Search results for: early science

Authors: Lauren B. Birney

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This project focuses upon the expansion of the existing "Curriculum and Community Enterprise for the Restoration of New York Harbor in New York City Public Schools" NSF EHR DRL 1440869, NSF EHR DRL 1839656 and NSF EHR DRL 1759006. This project is recognized locally as “Curriculum and Community Enterprise for Restoration Science,” or CCERS. CCERS is a comprehensive model of ecological restoration-based STEM education for urban public-school students. Following an accelerated rollout, CCERS is now being implemented in 120+ Title 1 funded NYC Department of Education middle schools, led by two cohorts of 250 teachers, serving more than 11,000 students in total. Initial results and baseline data suggest that the CCERS model, with the Billion Oyster Project (BOP) as its local restoration ecology-based STEM curriculum, is having profound impacts on students, teachers, school leaders, and the broader community of CCERS participants and stakeholders. Students and teachers report being receptive to the CCERS model and deeply engaged in the initial phase of curriculum development, citizen science data collection, and student-centered, problem-based STEM learning. The BOP CCERS Digital Platform will serve as the central technology hub for all research, data, data analysis, resources, materials and student data to promote global interactions between communities, Research conducted included qualitative and quantitative data analysis. We continue to work internally on making edits and changes to accommodate a dynamic society. The STEM Collaboratory NYC® at Pace University New York City continues to act as the prime institution for the BOP CCERS project since the project’s inception in 2014. The project continues to strive to provide opportunities in STEM for underrepresented and underserved populations in New York City. The replicable model serves as an opportunity for other entities to create this type of collaboration within their own communities and ignite a community to come together and address the notable issue. Providing opportunities for young students to engage in community initiatives allows for a more cohesive set of stakeholders, ability for young people to network and provide additional resources for those students in need of additional support, resources and structure. The project has planted more than 47 million oysters across 12 acres and 15 reef sites, with the help of more than 8,000 students and 10,000 volunteers. Additional enhancements and features on the BOP CCERS Digital Platform will continue over the next three years through funding provided by the National Science Foundation, NSF DRL EHR 1759006/1839656 Principal Investigator Dr. Lauren Birney, Professor Pace University. Early results from the data indicate that the new version of the Platform is creating traction both nationally and internationally among community stakeholders and constituents. This project continues to focus on new collaborative partners that will support underrepresented students in STEM Education. The advanced Digital Platform will allow for us connect with other countries and networks on a larger Global scale.

Keywords: STEM education, environmental restoration science, technology, citizen science

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Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Adawati Suhaili, Kamisah Osman, Mohd Effendi, Ewan Mohd Matore

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The global education reform has prompted Malaysia to transform the education system in Malaysia through the Malaysian Education Blueprint (MEB) 2013-2025. This transformation is aimed to achieve the top one-third rank in international assessment. The low achievement of student scientific literacy in TIMMS (Trends in International Mathematics and Science Study ) and PISA (Programme for International Student Assessment) has caused concern to the Ministry Of Education (MOE) despite various reform efforts. Therefore, an alternative action by enhancing the role of the Head of Science Panels (HoSPs) as a key change agent in catalyzing the improvement of student performance should be considered. Highlights of previous studies have shown that subject leadership is able to enhance teacher teaching quality in order to increase student learning. To lead the Science department and guide Science teachers more effectively, HoSPs need to strengthen their leadership skills. However, the issue of weaknesses in the leadership competencies of HoSPs in Malaysia has caused them to lack confidence and ability in leading the Science Department. The main objective of this study is to explore the factors that contribute to the problems faced by HoSPs at Sarawak in their leadership roles. This study used a qualitative design framework and using a semi-structured interview method for data collection. There were six informants involved in the interview consisting of lecturers, Senior Administrative Assistant Teacher and HoSPs. The findings of the study had been identified four main factors that contribute to problems in the leadership competencies of HoSPs in Sarawak, namely leadership practices, leadership structure, academic subjects and school change. The results are significant to the MOE in strengthening the leadership competencies of HoSPs in a more focus for improving the achievement of scientific literacy of students in Malaysia. This study can help improve the Hosps' leadership competencies in Malaysia.

