Search results for: state of learning

Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: Takashi Shimizu, Tomoaki Hashimoto

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Controlling the flow of fluids is a challenging problem that arises in many fields. Burgers’ equation is a fundamental equation for several flow phenomena such as traffic, shock waves, and turbulence. The optimal feedback control method, so-called model predictive control, has been proposed for Burgers’ equation. However, the model predictive control method is inapplicable to systems whose all state variables are not exactly known. In practical point of view, it is unusual that all the state variables of systems are exactly known, because the state variables of systems are measured through output sensors and limited parts of them can be only available. In fact, it is usual that flow velocities of fluid systems cannot be measured for all spatial domains. Hence, any practical feedback controller for fluid systems must incorporate some type of state estimator. To apply the model predictive control to the fluid systems described by Burgers’ equation, it is needed to establish a state estimation method for Burgers’ equation with limited measurable state variables. To this purpose, we apply unscented Kalman filter for estimating the state variables of fluid systems described by Burgers’ equation. The objective of this study is to establish a state estimation method based on unscented Kalman filter for Burgers’ equation. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: observer systems, unscented Kalman filter, nonlinear systems, Burgers' equation

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Authors: Akolo Ajige

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Christian-Muslim relations had been existing for a long time in Nigeria. Despite the long standing relations between the two faith communities, there had been occasional religious crises in Nigeria (especially in Northern part of Nigeria). These crises have rendered some people homeless, left some without a family, while property worth millions of naira destroyed, and thereby putting some people in perpetual trauma. The situation seemed to be entirely different in Nasarawa State where there is relative peace between Christians and Muslims. The purpose of the study therefore was to examine Christian-Muslim relations in Nasarawa State. Its objectives were to: (i) identify the factors responsible for the peaceful coexistence between Christians and Muslims in Nasarawa State; (ii) state how they were relating in times of politics, worship, celebration of religious festivals etc; (iii) discuss how issues which could have led to crises were resolved between the two faiths, and (iv) examine the roles played by the religious leaders, traditional rulers and the media on peaceful co-existence between the Muslims and the Christians in Nasarawa State. Historical and Comparative methods were adopted in this research. Historical method helped to evaluate the history of Islam and Christianity in Nasarawa State, while comparative method was adopted to assess the extent of interaction of Muslims and Christians in the State. The study employed primary and secondary sources as tools for gathering information.

Keywords: historo-religious, christian, muslim, relations

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Authors: Armine Vahanyan

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Humanity has been still coping with the new COVID-19 pandemic. Healthcare providers, economists, psychologists, and other specialists speak about the impact of the virus on different spheres of our life. In the list of similar discussions, the impact of pandemics on global education is of utmost importance. Ideally, providing quality education services should be crucial, and the ways education programs are being adapted will determine the success or failure of the service providers. The paper aims to summarize the research touching upon the current situation of higher education in Armenia. The research includes data from official reports, surveys among education leads, faculty, and students, as well as personal observations and consideration. Through descriptive analysis, the findings of the research are being presented from various aspects. Interim results of the research unveiled two major issues in the sector of higher education in Armenia. On the one hand, the entire compulsory digitization of instruction, assessment, and grading has evoked serious gaps related to the lack of technical competencies. There is an urgent need for professional development programs that will address most of the concerns due to the shift to the online instruction mode. On the other hand, online teaching and learning require revision and adaptation of the existing curricula. Given that the content of certain programs may not be compromised, the teaching methods, the assignments, and evaluation require profound transformation, which will still be in line with course learning outcomes and student learning outcomes. The given paper focuses on the ways the mentioned issues are being addressed in Armenia. The extent of commitment for changes and adaptability to the new situation varies from the government-funded and private universities. In particular, the paper compares and contrasts activities and measures taken at the Armenian State Pedagogical University and the American University of Armenia. Thus, the Pedagogical University focused on the use of Google Classroom as the only means for teaching and learning as well as adopted the compulsory synchronous instruction mode. The American University, on the contrary, kept practicing the academic freedom, enabling both synchronous and asynchronous instruction modes, ensuring alignment of the course learning outcomes and student learning outcomes. The State University utilized the assignments and assessment, which would work for the on-campus instruction mode, while the American university employed a variety of assignments applicable for online teaching mode. The latter has suggested the utilization of multiple apps, internet sources, and online library access for a better online instant. Discussions with faculty through online forums and/or professional development workshops also facilitate restructuring and adaptation of the courses. Finally, the paper will synthesize the results of the undertaken research and will outline the e-learning perspectives and opportunities boosted by the known devastating healthcare issue.

