Search results for: federated learning system

Authors: Temitayo Ogunsanwo

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Problem-solving is an important way of learning way of learning because it propels children to use previous experiences to deal with new situations. The purpose of this study is to find out the attitude of pre-service teachers to problem-solving as a strategy for promoting early mathematics learning in children. This qualitative study employed a descriptive design to investigate the experiences of twenty second-year undergraduate early childhood education Pre-service teachers in a teaching practice and their attitude towards five-year-old children’s problem-solving strategies in mathematics. Pre-service teachers were exposed to different strategies for teaching children how to solve problems in mathematics. They were taken through a micro teaching in class using different strategies to teach problem-solving in different topics in the five-year-old mathematics curriculum. The students were then made to teach five-year-olds in neighbouring schools for three weeks, working in pairs, observing and recording children’s problem-solving activities and strategies. After the three weeks exercise, their experiences and attitude towards children’s problem-solving strategies were collected using open-ended questions and analysed in themes. Findings were discussed.

Keywords: attitude, early mathematics learning, experience, pre-service teachers, problem-solving, strategies

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Authors: Iliya Musa Adamu

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This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.

Keywords: expert system, forward chaining rule based system, network, troubleshooting

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Authors: N. Bolong, J. Makinda, I. Saad

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Laboratory activities have produced benefits in student learning. With current drives of new technology resources and evolving era of education methods, renewal status of learning and teaching in laboratory methods are in progress, for both learners and the educators. To enhance learning outcomes in laboratory works particularly in engineering practices and testing, learning via hands-on by instruction may not sufficient. This paper describes and compares techniques and implementation of traditional (expository) with open-ended laboratory (problem-based) for two consecutive cohorts studying environmental laboratory course in civil engineering program. The transition of traditional to problem-based findings and effect were investigated in terms of course assessment student feedback survey, course outcome learning measurement and student performance grades. It was proved that students have demonstrated better performance in their grades and 12% increase in the course outcome (CO) in problem-based open-ended laboratory style than traditional method; although in perception, students has responded less favorable in their feedback.

Keywords: engineering education, open-ended laboratory, environmental engineering lab

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Authors: Hebe Wong, Luz Fernandez Calventos

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Tandem language learning, a language exchange process based on the principles of autonomy and reciprocity, provides opportunities for interlocutors to learn each other’s language by communicating online or face-to-face. While much attention has been paid to the process and outcomes of tandem learning via email, little has been discussed about the effectiveness of face-to-face tandem learning on language and culture exchange for university students. The LACTS (Language and Culture Tandem Scheme), an 8-week project, was set up to study students’ perceptions of conducting tandem learning to assist their language and culture exchange. Students of both post-graduate and undergraduate programmes (N=103) from a Hong Kong SAR university were put in groups of 4 to 6 according to their availability and language preferences and met for an hour a week. While sample task sheets on a range of topics were provided to assist the language exchange, all groups were encouraged to take charge of their meeting format and choose their own topics. At the end of the project, a 19-item questionnaire, which included both open-and closed-ended questions investigating students’ perceptions of reciprocal teaching and cultural exchange, was administered. Thirty-minute individual interviews were conducted to elicit students’ views and experiences in the LACTS activities. Quantitative and qualitative data analysis showed that most students agreed that the project had enhanced their cultural awareness and helped create an inclusive and participatory learning environment. Significant differences were found in students’ confidence in speaking their targeted language after joining the scheme. The interviews also provided rich data on the variety of formats and leadership patterns in student-led meetings, which could shed light on student autonomy and future tandem language learning projects.

Keywords: autonomy, reciprocity, tandem language learning, university students

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Authors: Arpit Rai

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In this work, we propose PatchMix, a semi-supervised method for pre-training visual representations. PatchMix mixes patches of two images and then solves an auxiliary task of predicting the label of each patch in the mixed image. Our experiments on the CIFAR-10, 100 and the SVHN dataset show that the representations learned by this method encodes useful information for transfer to new tasks and outperform the baseline Residual Network encoders by on CIFAR 10 by 12% on ResNet 101 and 2% on ResNet-56, by 4% on CIFAR-100 on ResNet101 and by 6% on SVHN dataset on the ResNet-101 baseline model.

