Pub Date : 2023-10-01DOI: 10.28991/esj-2023-07-05-018
Vera V. Orlova, Larisa V. Shevchenko
Creating and maintaining a secure and supportive educational environment is essential for the success and well-being of university students. This study investigates the interplay between drug abuse, delinquency, sociocultural factors, and the security of the educational environment. Drawing upon a sample of 356 students from the Federal State-Funded Institution of Higher Education—Tomsk State University of Control Systems and Radioelectronics (TUSUR), we employed a partial least squares structural equation modeling (PLS-SEM) approach to analyze the data. The findings indicate that sociocultural security significantly influences students' behavioral intentions, with a confirmed negative impact on the intention to commit delinquency (β = -0.461, p < 0.05). Additionally, student well-being demonstrates a significant negative relationship with the intention to use drugs (β = -0.583, p < 0.01) and the intention to commit delinquency (β = -0.714, p < 0.001). However, the impact of sociocultural security and well-being on the intention to use drugs was not confirmed (β = -0.731, p > 0.05). Furthermore, the study reveals that students' behavioral intentions significantly affect the security of the educational environment. The intention to use drugs and the intention to commit delinquency negatively impact the security of the educational environment (β = -0.635, p > 0.05; β = -0.660, p < 0.05, respectively). These findings contribute to the understanding of the complex dynamics that shape the educational environment in universities. The study highlights the importance of promoting sociocultural security and fostering student well-being to prevent negative behavioral intentions and maintain a secure learning environment. Doi: 10.28991/ESJ-2023-07-05-018 Full Text: PDF
创造和维护一个安全和支持性的教育环境对大学生的成功和幸福至关重要。本研究旨在探讨毒品滥用、犯罪、社会文化因素与教育环境安全之间的相互作用。从联邦国家资助的高等教育机构-托木斯克国立控制系统和无线电电子大学(TUSUR)的356名学生中提取样本，我们采用偏最小二乘结构方程建模(PLS-SEM)方法来分析数据。研究结果表明，社会文化安全显著影响学生的行为意向，并对犯罪意向产生负向影响(β = -0.461, p <0.05)。此外，学生幸福感与吸毒倾向呈显著负相关(β = -0.583, p <0.01)和犯罪意图(β = -0.714, p <0.001)。然而，社会文化安全和幸福感对吸毒意愿的影响尚未得到证实(β = -0.731, p >0.05)。此外，研究发现学生的行为意向显著影响教育环境的安全性。吸毒倾向和犯罪倾向对教育环境的安全性产生负向影响(β = -0.635, p >0.05;β = -0.660, p <分别为0.05)。这些发现有助于理解塑造大学教育环境的复杂动态。该研究强调了促进社会文化安全和培养学生幸福感的重要性，以防止消极的行为意图和维护安全的学习环境。Doi: 10.28991/ESJ-2023-07-05-018全文:PDF
{"title":"The Impact of Drug Abuse and Delinquency on Educational Environment Security","authors":"Vera V. Orlova, Larisa V. Shevchenko","doi":"10.28991/esj-2023-07-05-018","DOIUrl":"https://doi.org/10.28991/esj-2023-07-05-018","url":null,"abstract":"Creating and maintaining a secure and supportive educational environment is essential for the success and well-being of university students. This study investigates the interplay between drug abuse, delinquency, sociocultural factors, and the security of the educational environment. Drawing upon a sample of 356 students from the Federal State-Funded Institution of Higher Education—Tomsk State University of Control Systems and Radioelectronics (TUSUR), we employed a partial least squares structural equation modeling (PLS-SEM) approach to analyze the data. The findings indicate that sociocultural security significantly influences students' behavioral intentions, with a confirmed negative impact on the intention to commit delinquency (β = -0.461, p < 0.05). Additionally, student well-being demonstrates a significant negative relationship with the intention to use drugs (β = -0.583, p < 0.01) and the intention to commit delinquency (β = -0.714, p < 0.001). However, the impact of sociocultural security and well-being on the intention to use drugs was not confirmed (β = -0.731, p > 0.05). Furthermore, the study reveals that students' behavioral intentions significantly affect the security of the educational environment. The intention to use drugs and the intention to commit delinquency negatively impact the security of the educational environment (β = -0.635, p > 0.05; β = -0.660, p < 0.05, respectively). These findings contribute to the understanding of the complex dynamics that shape the educational environment in universities. The study highlights the importance of promoting sociocultural security and fostering student well-being to prevent negative behavioral intentions and maintain a secure learning environment. Doi: 10.28991/ESJ-2023-07-05-018 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135849678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.28991/esj-2023-07-05-03
Francisco Cruz, Mauro Castelli
