Search results for: community learning and development

Authors: Supranee Sittikan, Darunee Jongudomkarn, Rutja Phuphaibul

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Thai’s families with disabilities are diverse, poor economy, low education disproportionately characterized their living that includes stress and suffering. This article reports a preliminary study using a qualitative case study with six disabilities (five physical and one mental problem) Their six family caregivers who perceived they were managing well with their conditions as well. Data were collected by in-depth interviews during November-December 2017 in North-East of Thailand. Preliminary results were found factors of moving in comprised of three themes as followings Karma: the families believe that the disability happened because of bad-karma which attached to them. From the reason, the members of families have to deserve and accept it. Family attachment: the families believe in the importance of being the family so they have to take good care in one another whether happy or suffering Community support: the families can get more to received helping hands from local health care providers and community health volunteers. These activities are very important to be representative in taking the families through health accessibility, which help them face with disabling problems. Nevertheless, the study needs further exploring on other families’ and health care team's perspective in larger scales leading to develop an appropriate health care service system which can support and promote the well-being of the families living with disabilities in the future.

Keywords: families with disabilities, Karma, family attachment, community support

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Authors: Mohana Basu, Snehamanju Basu

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Urbanization has an immense impact on the holistic development of a region. In that same context, the level of women empowerment plays a significant role in the development of any region, particularly a region belonging to a developing country. The present study investigates the status of women empowerment in the Asansol Durgapur Planning Area of the state of West Bengal, India by investigating the status of women and their access to various facilities and awareness about the various governmental and non-governmental schemes meant for their elevation. Through this study, an attempt has been to made to understand the perception of the respondents on the context of women's empowerment. The study integrates multiple sources of qualitative and quantitative data collected from various reports, field-based measurements, questionnaire survey and community based participatory appraisals. Results reveal that women of the rural parts of the region are relatively disempowered due to the various restrictions imposed on them and enjoy lower socioeconomic clout than their male counterparts in spite of the several remedial efforts taken by the government and NGOs to elevate their position in the society. A considerable gender gap still exists regarding access to education, employment and decision-making power in the family and significant differences in attitude towards women are observable in the rural and urban areas. Freedom of women primarily vary according to their age group, educational level, employment and income status and also on the degree of urbanization. Asansol Durgapur Planning Area is primarily an industrial region where huge employment generation scope exists. But these disparities are quite alarming and indicate that economic development does not always usher in socially justifiable rights and access to resources for both men and women alike in its awake. In this backdrop, this study will attempt to forward relevant suggestions which can be followed for betterment of the status of women.

Keywords: development, disempowered, economic development, urbanization, women empowerment

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Authors: Omar Alshehri, Vic Lally

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This paper examined the attitudes of using social media tools to support learning at a university in Saudi Arabia. Moreover, it investigated the students’ current usage of these tools and examined the barriers they could face during the use of social media tools in the education process. Participants in this study were 42 university students. A web-based survey was used to collect data for this study. The results indicate that all of the students were familiar with social media and had used at least one type of social media for learning. It was found out that all students had very positive attitudes towards the use of social media and welcomed using these tools as a supplementary to the curriculum. However, the results indicated that the major barriers to using these tools in learning were distraction, opposing Islamic religious teachings, privacy issues, and cyberbullying. The study recommended that this study could be replicated at other Saudi universities to investigate factors and barriers that might affect Saudi students’ attitudes toward using social media to support learning.

Keywords: barriers to social media use, benefits of social media use, higher education, Saudi Arabia, social media

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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: Dalal Benboutrif