Keywords: assessment, compulsory digitization of education services, online teaching, instruction mode, program restructuring

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Authors: Julian Thrash, Douglas Folk, Michael Ciracy, Audrey C. Tseng, Kristen M. Stromsodt, Amber Younggren, Christopher Maciolek

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The cardiopulmonary system is comprised of the heart, lungs, and many dynamic feedback mechanisms that control its function based on a multitude of variables. The next generation of cardiopulmonary medical devices will involve adaptive control and smart pacing techniques. However, testing these smart devices on living systems may be unethical and exceedingly expensive. As a solution, a comprehensive computational model of the cardiopulmonary system was implemented in Simulink. The model contains over 240 state variables and over 100 equations previously described in a series of published articles. Simulink was chosen because of its ease of introducing machine learning elements. Initial results indicate that physiologically correct waveforms of pressures and volumes were obtained in the simulation. With the development of a comprehensive computational model, we hope to pioneer the future of predictive medicine by applying our research towards the initial stages of smart devices. After validation, we will introduce and train reinforcement learning agents using the cardiopulmonary model to assist in adaptive control system design. With our cardiopulmonary model, we will accelerate the design and testing of smart and adaptive medical devices to better serve those with cardiovascular disease.

Keywords: adaptive control, cardiopulmonary, computational model, machine learning, predictive medicine

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Authors: S. Chami, J. Chauvin, T. Demarest, Stan Ng, M. Straus, W. Jahner

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Biometrics tools such as fingerprint and iris are widely used in industry to protect critical assets. However, their vulnerability and lack of robustness raise several worries about the protection of highly critical assets. Biometrics based on Electrocardiographic (ECG) signals is a robust identification tool. However, most of the state-of-the-art techniques have worked on clinical signals, which are of high quality and less noisy, extracted from wearable devices like a smartwatch. In this paper, we are presenting a complete machine learning pipeline that identifies people using ECG extracted from an off-person device. An off-person device is a wearable device that is not used in a medical context such as a smartwatch. In addition, one of the main challenges of ECG biometrics is the variability of the ECG of different persons and different situations. To solve this issue, we proposed two different approaches: per person classifier, and one-for-all classifier. The first approach suggests making binary classifier to distinguish one person from others. The second approach suggests a multi-classifier that distinguishes the selected set of individuals from non-selected individuals (others). The preliminary results, the binary classifier obtained a performance 90% in terms of accuracy within a balanced data. The second approach has reported a log loss of 0.05 as a multi-class score.

Keywords: biometrics, electrocardiographic, machine learning, signals processing

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Authors: Nasrin Badrkhani

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The increasing use of educational technologies has created a tremendous transformation in all fields and most importantly, in the field of education and learning. In recent decades, traditional learning approaches have undergone fundamental changes with the emergence of new learning technologies. Research shows that suitable educational tools play an effective role in the transmission, comprehension, and impact of educational concepts. These tools provide a tangible basis for thinking and constructing concepts, resulting in an increased interest in learning. They provide real and true experiences to students and convey educational meanings and concepts more quickly and clearly. It can be said that educational technology, as an active and modern teaching method, with capabilities such as engaging multiple senses in the educational process and involving the learner, makes the learning environment more flexible. It effectively impacts the skills of children with special needs by addressing their specific needs. Teachers are no longer the sole source of information, and students are not mere recipients of information. They are considered the main actors in the field of education and learning. Since education is one of the basic rights of every human being and children with special needs face unique challenges and obstacles in education, these challenges can negatively affect their abilities and learning. To combat these challenges, one of the ways is to use educational technologies for more diverse, effective learning. Also, the use of educational technology for students with special needs has increasingly proven effective in boosting their self-confidence and helping them overcome learning challenges, enhancing their learning outcomes.

