Search results for: module based teaching and learning

Authors: Asmaa El Harat, Toumi Hicham, Youssef Baddi

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This survey delves into the complex realm of Internet of Things (IoT) security, highlighting the urgent need for effective cybersecurity measures as IoT devices become increasingly common. It explores a wide array of cyber threats targeting IoT devices and focuses on mitigating these attacks through the combined use of deep learning and machine learning algorithms, as well as edge and cloud computing paradigms. The survey starts with an overview of the IoT landscape and the various types of attacks that IoT devices face. It then reviews key machine learning and deep learning algorithms employed in IoT cybersecurity, providing a detailed comparison to assist in selecting the most suitable algorithms. Finally, the survey provides valuable insights for cybersecurity professionals and researchers aiming to enhance security in the intricate world of IoT.

Keywords: internet of things (IoT), cybersecurity, machine learning, deep learning

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

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Authors: Elisabeth Eder

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Memorizing music plays an important role for instrumentalists and has been researched very little so far. Almost every musician is confronted with memorizing music in the course of their musical career. For numerous competitions, examinations (e.g., at universities, music schools), solo performances, and the like, memorization is a requirement. Learners are often required to learn a piece by heart but are rarely given guidance on how to proceed. This was also confirmed by Eder's preliminary study to examine the topicality and relevance of the topic, in which 111 instrumentalists took part. The preliminary study revealed a great desire for more knowledge or information about learning strategies as well as a greater sense of security when performing by heart on stage through the use of learning strategies by those musicians who use learning strategies. Eder’s research focuses on learning strategies for memorizing music. As part of a large-scale empirical study – an online questionnaire translated into 10 languages was used to conduct the study – 1091 musicians from 64 different countries described how they memorize. The participants in the study also evaluated their learning strategies and justified their choice in terms of their degree of effectiveness. Based on the study and pedagogical literature, 100 learning strategies were identified and categorized; the strategies were examined with regard to their effectiveness, and instrument-specific, age-specific, country-specific, gender-specific, and education-related differences and similarities concerning the choice of learning strategies were investigated. Her research also deals with forms and models of memory and how music-related information can be stored and retrieved and also forgotten again. A further part is devoted to the possibilities that teachers and learners have to support the process of memorization independently of learning strategies. The findings resulting from Elisabeth Eder's research should enable musicians and instrumental students to memorize faster and more confidently.

Keywords: memorizing music, learning strategies, empirical study, effectiveness of strategies

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Authors: Malak Alqaydhi

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A problem in the Saudi Arabia education system is that there is a lack of curriculum- based Social, emotional learning (SEL) teaching practices with the pedagogical concept of SEL yet to be practiced in the Kingdom of Saudi Arabia (KSA). Furthermore, voices of teachers and parents have not been captured regarding the use of SEL, particularly in preschools. The importance of this research is to help determine, with the input of teachers and mothers of preschoolers, the efficacy of a culturally adapted SEL program. The purpose of this research is to determine the most appropriate SEL intervention method to appropriately apply in the cultural context of the Saudi preschool classroom setting. The study will use a mixed method exploratory sequential research design, applying qualitative and quantitative approaches including semi-structured interviews with teachers and parents of preschoolers and an experimental research approach. The research will proceed in four phases beginning with a series of interviews with Saudi preschool teachers and mothers, whose voices and perceptions will help guide the second phase of selection and adaptation of a suitable SEL preschool program. The third phase will be the implementation of the intervention by the researcher in the preschool classroom environment, which will be facilitated by the researcher’s cultural proficiency and practical experience in Saudi Arabia. The fourth and final phase will be an evaluation to assess the effectiveness of the trialled SEL among the preschool student participants. The significance of this research stems from its contribution to knowledge about SEL in culturally appropriate Saudi preschools and the opportunity to support initiatives for Saudi early childhood educators to consider implementing SEL programs. The findings from the study may be useful to inform the Saudi Ministry of Education and its curriculum designers about SEL programs, which could be beneficial to trial more widely in the Saudi preschool curriculum.