Keywords: self-supervised learning, representation learning, computer vision, generalization

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: Sara Bilal, Abdi Omar Shuriye, Raihan Othman

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Numerical Methods is a course that can be conducted using workshops and group discussion. This study has been implemented on undergraduate students of level two at the Faculty of Engineering, International Islamic University Malaysia. The Numerical Method course has been delivered to two Sections 1 and 2 with 44 and 22 students in each section, respectively. Systematic steps have been followed to apply the student centered learning approach in teaching Numerical Method course. Initially, the instructor has chosen the topic which was Euler’s Method to solve Ordinary Differential Equations (ODE) to be learned. The students were then divided into groups with five members in each group. Initial instructions have been given to the group members to prepare their subtopics before meeting members from other groups to discuss the subtopics in an expert group inside the classroom. For the time assigned for the classroom discussion, the setting of the classroom was rearranged to accommodate the student centered learning approach. Teacher strength was by monitoring the process of learning inside and outside the class. The students have been assessed during the migrating to the expert groups, recording of a video explanation outside the classroom and during the final examination. Euler’s Method to solve the ODE was set as part of Question 3(b) in the final exam. It is observed that none of the students from both sections obtained a zero grade in Q3(b), compared to Q3(a) and Q3(c). Also, for Section 1(44 students), 29 students obtained the full mark of 7/7, while only 10 obtained 7/7 for Q3(a) and no students obtained 6/6 for Q3(c). Finally, we can recommend that the Numerical Method course be moved toward more student-centered Learning classrooms where the students will be engaged in group discussion rather than having a teacher one man show.

Keywords: teacher centered learning, student centered learning, mathematic, numerical methods

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Authors: A.Knox

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Student diversity in postgraduate classes puts major challenges on educators seeking to encourage student engagement and desired to learn outcomes. This paper outlines the impact of a set of teaching initiatives aimed at addressing challenges associated with teaching and learning in an environment characterized by diversity in the student cohort. The study examines postgraduate students completing the core capstone unit within a specialized business degree. Although relatively small, the student cohort is highly diverse in terms of cultural backgrounds represented, prior learning and/or qualifications, as well as duration and type of work experience relevant to the degree, is completed. The wide range of cultures, existing knowledge and experience create enormous challenges with respect to students’ learning needs and outcomes. Subsequently, a suite of teaching innovations has been adopted to enhance curriculum content/delivery and the design of assessments. This paper explores the impact of these specific teaching and learning practices, examining the ways they have supported students’ diverse needs and enhanced students’ learning outcomes. Data from surveys and focus groups are used to assess the effectiveness of these practices. The results highlight the effectiveness of peer-assisted learning, cultural competence-building, and advanced assessment options in addressing diverse student needs and enhancing student engagement and learning outcomes. These findings suggest that such practices would benefit students’ learning in environments marked by diversity in the student cohort. Specific recommendations are offered for other educators working with diverse classes.

Keywords: assessment design, curriculum content, curriculum delivery, student diversity

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Authors: Efuwape Bamidele Michael, Efuwape Oluwabunmi Asake

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Nigeria has some deep rural environments that seem secluded from most of the technological amenities for convenient living and learning. Most schools in such environments are yet to be captured in the educational applications of technological facilities. The study explores the facilitation of basic technology instructions with micro-learning and gamification among students in rural Junior Secondary Schools in the Ipokia Local Government Area (LGA) of Ogun state. The study employed a quasi-experimental design, specifically the pre-test and post-test control group design. The study population comprised all Junior Secondary School students in the LGA. Four Junior Secondary Schools in the LGA were randomly selected for the study and classified into two experimental and two control groups. A total sample of 156 students participated in the study. Basic Technology Achievement Test and Junior School Students’ Attitudinal Scale were instruments used for data collection in the study with reliability coefficients of 0.87 and 0.83, respectively. Five hypotheses guided the study and were tested using Analysis of covariance (ANCOVA) at a 0.05 level of significance. Findings from the study established significant marginal differences in students’ academic performance (F = 644.301; p = .000), learning retention (F = 583.335; p = .000), and attitude towards learning basic technology (F = 491.226; p = .000) between the two groups in favour of the experimental group exposed to micro-learning and gamification. As a recommendation, adequate provisions for inclusive educational practices with technological applications should be ensured for all children irrespective of location within the country, especially to encourage effective learning in rural schools.

