijo Batista

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This paper analyzes how the Socially Aware Design (SAwD) and the Value-oriented and Culturally Informed Approach (VCIA) design model can be used to develop an edutainment game for children with Attention Deficit Hyperactivity Disorder (ADHD). The SAwD approach seeks a design that considers new dimensions in human-computer interaction, such as culture, aesthetics, emotional and social aspects of the user's everyday experience. From this perspective, the game development was VCIA model-based, including the users in the design process through participatory methodologies, considering their behavioral patterns, culture, and values. This is because values, beliefs, and behavioral patterns influence how technology is understood and used and the way it impacts people's lives. This model can be applied at different stages of design, which goes from explaining the problem and organizing the requirements to the evaluation of the prototype and the final solution. Thus, this paper aims to understand how this model can be used in the development of an edutainment game for children with ADHD. In the area of education and learning, children with ADHD have difficulties both in behavior and in school performance, as they are easily distracted, which is reflected both in classes and on tests. Therefore, they must perform tasks that are exciting or interesting for them, once the pleasure center in the brain is activated, it reinforces the center of attention, leaving the child more relaxed and focused. In this context, serious games have been used as part of the treatment of ADHD in children aiming to improve focus and attention, stimulate concentration, as well as be a tool for improving learning in areas such as math and reading, combining education and entertainment (edutainment). Thereby, as a result of the research, it was developed, in a participatory way, applying the VCIA model, an edutainment game prototype, for a mobile platform, for children between 8 and 12 years old.

Keywords: ADHD, edutainment, SAwD, VCIA

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Danielle Schneider, Ying Xie

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Middle school science, technology, engineering, and math (STEM) teachers experience an exceptional challenge in the expectation to incorporate curricula that builds strong spatial reasoning skills on rudimentary geometry concepts. Because spatial ability is so closely tied to STEM students’ success, researchers are tasked to determine effective instructional practices that create an authentic learning environment within the immersive virtual reality learning environment (IVRLE). This study looked to investigate the effect of the IVRLE on middle school STEM students’ spatial reasoning skills as a methodology to benefit the STEM middle school students’ spatial reasoning skills. This experimental study was comprised of thirty 7th-grade STEM students divided into a treatment group that was engaged in an immersive VR platform where they engaged in building an object in the virtual realm by applying spatial processing and visualizing its dimensions and a control group that built the identical object using a desktop computer-based, computer-aided design (CAD) program. Before and after the students participated in the respective “3D modeling” environment, their spatial reasoning abilities were assessed using the Middle Grades Mathematics Project Spatial Visualization Test (MGMP-SVT). Additionally, both groups created a physical 3D model as a secondary measure to measure the effectiveness of the IVRLE. The results of a one-way ANOVA in this study identified a negative effect on those in the IVRLE. These findings suggest that with middle school students, virtual reality (VR) proved an inadequate tool to benefit spatial relation skills as compared to desktop-based CAD.

Keywords: virtual reality, spatial reasoning, CAD, middle school STEM

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Authors: A. F. Alves, L. Schmidt, J. Ferrao

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Portugal is one of the more vulnerable European countries to the impacts of climate change. These include: temperature increase; coastal sea level rise; desertification and drought in the countryside; and frequent and intense extreme weather events. Hence, adaptation strategies to climate change are of great importance. This is what was addressed by ClimAdaPT.Local. This policy-oriented project had the main goal of developing 26 Municipal Adaptation Strategies for Climate Change, through the identification of local specific present and future vulnerabilities, the training of municipal officials, and the engagement of local communities. It is intended to be replicated throughout the whole territory and to stimulate the creation of a national network of local adaptation in Portugal. Supported by methodologies and tools specifically developed for this project, our paper is based on the surveys, training and stakeholder engagement workshops implemented at municipal level. In an 'adaptation-as-learning' process, these tools functioned as a social-learning platform and an exercise in knowledge and policy co-production. The results allowed us to explore the nature of local vulnerabilities and the exposure of gaps in the context of reappraisal of both future climate change adaptation opportunities and possible dysfunctionalities in the governance arrangements of municipal Portugal. Development issues are highlighted when we address the sectors and social groups that are both more sensitive and more vulnerable to the impacts of climate change. We argue that a pluralistic dialogue and a common framing can be established between them, with great potential for transformational adaptation. Observed climate change, present-day climate variability and future expectations of change are great societal challenges which should be understood in the context of the sustainable development agenda.