Keywords: communication technology, students with special needs, self-confidence, raising the expectations and progress

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Authors: Abdi Omar Shuriye

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A social business is a business designed to address socio-economic problems to enhance the welfare of the communities involved. Lately, social business, with its focus on innovative ideas, is capturing the interest of educational institutions, governments, and non-governmental organizations. Social business uses a business model to achieve a social goal, and in the last few decades, the idea of imbuing social business into the education system of higher learning institutions has spurred much excitement. This is due to the belief that it will lead to job creation and increased social resilience. One of the higher learning institutions which have invested immensely in the idea is Albukhari International University; it is a private education institution, on a state-of-the-art campus, providing an advantageous learning ecosystem. The niche area of this institution is social business, and it graduates job creators, not job seekers; this Malaysian institution is unique and one of its kind. The objective of this paper is to develop a work plan, direction, and milestone as well as the focus area for the infusion of social business into higher learning institutions with special reference to Al-Bukhari International University. The purpose is to develop a prototype and model full-scale to enable higher learning education institutions to construct the desired curriculum fermented with social business. With this model, major predicaments faced by these institutions could be overcome. The paper sets forth an educational plan and will spell out the basic tenets of social business, focusing on the nature and implementational aspects of the curriculum. It will also evaluate the mechanisms applied by these educational institutions. Currently, since research in this area remains scarce, institutions adopt the process of experimenting with various methods to find the best way to reach the desired result on the matter. The author is of the opinion that social business in education is the main tool to educate holistic future leaders; hence educational institutions should inspire students in the classroom to start up their own businesses by adopting creative and proactive teaching methods. This proposed model is a contribution in that direction.

Keywords: social business, curriculum, skills, university

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: Aofan Liu, Qianqian Tan, Burra Venkata Durga Kumar

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Data security is of the utmost importance in the healthcare area, as sensitive patient information is constantly sent around and analyzed by many different parties. The use of federated learning, which enables data to be evaluated locally on devices rather than being transferred to a central server, has emerged as a potential solution for protecting the privacy of user information. To protect against data breaches and unauthorized access, federated learning alone might not be adequate. In this context, the application of blockchain technology could provide the system extra protection. This study proposes a distributed federated learning system that is built on blockchain technology in order to enhance security in healthcare. This makes it possible for a wide variety of healthcare providers to work together on data analysis without raising concerns about the confidentiality of the data. The technical aspects of the system, including as the design and implementation of distributed learning algorithms, consensus mechanisms, and smart contracts, are also investigated as part of this process. The technique that was offered is a workable alternative that addresses concerns about the safety of healthcare while also fostering collaborative research and the interchange of data.

Keywords: data privacy, distributed system, federated learning, machine learning

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Dur-E- Shahwar

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Much attention has been given to ‘bridging the gap’ between neuroscience and educational practice. In order to gain a better understanding of the nature of this gap and of possibilities to enable the linking process, we have taken a boundary perspective on these two fields and the brain-based learning approach, focusing on boundary-spanning actors, boundary objects, and boundary work. In 26 semi-structured interviews, neuroscientists and education professionals were asked about their perceptions in regard to the gap between science and practice and the role they play in creating, managing, and disrupting this boundary. Neuroscientists and education professionals often hold conflicting views and expectations of both brain-based learning and of each other. This leads us to argue that there are increased prospects for a neuro-scientifically informed learning practice if science and practice work together as equal stakeholders in developing and implementing neuroscience research.

Keywords: language learning, explore, educational practices, mentalist, practice

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Authors: Malainine Ebnou

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This study investigates the effectiveness of using translanguaging techniques in EFL classrooms. The interest in this topic stems from the lack of research on the effectiveness of translanguaging techniques in foreign language learning, both domestically in Japan and globally, as research has focused on translanguaging from a teaching perspective but not much on it from a learning perspective. The main question that the study departs from is whether students’ use of translanguaging techniques can produce better learning outcomes when used at the university level. The sample population of the study is first-year Japanese university students. The study takes an experimental approach where translanguaging is introduced to one group, the experimental group, and withheld from another group, the control group. Both groups will then be assessed and compared to see if the use of translanguaging has had a positive impact on learning. The impact of the research could be in three ways: challenging the prevailing argument that using learners' mother tongue in the classroom is detrimental to the learning process, challenging native speaker-centered approaches in the EFL field, and arguing that translanguaging in EFL classrooms can produce more meaningful learning outcomes. If the effectiveness of translanguaging is confirmed, it will be possible to promote the use of translanguaging in English learning at Japanese universities and contribute to the improvement of students' English, and even lay the foundations for extending the use of translanguaging to people of other ages/nationalities and other languages in the future.