One of the main challenges when training or fine-tuning a machine learning model concerns the number of observations necessary to achieve satisfactory performance. While, in general, more training observations result in a better-performing model, collecting more data can be time-consuming, expensive, or even impossible. For this reason, investigating the relationship between the dataset's size and the performance of a machine learning model is fundamental to deciding, with a certain likelihood, the minimum number of observations that are necessary to ensure a satisfactory-performing model is obtained as a result of the training process. The learning curve represents the relationship between the dataset’s size and the performance of the model and is especially useful when choosing a model for a specific task or planning the annotation work of a dataset. Thus, the purpose of this paper is to find the functions that best fit the learning curves of a Transformers-based model (LayoutLM) when fine-tuned to extract information from invoices. Two new datasets of invoices are made available for such a task. Combined with a third dataset already available online, 22 sub-datasets are defined, and their learning curves are plotted based on cross-validation results. The functions are fit using a non-linear least squares technique. The results show that both a bi-asymptotic and a Morgan-Mercer-Flodin function fit the learning curves extremely well. Also, an empirical relation is presented to predict the learning curve from a single parameter that may be easily obtained in the early stage of the annotation process. Doi: 10.28991/ESJ-2023-07-05-03 Full Text: PDF
{"title":"Learning Curves Prediction for a Transformers-Based Model","authors":"Francisco Cruz, Mauro Castelli","doi":"10.28991/esj-2023-07-05-03","DOIUrl":"https://doi.org/10.28991/esj-2023-07-05-03","url":null,"abstract":"One of the main challenges when training or fine-tuning a machine learning model concerns the number of observations necessary to achieve satisfactory performance. While, in general, more training observations result in a better-performing model, collecting more data can be time-consuming, expensive, or even impossible. For this reason, investigating the relationship between the dataset's size and the performance of a machine learning model is fundamental to deciding, with a certain likelihood, the minimum number of observations that are necessary to ensure a satisfactory-performing model is obtained as a result of the training process. The learning curve represents the relationship between the dataset’s size and the performance of the model and is especially useful when choosing a model for a specific task or planning the annotation work of a dataset. Thus, the purpose of this paper is to find the functions that best fit the learning curves of a Transformers-based model (LayoutLM) when fine-tuned to extract information from invoices. Two new datasets of invoices are made available for such a task. Combined with a third dataset already available online, 22 sub-datasets are defined, and their learning curves are plotted based on cross-validation results. The functions are fit using a non-linear least squares technique. The results show that both a bi-asymptotic and a Morgan-Mercer-Flodin function fit the learning curves extremely well. Also, an empirical relation is presented to predict the learning curve from a single parameter that may be easily obtained in the early stage of the annotation process. Doi: 10.28991/ESJ-2023-07-05-03 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135849837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.28991/esj-2023-07-05-017
T. Aznal Zahri, Abdul Rahman Lubis, Muslim A. Djalil, . Syafruddin
Objective: This study examines how collaborative public innovation, transformational leadership, knowledge acquisition, employee competencies, innovative climate, and organizational performance affect service quality at the Regional Planning Agency of Aceh. Methods/Analysis: The study used quantitative analysis, qualitative interviews, and surveys. The data were analyzed using the SERVQUAL model and scatter analysis approaches. The correlation between variables was analyzed by Spearman rho correlation, while Kruskal-Wallis analyzed the significance between variables. Finding: The SERVQUAL model shows the Regional Planning Agency of Aceh provides good quality services; 98% of respondents gave an excellent rating, and 12% were good. Scatter analysis shows that the agency consistently meets expectations. Spearman rho correlation analysis shows that all determinant factor variables have a strong relationship with improving service quality and are also significant between variables (p<0.05). Novelty/Improvement: Improving the quality of the organization (Regional Planning Agency of Aceh) is primarily determined by the knowledge acquisition factor, which is followed by collaborative public innovation, transformational leadership, employee competencies, and an innovative climate. Doi: 10.28991/ESJ-2023-07-05-017 Full Text: PDF