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Religion and Development relation is one of the most arguable phrases amongst politicians, philosophers, clerics, scientists, sociologists and even the public. The main objective of this research is to clarify the relations, contrasts and interactions between religion and the major types of development including social, political, economic and scientific developments, by focusing on Islam religion. A review of the literature was performed concerning religion and development relations and conflicts, by focusing on Islam religion and then the unprocessed tips of the review were characterized. Regarding clarification of the key points of the literature, three main sectors were considered in the research. The first sector of the research mainly focused on the philosophical views on religion, which were analyzed by main evaluation of three famous philosophers’ ideas: ‘Kant’, ‘Hegel’ and ‘Weber’, and then a critical discussion on Weber’s idea about Islam and development was applied. The second sector was specified to ‘Religion and Development’ and mainly discussed the role of religion in development through poverty reduction, the interconnection of religion, spirituality and social development, religious education effects on social development, and the relation of religion with political development. The third sector was specified to ‘Islam and Development’ and mainly discussed the Islamic golden age of science, major reasons of today’s backwardness (non-development) of most Islamic countries, and Quranic instructions regarding adaptability of Islam with development. The findings of the current research approved the research hypothesis as: ‘Religious instructions (included Islam) are not in conflict with development’, rather, it could have positive effects mainly on social development and it can pave the way for society to develop. Turkey was considered as a study model, as a successful developed Islamic country demonstrating the non-conflicting relation of Islam and development.

Keywords: development, Islam, philosophy, religion

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Authors: Ashish James, Anusha James

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The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

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Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

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Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

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Authors: Yonatan Sverdlov, Shimon Ullman

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Artificial neural networks encounter a notable challenge known as continual learning, which involves acquiring knowledge of multiple tasks over an extended period. This challenge arises due to the tendency of previously learned weights to be adjusted to suit the objectives of new tasks, resulting in a phenomenon called catastrophic forgetting. Most approaches to this problem seek a balance between maximizing performance on the new tasks and minimizing the forgetting of previous tasks. In contrast, our approach attempts to maximize the performance of the new task, while ensuring zero forgetting. This is accomplished through the introduction of task-specific modulation parameters for each task, and only these parameters are learned for the new task, after a set of initial tasks have been learned. Through comprehensive experimental evaluations, our model demonstrates superior performance in acquiring and retaining novel tasks that pose difficulties for other multi-task models. This emphasizes the efficacy of our approach in preventing catastrophic forgetting while accommodating the acquisition of new tasks.

Keywords: continual learning, life-long learning, neural analogies, adaptive modulation

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Authors: Peiming Li

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This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

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Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

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Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: recognition, CNN, Yi character, divergence

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Authors: Francisco A. Ribeiro Da Costa

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Who is responsible for teaching architecture; consider various ways to participate in learning, manipulating various pedagogical tools to streamline the creative process. The Architectural Design Studio (ADS) should become a holistic, systemic process responding to the complexity of our world. This essay corresponds to a deep reflection developed by the author on the teaching of architecture. The outcomes achieved are the corollary of experimentation; discussion and application of pedagogical methods that allowed consolidate the creativity applied by students. The purpose is to show the conjectures that have been considered effective in creating an intellectual environment that nurtures the subject of Architectural Design Studio (ADS), as an operational synthesis in the final stage of the degree. These assumptions, which are part of the proposed model, displaying theories and teaching methodologies that try to respect the learning process based on student learning styles Kolb, ensuring their latent specificities and formulating the structure of the ASD discipline. In addition, the assessing methods are proposed, which consider the architectural Design Studio as an operational synthesis in the teaching of architecture.

Keywords: teaching-learning, architectural design studio, architecture, education

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Authors: Francisco J. García-de-Quirós, Gianmarco Radice

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When considering small robots working in a cooperative community for Moon surface exploration, navigation and inter-nodes communication aspects become a critical issue for the mission success. For this approach to succeed, it is necessary however to deploy the required infrastructure for the robotic community to achieve efficient self-localization as well as relative positioning and communications between nodes. In this paper, an exploration mission concept in which two cooperative robotic systems co-exist is presented. This paradigm hinges on a community of reference agents that provide support in terms of communication and navigation to a second agent community tasked with exploration goals. The work focuses on the role of the agent community in charge of the overall support and, more specifically, will focus on the positioning and navigation methods implemented in RF microwave bands, which are combined with the communication services. An analysis of the different methods for range and position calculation are presented, as well as the main limiting factors for precision and resolution, such as phase and frequency noise in RF reference carriers and drift mechanisms such as thermal drift and random walk. The effects of carrier frequency instability due to phase noise are categorized in different contributing bands, and the impact of these spectrum regions are considered both in terms of the absolute position and the relative speed. A mission scenario is finally proposed, and key metrics in terms of mass and power consumption for the required payload hardware are also assessed. For this purpose, an application case involving an RF communication network in UHF Band is described, in coexistence with a communications network used for the single agents to communicate within the both the exploring agents as well as the community and with the mission support agents. The proposed approach implements a substantial improvement in planetary navigation since it provides self-localization capabilities for robotic agents characterized by very low mass, volume and power budgets, thus enabling precise navigation capabilities to agents of reduced dimensions. Furthermore, a common and shared localization radiofrequency infrastructure enables new interaction mechanisms such as spatial arrangement of agents over the area of interest for distributed sensing.