Keywords: inclusive education, educational technology, basic technology students, rural areas in Nigeria, micro-learning, gamification

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

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Authors: Naoko Ono, Junko Kato

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According to the Ministry of Justice, 9,044,000 foreigners visited Japan in 2010. The number of foreign residents in Japan was over 2,134,000 at the end of 2010. Further, medical tourism has emerged as a new area of business. Against this background, language barriers put the health of foreigners in Japan at risk, because they have difficulty in accessing health care and communicating with medical professionals. Medical interpreting training is urgently needed in response to language problems resulting from the rapid increase in the number of foreign workers in Japan over recent decades. Especially, there is a growing need in medical settings in Japan to speak international languages for communication, with Tokyo selected as the host city of the 2020 Summer Olympics. Due to the limited number of practical activities on medical interpreting, it is difficult for learners to acquire the interpreting skills. In order to eliminate the shortcoming, a web-based English-Japanese medical interpreting training system was developed. We conducted a literature review to identify learning contents, core competencies for medical interpreters by using Pubmed, PsycINFO, Cochrane Library, and Google Scholar. Selected papers were investigated to find core competencies in medical interpreting. Eleven papers were selected through literature review indicating core competencies for medical interpreters. Core competencies in medical interpreting abstracted from the literature review, showed consistency in previous research whilst the content of the programs varied in domestic and international training programs for medical interpreters. Results of the systematic review indicated five core competencies: (a) maintaining accuracy and completeness; (b) medical terminology and understanding the human body; (c) behaving ethically and making ethical decisions; (d) nonverbal communication skills; and (e) cross-cultural communication skills. We developed an e-leaning program for training medical interpreters. A Web-based Medical Interpreter Training Program which cover these competencies was developed. The program included the following : online word list (Quizlet), allowing student to study online and on their smartphones; self-study tool (Quizlet) for help with dictation and spelling; word quiz (Quizlet); test-generating system (Quizlet); Interactive body game (BBC);Online resource for understanding code of ethics in medical interpreting; Webinar about non-verbal communication; and Webinar about incompetent vs. competent cultural care. The design of a virtual environment allows the execution of complementary experimental exercises for learners of medical interpreting and introduction to theoretical background of medical interpreting. Since this system adopts a self-learning style, it might improve the time and lack of teaching material restrictions of the classroom method. In addition, as a teaching aid, virtual medical interpreting is a powerful resource for the understanding how actual medical interpreting can be carried out. The developed e-learning system allows remote access, enabling students to perform experiments at their own place, without being physically in the actual laboratory. The web-based virtual environment empowers students by granting them access to laboratories during their free time. A practical example will be presented in order to show capabilities of the system. The developed web-based training program for medical interpreters could bridge the gap between medical professionals and patients with limited English proficiency.

Keywords: e-learning, language education, moodle, medical interpreting

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Authors: Kemal Izci

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Assessment forms an important part of instruction. Assessment that aims to support learning is known as formative assessment and it contributes student’s learning gain and motivation. However, teachers rarely use assessment formatively to aid their students’ learning. Thus, reviewing the factors that limit or support teachers’ practices of formative assessment will be crucial for guiding educators to support prospective teachers in using formative assessment and also eliminate limiting factors to let practicing teachers to engage in formative assessment practices during their instruction. The study, by using teacher’s change environment framework, reviews literature on formative assessment and presents a tentative model that illustrates the factors impacting teachers’ adoption of formative assessment in their teaching. The results showed that there are four main factors consisting personal, contextual, resource-related and external factors that influence teachers’ practices of formative assessment.

Keywords: assessment practices, formative assessment, teacher education, factors for use of formative assessment

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Authors: Aadiv Shah, Hari Nair, Vedant Mittal, Alice Cheeran

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Present-day agricultural practices such as blanket spraying not only lead to excessive usage of pesticides but also harm the overall crop yield. This paper introduces an algorithm to optimize the traversal of an unmanned aerial vehicle (UAV) in constrained environments. The proposed system focuses on the agricultural application of targeted spraying for locust elimination. Given a satellite image of a farm, target zones that are prone to locust swarm formation are detected through the calculation of the normalized difference vegetation index (NDVI). This is followed by determining the optimal path for traversal of a UAV through these target zones using the proposed algorithm in order to perform pesticide spraying in the most efficient manner possible. Unlike the classic travelling salesman problem involving point-to-point optimization, the proposed algorithm determines an optimal path for multiple regions, independent of its geometry. Finally, the paper explores the idea of implementing reinforcement learning to model complex environmental behaviour and make the path planning mechanism for UAVs agnostic to external environment changes. This system not only presents a solution to the enormous losses incurred due to locust attacks but also an efficient way to automate agricultural practices across the globe in order to improve farmer ergonomics.