{"title":"Analysis of Service Quality Factors of the Regional Planning Agency of Aceh","authors":"T. Aznal Zahri, Abdul Rahman Lubis, Muslim A. Djalil, . Syafruddin","doi":"10.28991/esj-2023-07-05-017","DOIUrl":"https://doi.org/10.28991/esj-2023-07-05-017","url":null,"abstract":"Objective: This study examines how collaborative public innovation, transformational leadership, knowledge acquisition, employee competencies, innovative climate, and organizational performance affect service quality at the Regional Planning Agency of Aceh. Methods/Analysis: The study used quantitative analysis, qualitative interviews, and surveys. The data were analyzed using the SERVQUAL model and scatter analysis approaches. The correlation between variables was analyzed by Spearman rho correlation, while Kruskal-Wallis analyzed the significance between variables. Finding: The SERVQUAL model shows the Regional Planning Agency of Aceh provides good quality services; 98% of respondents gave an excellent rating, and 12% were good. Scatter analysis shows that the agency consistently meets expectations. Spearman rho correlation analysis shows that all determinant factor variables have a strong relationship with improving service quality and are also significant between variables (p<0.05). Novelty/Improvement: Improving the quality of the organization (Regional Planning Agency of Aceh) is primarily determined by the knowledge acquisition factor, which is followed by collaborative public innovation, transformational leadership, employee competencies, and an innovative climate. Doi: 10.28991/ESJ-2023-07-05-017 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135849838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-24DOI: 10.28991/esj-2023-sied2-014
M. Alkhazaleh, B. F. Obeidat, S. Abdel-Hadi, Reema Al-Qaruty
The study aimed to assess the relationship between a safe learning environment in Emirati schools and the development of student's creative thinking. Using a descriptive method with stratified random sampling, the researchers selected a sample of 500 male and female teachers. Two questionnaires were employed: one assessing the safe learning environment (20 items) and another measuring creative thinking (20 items). Results indicated a high teacher perception of a safe learning environment, with statistically significant chi-square values for all items. Similarly, teachers perceived a high level of creative thinking development, with significant chi-square values for all items. Gender and experience did not show statistically significant differences in the perception of a safe learning environment. However, teachers with over 10 years of experience demonstrated higher levels of creative thinking development. Notably, a significant correlation was found between a safe learning environment and the development of students' creative thinking in Emirati schools. This study aligns with the UAE Ministry of Education's mission to create a safe and creative educational system that meets the needs of a globally competitive knowledge society. Doi: 10.28991/ESJ-2023-SIED2-014 Full Text: PDF
{"title":"The Safe Learning Environment in the United Arab Emirates Schools and Its Relationship to the Development of Creative Thinking Among Students","authors":"M. Alkhazaleh, B. F. Obeidat, S. Abdel-Hadi, Reema Al-Qaruty","doi":"10.28991/esj-2023-sied2-014","DOIUrl":"https://doi.org/10.28991/esj-2023-sied2-014","url":null,"abstract":"The study aimed to assess the relationship between a safe learning environment in Emirati schools and the development of student's creative thinking. Using a descriptive method with stratified random sampling, the researchers selected a sample of 500 male and female teachers. Two questionnaires were employed: one assessing the safe learning environment (20 items) and another measuring creative thinking (20 items). Results indicated a high teacher perception of a safe learning environment, with statistically significant chi-square values for all items. Similarly, teachers perceived a high level of creative thinking development, with significant chi-square values for all items. Gender and experience did not show statistically significant differences in the perception of a safe learning environment. However, teachers with over 10 years of experience demonstrated higher levels of creative thinking development. Notably, a significant correlation was found between a safe learning environment and the development of students' creative thinking in Emirati schools. This study aligns with the UAE Ministry of Education's mission to create a safe and creative educational system that meets the needs of a globally competitive knowledge society. Doi: 10.28991/ESJ-2023-SIED2-014 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45562908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-24DOI: 10.28991/esj-2023-sied2-015