Keywords: social emotional learning, preschool children, saudi Arabia, child behavior

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Authors: Arianna Sacerdoti

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The translation of Haiku Poetry into Latin is fundamentally experimental in nature. One of the first seminal books containing such translations, alongside translations into different modern languages, 'A Piedi Scalzi', was written by Tartamella in 2016. The results of a text-oriented study of this book will be commented upon and analyzed. The author Arianna Sacerdoti made similar translations with high school student. Such an experiment garners interest across a diverse range of disciplines such as teaching, translation studies, and classics reception studies. The methodology employed is text-oriented as the Haiku poem translations will be commented on by considering their relationship with the original. The results of this investigation, conducted within the field of experimental teaching, are expected to confirm the usefulness of this approach to the teaching of Latin and its potential to actively involve students in identifying the diachronic differences between the world of classical antiquity and the contemporary one.

Keywords: ancient latin, Haiku, translation studies, reception of classics

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Authors: Yahia A. M. AlKhoudary

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This Study presents the outcome of an investigation to evaluate the importance of autonomous learning as a means of motivation. However, very little research done in this field. Thus, the aims of this study are to ascertain the needs of the learners and to investigate their attitudes and motivation towards the mode of learning. Various suggestions made on how to improve learners’ participation in the learning process. A survey conducted on a sample group of 60 Omani College students. Self-report questionnaires and retrospective interviews conducted to find out their material-type preferences in a self-access learning context. Achieving autonomous learning system, which learners is one of the Ministry of Education goals in the Sultanate of Oman. As a result, this study presents the outcome of an investigation to evaluate the students’ performance in English as a Foreign Language (EFL). It focuses on the effect of autonomous learning that encourages students to learn English, a research conducted at Buraimi city, the Sultanate of Oman. The procedure of this investigation based on four dimensions: (1) sixty students are selected and divided into two groups, (2) pre and posttest projects are given to them, and (3) questionnaires are administered to both students who are involved in the experiment and 50 teachers (25 males and 25 females) to collect accurate data, (4) an interview with students and teachers to find out their attitude towards autonomous learning. Analysis of participants’ responses indicated that autonomous learning motivates students to learn English independently and increase the intrinsic rather than extrinsic motivation to improve their English language as a long-life active learning. The findings of this study show that autonomous learning approach is the best remedy to empower the students’ skills and overcome all relevant difficulties. They also show that secondary school teachers can fully rely on this learning approach that encourages language learners to monitor their progress, increase both learners and teachers’ motivation and ameliorate students’ behavior in the classroom. This approach is also an ongoing process, which takes time, patience and support to be lifelong learning.

Keywords: Omani, autonomous learning system, English as a Foreign Language (EFL), learning approach

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Authors: Jiangbo Shi, Zeyu Gao, Chen Li

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Nuclei segmentation is a fundamental task in digital pathology analysis and can be automated by deep learning-based methods. However, the development of such an automated method requires a large amount of data with precisely annotated masks which is hard to obtain. Training with weakly labeled data is a popular solution for reducing the workload of annotation. In this paper, we propose a novel meta-learning-based nuclei segmentation method which follows the label correction paradigm to leverage data with noisy masks. Specifically, we design a fully conventional meta-model that can correct noisy masks by using a small amount of clean meta-data. Then the corrected masks are used to supervise the training of the segmentation model. Meanwhile, a bi-level optimization method is adopted to alternately update the parameters of the main segmentation model and the meta-model. Extensive experimental results on two nuclear segmentation datasets show that our method achieves the state-of-the-art result. In particular, in some noise scenarios, it even exceeds the performance of training on supervised data.

Keywords: deep learning, histopathological image, meta-learning, nuclei segmentation, weak annotations

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Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Emmanuel Carlos De Mata Castrejón

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Music education has shown to be connected to many areas of sciences and arts, it has also been associated with several facets of human life. The many aspects around the study of music and education, make very difficult for the music educator to find a way through, even though there are lots of methods of teaching music to young children, they are different between one another and so are the students. For the music to help improve children’s development, it is necessary for the children to explore their musicality as they explore their creativity; it must be a challenging, playful, and enjoyable activity. The purpose of this investigation is to focus the music education not in the music, nor the teaching, but the children to be guided through their own musicality. The first approach to this kind of music education comes from the Active learning methods during the nineteenth century, most of which are still used around the world, sometimes with modifications to fit a certain place or type of students. This approach on children’s musicality requires some knowledge of music, pedagogy, and developmental psychology at least, but more important than the theory or the method used for music education, the focus should be on developing the student’s musicality, considering the complexity of this concept. To get this, it is needed, indeed, far more research in the topic, so this is a call for collaborative research and for interdisciplinary teams to emerge. This is a review of authors and methods in music education trying to trace a line pointing to transdisciplinary work and pursuing the development of children’s musicality.