Keywords: locust, NDVI, optimization, path planning, reinforcement learning, UAV

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Md. Minhazul Islam, Shah Ashisul Abed Nipun, Majharul Islam, Md. Abdur Rakib Rahat, Jonayet Miah, Salsavil Kayyum, Anwar Shadaab, Faiz Al Faisal

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The target of this research is to predict Myocardial Infarction using unsupervised Machine Learning algorithms. Myocardial Infarction Prediction related to heart disease is a challenging factor faced by doctors & hospitals. In this prediction, accuracy of the heart disease plays a vital role. From this concern, the authors have analyzed on a myocardial dataset to predict myocardial infarction using some popular Machine Learning algorithms K-Means and Hierarchical Clustering. This research includes a collection of data and the classification of data using Machine Learning Algorithms. The authors collected 345 instances along with 26 attributes from different hospitals in Bangladesh. This data have been collected from patients suffering from myocardial infarction along with other symptoms. This model would be able to find and mine hidden facts from historical Myocardial Infarction cases. The aim of this study is to analyze the accuracy level to predict Myocardial Infarction by using Machine Learning techniques.

Keywords: Machine Learning, K-means, Hierarchical Clustering, Myocardial Infarction, Heart Disease

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Authors: Ida Srdić, Luka Mandić, LidijaMandić

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Digitization and intensive use of tablets, smartphones, the internet, mobile, and web applications have massively disrupted our habits, and the way audiences (especially youth) consume content. To introduce educational content in games and animations, and at the same time to keep it interesting and compelling for kids, is a challenge. In our work, we are comparing the different possibilities and potentials that digital games could provide to successfully mitigate direct connection with education. We analyze the main directions and educational methods in game-based learning and the possibilities of interactive modeling through questionnaires for user experience and requirements. A pre and post-quantitative survey will be conducted in order to measure levels of objective knowledge as well as the games perception. This approach enables quantitative and objective evaluation of the impact the game has on participants. Also, we will discuss the main barriers to the use of games in education and how games can be best used for learning.

Keywords: Bloom’s taxonomy, epistemic games, learning objectives, virtual learning environments

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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Authors: Saman Khairani

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Assessment is a pivotal component of the teaching and learning process, serving as a critical tool for evaluating student progress, diagnosing learning needs, and informing instructional decisions. In the context of English Language Teaching (ELT), effective assessment practices are essential to promote meaningful learning experiences and foster continuous improvement in language proficiency. This paper delves into various assessment strategies, explores associated challenges, and highlights best practices for assessing student learning in ELT. The paper begins by examining the diverse forms of assessment, including formative assessments that provide timely feedback during the learning process and summative assessments that evaluate overall achievement. Additionally, alternative methods such as portfolios, self-assessment, and peer assessment play a significant role in capturing various aspects of language learning. Aligning assessments with learning objectives is crucial. Educators must ensure that assessment tasks reflect the desired language skills, communicative competence, and cultural awareness. Validity, reliability, and fairness are essential considerations in assessment design. Challenges in assessing language skills—such as speaking, listening, reading, and writing—are discussed, along with practical solutions. Constructive feedback, tailored to individual learners, guides their language development. In conclusion, this paper synthesizes research findings and practical insights, equipping ELT practitioners with the knowledge and tools necessary to design, implement, and evaluate effective assessment practices. By fostering meaningful learning experiences, educators contribute significantly to learners’ language proficiency and overall success.

Keywords: ELT, formative, summative, fairness, validity, reliability

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Authors: Adil Ishag

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Diglossia emerges in a situation where two distinctive varieties of a language are used alongside within a certain community. In this case, one is considered as a high or standard variety and the second one as a low or colloquial variety. Arabic is an extreme example of a highly diglossic language. This diglossity is due to the fact that Arabic is one of the most spoken languages and spread over 22 Countries in two continents as a mother tongue, and it is also widely spoken in many other Islamic countries as a second language or simply the language of Quran. The geographical variation between the countries where the language is spoken and the duality of the classical Arabic and daily spoken dialects in the Arab world on the other hand; makes the Arabic language one of the most diglossic languages. This paper tries to investigate this phenomena and its relation to learning Arabic as a first and second language.