Keywords: translanguaging, EFL, language learning and teaching, applied linguistics

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Authors: Chin-Wen Chien

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Protocols are tools that help teachers inquire into the teaching and professional learning during the professional dialogue. This study focused on the integration of protocols into elementary school English teachers’ professional dialogue and discussed the influence of protocols on teachers’ teaching and learning. Based on the analysis of documents, observations, and interviews, this study concluded that with the introduction of protocols to elementary school English teachers, three major protocols were used during their professional dialogue. These protocols led the teachers to gain professional learning in content knowledge and pedagogical content knowledge. However, the facilitators’ lack of experience in using protocols led to interruptions during the professional dialogue. Suggestions for effective protocol-based professional dialogue are provided.

Keywords: protocols, professional learning, professional dialogue, classroom practice

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Authors: Rajan Ghimire

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One of the diseases caused by the coronavirus shook the whole world. This situation challenged the education system across the world and compelled educators to shift to an online mode of teaching. Many academic institutions that were persistent to keep their traditional pedagogical approach were also forced to change their teaching methods. This study aims to assess science education students' experiences and perceptions of this global issue, especially on the science teaching and learning process. The study is based on qualitative research and through in-depth interviews with respondents and data is analyzed. Online distance teaching and learning processes meet the requirements of students who cannot or prefer not to participate in conventional classroom settings. But there are some challenges for the students and teachers in the science teaching learning process. This study recommends some points to all stakeholders.

Keywords: electronic devices, internet, online and distance learning, science education, educational policy

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Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: building measurement, construction management, learning challenges, evaluate survey

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Authors: F. S. Irwansyah, I. Farida, Y. Maulana

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Studying chemistry requires the ability to understand three levels of understanding in the form of macroscopic, submicroscopic and symbolic, but the lack of emphasis on the submicroscopic level leads to the understanding of chemical concepts becoming incomplete, due to the limitations of the tools capable of providing visualization of submicroscopic concepts. The purpose of this study describes the stages of making augmented reality learning media on the concept of molecular geometry and analyze the feasibility test result of augmented reality learning media on the concept of molecular geometry. This research uses Research and Development (R & D) method which produces a product of AR learning media on molecular geometry concept and test the effectiveness of the product. Research stages include concept analysis and learning indicators, design development, validation, feasibility, and limited testing. The stages of validation and limited trial are aimed to get feedback in the form of assessment, suggestion and improvement on learning aspect, material substance aspect, visual communication aspect and software engineering aspects and media feasibility in terms of media creation purpose to be used in learning. The results of the overall feasibility test obtained r-calculation 0,7-0,9 with the interpretation of high feasibility value, whereas the result of limited trial got the percentage of eligibility with the average value equal to 70,83-92,5%. This percentage indicates that AR's learning media product on the concept of molecular geometry, deserves to be used as a learning resource.

Keywords: android, augmented reality, chemical learning, geometry

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Authors: Jacqueline Mary Jepson

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This article provides a case study centred on the development of 13 video episodes which have been created to enhance student engagement with a post graduate online course in Project Management. The student group was unique as their online course needed to provide for asynchronistic learning and an adult learning pedagogy. In addition, students had come from a wide range professional backgrounds, with some having no Project Management experience, while others had 20 years or more. Students had to gain an understanding of an advanced body of knowledge and the course needed to achieve the academic requirements to qualify individuals to apply their learning in a range of contexts for professional practice and scholarship. To achieve this, a 13 episode case study was developed along with supportive learning materials based on the relocation of a zoo. This unique project provided a learning environment where the project could evolve over each video episode demonstrating the application of Project Management methodology which was then tied into the learning outcomes for the course and the assessment tasks. Discussion forums provided a way for students to converse and demonstrate their own understanding of content and how Project Management methodology can be applied.