Keywords: issues, problems, Malaysia education blueprint, leadership competencies, head of science panels

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Authors: Sanskar, Abhinav Pal, Aryush Gupta, Sushil Kumar Mishra

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One of the critical and tedious assignments in agricultural practices is the detection of diseases on vegetation. Agricultural production is very important in today’s economy because plant diseases are common, and early detection of plant diseases is important in agriculture. Automatic detection of such early diseases is useful because it reduces control efforts in large productive farms. Using digital image processing and machine learning algorithms, this paper presents a method for plant disease detection. Detection of the disease occurs on different leaves of the plant. The proposed system for plant disease detection is simple and computationally efficient, requiring less time than learning-based approaches. The accuracy of various plant and foliar diseases is calculated and presented in this paper.

Keywords: plant diseases, machine learning, image processing, deep learning

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Sonia Anand Knowlton

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With the rise of artificial intelligence, computer science is becoming increasingly integrated in virtually every area of life. Of course, the law is no exception. Through argumentation frameworks (AFs), computer scientists have used abstract algebra to structure the legal reasoning process in a way that allows conclusions to be drawn from a formalized system of arguments. In AFs, arguments compete against each other for logical success and are related to one another through the binary operation of the attack. The prevailing arguments make up the preferred extension of the given argumentation framework, telling us what set of arguments must be accepted from a logical standpoint. There have been several developments of AFs since its original conception in the early 90’s in efforts to make them more aligned with the human reasoning process. Generally, these developments have sought to add nuance to the factors that influence the logical success of competing arguments (e.g., giving an argument more logical strength based on the underlying value it promotes). The most cogent development was that of the Extended Argumentation Framework (EAF), in which attacks can themselves be attacked by other arguments, and the promotion of different competing values can be formalized within the system. This article applies the logical structure of EAFs to current theoretical understandings of judicial reasoning to contribute to theories of judging and to the evolution of AFs simultaneously. The argument is that the main limitation of EAFs, when applied to judicial reasoning, is that they require judges to themselves assign values to different arguments and then lexically order these values to determine the given framework’s preferred extension. Drawing on John Rawls’ Theory of Justice, the examination that follows is whether values are lexical and commensurable to this extent. The analysis that follows then suggests a potential extension of the EAF system with an approach that formalizes different “planes of attack” for competing arguments that promote lexically ordered values. This article concludes with a summary of how these insights contribute to theories of judging and of legal reasoning more broadly, specifically in indeterminate cases where judges must turn to value-based approaches.

Keywords: computer science, mathematics, law, legal theory, judging

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Authors: Dammar Bahadur Adhikari

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Mathematics teaching begins with human civilization. The rular used to choose mathematician as prime adviser in many tribes and country. Mathematics was powerful tool for understanding economial situation and strength of rular. In ancient Nepal teaching of mathematics starts with informal education provided by religious leaders there after in modern education system seems to follow the world’s educational system. The aim of this paper is to present a brief historical background of the Nepalese mathematicians up to nineteenth century and highlight the transformation in mathematical science in the line with modern world. Secondary data and formal papers and informal publications were studied to explore the present situation of education. The study concluded that there is remarcable change in quality of education and there are sufficient human powers in the mathematical sciences in Nepal.

Keywords: human development, mathematics, Nepal, science, traditional

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Authors: Shri Krishna Mishra, Badri Yadav

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Effect of collaborative learning on development of process skills and attitude towards science is It rightly said that the destiny of the nation is shaped inside its classroom. Classroom is a place where the pupil and teacher interact purposefully to gain knowledge. Teaching is the principal mode of education. It can be called a transaction between teacher and pupil, in which one transmits knowledge to other. The teaching learning process consists of three important components, the pupils, the teacher and the curriculum; the classroom is the collection of students of their own individual abilities and needs. In the present classroom teaching learners are either persuasive recipient or passive observant. The school environment leading to low-achievement we have to try better to develop in the young mind. Children are the sticks of dynamite, bundles of energy and potential power waiting to be ignited. Guide them carefully to a place where their potentialities and strength will be used to build a better world. Man’s future depends to large extent on scientific advances and development of productive activity. Science is considered as an important subject in school curricular. The education commission (1964-66) has suggested that science education is necessary for all children at school stage. It is essential to develop children’s logical and critical thinking. But these days thinking process and academic achievement of students have been suppressed by competitive environment of our schools. How the students perceive each other and interact with one another is a neglected aspect of instruction. In the constructivist perspective learning in a process of construction of knowledge. Learners actively construct their own knowledge by connecting new ideas to existing ideas on the basis of materials/ activities presented to them (experience).