Keywords: cooperative robotics, localization, robot navigation, surface exploration

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Authors: Sakinah Idris, Femke Ten Hoeve, Kirstin Greaves-Lord

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Background: Social skills interventions are considered to be efficacious if social skills are improved as a result of an intervention. Nevertheless, the objective assessment of social skills is hindered by a lack of sensitive and validated measures. To measure the change in social skills after an intervention, questionnaires reported by parents, clinicians and/or teachers are commonly used. Observations are the most ecologically valid method of assessing improvements in social skills after an intervention. For this purpose, The Program for the Educational and Enrichment of Relational Skills (PEERS) was developed for adolescents, in order to teach them the age-appropriate skills needed to participate in society. It is an evidence-based intervention for adolescents with ASD that taught ecologically valid social skills techniques. Objectives: The current study aims to describe the development and psychometric evaluation of the Dutch Contextual Assessment of Social Skills (CASS), an observational outcome measure of social skills for adolescents with Autism Spectrum Disorder (ASD). Methods: 64 adolescents (M = 14.68, SD = 1.41, 71% boys) with ASD performed the CASS before and after a social skills intervention (i.e. PEERS or the active control condition). Each adolescent completed a 3-minute conversation with a confederate. The conversation was prompt as a natural introduction between two-unfamiliar, similar ages, opposite-sex peers who meet for the first time. The adolescent and the confederate completed a brief questionnaire about the conversation (Conversation Rating Scale). Results: Results indicated sufficient psychometric properties. The Dutch CASS has a high level of internal consistency (Cronbach's α coefficients = 0.84). Data supported the convergent validity (i.e., significant correlated with the Social Skills Improvement System (SSiS). The Dutch CASS did not significantly correlate with the autistic mannerism subscale from Social Responsiveness Scale (SRS), thus proved the divergent validity. Based on scorings made by raters who were kept blind to the time points, reliable change index was computed to assess the change in social skills. With regard to the content validity, only the learning objectives of the first two meetings of PEERS about conversational skills relatively matched with rating domains of the CASS. Due to this underrepresentation, we found an existing observational measure (TOPICC) that covers some of the other learning objectives of PEERS. TOPICC covers 22% of the learning objectives of PEERS about conversational skills, meanwhile, CASS is 45%. Unfortunately, 33% of the learning objectives of PEERS was not covered by CASS or TOPICC. Conclusion: Recommendations are made to improve the psychometric properties and content validity of the Dutch CASS.

Keywords: autism spectrum disorder, observational, PEERS, social skills

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Authors: Munirah Alaboudi

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This paper discusses a research project carried out with 12 first-year graduate students enrolled in research methods course prior to undertaking a graduate thesis during the academic year 2019. The research was designed for the objective of creating research methods course structure that embraces an individualized and activity-based approach to learning in a highly engaging group environment. This approach targeted innovating the traditional research methods lecture-based, theoretical format where students reported less engagement and limited learning. This study utilized action research methodology in developing a different approach to research methods course instruction where student performance indicators and feedback were periodically collected to assess the new teaching method. Student learning was achieved through utilizing the flipped classroom approach where students learned the material at home and classroom activities were designed to implement and experiment with the newly acquired information, with the guidance of the course instructor. Student learning in class was practiced through a series of activities based on different research methods. With the goal of encouraging student engagement, a wide range of activities was utilized including workshops, role play, mind-mapping, presentations, peer evaluations. Data was collected through an open-ended qualitative questionnaire to establish whether students were engaged in the material they were learning, and to what degree were they engaged, and to test their mastery level of the concepts discussed. Analysis of the data presented positive results as around 91% of the students reported feeling more engaged with the active learning experience and learning research by “actually doing research, not just reading about it”. The students expressed feeling invested in the process of their learning as they saw their research “gradually come to life” through peer learning and practice during workshops. Based on the results of this study, the research methods course structure was successfully remodeled and continues to be delivered.