Keywords: project management, adult learning, video case study, asynchronistic education

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Authors: Jarmon Sirigunna

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The objective of this study were to investigate the success of the implementation of problem-based learning in classroom and to evaluate the level of satisfaction of Suan Sunandra Rajabhat University’s students who participated in the study. This paper aimed to study and focus on a university students survey conducted in Suan Sunandha Rajabhat University during January to March of 2014. The quota sampling was utilized to obtain the sample which included 60 students, 50 percent male and 50 percent female students. The pretest and posttest method was utilized. The findings revealed that the majority of respondents had gained higher knowledge after the posttest significantly. The respondents’ knowledge increased about 40 percent after the experiment. Also, the findings revealed the top three highest level of satisfaction as follows: 1) the proper roles of teacher and students, 2) the knowledge gained from the method of the problem-based learning, 3) the activities of the problem-based learning, 4) the interaction of students from the problem-based learning, and 5) the problem-based learning model. Also, the mean score of all categories was 4.22 with a standard deviation of 0.7435 which indicated that the level of satisfaction was high.

Keywords: implement, problem-based learning, satisfaction, university students

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Authors: Hassan Habibi, Hossein Soltani, Amir Moghadam, Najmeh Bakhshi

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The purpose of this study was to compare competitive state anxiety among elite and non-elite futsal players and its relationship with situational factors. 130 non-elite and 70 elite male futsal players participated in the study. Competitive State Anxiety Inventory-2 and situational factors Inventory were applied. Data was analyzed using one-way ANOVA and product moment correlation. Results showed there was significant difference between competitive state anxiety subscales (cognitive anxiety somatic anxiety & self-confidence) and situational factors among elite and non-elite futsal players (P<0.05) but there was no significant correlations between situational factors subscales among elite and non-elite futsal players (P<0.05).

Keywords: competitive state anxiety, situational factors, elite players, non-elite players

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Authors: Adeep Hande, Shubham Agarwal

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This paper presents a study on identifying sexism in online texts using various state-of-the-art deep learning models based on BERT. We experimented with different feature sets and model architectures and evaluated their performance using precision, recall, F1 score, and accuracy metrics. We also explored the use of pseudolabeling technique to improve model performance. Our experiments show that the best-performing models were based on BERT, and their multilingual model achieved an F1 score of 0.83. Furthermore, the use of pseudolabeling significantly improved the performance of the BERT-based models, with the best results achieved using the pseudolabeling technique. Our findings suggest that BERT-based models with pseudolabeling hold great promise for identifying sexism in online texts with high accuracy.

Keywords: large language models, semi-supervised learning, sexism detection, data sparsity

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study explored whether academic emotion, major satisfaction, and learning flow are associated with academic achievement in medical school. We know that emotion and affective factors are important factors in students' learning and performance. Emotion has taken the stage in much of contemporary educational psychology literature, no longer relegated to secondary status behind traditionally studied cognitive constructs. Medical school students (n=164) completed academic emotion, major satisfaction, and learning flow online survey. Academic performance was operationalized as students' average grade on two semester exams. For data analysis, correlation analysis, multiple regression analysis, hierarchical multiple regression analyses and ANOVA were conducted. The results largely confirmed the hypothesized relations among academic emotion, major satisfaction, learning flow and academic achievement. Positive academic emotion had a correlation with academic achievement (β=.191). Positive emotion had 8.5% explanatory power for academic achievement. Especially, sense of accomplishment had a significant impact on learning performance (β=.265). On the other hand, negative emotion, major satisfaction, and learning flow did not affect academic performance. Also, there were differences in sense of great (F=5.446, p=.001) and interest (F=2.78, p=.043) among positive emotion, boredom (F=3.55, p=.016), anger (F=4.346, p=.006), and petulance (F=3.779, p=.012) among negative emotion by grade. This study suggested that medical students' positive emotion was an important contributor to their academic achievement. At the same time, it is important to consider that some negative emotions can act to increase one’s motivation. Of particular importance is the notion that instructors can and should create learning environment that foster positive emotion for students. In doing so, instructors improve their chances of positively impacting students’ achievement emotions, as well as their subsequent motivation, learning, and performance. This result had an implication for medical educators striving to understand the personal emotional factors that influence learning and performance in medical training.