Keywords: Arabic language, diglossia, first and second language, language learning

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Authors: Fernanda Laureti T. Ferreira, Kazuo Nishimoto

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This paper presents a summary of the experience on videoconferencing tools that have been used to teach regular classes during this pandemic period in educational institutions in São Paulo, which tools and applications are most used and the challenges related to this mode of delivery. At this moment, the massive online education is not a choice of students or a structured development of education system, but a solution that emerged to attend urgent needs and it presents the opportunity to teach and learning available for the most students in this single time of social isolation that forced among others, this significant change for education, students, teachers, institutions and families. Distance education enables synchronous and asynchronous mode classes, and even though the current circumstances generate discomfort and uncertainty, on the other hand, there is a chance to promote a 'learning to learn'. The videoconference is a preferred choice of schools because synchronous mode to give more interaction between a group of students and teachers, but this mode requires specifics teacher competencies and skills, in addition to equipment and provision of adequate internet signal for all participants of the process. The approach is making use of known technical information about video conference tools and the results of search answered by a group of students, teachers, schools, and parents. The results presented refer to the perspectives of students and parents as respondents.

Keywords: distance education, interaction on education, online classes, synchronous e-learning, videoconference

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Amita Singha

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The project describes the scope of magnetic braking. The potential applications of the braking system can be a de-accelerating system to increase the safety of an elevator or any guided rail transportation system.

Keywords: boost and buck converter, electromagnet, elevator, ferromagnetic material, sensor, solenoid, timer

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Authors: Vilma Zydziunaite, Monika Kelpsiene

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In early childhood and preschool education, play has an important role in learning and cognitive processes. In the context of a changing world, personal autonomy and the use of technology are becoming increasingly important for the development of a wide range of learner competencies. By integrating technology into learning environments, the educational reality is changed, promoting unusual learning experiences for children through play-based activities. Alongside this, teachers are challenged to develop encouragement and motivation strategies that empower children to act independently. The aim of the study was to reveal the changes in the roles and experiences of teachers in the application of AR technology for the enrichment of the learning process. A quantitative research approach was used to conduct the study. The data was collected through an electronic questionnaire. Participants: 319 teachers of 5-6-year-old children using AR technology tools in their educational process. Methods of data analysis: Cronbach alpha, descriptive statistical analysis, normal distribution analysis, correlation analysis, regression analysis (SPSS software). Results. The results of the study show a significant relationship between children's learning and the educational process modeled by the teacher. The strongest predictor of child learning was found to be related to the role of the educator. Other predictors, such as pedagogical strategies, the concept of AR technology, and areas of children's education, have no significant relationship with child learning. The role of the educator was found to be a strong determinant of the child's learning process. Conclusions. The greatest potential for integrating AR technology into the teaching-learning process is revealed in collaborative learning. Teachers identified that when integrating AR technology into the educational process, they encourage children to learn from each other, develop problem-solving skills, and create inclusive learning contexts. A significant relationship has emerged - how the changing role of the teacher relates to the child's learning style and the aspiration for personal leadership and responsibility for their learning. Teachers identified the following key roles: observer of the learning process, proactive moderator, and creator of the educational context. All these roles enable the learner to become an autonomous and active participant in the learning process. This provides a better understanding and explanation of why it becomes crucial to empower the learner to experiment, explore, discover, actively create, and foster collaborative learning in the design and implementation of the educational content, also for teachers to integrate AR technologies and the application of the principles of shared leadership. No statistically significant relationship was found between the understanding of the definition of AR technology and the teacher’s choice of role in the learning process. However, teachers reported that their understanding of the definition of AR technology influences their choice of role, which has an impact on children's learning.

Keywords: teacher, learner, augmented reality, collaboration, shared leadership, preschool education

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Authors: Mukadder Baran, Mustafa Sözbilir

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The purpose of this paper is to investigate the applicabillity of the Context- and Problem-Based Learning (CPBL) in general chemistry course to the subject of “Thermodynamics” but also the influence of CPBL on students’ achievement, retention of knowledge, their interest, attitudes, motivation and problem-solving skills. The study group included 13 freshman students who were selected with the sampling method appropriate to the purpose among those taking the course of General Chemistry within the Program of Medical Laboratory Techniques at Hakkari University. The application was carried out in the Spring Term of the academic year of 2012-2013. As the data collection tool, Lesson Observation form were used. In the light of the observations held, it was revealed that CPBL increased the students’ intragroup and intergroup communication skills as well as their self-confidence and developed their skills in time management, presentation, reporting, and technology use; and that they were able to relate chemistry to daily life. Depending on these findings, it could be suggested that the area of use of CPBL be widened; that seminars related to constructive methods be organized for teachers. In this way, it is believed that students will not be passive in the group any longer. In addition, it was concluded that in order to avoid the negative effects of the socio-cultural structure on the education system, research should be conducted in places where there is socio-cultural obstacles, and appropriate solutions should be suggested and put into practice.