Lenka Pasternáková, Silvia Barnová, M. Zelina, Slávka Krásna, Gabriela Gabrhelová
The aim of the study is to present a newly developed research instrument examining the determinants of second chance programmes’ success or failure from the perspective of teachers. In the theoretical part of the study, the authors elaborate on the issues of second chance education and focus on factors having a direct impact on the results of its realization. Subsequently, the Second Chance Education Indicators Questionnaire developed by the authors, the results of the carried out internal factorial analysis, as well as the calculated correlations, are presented. Based on the gathered data from 1,038 teachers, seven factors – "Satisfying employers’ needs in the field of education"; "Promoting the development of teachers’ competencies for second chance education"; "Providing teachers with support in developing their professional skills in the field of second chance education"; "Funding schools providing second chance education"; "The system of dual VET in second chance education"; and "Potentials for increasing the quality of second chance education" – were identified, and the existence of an internal factorial structure was confirmed. Since there is no other available research tool for identifying these determinants, it can be assumed that the Second Chance Education Indicators Questionnaire is a unique research tool, which can be used for further research activities and can contribute to broadening the current knowledge in the field. Doi: 10.28991/ESJ-2023-SIED2-015 Full Text: PDF
{"title":"Determinants of the Realization of Second Chance Education","authors":"Lenka Pasternáková, Silvia Barnová, M. Zelina, Slávka Krásna, Gabriela Gabrhelová","doi":"10.28991/esj-2023-sied2-015","DOIUrl":"https://doi.org/10.28991/esj-2023-sied2-015","url":null,"abstract":"The aim of the study is to present a newly developed research instrument examining the determinants of second chance programmes’ success or failure from the perspective of teachers. In the theoretical part of the study, the authors elaborate on the issues of second chance education and focus on factors having a direct impact on the results of its realization. Subsequently, the Second Chance Education Indicators Questionnaire developed by the authors, the results of the carried out internal factorial analysis, as well as the calculated correlations, are presented. Based on the gathered data from 1,038 teachers, seven factors – \"Satisfying employers’ needs in the field of education\"; \"Promoting the development of teachers’ competencies for second chance education\"; \"Providing teachers with support in developing their professional skills in the field of second chance education\"; \"Funding schools providing second chance education\"; \"The system of dual VET in second chance education\"; and \"Potentials for increasing the quality of second chance education\" – were identified, and the existence of an internal factorial structure was confirmed. Since there is no other available research tool for identifying these determinants, it can be assumed that the Second Chance Education Indicators Questionnaire is a unique research tool, which can be used for further research activities and can contribute to broadening the current knowledge in the field. Doi: 10.28991/ESJ-2023-SIED2-015 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41577947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-27DOI: 10.28991/esj-2023-sied2-010
David Mhlanga
Digital transformation is the coordination of digital technologies with organizational aspects and human variables in a specific setting. It goes beyond simply implementing a technology solution. Additionally, it calls for the thoughtful and complete application of digital technology to the creation of new skills and theoretical frameworks. The goal of the current study is to examine the basic practices that will propel Industry 4.0's digital transformation of the educational sector. Utilizing a qualitative research approach that included a comparison and analysis of the relevant body of earlier work, the study discovered that digital transformation in education can be driven by several factors, including campus safety, data security, student achievement, strategy, data enablement, student-cantered services, cost and availability, digital integration, and artificial intelligence. The study concluded with a variety of strategies that can aid in the digital transformation of universities and other institutions of higher learning, like establishing a solid foundation for information and communication technology systems and delivering cyber security that is up to date with current best practices, among the many strategies suggested. Doi: 10.28991/ESJ-2023-SIED2-010 Full Text: PDF