Keywords: children, methods, music education, musicality

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Authors: Piyapat Chitpirom, Teerakiat Jareonsettasin, Chintida Vichitsophaphan

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The Foundation of Virtuous Youth was established and supported by the Crown Property Bureau, with the intention to instill goodness in Thai youth. The Centre for Educational Psychology is one of the three units under the foundation. We aim to develop programmes that can be used to improve the quality of education in schools. Translation of the King’s message in keeping with the modern research from various sources, our team create 6 programmes: (1) Teacher-Student Relationship (2) Growth Mindset (3) Socratic Teaching (4) Peer Tutoring (5) Parental Involvement (6) Inclusion. After nine months of implementing the programmes in the schools, we found that there were more cooperation between student-student, teacher-student, teacher-parent, and student-parent and the school regained trust from the community. Our ideas were accepted well by the government as our director was promoted to be the Vice Minister of Education in order to implement our programmes into national education system. We consider that the key of our success is that we do practical things. We are still continuing, improving, and learning from our work with hope that the quality of Thai education will improve in near future.

Keywords: education reform, educational psychology, effective teaching, teacher-student relationship

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Arlene Villarama, Micol Grace Guanzon, Zenaida Ramos

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This paper provides insights into teaching English as a Foreign Language in the Philippines. The authors reviewed relevant theories and literature, and provide an analysis of the issues in teaching English in the Philippine setting in the light of these theories. The authors made an investigation in Bagong Barrio National High School (BBNHS) - a public school in Caloocan City. The institution has a population of nearly 3,000 students. The performances of randomly chosen 365 respondents were scrutinised. The study regarding the success of teaching English as a foreign language to Filipino children were highlighted. This includes the respondents’ family background, surroundings, way of living, and their behavior and understanding regarding education. The results show that there is a significant relationship between demonstrative, communal, and logical areas that touch the efficacy of introducing English as a foreign Dialectal. Filipino children, by nature, are adventurous and naturally joyful even for little things. They are born with natural skills and capabilities to discover new things. They highly consider activities and work that ignite their curiosity. They love to be recognised and are inspired the most when given the assurance of acceptance and belongingness. Fun is the appealing influence to ignite and motivate learning. The magic word is excitement. The study reveals the many facets of the accumulation and transmission of erudition, in introduction and administration of English as a foreign phonological; it runs and passes through different channels of diffusion. Along the way, there are particles that act as obstructions in protocols where knowledge are to be gathered. Data gained from the respondents conceals a reality that is beyond one’s imagination. One significant factor that touches the inefficacy of understanding and using English as a foreign language is an erroneous outset gained from an old belief handed down from generation to generation. This accepted perception about the power and influence of the use of language, gives the novices either a negative or a positive notion. The investigation shows that a higher number of dislikes in the use of English can be tracked down from the belief of the story on how the English language came into existence. The belief that only the great and the influential have the right to use English as a means of communication kills the joy of acceptance. A significant notation has to be examined so as to provide a solution or if not eradicate the misconceptions that lie behind the substance of the matter. The result of the authors’ research depicts a substantial correlation between the emotional (demonstrative), social (communal), and intellectual (logical). The focus of this paper is to bring out the right notation and disclose the misconceptions with regards to teaching English as a foreign language. This will concentrate on the emotional, social, and intellectual areas of the Filipino learners and how these areas affect the transmittance and accumulation of learning. The authors’ aim is to formulate logical ways and techniques that would open up new beginnings in understanding and acceptance of the subject matter.