Keywords: adaptation, ClimAdaPT.Local, climate change, Portugal, sustainable development

Procedia PDF Downloads 181

Authors: Michael Howard

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The growing popularity of electric vehicles in the United States requires an ever-expanding infrastructure of commercial DC fast charging stations. The U.S. Department of Energy estimates 33,355 publicly available DC fast charging stations as of September 2023. In 2017, 115,370 gasoline stations were operating in the United States, much more ubiquitous than DC fast chargers. Range anxiety is an important impediment to the adoption of electric vehicles and is even more relevant in underserved regions in the country. The peer-to-peer energy marketplace helps fill the demand by allowing private home and small business owners to rent their 240 Volt, level-2 charging facilities. The existing, publicly accessible outlets are wrapped with a Cloud-connected microcontroller managing security and charging sessions. These microcontrollers act as Edge devices communicating with a Cloud message broker, while both buyer and seller users interact with the framework via a web-based user interface. The database storage used by the marketplace framework is a key component in both the cost of development and the performance that contributes to the user experience. A traditional storage solution is the SQL database. The architecture and query language have been in existence since the 1970s and are well understood and documented. The Structured Query Language supported by the query engine provides fine granularity with user query conditions. However, difficulty in scaling across multiple nodes and cost of its server-based compute have resulted in a trend in the last 20 years towards other NoSQL, serverless approaches. In this study, we evaluate the NoSQL vs. SQL solutions through a comparison of Google Cloud Firestore and Cloud SQL MySQL offerings. The comparison pits Google's serverless, document-model, non-relational, NoSQL against the server-base, table-model, relational, SQL service. The evaluation is based on query latency, flexibility/scalability, and cost criteria. Through benchmarking and analysis of the architecture, we determine whether Firestore can support the energy marketplace storage needs and if the introduction of a GraphQL middleware layer can overcome its deficiencies.

Keywords: non-relational, relational, MySQL, mitigate, Firestore, SQL, NoSQL, serverless, database, GraphQL

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Authors: André Melo Franco Lorena De Barros, Elida Geralda Campos

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The bilingual education has just started in Brazils public schools. This paper is a didactic sequence of biology bilingual lessons about biologic control in the Brazilian Savana. This sequence has been applied in the first year of a bilingual education program in the only public English and Portuguese bilingual high school in Brazil. The aim of this work is to develop and apply a didactic sequence capable of developing the scientific literacy through the bilingual education associated with Problem Based Learning. This didactic sequence was applied in a class of 30 students. It was divided in three lessons. In the first lesson the students were divided in groups and received a fiction Letter from a mayor explaining the problem and asking students for help. The organic soy plantation of the mayor’s is been attacked by caterpillars. The students read the text then raised hypothesis of how they could solve the problem. In the second lesson the students searched online to verify if theirs hypothesis were correct and to find answers for the question proposed. In the third lesson the groups got together and discussed about their results and wrote a final essay with the answers for the problem proposed. The tools used to acquire information about the didactic sequence were: researcher’s diary, survey, interview and essay developed by the students. Most of the initial hypothesis couldn’t answer the problem properly. By the second lesson most of the students could answer properly. During the third lesson all the groups figured out suitable answers. The forms of biological control, birds habits and transgenic were deeply studied by the students. This methodology was successful for developing the scientific literacy with most of the students and also concluded that the quality of learning is directly associated with the effort of each student during the process. [ARAÚJO, Denise Lino de. O que é (e como se faz) sequência didática. Entrepalavras, Fortaleza, v. 3, n. 3, p.322-334, jul. 2013.] [FRANCO, Aline Aparecida et al. Preferência alimentar de Anticarsia gemmatalis Hübner (Lepidoptera: Noctuidae) por cultivares de soja. Científica: Revista de Ciências Agrárias, Jaboticabal, v. 1, n. 42, p.32-38, 29 jan. 2014.] [RIBEIRO, Luis Roberto de Camargo. Aprendizagem baseada em problemas (PBL): Uma experiência no ensino superior. São Carlos: Editora da Universidade Federal de São Carlos Ribeiro, 2008. 151 p.] [TRIVELATO, Sílvia L. Frateschi; TONIDANDEL, Sandra M. Rudella. Ensino Por Investigação: Eixos Organizadores Para Sequências De Ensino De Biologia. Ensaio Pesquisa em Educação em Ciências, Belo Horizonte, v. 17, n. especial, p.97-114, nov. 2015.].

Keywords: Bilingual Education, Environmental Education, Problem Based Learning, Science education

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Authors: Tien-Ling Yeh, Jo-Han Chan

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The percentage of dual-earner couples has become higher and higher each year. Family lifestyles in Taiwan have also been changing. This fact reflects the importance of family communication and parent-child relationship. This study aimed to explore the influences of family lifestyles and accompany forms on children’s capability to solve problems. The research process included two phases: (1) literature review, to explore the characteristics of children’s capability to solve problems and methods to measure this capability; and (2) questionnaire analyses, to explore the influences of lifestyles and accompany time and forms of modern families on their children’s capability to solve problems. The questionnaires were issued in October and November, 2016. A total of 300 questionnaires were retrieved, among which 250 were valid. The findings are summarized below: -The linguistic performances of the children from families of the busy and haggling lifestyle or the intermittent childcare lifestyle were rather good. Besides being interested in learning, these children could solve problems or difficulties independently. -The capability to ‘analyze problems’ of children from families with accompanying time during 19:00-19:30 (family dinner time) or 22:00-23:30 (before bedtime) was good. When facing a complex problem, these children could identify the most important factor in the problem. When seeing a problem, they would first look for the cause. If they encountered a bottleneck while solving a problem, they would review the context of the problem and related conditions to come up with another solution. -According to the literature, learning toys with numbers and symbols to learn to read can help develop children’s logic thinking, which is helpful to solve problems. Interestingly, some study suggested that children playing with fluid constructive toys are less likely to give up what they are doing and more likely to identify problems in their daily life. Some of them can even come up with creative and effective solutions.