{"title":"The Fundamental Strategies that will Drive Higher Educational Sector Towards Digital Transformation in Industry 4.0","authors":"David Mhlanga","doi":"10.28991/esj-2023-sied2-010","DOIUrl":"https://doi.org/10.28991/esj-2023-sied2-010","url":null,"abstract":"Digital transformation is the coordination of digital technologies with organizational aspects and human variables in a specific setting. It goes beyond simply implementing a technology solution. Additionally, it calls for the thoughtful and complete application of digital technology to the creation of new skills and theoretical frameworks. The goal of the current study is to examine the basic practices that will propel Industry 4.0's digital transformation of the educational sector. Utilizing a qualitative research approach that included a comparison and analysis of the relevant body of earlier work, the study discovered that digital transformation in education can be driven by several factors, including campus safety, data security, student achievement, strategy, data enablement, student-cantered services, cost and availability, digital integration, and artificial intelligence. The study concluded with a variety of strategies that can aid in the digital transformation of universities and other institutions of higher learning, like establishing a solid foundation for information and communication technology systems and delivering cyber security that is up to date with current best practices, among the many strategies suggested. Doi: 10.28991/ESJ-2023-SIED2-010 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135753716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-27DOI: 10.28991/esj-2023-sied2-013
David Jacob, R. Henriques
Predicting academic success is essential in higher education because it is perceived as a critical driver for scientific and technological advancement and countries’ economic and social development. This paper aims to retrieve the most relevant attributes for academic success by applying educational data mining (EDM) techniques to a Portuguese business school bachelor’s historical data. We propose two predictive models to classify each student regarding academic success at enrolment and the end of the first academic year. We implemented a SEMMA methodology and tried several machine learning algorithms, including decision trees, KNN, neural networks, and SVM. The best classifier for academic success at the entry-level reached is a random forest with an accuracy of 69%. At the end of the first academic year, an MLP artificial neural network’s best performance was achieved with an accuracy of 85%. The main findings show that at enrolment or the end of the first year, the grades and, thus, the student’s previous education and engagement with the school environment are decisive in achieving academic success. Doi: 10.28991/ESJ-2023-SIED2-013 Full Text: PDF
{"title":"Educational Data Mining to Predict Bachelors Students’ Success","authors":"David Jacob, R. Henriques","doi":"10.28991/esj-2023-sied2-013","DOIUrl":"https://doi.org/10.28991/esj-2023-sied2-013","url":null,"abstract":"Predicting academic success is essential in higher education because it is perceived as a critical driver for scientific and technological advancement and countries’ economic and social development. This paper aims to retrieve the most relevant attributes for academic success by applying educational data mining (EDM) techniques to a Portuguese business school bachelor’s historical data. We propose two predictive models to classify each student regarding academic success at enrolment and the end of the first academic year. We implemented a SEMMA methodology and tried several machine learning algorithms, including decision trees, KNN, neural networks, and SVM. The best classifier for academic success at the entry-level reached is a random forest with an accuracy of 69%. At the end of the first academic year, an MLP artificial neural network’s best performance was achieved with an accuracy of 85%. The main findings show that at enrolment or the end of the first year, the grades and, thus, the student’s previous education and engagement with the school environment are decisive in achieving academic success. Doi: 10.28991/ESJ-2023-SIED2-013 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44632924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-27DOI: 10.28991/esj-2023-sied2-012
E. Gkintoni, I. Dimakos, C. Halkiopoulos, H. Antonopoulou