Keywords: academic achievement, learning emotion, learning flow, major satisfaction

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Authors: Aminath Waseela, Vinesh Chandra, Shaun Nykvist,

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The success of technology integration initiatives hinges on the knowledge and skills of teachers to effectively integrate technology in classroom teaching. Consequently, gaining an understanding of teachers' technology knowledge and its integration can provide useful insights on strategies that can be adopted to enhance teaching and learning, especially in developing country contexts where research is scant. This paper extends existing knowledge on teachers' use of technology by developing a conceptual framework that recognises how three key types of knowledge; content, pedagogy, technology, and their integration are at the crux of teachers' technology use while at the same time is amenable to empirical studies. Although the aforementioned knowledge is important for effective use of technology that can result in enhanced student engagement, literature on how this knowledge leads to effective technology use and enhanced student engagement is limited. Thus, this theoretical paper proposes a framework to explore teachers' knowledge through the lens of the Technological Pedagogical and Content Knowledge (TPACK); the integration of technology in classroom teaching through the Substitution Augmentation Modification and Redefinition (SAMR) model and how this affects students' learning through the Bloom's Digital Taxonomy (BDT) lens. Studies using this framework could inform the design of professional development to support teachers to develop skills for effective use of available technology that can enhance student learning engagement.

Keywords: information and communication technology, ICT, in-service training, small island developing states, SIDS, student engagement, technology integration, technology professional development training, technological pedagogical and content knowledge, TPACK

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Authors: Pajaree Naramitpanich, Natchanok Jansawang, Panwilai Chomchid

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The aims of this are compared between the students’ logical thinking abilities of their learning for designing the 5-lesson instructional plans of the 2-instructional methods, namely; the STEM Education and the Creative Learning Process (CLP) for developing students’ logical thinking abilities that a sample consisted of 90 students from two chemistry classes of different learning outcomes in Wapi Phathum School with the cluster random sampling technique was used at the 11th grade level. To administer of their learning environments with the 45-experimenl student group by the STEM Education method and the 45-controlling student group by the Creative Learning Process. These learning different groups were obtained using the 5 instruments; the 5-lesson instructional plans of the STEM Education and the Creative Learning Process to enhance the logical thinking tests on Mineral issue were used. The efficiency of the Creative Learning Processes (CLP) Model and the STEM Education’s innovations of these each five instructional lesson plans based on criteria are higher than of 80/80 standard level with the IOC index from the expert educators. The averages mean scores of students’ learning achievement motives were assessed with the Pre and Post Techniques and Logical Thinking Ability Test (LTAT) and dependent t-test analysis were differentiated between the CLP and the STEM, significantly. Students’ perceptions of their chemistry classroom environment inventories with the MCI with the CLP and the STEM methods also were found, differently. Associations between students’ perceptions of their chemistry classroom learning environment inventories on the CLP Model and the STEM Education learning designs toward their logical thinking abilities toward chemistry, the predictive efficiency of R2 values indicate that 68% and 76% of the variances in students’ logical thinking abilities toward chemistry to their controlling and experimental chemistry classroom learning environmental groups with the MCI were correlated at .05 levels, significantly. Implementations of this result are showed the students’ learning by the CLP of the potential thinking life-changing roles in most their logical thinking abilities that it is revealed that the students perceive their abilities to be highly learning achievement in chemistry group are differentiated with the STEM education of students’ outcomes.

Keywords: design, the lesson instructional plans, the stem education, the creative learning process, logical thinking ability, different, learning outcome, student, chemistry class

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Authors: Fang Gong

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Distance measures are an indispensable part of many instance-based learning (IBL) and machine learning (ML) algorithms. The value difference metrics (VDM) and inverted specific-class distance measure (ISCDM) are among the top-performing distance measures that address nominal attributes. VDM performs well in some domains owing to its simplicity and poorly in others that exist missing value and non-class attribute noise. ISCDM, however, typically works better than VDM on such domains. To maximize their advantages and avoid disadvantages, in this paper, a selection approach: a discriminative model for nominal attributes-based distance measures is proposed. More concretely, VDM and ISCDM are built independently on a training dataset at the training stage, and the most credible one is recorded for each training instance. At the test stage, its nearest neighbor for each test instance is primarily found by any of VDM and ISCDM and then chooses the most reliable model of its nearest neighbor to predict its class label. It is simply denoted as a discriminative distance measure (DDM). Experiments are conducted on the 34 University of California at Irvine (UCI) machine learning repository datasets, and it shows DDM retains the interpretability and simplicity of VDM and ISCDM but significantly outperforms the original VDM and ISCDM and other state-of-the-art competitors in terms of accuracy.