Keywords: research methods, higher education instruction, flipped classroom, graduate education

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Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

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Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

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Authors: Kemal Izci, Ahmet Oguz Akturk

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Learning is dependent on cognitive and physical differences as well as other differences such as ethnicity, language, and culture. Furthermore, these differences also influence how students show their learning. Assessment is an integral part of learning and teaching process and is essential for effective instruction. In order to provide effective instruction, teachers need to provide equal assessment opportunities for all students to see their learning difficulties and use them to modify instruction to aid learning. Successful assessment practices are dependent upon the knowledge and value of teachers. Therefore, in order to use assessment to assess and support diverse students learning, preservice and inservice teachers should hold an appropriate understanding of equitable assessment. In order to prepare teachers to help them support diverse student learning, as a first step, this study aims to explore how preservice teachers’ understand equitable assessment. 105 preservice science teachers studying at teacher preparation program in a large university located at Eastern part of Turkey participated in the current study. A questionnaire, preservice teachers’ reflection papers and interviews served as data sources for this study. All collected data qualitatively analyzed to develop themes that illustrate preservice science teachers’ understanding of equitable assessment. Results of the study showed that preservice teachers mostly emphasized fairness including fairness in grading and fairness in asking questions not out of covered concepts for equitable assessment. However, most of preservice teachers do not show an understanding of equity for providing equal opportunities for all students to display their understanding of related content. For some preservice teachers providing different opportunities (providing extra time for non-native speaking students) for some students seems to be unfair for other students and therefore, these kinds of refinements do not need to be used. The results of the study illustrated that preservice science teachers mostly understand equitable assessment as fairness and less highlight the role of using equitable assessment to support all student learning, which is more important in order to improve students’ achievement of science. Therefore, we recommend that more opportunities should be provided for preservice teachers engage in a more broad understanding of equitable assessment and learn how to use equitable assessment practices to aid and support all students learning trough classroom assessment.

Keywords: science teaching, equitable assessment, assessment literacy, preservice science teachers

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Authors: Heba Salem

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This paper aims to share the researcher’s experience of using e-Portfolios as an assessment tool to follow up on students’ learning experiences and performance throughout the semester. It also aims at highlighting the importance of students’ self-reflection in the process of language learning. The paper begins by introducing the advanced media course, with its focus on listening and speaking skills, and introduces the students’ profiles. Then it explains the students’ role in the e-portfolio process as they are given the option to choose a listening text they studied throughout the semester and to choose a recorded oral production of their collection of artifacts throughout the semester. Students showcase and reflect on their progress in both listening comprehension and speaking. According to the research, re-listening to work given to them and to their production is a means of reflecting on both their progress and achievement. And choosing the work students want to showcase is a means to promote independent learning as well as self-expression. Students are encouraged to go back to the class learning outcomes in the process of choosing the work. In their reflections, students express how they met the specific learning outcome. While giving their presentations, students expressed how useful the experience of returning and going over what they covered to select one and going over their production as well. They also expressed how beneficial it was to listen to themselves and literally see their progress in both listening comprehension and speaking. Students also reported that they grasped more details from the texts than they did when first having it as an assignment, which coincided with one of the class learning outcomes. They also expressed the fact that they had more confidence speaking as well as they were able to use a variety of vocabulary and idiomatic expressions that students have accumulated. For illustration, this paper includes practical samples of students’ tasks and instructions as well as samples of their reflections. The results of students’ reflections coincide with what the research confirms about the effectiveness of the e-portfolios as a means of assessment. The employment of e-Portfolios has two-folded benefits; students are able to measure the achievement of the targeted learning outcomes, and teachers receive constructive feedback on their teaching methods.