Keywords: accumulation, behaviour, facets, misconceptions, transmittance

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Authors: Sean Gay, Cristina Tat

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This presentation will detail how a university in Western Japan has implemented its English for Academic Purposes (EAP) program during the onset of CoViD-19 in the spring semester of 2020. In the spring semester of 2020, after a 2 week delay, all courses within the School of Policy Studies EAP Program at Kwansei Gakuin University were offered in an online asynchronous format. The rationale for this decision was not to disadvantage students who might not have access to devices necessary for taking part in synchronous online lessons. The course coordinators were tasked with consolidating the materials originally designed for face-to-face14 week courses for a 12 week asynchronous online semester and with uploading the modified course materials to Luna, the university’s network, which is a modified version of Blackboard. Based on research to determine the social and academic impacts of this CoViD-19 ERT approach on the students who took part in this EAP program, this presentation explains how future curriculum design and implementation can be managed in a post-CoViD world. There are a wide variety of lessons that were salient. The role of the classroom as a social institution was very prominent; however, awareness of cognitive burdens and strategies to mitigate that burden may be more valuable for teachers. The lessons learned during this period of ERT can help teachers moving forward.

Keywords: asynchronous online learning, emergency remote teaching (ERT), online curriculum design, synchronous online learning

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Authors: Vijaya Yuvaram Singh V M, Kameshwar Rao J V

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The challenge with development of neural network based methods for medical is the availability of data. Anatomical landmark detection in the medical domain is a process to find points on the x-ray scan report of the patient. Most of the time this task is done manually by trained professionals as it requires precision and domain knowledge. Traditionally object detection based methods are used for landmark detection. Here, we utilize reinforcement learning and query based method to train a single agent capable of detecting multiple landmarks. A deep Q network agent is trained to detect single and multiple landmarks present on hip and shoulder from x-ray scan of a patient. Here a single agent is trained to find multiple landmark making it superior to having individual agents per landmark. For the initial study, five images of different patients are used as the environment and tested the agents performance on two unseen images.

Keywords: reinforcement learning, medical landmark detection, multi target detection, deep neural network

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Authors: Yanyan Wang

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This paper on second language teaching and learning uses conversation analysis (CA) approach and focuses on how second language learners of Chinese do repair when making clarification requests. In order to demonstrate their behavior in interaction, a comparison was made to study the differences between native speakers of Chinese with non-native speakers of Chinese. The significance of the research is to make second language teachers and learners aware of repair and how to seek clarification. Utilizing the methodology of CA, the research involved two sets of naturally occurring recordings, one of native speaker students and the other of non-native speaker students. Both sets of recording were telephone talks between students and teachers. There were 50 native speaker students and 50 non-native speaker students. From multiple listening to the recordings, the parts with repairs for clarification were selected for analysis which included the moments in the talk when students had problems in understanding or hearing the speaker and had to seek clarification. For example, ‘Sorry, I do not understand ‘and ‘Can you repeat the question? ‘were the parts as repair to make clarification requests. In the data, there were 43 such cases from native speaker students and 88 cases from non-native speaker students. The non-native speaker students were more likely to use repair to seek clarification. Analysis on how the students make clarification requests during their conversation was carried out by investigating how the students initiated problems and how the teachers repaired the problems. In CA term, it is called other-initiated self-repair (OISR), which refers to student-initiated teacher-repair in this research. The findings show that, in initiating repair, native speaker students pay more attention to mutual understanding (inter-subjectivity) while non-native speaker students, due to their lack of language proficiency, pay more attention to their status of knowledge (epistemic) switch. There are three major differences: 1, native Chinese students more often initiate closed-class OISR (seeking specific information in the request) such as repeating a word or phrases from the previous turn while non-native students more frequently initiate open-class OISR (not specifying clarification) such as ‘sorry, I don’t understand ‘. 2, native speakers’ clarification requests are treated by the teacher as understanding of the content while non-native learners’ clarification requests are treated by teacher as language proficiency problem. 3, native speakers don’t see repair as knowledge issue and there is no third position in the repair sequences to close repair while non-native learners take repair sequence as a time to adjust their knowledge. There is clear closing third position token such as ‘oh ‘ to close repair sequence so that the topic can go back. In conclusion, this paper uses conversation analysis approach to compare differences between native Chinese speakers and non-native Chinese learners in their ways of conducting repair when making clarification requests. The findings are useful in future Chinese language teaching and learning, especially in teaching pragmatics such as requests.