Keywords: distance measure, discriminative model, nominal attributes, nearest neighbor

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Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

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Authors: U.-B. Schaer, M. Wehr, R. Hodler

Abstract:

Background: Most nursing students require more training time for necessary nursing skills than defined by nursing schools curriculum to acquire basic nursing skills. Given skills training lessons are too brief to enable effective student learning, meaning in-depth skills practice and repetition various learning steps. This increases stress levels and the pressure to succeed for a nursing student with slower learning capabilities. Another possible consequence is that nursing students are less prepared in the required skills for future clinical practice. Intervention: The Bern College of Higher Education of Nursing, Switzerland, started the independent peer practice learning program in 2012. A concept was developed which defines specific aims and content as well as student’s rights and obligations. Students enlist beforehand and order the required materials. They organize themselves and train in small groups in allocated training location in the area of Learning Training and Transfer (LTT). During the peer practice, skills and knowledge can be repeatedly trained and reflected in the peer groups without the presence of a tutor. All invasive skills are practiced only on teaching dummies. This allows students to use all their potential. The students may access learning materials as literature and their own student notes. This allows nursing students to practice their skills and to deepen their knowledge on corresponding with their own learning rate. Results: Peer group discussions during the independent peer practice learning support the students in gaining certainty and confidence in their knowledge and skills. This may improve patient safety in future daily care practice. Descriptive statics show that the number of students who take advantage of the independent peer practice learning increased continuously (2012-2018). It has to be mentioned that in 2012, solely students of the first semester attended the independent peer practice learning program, while in 2018 over one-third of the participating students were in their fifth semester and final study year. It is clearly visible that the demand for independent peer practice learning is increasing. This has to be considered in the development of future teaching curricula.

Keywords: learning program, nursing students, peer learning, skill training

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Authors: Mairo Musa Galadima, Phoebe Mshelia

Abstract:

In Nigeria, the national policy of education stipulates that the kindergarten-primary schools and the legislature are to use the three popular Nigerian Languages namely: Hausa, Igbo, and Yoruba. However, the English language seems to be preferred and this calls for this paper. Attempts were made to draw out the challenges faced by learners in understanding English speech sounds and using them to communicate effectively in English; using 5 (five) selected secondary school in Bauchi. It was discovered that challenges abound in the wrong use of stress and intonation, transfer of phonetic features from their first language. Others are inadequately qualified teachers and relevant materials including textbooks. It is recommended that teachers of English should lay more emphasis on the teaching of supra-segmental features and should be encouraged to go for further studies, seminars and refresher courses.

Keywords: stress and intonation, phonetic and challenges, teaching and learning English, secondary schools

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Authors: Joanne Rieta Miranda

Abstract:

Learning anatomy and physiology among Deaf Non-Science major students is a challenge. They have this mindset that Anatomy and Physiology are difficult and very technical. In this study, nine (9) deaf students who are business majors were considered. Non-conventional teaching strategies and classroom activities were employed such as cooperative learning, virtual lab, Facebook live, big sky, blood typing, mind mapping, reflections, etc. Of all the activities; the deaf students ranked cooperative learning as the best learning activity. This is where they played doctors. They measured the pulse rate, heart rate and blood pressure of their partner classmate. In terms of mindset, 2 out of 9 students have a growth mindset with some fixed ideas while 7 have a fixed mindset with some growth ideas. All the students passed the course. Three out of nine students got a grade of 90% and above. The teacher was evaluated by the deaf students as very satisfactory with a mean score of 3.54. This means that the learner-centered practices in the classroom are manifested to a great extent.

Keywords: deaf students, learning anatomy and physiology, teaching strategies, learner-entered practices

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Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

Abstract:

A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

Procedia PDF Downloads 140