Keywords: effect of collaborative learning, development of process skills, science education, attitude towards science

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Authors: Cecile Garry, Katia Rovira, Julie Brisson

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Autism Spectrum Disorder (ASD) is defined by a qualitative and quantitative impairment of social interaction. Indeed early intervention programs, such as the Early Start Denver Model (ESDM), aimed at encouraging the development of social skills. In classroom, the children need to be socially engaged to learn. Early intervention programs can thus be implemented in kindergarten schools. In these schools, ASD children have more opportunities to interact with their peers or adults than in elementary schools. However, the preschool children with ASD are less socially engaged than their typically developing peers in the classroom. They initiate, respond and maintain less the social interactions. In addition, they produce more responses than initiations. When they interact, the non verbal communication is more used than verbal or symbolic communication forms and they are more engaged with adults than with peers. Nevertheless, communicative patterns may vary according to the clinical profiles of ASD children. Indeed, the ASD children with better cognitive skills interact more with their peers and use more symbolic communication than the ASD children with a low cognitive level. ASD children with the less severe symptoms use more the verbal communication than ASD children with the more severe symptoms. Small groups and structured activities encourage coordinated joint engagement episodes in ASD children. Our goal is to evaluate ASD children’s social engagement development in class, with their peers or adults, during dyadic or group activities. Participants were 19 preschool children with ASD aged from 3 to 6 years old that benefited of an early intervention in special kindergarten schools. Severity of ASD symptoms was measured with the CARS at the beginning of the follow-up. Classroom situations of interaction were recorded during 10 minutes (5 minutes of dyadic interaction and 5 minutes of a group activity), every 2 months, during 10 months. Social engagement behaviors of children, including initiations, responses and imitation, directed to a peer or an adult, were then coded. The Observer software (Noldus) that allows to annotate behaviors was the coding system used. A double coding was conducted and revealed a good inter judges fidelity. Results show that ASD children were more often and longer socially engaged in dyadic than in groups situations. They were also more engaged with adults than with peers. Children with the less severe symptoms of ASD were more socially engaged in groups situations than children with the more severe symptoms of ASD. Then, ASD children with the less severe symptoms of ASD were more engaged with their peers than ASD children with the more severe symptoms of ASD. However, the engagement frequency increased during the 10 month of follow-up but only for ASD children with the more severe symptoms at the beginning. To conclude, these results highlighted the necessity of individualizing early intervention programs according to the clinical profile of the child.

Keywords: autism spectrum disorder, preschool children, developmental psychology, early interventions, social interactions

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Authors: Basman Abdul Jabbar

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The researchers aimed to improve the importance of the good posture without any divisions & deformities. The importance of research lied in the discovery posture deformities early so easily treated before its transformation into advanced abnormalities difficult to treat and may need surgical intervention. Research problem was noting that some previous studies were based on the discovery of posture deformities, which was dependent on the (self-evaluation) which this type did not have accuracy to discover deformities. The Samples were (500) schoolchildren aged (9-11 years, males) at Baghdad al Karak. They were students at primary schools. The measure included all posture deformities. The researcher used video camera to analyze the posture deformities according to biomechanical variables by Kinovea software for motion analysis. The researcher recommended the need to use accurate scientific methods for early detection of posture deformities in children which contribute to the prevention and reduction of distortions.

Keywords: biomechanics, children, deformities, posture

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Authors: Amanda Kavner, Richard Lamb

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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.

Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience

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Authors: Taibat Busari

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Electronic media has created new options for enhancing education. It has long been providing innovative methods for arousing students’ attention in learning and improves teachers’ performance in disseminating instructional contents. However, the advancement of electronic media has increased the flexibility, availability, accessibility and improved communications among students-students, students-teacher, and teacher-students. This study investigated: (i) teachers’ accessibility to, and utilization of electronic media for teaching basic science and technology in Ilorin metropolis; (ii) the influence of school proprietorship on teachers’ access to and utilization of electronic media for teaching and; the influence of teachers’ gender on the use of electronic media. The research was a descriptive design using the survey method. The study sample was drawn for private and public secondary schools in Ilorin Metropolis. The respondents were 285 basic science and technology teachers, which comprised of 146 males and 139 females. A structured researcher designed questionnaire was used to gather data for the study. Pilot study was carried out on mini sample of 20 basic science and technology teachers in five schools which are not part of the study’s population. It was then subjected to Cronbach’s Alpha and yielded the values 0.794 for availability, 0.730 for accessibility and 0.84 for utilization of electronic media. The research questions were answered using mean and percentage while research hypotheses one and two was tested using t- test. The findings of the study showed that: (i) electronic media are available for teaching basic science and technology; (ii) teachers’ had access to electronic media for teaching; (iii) teachers’ utilized electronic media for teaching basic science and technology; (iv) there was no significant difference between teachers’ utilization of electronic media for teaching; (v) there was no significant difference between teachers’ utilization of electronic media for teaching based on school proprietorship. The study, therefore, concluded that teachers’ had access to electronic media and utilized it for teaching purposes. Gender had no influence on teachers’ access to and utilization on electronic media for teaching and also, school proprietorship had no influence on access and utilization of electronic media for teaching. Based on findings it was recommended that electronic media should be made available and utilized in all schools across the nation to improve the learning rate of the students.

Keywords: electronic media, basic science and technology, teachers' accessibility, Nigeria

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Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

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This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

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Authors: Miao Zhang, Limin Liu, Feng Zhi, Panpan Niu, Mengya Yang, Xuemei Zhu, Ying Diao, Jun Wang, Ying Zhao

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Background and Aims: Clinical studies have demonstrated that serum semicarbazide-sensitive amine oxidase (SSAO) activities positively correlate with the progression of atherosclerosis. The aim of the present study is to investigate the effect of SSAO inactivation on the development of atherosclerosis. Methods: Female LDLr knockout (KO) mice were given the Western-type diet for 6 and 9 weeks to induce the formation of early and advanced lesions, and semicarbazide (SCZ, 0.125%) was added into the drinking water to inactivate SSAO in vivo. Results: Despite no impact on plasma total cholesterol levels, abrogation of SSAO by SCZ not only resulted in the enlargement of both early (1.5-fold, p=0.0043) and advanced (1.8-fold, p=0.0013) atherosclerotic lesions, but also led to reduced/increased lesion contents of macrophages/smooth muscle cells (SMCs) (macrophage: ~0.74-fold, p=0.0002(early)/0.0016(advanced); SMC: ~1.55-fold, p=0.0003(early) /0.0001(advanced)), respectively. Moreover, SSAO inactivation inhibited the migration of circulating monocytes into peripheral tissues and reduced the amount of circulating Ly6Chigh monocytes (0.7-fold, p=0.0001), which may account for the reduced macrophage content in lesions. In contrast, the increased number of SMCs in lesions of SCZ-treated mice is attributed to an augmented synthetic vascular SMC phenotype switch as evidenced by the increased proliferation of SMCs and accumulation of collagens in vivo. Conclusion: SSAO inactivation by SCZ promotes the phenotypic switch of SMCs and the development of atherosclerosis. The enzymatic activity of SSAO may thus represent a potential target in the prevention and/or treatment of atherosclerosis.

Keywords: atherosclerosis, phenotype switch of smooth muscle cells, SSAO/VAP-1, semicarbazide

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Authors: Ambika Perisamy, Asyriawati binte Mohd Hamzah