Keywords: accompany, lifestyle, parent-child, problem-solving

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Authors: Elena G. Diryugina, Maria A. Dovger, Maria V. Lunkina, Alexandra A. Ianchenko

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The personality development and well-being of children have become important focuses of school education and indicators of its quality. The studies show that academic success depends more on personality and motivation than on intelligence and giftedness. Those personality resources that help a person to maintain well-being both here and now and in the future constitute their personality potential. The development of schoolchildrens' personality potential can help them meet the challenges of the modern world and achieve new educational goals. At the same time, it is noted that the pedagogical factor is one of the most significant in relation to schoolchildrens' success and well-being. What is important for teachers to develop in order to make their students feel more competent and maintain well-being? As part of the Developmental Environment Programme of the Charitable Foundation ‘Investment in the Future’, a longitudinal study of the personality potential and well-being of educators and schoolchildren was conducted from 2018 to 2023. More than 2,500 teachers and over 4,000 students from Russia took part. It was found that behind a teacher's communication style, an important construct that influences the motivation of schoolchildren and the satisfaction of their basic psychological needs, is the personal potential of that teacher. Their personality potential correlates with the social-emotional development of schoolchildren in junior grades. A teacher's communication style with adolescents contributes to their academic motivation, self-esteem and satisfaction with life and learning. In addition, child well-being cannot be promoted in isolation from attention to the psychological well-being of teachers. Their social well-being and engagement are higher when they are included in professional learning communities. The results will be helpful for both positive education researchers and practitioners to identify an approach to child personality development and well-being that is achieved primarily through the personality development and well-being of school staff members and mostly teachers.

Keywords: Personality development, personality potential, schoolchildren, teaching style, well-being

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Authors: John Q. Todd

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Given that modern equipment can provide comprehensive health, status, and error condition data via built-in sensors, maintenance organizations have a new and valuable source of insight to take advantage of. This presentation will expose what these data payloads might look like and how they can be filtered, visualized, calculated into metrics, used for machine learning, and generate alerts for further action.

Keywords: condition based maintenance, equipment data, metrics, alerts

Procedia PDF Downloads 167

Authors: Aleksandra Tomic

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According to reliable sources, 4% of all websites is devoted to pornographic material, yet these estimates are often reported to be much higher. The largest internet pornography streaming website reports 21.2 billion visits in 2015 only. Considering the ubiquity of online pornography and the frequency of use, it is necessary to examine its potential influence on the construal of the sexual act and the roles of participants. Apart from the verbal and physical interactions in the pornographic movies themselves, the language in the titles of movies has the power to frame the sexual intercourse. In this study, Critical Discourse Analysis and corpus linguistics approaches will be used to examine the way the sexual intercourse and the roles of the participants are ideologically construed and perpetuated in the Internet pornography discourse. To this end, the study will explore the association between the specific morphosyntactic aspects of the references to performers of both genders, the person and the thematic role, and the gender of referred performer in the corpus of online pornographic movie titles. Distinctive collexeme analysis will be conducted to uncover possible associations between for gender of the performer denoted by the linguistic expression, and the person and thematic role assigned to it in the titles of online pornography movies. Initial results of the chi-square procedure performed on a sample of 295 online pornography movie titles on the largest pornography streaming website ‘Pornhub’ yielded significant results. The use of the three person categories was not equally distributed between genders, X2 (2, N = 106) = 32.52, p < 0.001, with female performers being referred to in the third person in 71.7% of the instances, and speaking in the first person 20.8% of the time, whereas male performers spoke in the first person 68% of the time, and were referred to in the third person in 17% of the instances. Moreover, there was a gender disparity in the assignment of thematic roles, with linguistic expressions for women being assigned the Patient role and men the Agent role in 58.8% of the cases, whereas the roles were reversed in 41.2% of the instances, X2 (1, N = 262) = 8.07633, p < 0.005. The results are discussed in terms of the ideologies surrounding female and male sexuality in the pornography discourse. Potential patterns of power imbalance, objectification, and discrimination are highlighted. Finally, the evidence from psycholinguistic studies on the influence of the language structure on event construal is related to the results of the study.

Keywords: corpus linguistics, gender studies, pornography, thematic roles

Procedia PDF Downloads 175