Keywords: conversation analysis (CA), clarification request, second language (L2), teaching implication

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Authors: Mercedes Rodriguez Sanchez, Laura Luceño Casals

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With the rise of social media, creative people and brands everywhere are constantly generating content. The students with Bachelor's Degrees in Fashion Design use platforms such as Instagram or TikTok to look for inspiration and entertainment, as well as a way to develop their own ideas and share them with a wide audience. Information and Communications Technologies (ICT) have become a central aspect of higher education, virtually affecting every aspect of the student experience. Following the current trend, during the first semester of the second year, a collaborative project across two subjects –Design Management and History of Fashion Design– was implemented. After an introductory class focused on the relationship between fashion and cinema, as well as a brief history of 20th-century fashion, the students freely chose a work team and an iconic look from a movie costume. They researched the selected movie and its sociocultural context, analyzed the costume and the work of the designer, and studied the style, fashion magazines and most popular films of the time. Students then redesigned and recreated the costume, for which they were compelled to recycle the materials they had available at home as an unavoidable requirement of the activity. Once completed the garment, students delivered in-class, team-based presentations supported by the final design, a project summary poster and a making-of video, which served as a documentation tool of the costume design process. The methodologies used include Challenge-Based Learning (CBL), debates, Internet research, application of Information and Communications Technologies, and viewing clips of classic films, among others. After finishing the projects, students were asked to complete two electronic surveys to measure the acquisition of transversal and specific competencies of each subject. Results reveal that this activity helped the students' knowledge acquisition, a deeper understanding of both subjects and their skills development. The classroom dynamic changed. The multidisciplinary approach encouraged students to collaborate with their peers, while educators were better able to keep students' interest and promote an engaging learning process. As a result, the activity discussed in this paper confirmed the research hypothesis: it is positive to propose innovative teaching projects that combine academic research with playful learning environments.

Keywords: cinema, cooperative learning, fashion design, higher education, upcycling

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Authors: Eiko Takaoka, Yoshiyuki Fukushima, Koichiro Hirose, Tadashi Hasegawa

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Although all high school students in Japan are required to learn informatics, many of them do not learn this topic sufficiently. In response to this situation, we propose a support package for high school informatics classes. To examine what students learned and if they sufficiently understood the context of the lessons, a questionnaire survey was distributed to 186 students. We analyzed the results of the questionnaire and determined the weakest units, which were “basic computer configuration” and “memory and secondary storage”. We then developed a package for teaching these units. We propose that our package be applied in high school classrooms.

Keywords: computer science unplugged, computer science outreach, high school curriculum, experimental evaluation

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Authors: Supranee Wattanasin

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The objectives of this research are to find and collect the knowledge in order to transmit the food wisdom of Salaya community. The research is qualitative tool to gather the data. Phase 1: Collect and analyze related literature review on food wisdom including documents about Salaya community to have a clear picture on Salaya community context. Phase 2: Conduct an action research, stage a people forum to exchange knowledge in food wisdom of Salaya community. Learning stage on cooking, types, and benefits of the food wisdom of Salaya community were also set up, as well as a people forum to find ways to transmit and add value to the food wisdom of Salaya community. The result shows that Salaya old market community was once a marketplace located by Mahasawat canal. The old market had become sluggish due to growing development of land transportation. This had affected the ways of food consumption. Residents in the community chose 3 menus that represent the community’s unique food: chicken green curry, desserts in syrup and Khanom Sai-Sai (steamed flour with coconut filling). The researcher had the local residents train the team on how to make these meals. It was found that people in the community transmit the wisdom to the next generation by teaching and telling from parents to children. ‘Learning through the back door’ is one of the learning methods that the community used and still does.

