Search results for: state of learning

Authors: Jin-Hee Kim

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The way that globalization distinguishes itself from the previous changes is scope and intensity of changes, which together affect many parts of a nation’s system. In this way, globalization has its relation with the concept of ‘internationalization’ in that a nation state formulates a set of strategies in many areas of its governance to actively react to it. In short, globalization is a ‘catalyst,’ and internationalization is a ‘response’. In this regard, the field of higher education is one of the representative cases that globalization has several consequences that change the terrain of national policy-making. Started and been dominated mainly by the Western world, it has now been expanded to the ‘late movers,’ such as Asia-Pacific countries. The case of internationalization of Korean higher education is, therefore, located in a unique place in this arena. Yet Korea still is one of the major countries of sending its students to the so-called, ‘first world.’ On the other hand, it has started its effort to recruit international students from the world to its higher education system. After new Millennium, particularly, internationalization of higher education has been launched in its full-scale and gradually been one of the important global policy agenda, striving in both ways by opening its turf to foreign educational service providers and recruiting prospective students from other countries. Particularly the latter, recruiting international students, has been highlighted under the government project named ‘Study Korea,’ launched in 2004. Not only global, but also local issues and motivations were based to launch this nationwide project. Bringing international students means various desirable economic outcomes such as reducing educational deficit as well as utilizing them in Korean industry after the completion of their study, to name a few. In addition, in a similar vein, Korea's higher education institutes have started to have a new comers of adult learners. When it comes to the questions regarding the quality and access of this new learning agency, the answer is quite tricky. This study will investigate the different dimension of education provision and learning process to empower diverse group regardless of nationality, race, class and gender in Korea. Listening to the voices of international students and adult learning as non-traditional participants in a changing Korean higher educational space not only benefit students themselves, but Korean stakeholders who should try to accommodate more comprehensive and fair educational provisions for more and more diversifying groups of learners.

Keywords: education equity, access, globalisation, international students, adult learning, learning support

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Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: Vasiliki Stratidou

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Modern simulation mobile games have the potential to enhance students’ interest, motivation and creativity. Research conducted on the effectiveness of digital games for educational purposes has shown that such games are also ideal at providing an appropriate environment for language learning. The paper examines the issue of simulation mobile games in regard to the potential positive impacts on L2 vocabulary learning. Sixteen intermediate level students, aged 10-14, participated in the experimental study for four weeks. The participants were divided into experimental (8 participants) and control group (8 participants). The experimental group was planned to learn some new vocabulary words via digital games while the control group used a reading passage to learn the same vocabulary words. The study investigated the effect of mobile games as well as the traditional learning methods on Greek EFL learners’ vocabulary learning in a pre-test, an immediate post-test, and a two-week delayed retention test. A teacher’s diary and learners’ interviews were also used as tools to estimate the effectiveness of the implementation. The findings indicated that the experimental group outperformed the control group in acquiring new words through mobile games. Therefore, digital games proved to be an effective tool in learning English vocabulary.

Keywords: control group, digital games, experimental group, second language vocabulary learning, simulation games

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Authors: Luis Miguel Méndez Díaz

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In this article, a mathematics teaching-learning strategy will be presented, specifically differential calculus in one variable, in a fun and competitive space in which the action on the part of the student is manifested and not only the repetition of information on the part of the teacher. Said action refers to motivating, problematizing, summarizing, and coordinating a game of dominoes whose thematic cards are designed around the basic and main contents of differential calculus. The strategies for teaching this area are diverse and precisely the game of dominoes is one of the most used strategies in the practice of mathematics because it stimulates logical reasoning and mental abilities. The objective on this investigation is to identify the way in which the game of dominoes affects the learning and understanding of fundamentals concepts of differential calculus in one variable through experimentation carried out on students of the first semester of the School of Engineering and Sciences of the Technological Institute of Monterrey Campus Querétaro. Finally, the results of this study will be presented and the use of this strategy in other topics around mathematics will be recommended to facilitate logical and meaningful learning in students.

Keywords: collaborative learning, logical-mathematical intelligence, mathematical games, multiple intelligences

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Authors: Mohamed Elhadi M. Sharif, Mona Masood

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The usage of e-health facilities is seen to be the first priority by the Libyan government. As such, this paper focuses on how the key factors or elements of working size in terms of technological availability, structural environment, and other competence-related matters may affect nurses’ sharing of knowledge in e-health. Hence, this paper investigates learning readiness assessment to raise e-health for Libyan regional hospitals by using e-health services in nursing education.