Keywords: e-portfolios, assessment, self assessment, listening and speaking progress, foreign language, reflection, learning out comes, sharing experience

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Authors: Azza Taha Zaki

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Technology-enhanced teaching has been in the limelight since the 90s when educators started investigating and experimenting with using computers in the classroom as a means of building 21^st. century skills and motivating students. The concept of technology-enhanced strategies in education is kaleidoscopic! It has meant different things to different educators. For the purpose of this paper, however, it will be used to refer to the diverse technology-based strategies used to support and enrich the flipped learning process, in the classroom and outside. The paper will investigate how technology is put in the service of teaching and learning to improve the students’ learning experience as manifested in students’ attendance and engagement, achievement rates and finally, students’ projects at the end of the semester. The results will be supported by a student survey about relevant specific aspects of their learning experience in the modules in the study.

Keywords: attendance, British University, Egypt, flipped, student achievement, student-centred, student engagement, students’ projects

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Authors: Gabriel Sunday Ayayia

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The paper argues that Ubuntu, as a philosophy that emphasizes the interconnectedness of all living things and importance of community and mutual support, can be used as a social framework to address the problems of climate change and promote environmental sustainability. The research demonstrate that Ubuntu is an ideological concept that encourages collective action on climate change, with the emphasis on individual and collective commitment to taking concrete action to address the problems of climate change. The paper shows that Ubuntu can be employed as a social tool that would enhance the cultivation of shared identity and promote the sense of shared response responsibility to develop the resilience to cope with climate change. Using qualitative and quantitative methodologies, the study establishes the imperativeness of mutual support and cooperation through the lens of Ubuntu as a human-centered scalable response to the debacle of climate change. It recommends that we can build a society that values the environment and promotes sustainable practices by encouraging community involvement in sustainable initiatives by integrating Ubuntu-based principles to our decision-making processes, collaboration, leadership, human agency and governance.

Keywords: ubuntu, climate change, humanity, collective actions, community-based

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Authors: Aneia Rajiel Busmente, Renato Gunio Jr., Jazin Mautante, Denise Joy Mendoza, Raymond Benedict Tagorio, Gabriel Uy, Natalie Quinn Valenzuela, Ma. Elayza Villa, Francine Yezha Vizcarra, Sofia Madelle Yapan, Eugene Kurt Yboa

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COVID-19’s rapid spread caused a dramatic change in the nation, especially the educational system. The Department of Education was forced to adopt a practical learning platform without neglecting health, a printed modular distance learning. The Philippines' K–12 curriculum includes Statistics and Probability as one of the key courses as it offers students the knowledge to evaluate and comprehend data. Due to student’s difficulty and lack of understanding of the concepts of Statistics and Probability in Normal Distribution. The Self-Learning Module in Statistics and Probability about the Normal Distribution created by the Department of Education has several problems, including many activities, unclear illustrations, and insufficient examples of concepts which enables learners to have a difficulty accomplishing the module. The purpose of this study is to determine the effectiveness of self-learning module on the academic performance of students in the subject Statistics and Probability, it will also explore students’ perception towards the quality of created Self-Learning Module in Statistics and Probability. Despite the availability of Self-Learning Modules in Statistics and Probability in the Philippines, there are still few literatures that discuss its effectiveness in improving the performance of Senior High School students in Statistics and Probability. In this study, a Self-Learning Module on Normal Distribution is evaluated using a quasi-experimental design. STEM students in Grade 11 from National University's Nazareth School will be the study's participants, chosen by purposive sampling. Google Forms will be utilized to find at least 100 STEM students in Grade 11. The research instrument consists of 20-item pre- and post-test to assess participants' knowledge and performance regarding Normal Distribution, and a Likert scale survey to evaluate how the students perceived the self-learning module. Pre-test, post-test, and Likert scale surveys will be utilized to gather data, with Jeffreys' Amazing Statistics Program (JASP) software being used for analysis.