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The focus of this presentation is to discuss teacher professional development (TPD) through the use of technology. TPD is necessary to prepare teachers for future challenges they will face throughout their careers and to develop new skills and good teaching practices. We will also be discussing current issues in embracing technology in the field of early childhood education and the impact on the professional development of teachers. Participants will also learn to apply teaching and learning practices through the use of technology. One major objective of this presentation is to coherently fuse practical, technology and theoretical content. The process begins by concretizing a set of preconceived ideas which need to be joined with theoretical justifications found in the literature. Technology can make observations fairer and more reliable, easier to implement, and more preferable to teachers and principals. Technology will also help principals to improve classroom observations of teachers and ultimately improve teachers’ continuous professional development. Video technology allows the early childhood teachers to record and keep the recorded video for reflection at any time. This will also provide opportunities for her to share with her principals for professional dialogues and continuous professional development plans. A total of 10 early childhood teachers and 4 principals were involved in these efforts which identified and analyze the gaps in the quality of classroom observations and its co relation to developing teachers as reflective practitioners. The methodology used involves active exploration with video technology recordings, conversations, interviews and authentic teacher child interactions which forms the key thrust in improving teaching and learning practice. A qualitative analysis of photographs, videos, transcripts which illustrates teacher’s reflections and classroom observation checklists before and after the use of video technology were adopted. Arguably, although PD support can be magnanimously strong, if teachers could not connect or create meaning out of the opportunities made available to them, they may remain passive or uninvolved. Therefore, teachers must see the value of applying new ideas such as technology and approaches to practice while creating personal meaning out of professional development. These video recordings are transferable, can be shared and edited through social media, emails and common storage between teachers and principals. To conclude the importance of reflective practice among early childhood teachers and addressing the concerns raised before and after the use of video technology, teachers and principals shared the feasibility, practical and relevance use of video technology.

Keywords: early childhood education, reflective, improve teaching and learning, technology

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Authors: Amir Halabianfar, Jamshid Razmjoo

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In order to evaluate the competitive effects of Lambsqua on the germination and early growth of two wheat (Triticum aestivum L.) varieties, an experiment was conducted in laboratory conditions in researches of agronomy, College of agriculture, Isfahan University of Technology in 2015. A laboratory experiment was conducted on a factorial arrangement in a randomized complete design with four replications. Testing factors include two wheat cultivars (Flat and Atila -4) and three level of Lambsqua (Chenopodium album) extract (30, 60 and 90 percent) plus control with no extract. Twenty-five seeds of each wheat varieties were placed in petri dish, then the root extract of lambsqua, which was prepared previously at three levels, was poured on the seeds in each petri dish. The result showed that allelopathic effect of Lambsquarter on germination, root, and shoot dry weight of two varieties was highly significant. Among varieties, the Atila–4 showed minimum germination at 60% while the Flat showed minimum germination at 90% concentration. In case of root dry weight, Atila–4 was more suppressed as compared to Flat at 60% concentration but at 90% concentration, the both wheat varieties were reduced non-significantly. Shoot dry weight of Flat were decreased non-significantly concentrations except Atila -4 that was more reduced at 60 % than 90% concentration.

Keywords: allelopathy, Chenopodium album, extract, germination, wheat, early growth

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Authors: Paraskevi Liosatou

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Climate change is considered to be of global concern being amplified by the fact that by its nature, cannot be spatially limited. This fact makes necessary the intergovernmental decision-making procedures. In the intergovernmental level, the institutions such as the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change develop efforts, methods, and practices in order to plan and suggest climate mitigation and adaptation measures. These measures are based on specific scientific findings and methods making clear the strong connection between science and policy. In particular, these scientific recommendations offer a series of practices, methods, and choices mitigating the problem by aiming at the indirect mitigation of the causes and the factors amplifying climate change. Moreover, modern production and economic context do not take into consideration the social, political, environmental and spatial dimensions of the problem. This work studies the decision-making process working in international and European level. In this context, this work considers the policy tools that have been implemented by various intergovernmental organizations. The methodology followed is based mainly on the critical study of standards and process concerning the connections and cooperation between science and policy as well as considering the skeptic debates developed. The finding of this work focuses on the links between science and policy developed by the institutional and scientific mechanisms concerning climate change mitigation. It also analyses the dimensions and the factors of the science-policy framework; in this way, it points out the causes that maintain skepticism in current scientific circles.