Keywords: chemistry, education, science, context-based learning

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

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Authors: Tahir Mehmood, Mumtaz Akhter

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The global need for conflict management is greater now in the early 21st century than ever before. According to UNESCO, half of the world’s 195 countries will have to expand their stock of educationist significantly, some by tens of thousands, if the goal development targets are desired to achieve. Socioeconomic inequities, political instability, demographic changes and crises such as the HIV/AIDs epidemic have engendered huge shortfalls in teacher supply and low teacher quality in many developing countries. Education serves as back bone in development process. Open learning and distance education programs are serving as pivotal part of development process. It is now clear that ‘bricks and mortar’ approaches to expanding teacher education may not be adequate if the current and projected shortfalls in teacher supply and low teacher quality are to be properly addressed. The study is designed to measure the perceptions of teaching learning community about conflict management with special reference to open and distance learning. It was descriptive study which targeted teachers, students, community members and experts. Data analysis was carried out by using statistical techniques served by SPSS. Findings reflected that audience perceives open and distance learning as change agent and as development tool. It is noticed that target audience has driven prominent performance by using facility of open and distance learning.

Keywords: conflict management, open and distance learning, teachers, students

Procedia PDF Downloads 395

Authors: Hatib Shabbir

Abstract:

Student support services play an important role in providing technical and motivational support to distance learner. ICT based systems have improved the efficiency and effectiveness of support services. In distance education, students being at distant require quick responses from their institution. In the manual system, it is practically hard to give prompt response to each and every student, so as a result student has to suffer a lot. The best way to minimize inefficiencies is to use automated systems. This project involves the development of centralized automated software that would not only replace the manual degree issuance system of 1.3 million students studying at AIOU but also provide online tracking to all the students applying for Degrees. DTS is also the first step towards the paperless culture which is adopted by the major organizations of the world. DTS would not only save university cost but also save students cost and time too by conveying all the information/objection through email and SMS. Moreover, DTS also monitors the performance of each and every individual working in the exam department AIOU and generates daily, monthly and yearly reports of every individual which helps a lot in continuous performance monitoring of the employees.

Keywords: aiou dts, dts aiou, dts, degree tracking aiou

Procedia PDF Downloads 204

Authors: Olubukola Olumuyiwa Tokede, Dominic D. Ahiaga-Dagbui, John Morrison

Abstract:

The project environment in construction has been widely criticised for its inability to learn from experience effectively. As each project is bespoke, learning is ephemeral, as it is often confined within its bounds and seldom assimilated with others that are being delivered in the project environment. To engender learning across construction projects, collaborative contractual arrangements, such as alliancing and partnering, have been embraced to aid the transferability of lessons across projects. These cooperative arrangements, however, tend to be costly, and hence construction organisations could revert to less expensive traditional procurement approaches after successful collaborative project delivery. This research, therefore, seeks to assess the lessons-learned in a post-alliance contractual framework. Using a case-study approach, we examine the experiences of a public sector authority who engaged a project facilitator to foster learning during the delivery of a significant piece of critical infrastructure. It was found that the facilitator enabled optimal learning outcomes in post-alliance contractual frameworks by attenuating the otherwise adversarial relationship between clients and contractors. Further research will seek to assess the effectiveness of different knowledge-brokering agencies in construction projects.

Keywords: facilitation, knowledge-brokering, learning, projects

Procedia PDF Downloads 119

Authors: Mohammed Sabri Ali Akresh

Abstract:

The modern technologies and developments in computer and Global Positioning System (GPS) as well as Geographic Information System (GIS) and total station TS. This paper presents a new proposal for coordinates system by a harmonic equations “United projections”, which have five projections (Mercator, Lambert, Russell, Lagrange, and compound of projection) in one zone coordinate system width 14 degrees, also it has one degree for overlap between zones, as well as two standards parallels for zone from 10 S to 45 S. Also this paper presents two cases; first case is to compare distances between a new coordinate system and UTM, second case creating local coordinate system for the city of Sydney to measure the distances directly from rectangular coordinates using projection of Mercator, Lambert and UTM.

Keywords: harmonic equations, coordinate system, projections, algorithms, parallels

Procedia PDF Downloads 457

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

Abstract:

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

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

Procedia PDF Downloads 140