Keywords: Libyan nurses, e-learning readiness, e-health, nursing education

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Authors: Gladys Gakenia Njoroge

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Mathematics is a compulsory subject in both primary and secondary schools in Kenya. However, learners’ poor performance in the subject in Kenya national examinations year in year out remains a serious concern for teachers of Mathematics, parents, curriculum developers, and the general public. This is particularly worrying because of the importance attached to the subject in national development hence the need to find out what could be affecting learning of Mathematics in Kenyan schools. The research on which this paper is based sought to examine the factors that influence performance in Mathematics in Kenyan schools; identify the characteristics of Mathematics learning disabilities; determine how the learners with such learning disabilities can be assessed and identified and interventions for these difficulties implemented. A case study was undertaken on class six learners in a primary school in Nairobi County. The tools used for the research were: classroom observations and an Individualized Education Program (IEP) developed by the teachers with the help of the researcher. This paper therefore highlights the findings from the research, discusses the implications of the findings and suggests the way forward as far as teaching, learning and assessment of Mathematics in Kenyan schools is concerned. Perhaps with the application of the right interventions, poor performance in Mathematics in the national examinations in Kenya will be a thing of the past.

Keywords: demystifying mathematics, individualized education program, learning difficulties, assessment

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Authors: Habtamu Anagaw Muluneh, Gebregziabher Kahsay, Tamiru Negussie

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Theoretical study of the density of state, condensation energy, specific heat, and magnetization in a spin-triplet superconductor are the main goals of this work. Utilizing the retarded double-time temperature-dependent Green's function formalism and building a model Hamiltonian for the system at hand, we were able to derive the expressions for the parameters mentioned above. The phase diagrams are plotted using MATLAB scripts. From the phase diagrams, the density of electrons increases as the excitation energy increases, and the maximum excitation energy is equal to the superconducting gap, but it decreases when the value exceeds the gap and finally becomes the same as the density of the normal state. On the other hand, the condensation energy decreases with the increase in temperature and attains its minimum value at the superconducting transition temperature but increases with the increase in superconducting transition temperature (TC) and finally becomes zero, implying the superconducting energy is equal to the normal state energy. The specific heat increases with the increase in temperature, attaining its maximum value at the TC and then undergoing a jump, showing the presence of a second-order phase transition from the superconducting state to the normal state. Finally, the magnetization of both the itinerant and localized electrons decreases with the increase in temperature and finally becomes zero at TC = 1.6 K and magnetic phase transition temperature T = 2 K, respectively, which results in a magnetic phase transition from a ferromagnetic to a paramagnetic state. Our finding is in good agreement with the previous findings.

Keywords: spin triplet superconductivity, Green’s function, condensation energy, density of state, specific heat, magnetization

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Authors: Michael Udey Udam

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Background: This study investigated the impact of cloud resources, a component of cloud computing, on science teachers’ effectiveness in secondary schools in Cross River State. Three (3) research questions and three (3) alternative hypotheses guided the study. Method: The descriptive survey design was adopted for the study. The population of the study comprised 1209 science teachers in public secondary schools of Cross River state. Sample: A sample of 487 teachers was drawn from the population using a stratified random sampling technique. The researcher-made structured questionnaire with 18 was used for data collection for the study. Research question one was answered using the Pearson Product Moment Correlation, while research question two and the hypotheses were answered using the Analysis of Variance (ANOVA) statistics in the Statistical Package for Social Sciences (SPSS) at a 0.05 level of significance. Results: The results of the study revealed that there is a positive correlation between the utilization of cloud resources in teaching and teaching effectiveness among science teachers in secondary schools in Cross River state; there is a negative correlation between gender and utilization of cloud resources among science teachers in secondary schools in Cross River state; and that there is a significant correlation between teaching experience and the utilization of cloud resources among science teachers in secondary schools in Cross River state. Conclusion: The study justifies the effectiveness of the Cross River state government policy of introducing cloud computing into the education sector. The study recommends that the policy should be sustained.

Keywords: cloud resources, science teachers, effectiveness, secondary school

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Authors: Gunniga Anugkakul, Suwaree Yordchim

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The objectives were to study language learning strategies (LLSs) employed by Chinese students, and the frequency of LLSs they used, and examine the relationship between the use of LLSs and gender. The Strategy Inventory for Language Learning (SILL) by Oxford was administered to thirty-six Chinese students at Suan Sunandha Rajabhat University in Thailand. The data obtained was analyzed using descriptive statistics and chi-square tests. Three useful findings were found on the use of LLSs reported by Chinese students. First, Chinese students used overall LLSs at a high level. Second, among the six strategy groups, Chinese students employed compensation strategy most frequently and memory strategy least frequently. Third, the research results also revealed that gender had significant effect on Chinese Student’s use of overall LLSs.