Keywords: self-learning module, academic performance, statistics and probability, normal distribution

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Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

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Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: pose estimation, deep learning, point cloud, bin-picking, 3D computer vision

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Authors: Violeta Juanico

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While there was a statement made by the RVM Education Ministry Commission that its strength is its Ignacian identity, shaped by the Ignacian spirituality that permeates the school community leading to a more defined RVM school culture, there has been no empirical study made in terms of a clear and convincing conceptual framework on how the RVM Educational mission is lived in the Religious of the Virgin Mary (RVM) learning institutions to the best of author’s knowledge. This dissertation is an attempt to come up with a substantive theory that supports and explains the stakeholders’ experiences with the RVM educational mission in the Philippines. Participants that represent the different stakeholders ranging from students to administrators were interviewed. The expressions and thoughts of the participants were initially coded and analyzed using the Barney Glaser’s original grounded theory methodology to find out how the RVM mission is lived in the field of education.

Keywords: catholic education, grounded theory, lived experience, RVM educational mission

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Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

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Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

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Authors: Charles Esambe Alobwede

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From the time of the biblical story of the Tower of Babel, languages as well as people have learnt to co-exist. It is obvious that when languages co-exist, there is the inevitable tendency of linguistic influence. This is because a language can either be a unifying factor or a factor of division within a given community, especially in a multicultural and multi-linguistic community where such a situation has led to socio-political and economic tension. Thus, leaders of such communities have a duty to plan and implement a language policy that will meet the needs of all members of the community in order to enhance its corporateness. The present article will focus on some of the major reasons that prompted the government of Cameroon to embark on an official bilingual policy after independence in 1961 and then evaluate the evolution of the linguistic situation. The article will equally look at the consequences, especially on a socio-political platform and what today has been termed 'the Anglophone problem' in Cameroon which has caused a fuse between the country’s minority Anglophone population and the majority Francophone administration. Data for the present article is collected from literature on the state of official bilingualism in Cameroon, newspapers articles on the prevailing situation in the country and interviews with actors on the field.

Keywords: language policy, linguistic influence, multicultural, official bilingualism, socio-political tension

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Authors: Dalila Lino

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Practicum is a central dimension of teacher education programs. Learning how to teach is, in effect, a complex process that integrates periods of observation, experimentation, reflection, planning, and evaluation in a real context of practices, providing opportunities for prospective teachers to understand the various dimensions of education and to implement the knowledge built over the theoretical courses they have taken. At the pre-service training of early childhood teachers, specialized guidance and in particular pedagogical supervision assumes a key role in the professional development of students in training. The main goal of this study is to describe and analyze the supervision process that occurs during the practicum of preschool education master programs in Portugal. The objectives of the study are: (i) to describe the cooperative process of professional development experienced by student teachers during the practicum; (ii) to identify the strengths and weaknesses of supervision process; (iii) to identify the supervision styles used by university supervisors and cooperating teachers. The methodology used is the mix-method research and data was collected through semi-structured interviews and online questionnaires. The participants are newly graduated Portuguese early childhood teachers, university supervisors and cooperating teachers. The results reveal gaps in the specialized training of cooperating teachers and university supervisors, a large number of trainees per supervisor, which makes it difficult to support students, and those interpersonal relationships between university supervisors and students and/or cooperating teachers and students interfere in the development of the supervisory processes. The study highlights the need to invest in the specialized training of university supervisors and cooperating teachers to create better opportunities to support the professional development of prospective teachers.

Keywords: mentoring, pedagogical supervision, practicum, preschool teacher education

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Authors: Ehi E. Aimiuwu

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As of 2017, many researchers in educational journals are still wondering if students are effectively and efficiently engaged in active learning in the online learning environment. The goal of this qualitative single case study and narrative research is to explore if students are actively engaged in their online learning. Seven online students in the United States from LinkedIn and residencies were interviewed for this study. Eleven online learning techniques from research were used as a framework.  Data collection tools were used for the study that included a digital audiotape, observation sheet, interview protocol, transcription, and NVivo 12 Plus qualitative software.  Data analysis process, member checking, and key themes were used to reach saturation. About 85.7% of students preferred individual grading. About 71.4% of students valued professor’s interacting 2-3 times weekly, participating through posts and responses, having good internet access, and using email.  Also, about 57.1% said students log in 2-3 times weekly to daily, professor’s social presence helps, regular punctuality in work submission, and prefer assessments style of research, essay, and case study.  About 42.9% appreciated syllabus usefulness and professor’s expertise.