Keywords: transmission, food wisdom, Salaya, cooking

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Authors: Christodoulakis Georgios, Kiourti Elisavet

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The Covid-19 pandemic has affected millions of people on a global scale, while lockdowns and quarantine measures were adopted periodically by a vast number of countries. These peculiar socio-historical conditions have led to the growth of participation in online environments. At the same time, the official educational bodies of many countries have been forced, for the first time at least for Greece and Cyprus, to switch to distance learning methods throughout the educational levels. However, this has not been done without issues, both in the technological and functional level, concerning the tools and the processes. Video games are the finest example of simulations of distance learning problem-solving environments. They incorporate different semiotic modes (e.g., a combination of image, sound, texts, gesture) while all this takes place in social and cultural constructed contexts. Players interact in the game environment in terms of spaces, objects, and actions in order to accomplish their goals, solve its problems, and win the game. In addition, players are engaging in layering literacies, which include combinations of independent and collaborative, digital and nondigital practices and spaces acting jointly to support meaning making, including interaction among and across texts and modalities (Abrams, 2017). From this point of view, players are engaged in collaborative, self-directed, and interest-based experiences by going back and forth and around gameplay. Within this context, this paper investigates the way Einstown, a greek serious video game, functions as an effective distance learning environment for teaching Greek as a second|foreign language to adults. The research methodology adopted is the case study approach using mixed methods. The participants were two adult women who are immigrants in Greece and who had zero gaming experience. The results of this research reveal that the videogame Einstown is, in fact, a digital environment of literacy through which the participants achieve active learning, cooperation, and engage in digital and non-digital literacy practices that result in improving the learning of specialized vocabulary presented throughout the gameplay.

Keywords: second/foreign language, vocabulary acquisition, literacy, serious video games

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Authors: Chanchai Supaartagorn

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Structured Query Language (SQL) is the standard de facto language to access and manipulate data in a relational database. Although SQL is a language that is simple and powerful, most novice users will have trouble with SQL syntax. Thus, we are presenting SQL generator tool which is capable of translating actions and displaying SQL commands and data sets simultaneously. The tool was developed based on Model-View-Controller (MVC) pattern. The MVC pattern is a widely used software design pattern that enforces the separation between the input, processing, and output of an application. Developers take full advantage of it to reduce the complexity in architectural design and to increase flexibility and reuse of code. In addition, we use White-Box testing for the code verification in the Model module.

Keywords: MVC, relational database, SQL, White-Box testing

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Authors: Hiesik Kim, YongBeum Kim

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Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to speed up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group(SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as Open source hardware, Gas sensor, and Bluetooth Module and algorithm controlling transmission speed is demonstrated. Experiment controlling transmission speed also is progressed by developing Android Application receiving measured data, and controlling this speed is available at the experiment result. it is important that in the future, improvement for communication algorithm be needed because few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, internet of things, transmission Speed

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Authors: Mark Archei O. Javier

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The Fourth Industrial Revolution (FIR) is a major industrial era characterized by the fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. Since this era teaches us how to thrive in the fast-paced developing world, it is important to be able to adapt. With this, there is a need to make learning and teaching in the bioscience laboratory more challenging and engaging. The goal of the research is to find out if using in silico and in vitro laboratory activities compared to the conventional conduct laboratory activities would have positive impacts on the academic performance of the learners. The potential contribution of the research is that it would improve the teachers’ methods in delivering the content to the students when it comes to topics that need laboratory activities. This study will develop a method by which teachers can provide learning materials to the students. A one-tailed t-Test for independent samples was used to determine the significant difference in the pre- and post-test scores of students. The tests of hypotheses were done at a 0.05 level of significance. Based on the results of the study, the gain scores of the experimental group are greater than the gain scores of the control group. This implies that using in silico and in vitro labs for the experimental group is more effective than the conventional method of doing laboratory activities.

Keywords: academic performance, general biology, in silico laboratory, in vivo laboratory, virtual laboratory

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

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Authors: Babajide Solomon Faloore

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This study on the comparative analysis of the performance of teachers in private and public schools was carried out in Ibadan North West Local Government Area of Oyo State. This study examined the justification for the claim that there is a difference in the performance of teachers in private and public primary schools and at the same time identified factors responsible for the difference in the performance of these teachers. A descriptive survey research design was used for the study. Data generated were analyzed using t-test and regression analysis. The findings of the study revealed that there is significance difference in the performance of teachers in private and private primary schools in Ibadan North West Local Government Area of Oyo State( t=64.09; df=459; p,.05). The findings also revealed that the method of teaching in private primary schools is significantly different from the method of teaching in public primary schools in Ibadan North West Local Government Area of Oyo State (t=73.08; df=459; p,.05). Findings revealed that school leadership and management have a significant contribution on the performance of private and public primary school teachers in Ibadan North West Local Area of Oyo State. Based on the finding, the following recommendations were made: Primary school teachers need to be motivated and rewarded for excellent performance. Primary schools should be properly equipped with teaching–aid facilities, laboratories, and libraries. The government should use the findings of this study to improve on teaching materials provided to the primary school teachers in Nigeria. Public primary schools should be designed by education planners, administrators, and government. Headmasters, proprietors, and teachers of primary schools should look inward and give a performance appraisal and evaluation of themselves from time to time based on the subject they taught. Finally, school administrators should be conscious of the way they manage the teachers in schools not only in informal situations but also in formal settings.