Keywords: climate change, climate change mitigation, climate change skepticism, IPCC, skepticism

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Authors: Teboho Moja, Frans Swanepoel, Okunade Samuel Kehinde

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Knowledge production is key to development worldwide. However, some countries are producers of knowledge used globally, whilst others are mainly consumers of that knowledge. There is a correlation between knowledge production and funding levels for research. Countries in Africa recognize the need to provide research funding at levels that would enhance knowledge production but struggle in balancing many competing needs. African countries have committed to funding research at the level of 1% of their GDP on research and development (R&D), which is the recommended percentage to be earmarked for education; however, many countries have not been able to fulfill this. In 2015-2016 Science Granting Councils in 15 out of 54 African states came together to form a Science Granting Council Initiative to strengthen the research capacity in their countries and to support research and evidence-based policies that will contribute to the continent’s economic and social development. The members of the SGCI work collaboratively; however, there is a challenge in addressing research problems that cut across national boundaries as many governments are more interested in prioritizing national issues given their limited resources. This article focuses on the governance structures of those science granting councils to understand and explore reasons for the continuing underfunding of research, the impact of research, and the perceived direct benefit of research outcomes in informing policy and in benefitting the broader society.

Keywords: research, Science Granting Council, funding, European Research Council, African Research Council

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Authors: Shahram Jamali, Samira Hamed

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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

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Authors: Nasser Mansour, Ziad Said, Abdullah Abu-Tineh

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STEM teachers face the challenge of possessing expertise not only in their subject disciplines but also in the pedagogical knowledge required for integrated STEM lessons. However, research reveals a lack of pedagogical competencies related to project-based learning (PBL) in the STEM context. To bridge this gap, the study examines teachers' competencies and self-efficacy in TPACK (Technological Pedagogical Content Knowledge) and its specific integration with PBL and STEM content. Data from 245 specialized science and math teachers were collected using a questionnaire. The study emphasizes the importance of addressing gender disparities, supporting formal teacher education, and recognizing the expertise and experiences of STEM teachers in effective technology integration. The findings indicate that gender plays a role in self-efficacy beliefs, with females exhibiting higher confidence in pedagogical knowledge and males demonstrating higher confidence in technological knowledge. Teaching experience and workload factors have a limited impact on teachers' Technological Pedagogical Content Knowledge (TPACK). These findings enhance our understanding of contextual factors impacting science and math teachers' self-efficacy in utilizing TPACK for STEM and PBL. They inform the development of targeted interventions, professional development programs, and support systems to enhance teachers' competencies and self-efficacy in TPACK for teaching science and Mathematics through STEM and PBL.

Keywords: technological pedagogical content knowledge, TPACK, STEM, project-based learning, PBL, self-efficacy, mathematics, science

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Authors: Dr. Jenit Gandhi, Dr. Manojith SS, Dr. Nakul GV, Dr. Sharath Honnani, Dr. Shaurav Ghosh, Dr. Neel Shetty, Dr. Nagabhushan JS, Dr. Manish Joshi

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Introduction: Acute pancreatitis is an inflammatory condition of the pancreas which begins in pancreatic acinar cells and triggers local inflammation that may progress to systemic inflammatory response (SIRS) and causing distant organ involvement and its function and ending up with multiple organ dysfunction syndromes (MODS). Aim: A comparative study in acute pancreatitis to find out the effectiveness of early addition of Ulinastatin to current standard care in Indian subjects . Methodology: A current prospective observational study is done during study period of 1year (Dec 2018 –Dec 2019) duration to evaluate the effect of early addition of Ulinastatin to the current standard treatment and its efficacy to reduce the early complication, analgesic requirement and duration of hospital stay in patients with Acute Pancreatitis. Results: In the control group 25 were males and 05 were females. In the test group 18 were males and 12 females. Majority was in the age group between 30 - 70 yrs of age with >50% in the 30-50yrs age group in both test and control groups. The VAS was median grade 3 in control group as compared to median grade 2 in test group , the pain was more in the initial 2 days in test group compared to 4 days in test group , the analgesic requirement was used for more in control group (median 6) to test group( median 3 days ). On follow up after 5 days for a period of 2 weeks none of the patients in the test group developed any complication. Where as in the control group 8 patients developed pleural effusion, 04-Pseudopancreatic cyst, 02 – patient developed portal vein and splenic vein thrombosis, 02 patients – ventilator with ARDS which were treated symptomatically whereas in test group 02 patient developed pleural effusions and 01 pseudo pancreatic cyst with splenic artery aneurysm, 01 – patient with AKI and MODS symptomatically treated. The duration of hospital stay for a median period of 4 days (2 – 7 days) in test group and 7 days (4 -10 days) in control group. All patients were able to return to normal work on an average of 5days compared 8days in control group, the difference was significant. Conclusion:The study concluded that early addition of Ulinastatin to current standard treatment of acute Pancreatitis is effective in reducing pain, early complication and duration of hospital stay in Indian subject