Objectives: In education, neuroscience is an interdisciplinary research field. It seeks to improve educational practice by applying brain research findings. Additional findings from the scientific fields of education, psychology, and neurophysiology aim to enhance the learning process and improve educational practices. The application of neuroscience to education involves neuroscientific and psychological knowledge. Methods/Analysis: In this systematic literature review, the final studies included in the analysis table are decided by searching databases according to predefined inclusion criteria. The PRISMA approach was utilized to study the relationship between neuroscience and the educational process and to optimize the educational process based on the relevant data. Findings: The review's findings emphasize the significance of integrating neuroscience into educational praxis and challenges and raise ethical concerns regarding its implementation in educational contexts. Novelty /Improvement: The discipline of educational neuroscience is associated with education, research, and the cognitive neuroscience of learning. Neuroscience can serve as the basis for education in a similar direction that biology serves as the basis for medicine, meaning that each field retains its innovation but cannot contravene the rules of the other. This study examines the relationship between neuroscience and educational praxis as well as how the educational community might bridge this gap to include prospective findings from neuroscientific research. Doi: 10.28991/ESJ-2023-SIED2-012 Full Text: PDF
{"title":"Contributions of Neuroscience to Educational Praxis: A Systematic Review","authors":"E. Gkintoni, I. Dimakos, C. Halkiopoulos, H. Antonopoulou","doi":"10.28991/esj-2023-sied2-012","DOIUrl":"https://doi.org/10.28991/esj-2023-sied2-012","url":null,"abstract":"Objectives: In education, neuroscience is an interdisciplinary research field. It seeks to improve educational practice by applying brain research findings. Additional findings from the scientific fields of education, psychology, and neurophysiology aim to enhance the learning process and improve educational practices. The application of neuroscience to education involves neuroscientific and psychological knowledge. Methods/Analysis: In this systematic literature review, the final studies included in the analysis table are decided by searching databases according to predefined inclusion criteria. The PRISMA approach was utilized to study the relationship between neuroscience and the educational process and to optimize the educational process based on the relevant data. Findings: The review's findings emphasize the significance of integrating neuroscience into educational praxis and challenges and raise ethical concerns regarding its implementation in educational contexts. Novelty /Improvement: The discipline of educational neuroscience is associated with education, research, and the cognitive neuroscience of learning. Neuroscience can serve as the basis for education in a similar direction that biology serves as the basis for medicine, meaning that each field retains its innovation but cannot contravene the rules of the other. This study examines the relationship between neuroscience and educational praxis as well as how the educational community might bridge this gap to include prospective findings from neuroscientific research. Doi: 10.28991/ESJ-2023-SIED2-012 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43324763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-27DOI: 10.28991/esj-2023-sied2-011
E. Alghazo, Mahmoud Gharaibeh, S. Abdel-Hadi
Children with learning difficulties often face challenges in social skills, hindering their ability to adjust and interact within society. The present study was designed to evaluate the effectiveness of a training program designed to enhance the social skills of individuals with disabilities. The quasi-experimental study involved 20 primary school students with learning difficulties exhibiting deficits in social skills in the United Arab Emirates. To evaluate the level of social skills of the sample children, a social skills assessment scale was employed, which was developed by the researchers. The assessment scale consisted of 24 statements that were organized into three dimensions based on previous research and theoretical frameworks. The results of the present study showed that the training program significantly and positively impacted the social skills of these children. There were statistically significant disparities between the mean ranks of the experimental group and the control group's scores on the social skills assessment scale after program completion. In conclusion, the study recommends integrating the developed training and similar programs into the public and private education curricula, including both government and private schools, to improve the social communication abilities of children with learning difficulties. Doi: 10.28991/ESJ-2023-SIED2-011 Full Text: PDF