Keywords: class facilitation, course management, online teaching, online education, student engagement

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Authors: G. Amariei, K. Boltes, R. Rosal, P. Leton

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Wastewater treatment plants (WWTPs) are supposed to hold an important place in the reduction of emerging contaminants, but provide an environment that has potential for the development and/or spread of adaptation, as bacteria are continuously mixed with contaminants at sub-inhibitory concentrations. Reviewing the literature, there are little data available regarding the use of adapted bacteria forming activated sludge community for toxicity assessment, and only individual validations have been performed. Therefore, the aim of this work was to study the toxicity of Triclosan (TCS) and Ibuprofen (IBU), individually and in binary combination, on adapted activated sludge (AS). For this purpose a battery of biomarkers were assessed, involving oxidative stress and cytotoxicity responses: glutation-S-transferase (GST), catalase (CAT) and viable cells with FDA. In addition, we compared the toxic effects on adapted bacteria with unadapted bacteria, from a previous research. Adapted AS comes from three continuous-flow AS laboratory systems; two systems received IBU and TCS, individually; while the other received the binary combination, for 14 days. After adaptation, each bacterial culture condition was exposure to IBU, TCS and the combination, at 12 h. The concentration of IBU and TCS ranged 0.5-4mg/L and 0.012-0.1 mg/L, respectively. Batch toxicity experiments were performed using Oxygraph system (Hansatech), for determining the activity of CAT enzyme based on the quantification of oxygen production rate. Fluorimetric technique was applied as well, using a Fluoroskan Ascent Fl (Thermo) for determining the activity of GST enzyme, using monochlorobimane-GSH as substrate, and to the estimation of viable cell of the sludge, by fluorescence staining using Fluorescein Diacetate (FDA). For IBU adapted sludge, CAT activity it was increased at low concentration of IBU, TCS and mixture. However, increasing the concentration the behavior was different: while IBU tends to stabilize the CAT activity, TCS and the mixture decreased this one. GST activity was significantly increased by TCS and mixture. For IBU, no variations it was observed. For TCS adapted sludge, no significant variations on CAT activity it was observed. GST activity it was significant decreased for all contaminants. For mixture adapted sludge the behaviour of CAT activity it was similar to IBU adapted sludge. GST activity it was decreased at all concentration of IBU. While the presence of TCS and mixture, respectively, increased the GST activity. These findings were consistent with the viability cells evaluation, which clearly showed a variation of sludge viability. Our results suggest that, compared with unadapted bacteria, the adapted bacteria conditions plays a relevant role in the toxicity behaviour towards activated sludge communities.

Keywords: adapted sludge community, mixture, PPCPs, toxicity

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Authors: Shafaq Rubab

Abstract:

One of the biggest reasons of dropouts from schools is lack of motivation and interest among the students, particularly in mathematics. Many developing countries are facing this problem and this issue is lowering the literacy rate in these developing countries. The best solution for increasing motivation level and interest among the students is using tablet game-based learning. However, a pedagogically sound game required a well-planned instructional design model to enhance learner’s attention and confidence otherwise effectiveness of the learning games suffers badly. This research aims to evaluate the impact of the pedagogically sound instructional design model on students’ motivation by using tablet game-based learning. This research was conducted among the out-of-school-students having an age range from 7 to 12 years and the sample size of two hundred students was purposively selected without any gender discrimination. Qualitative research was conducted by using a survey tool named Instructional Material Motivational Survey (IMMS) adapted from Keller Arcs model. A comparison of results from both groups’ i.e. experimental group and control group revealed that motivation level of the students taught by the game was higher than the students instructed by using conventional methodologies. Experimental group’s students were more attentive, confident and satisfied as compared to the control group’s students. This research work not only promoted the trend of digital game-based learning in developing countries but also supported that a pedagogically sound instructional design model utilized in an educational game can increase the motivation level of the students and can make the learning process a totally immersive and interactive fun loving activity.

Keywords: digital game-based learning, student’s motivation, instructional design model, learning process

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