Keywords: Ulinastatin, VAS – visual analogue score , AKI – acute kidney injury , ARDS – acute respiratory distress syndrome

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Authors: Xiaoqiang Fu, Baihao Li

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In 1895, the failure of Sino-Japanese prompted the trend of comprehensive and systematic study of western pattern in China. In urban planning and construction, urban reform movement sprang up slowly, which aimed at renovating and reconstructing the traditional cities into modern cities similar to the concessions. During the movement, Chinese traditional city initiated a process of modern urban planning for its modernization. Meanwhile, the traditional planning morphology and system started to disintegrate, on the contrary, western form and technology had become the paradigm. Therefore, the improvement of existing cities had become the prototype of urban planning of early modern China. Currently, researches of the movement mainly concentrate on large cities, concessions, railway hub cities and some special cities resembling those. However, the systematic research about the large number of traditional small and medium-sized cities is still blank, up to now. This paper takes the improvement constructions of small and medium-sized cities in Southern region of Jiangsu Province as the research object. First of all, the criteria of small and medium-sized cities are based on the administrative levels of general office and cities at the county level. Secondly, the suitability of taking the Southern Jiangsu as the research object. The southern area of Jiangsu province called Southern Jiangsu for short, was the most economically developed region in Jiangsu, and also one of the most economically developed and the highest urbanization regions in China. As the most developed agricultural areas in ancient China, Southern Jiangsu formed a large number of traditional small and medium-sized cities. In early modern times, with the help of the Shanghai economic radiation, geographical advantage and powerful economic foundation, Southern Jiangsu became an important birthplace of Chinese national industry. Furthermore, the strong business atmosphere promoted the widespread urban improvement practices, which were incomparable of other regions. Meanwhile, the demonstration of Shanghai, Zhenjiang, Suzhou and other port cities became the improvement pattern of small and medium-sized city in Southern Jiangsu. This paper analyzes the reform movement of the small and medium-sized cities in Southern Jiangsu (1895-1927), including the subjects, objects, laws, technologies and the influence factors of politic and society, etc. At last, this paper reveals the formation mechanism and characteristics of urban improvement movement in early modern China. According to the paper, the improvement of small-medium city was a kind of gestation of the local city planning culture in early modern China，with a fusion of introduction and endophytism.

Keywords: early modern China, improvement of small-medium city, southern region of Jiangsu province, urban planning history of China

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Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

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Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the function that called carrier content: on the latter it arises that emotions give the material reasoning that later transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. In this paper I argue that science education should start from the presence of certain emotions in the learner if it is to form citizens with scientific or cultural future scientists.

Keywords: epistemic emotions, science education, formation of citizens and scientists., philosophy of emotions

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Authors: Mi Sun Park

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Biotechnology provides us with technological solutions to resource-based challenges facing the global society. A bioeconomy or bio-based economy emerged as all economic activities derived from biotechnology. This paper aims to understand discourses on bioeconomy in the sector of agriculture with three dimensions; media discourse, science discourse, and policy discourse. For achieving research goals, content analysis was applied to this research. Media articles, academic journal articles and policy documents published from 2000 to 2016 were collected in South Korea. The text was coded and analyzed with the categories of speakers and their arguments. The research findings indicate that powerful actors and key messages of bioeconomy in South Korean agriculture. Differences and similarities among media, science, and policy were examined. Therefore this case study can contribute to understanding dynamic interaction and interfaces of media, science and policy discourse on biotechnology in the sector of agriculture.