{"title":"Effect of a Classroom-based Intervention on the Social Skills of Students with Learning Difficulties","authors":"E. Alghazo, Mahmoud Gharaibeh, S. Abdel-Hadi","doi":"10.28991/esj-2023-sied2-011","DOIUrl":"https://doi.org/10.28991/esj-2023-sied2-011","url":null,"abstract":"Children with learning difficulties often face challenges in social skills, hindering their ability to adjust and interact within society. The present study was designed to evaluate the effectiveness of a training program designed to enhance the social skills of individuals with disabilities. The quasi-experimental study involved 20 primary school students with learning difficulties exhibiting deficits in social skills in the United Arab Emirates. To evaluate the level of social skills of the sample children, a social skills assessment scale was employed, which was developed by the researchers. The assessment scale consisted of 24 statements that were organized into three dimensions based on previous research and theoretical frameworks. The results of the present study showed that the training program significantly and positively impacted the social skills of these children. There were statistically significant disparities between the mean ranks of the experimental group and the control group's scores on the social skills assessment scale after program completion. In conclusion, the study recommends integrating the developed training and similar programs into the public and private education curricula, including both government and private schools, to improve the social communication abilities of children with learning difficulties. Doi: 10.28991/ESJ-2023-SIED2-011 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46821832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.28991/esj-2023-07-04-016
A. W. Bustan, A. Salman, P. E. Putri, Z. Awanis
Locating the rainbow connection number of graphs is a new mathematical concept that combines the concepts of the rainbow vertex coloring and the partition dimension. In this research, we determine the lower and upper bounds of the locating rainbow connection number of a graph and provide the characterization of graphs with the locating rainbow connection number equal to its upper and lower bounds to restrict the upper and lower bounds of the locating rainbow connection number of a graph. We also found the locating rainbow connection number of trees and regular bipartite graphs. The method used in this study is a deductive method that begins with a literature study related to relevant previous research concepts and results, making hypotheses, conducting proofs, and drawing conclusions. This research concludes that only path graphs with orders 2, 3, 4, and complete graphs have a locating rainbow connection number equal to 2 and the order of graph G, respectively. We also showed that the locating rainbow connection number of bipartite regular graphs is in the range of r-⌊n/4⌋+2 to n/2+1, and the locating rainbow connection number of a tree is determined based on the maximum number of pendants or the maximum number of internal vertices. Doi: 10.28991/ESJ-2023-07-04-016 Full Text: PDF
{"title":"On the Locating Rainbow Connection Number of Trees and Regular Bipartite Graphs","authors":"A. W. Bustan, A. Salman, P. E. Putri, Z. Awanis","doi":"10.28991/esj-2023-07-04-016","DOIUrl":"https://doi.org/10.28991/esj-2023-07-04-016","url":null,"abstract":"Locating the rainbow connection number of graphs is a new mathematical concept that combines the concepts of the rainbow vertex coloring and the partition dimension. In this research, we determine the lower and upper bounds of the locating rainbow connection number of a graph and provide the characterization of graphs with the locating rainbow connection number equal to its upper and lower bounds to restrict the upper and lower bounds of the locating rainbow connection number of a graph. We also found the locating rainbow connection number of trees and regular bipartite graphs. The method used in this study is a deductive method that begins with a literature study related to relevant previous research concepts and results, making hypotheses, conducting proofs, and drawing conclusions. This research concludes that only path graphs with orders 2, 3, 4, and complete graphs have a locating rainbow connection number equal to 2 and the order of graph G, respectively. We also showed that the locating rainbow connection number of bipartite regular graphs is in the range of r-⌊n/4⌋+2 to n/2+1, and the locating rainbow connection number of a tree is determined based on the maximum number of pendants or the maximum number of internal vertices. Doi: 10.28991/ESJ-2023-07-04-016 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41605396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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