Keywords: private education, public education, school leadership, school management, teachers performance

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Authors: Gunmala Suri

Abstract:

The purpose of this study was to investigate the relationship between various dimensions of Knowledge Management and Learning Organizations. On the basis of the dimensions of Learning Organization, Hypothesis were formulated. Knowledge Management (KM) is taken as the independent variable and Learning Organization (LO) as a dependent variable. KM had 5 dimensions and LO had 7. For this study, a total of 92 participants took part and answered the questionnaire. The respondents were selected using Judgemental and Snowball sampling. The respondents were from SMEs in and around Chandigarh. SPSS was used to for the data analysis purposes. The results showed that the dimensions of KM had a positive influence on the dimensions of LO. The hypothesis were accepted.

Keywords: knowledge management leadership, knowledge management, learning organization, knowledge management culture

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Authors: Qaisara Parveen, M. Imran Yousuf

Abstract:

The purpose of this study was to find the effectiveness of the use of advance organizer model for enhancing meta-cognition of students in the subject of science. It was hypothesized that the students of experimental group taught through advance organizer model would show the better cognition than the students of control group taught through traditional teaching. The population of the study consisted of all secondary school students studying in government high school located in Rawalpindi. The sample of the study consisted of 50 students of 9th class of humanities group. The sample was selected on the basis of their pretest scores through matching, and the groups were randomly assigned for the treatment. The experimental group was taught through advance organizer model while the control group was taught through traditional teaching. The self-developed achievement test was used for the purpose of pretest and posttest. After collecting the pre-test score and post-test score, the data was analyzed and interpreted by use of descriptive statistics as mean and standard deviation and inferential statistics t-test. The findings indicate that students taught using advance organizers had a higher level of meta-cognition as compared to control group. Further, meta cognition level of boys was found higher than that of girls students. This study also revealed the fact that though the students at different meta-cognition level approached learning situations in a different manner, Advance organizer model is far superior to Traditional method of teaching.

Keywords: descriptive, experimental, humanities, meta-cognition, statistics, science

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Authors: Fabio Fabris, Alex A. Freitas

Abstract:

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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Authors: Humaira Irfan Khan

Abstract:

The paper explores teaching of creative writing in Pakistani classroom. The data collected from the questionnaire and focus group interview with a large public sector university’s Master of Arts in English students, who are also in-service school teachers, discovers that English teachers in Pakistan do not teach to develop the creative writing of pupils. The findings show that English teachers can define creative writing but are confused about strategies needed in rousing learners’ interest in creative writing. The teachers make their students memorise compositions from the textbooks to be reproduced in class. English teachers must be encouraged and trained to engage in activities that are essential for enhancing creative writing in schools.

Keywords: creative writing, teaching creative writing, textbooks, Pakistan

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Authors: Anirudha S. Joshi

Abstract:

The 21st century classroom is filled with a vibrant assortment of learners. In India the different socio-economic background with culturally diversified experiences need the English teacher of the teenage group to be more dynamic, innovative and competent. The boycott of conventional ways of teaching and the warm reception of modern approaches give place to the modern devices like Television. Instead of calling it an idiot? box why not a dynamic teacher utilize it for the purpose of developing the skills among the students? The teacher applies various strategies for the learners. One of them is selecting a particular popular T.V. program in the national language ‘Hindi’ and motivating the constructivist students to take part in the activities based on it. This bilingual method enables them to develop the speaking, writing and conversational skills in English in a very natural, informal and enthusiastic way.

Keywords: bilingual method, modern approaches, natural way, TV program

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

Abstract:

Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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