Keywords: media, discourse, bioeconomy, agriculture

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Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: early stage prediction, heart rate variability, linear and non-linear analysis, sudden cardiac death

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Authors: Kemal Izci, Ahmet Oguz Akturk

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

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

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Authors: Dyna Ann C. Sevilles, Noel J. Belonguel, Jarungchai Anton S. Vatanagul, Mary Jeanne O. Flordelis, Grace G. Anota

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Guillain Barre syndrome is an acute inflammatory polyradiculoneuropathy causing progressive symmetrical weakness which can be debilitating to the patient. Early diagnosis is important especially in the acute phase when treatment favors good outcome and reduces the incidence of the need for mechanical ventilation. Electrodiagnostic studies aid in the evaluation of patients suspected with GBS. However, the characteristic electrical changes may not be evident until after several weeks. Thus, studies performed early in the course may give unclear results. The aim of this study is to associate the symptom onset of patients diagnosed with Guillain Barre syndrome with the EMG NCV results and determine the earliest time when there is evident findings supporting the diagnosis. This is a retrospective descriptive chart review study involving patients of >/= 18 years of age with GBS written on their charts in a Tertiaty hospital in Cebu City, Philippines from January 2000 to July 2014. Twenty patients showed electrodiagnostic findings suggestive of GBS. The mean day of illness when EMG NCV was carried out was 7 days. The earliest with suggestive findings was done on day 2 (10%) of illness. Moreover, the highest frequency with positive results was done on day 3 (20%) of illness. Based on the Dutch Guillain Barre Study group criteria, the most frequent variables noted were: prolonged distal motor latency in both median and ulnar nerves(65%) and both peroneal and tibial nerves (71%); and reduced CMAP in both median and ulnar nerves (65%) and both tibial and peroneal nerves (71%). The EMG NCV findings showed majority of demyelinating type (59%). Electrodiagnostic studies are helpful in aiding the physician in the diagnosis and treatment of the disease in the early stage. Based on this study, neurophysiologic evidence of GBS can be seen in as early as day 2 of clinical illness.

Keywords: Acute Inflammatory Demyelinating Polyneuropathy, electrophysiologic study, EMG NCV, Guillain Barre Syndrome

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Authors: Alaina Caulkett, Audra Selkowitz, Lauren Harter, Aimee DeFoe

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Educational robotics is an effective tool for teaching and learning STEM curricula. Yet, most traditional professional development programs do not cover engineering, coding, or robotics. This paper will give an overview of how and why the VEX Professional Development Plus Introductory Training courses were developed to provide guided, simple professional development in the area of robotics and computer science instruction. These training courses guide educators through learning the basics of VEX robotics platforms, including VEX 123, GO, IQ, and EXP. Because many educators do not have experience teaching robotics or computer science, this course is meant to simulate one on one training or tutoring through video-based instruction. These videos, led by education professionals, can be watched at any time, which allows educators to watch at their own pace and create their own personalized professional development timeline. This personalization expands beyond the course itself into an online community where educators at different points in the self-paced course can converse with one another or with instructors from the videos and learn from a growing community of practice. By the end of each course, educators are armed with the skills to introduce robotics or computer science in their classroom or educational setting. The design of the course was guided by a variation of the Understanding by Design (UbD) framework and included hands-on activities and challenges to keep educators engaged and excited about robotics. Some of the concepts covered include, but are not limited to, following build instructions, building a robot, updating firmware, coding the robot to drive and turn autonomously, coding a robot using multiple methods, and considerations for teaching robotics and computer science in the classroom, and more. A secondary goal of this research is to discuss how this professional development approach can serve as an example in the larger educational community and explore ways that it could be further researched or used in the future.

Keywords: computer science education, online professional development, professional development, robotics education, video-based instruction

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Authors: Matias Micheletto, Rodrigo Santos, Sergio F. Ochoa

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In developing countries, the most roads in rural areas are dirt road. They require frequent maintenance since are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the main-tenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like in Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision

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Authors: Somtop Keawchuer

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The objectives of this research are to compare the satisfaction of students, towards the happiness learning, sorted by their personal profiles, and to figure out the factors that affect the students’ happiness learning. This paper used survey method to collect data from 362 students. The survey was mainly conducted in the Faculty of Management Science, Suan Sunandha Rajabhat University, including 3,443 students. The statistics used for interpreting the results included the frequencies, percentages, standard deviations and One-way ANOVA. The findings revealed that the students are aware and satisfaction that all the factors in 3 categories (knowledge, skill and attitude) influence the happiness learning at the highest levels. The comparison of the satisfaction levels of the students toward their happiness learning leads to the results that the students with different genders, ages, years of study, and majors of the study have the similar satisfaction at the high level.

Keywords: happiness, learning satisfaction, students, Faculty of Management Science

Procedia PDF Downloads 310