Keywords: English language, language learning strategy, Chinese students, compensation strategy

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Authors: Nigar Hussain

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It is a subset of big data. Dark data means those data in which we fail to use for future decisions. There are many issues in existing work, but some need powerful tools for utilizing dark data. It needs sufficient techniques to deal with dark data. That enables users to exploit their excellence, adaptability, speed, less time utilization, execution, and accessibility. Another issue is the way to utilize dark data to extract helpful information to settle on better choices. In this paper, we proposed upgrade strategies to remove the dark side from dark data. Using a supervised model and machine learning techniques, we utilized dark data and achieved an F1 score of 89.48%.

Keywords: big data, dark data, machine learning, heatmap, random forest

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Authors: Didiosky Benítez-Erice, Frederik Questier, Dalgys Pérez-Luján

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This paper aims to present two models around the production of students’ experiential knowledge in the teaching-learning process of higher education: the teacher-centered production model and the student-centered production model. From a range of knowledge management and experiential learning theories, the paper elaborates into the nature of students’ experiential knowledge and proposes further adjustments of existing second-generation knowledge management theories taking into account the particularities of higher education. Despite its theoretical nature the paper can be relevant for future studies that stress student-driven improvement and innovation at higher education institutions.

Keywords: experiential knowledge, higher education, knowledge management, teaching-learning process

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

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Authors: Amal A. Abdel-Sattar

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The curriculum of architecture department in Prince Sultan University includes ‘Building Surveying’ course which is usually a part of civil engineering courses. As a fundamental requirement of the course, it requires a strong background in mathematics and physics, which are not usually preferred subjects to the architecture students and many of them are not giving the required and necessary attention to these courses during their preparation year before commencing their architectural study. This paper introduces the concept and the methodology of the student-centered learning approach in the course of building surveying for architects. One of the major outcomes is the improvement in the students’ involvement in the course and how this will cover and strength their analytical weak points and improve their mathematical skills. The study is conducted through three semesters with a total number of 99 students. The effectiveness of the student-centered learning approach is studied using the student survey at the end of each semester and teacher observations. This survey showed great acceptance of the students for these methods. Also, the teachers observed a great improvement in the students’ mathematical abilities and how keener they became in attending the classes which were clearly reflected on the low absence record.

Keywords: architecture, building surveying, student-centered learning, teaching and learning

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Authors: Kanlaya Ratanasuphakarn, Suttipong Boonphadung

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The research on the development of ability in reading comprehension based on metacognitive strategies aimed to (1) improve the students’development of ability in reading comprehension based on metacognitive strategies, (2) evaluate the students’ satisfaction on using metacognitive strategies in learning as a tool developing the ability in reading comprehension. Forty-eight of Mattayom 3 students who have enrolled in the subject of research for learning development of semester 2 in 2013 were purposively selected as the research cohort. The research tools were lesson plans for reading comprehension, pre-posttest and satisfaction questionnaire that were approved as content validity and reliability (IOC=.66-1.00,0.967). The research found that the development of ability in reading comprehension of the research samples before using metacognitive strategies in learning activities was in the normal high level. Additionally, the research discovered that the students’ satisfaction of the research cohort after applying model in learning activities appeared to be high level of satisfaction on using metacognitive strategies in learning as a tool for the development of ability in reading comprehension.

Keywords: development of ability, metacognitive strategies, satisfaction, reading comprehension

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Authors: C. W. Kan

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This study examines the results of optical whitening process of different textiles such as cotton, wool and polyester. The optical whitening agents used are commercially available products, and the optical whitening agents were applied to the textiles with manufacturers’ suggested methods. The aim of this study is to illustrate the proper application methods of optical whitening agent to different textiles and hence to provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, optical whitening agent, wool, cotton, polyester

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Authors: Djehich Mohamed Yousri

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This research tries to highlight the different stages and developments of financial policy which has evolved significantly in its means and mechanism, goals as well, according to the successful developments of the society, in addition to that, the role of the country has been developed from custody to intervening country, that evolution does not impact only on financial science but it was reflected on financial system concepts, that helped fr transport it from neutral financial policy to intervening policy, since each stage was characterized by a set of characteristics, financial policy considers like reflective mirror to the role of state in all times, when the state has been absent as an organized authority to society, the role of financial policy was weakened and has been limited under the impact of ideology which exists at all time, financial role has was limited until the state intervened in all aspects of life, the state role is also influential in economic, social, and political life, this study highlighting the most important developments of financial policy under successful economic systems.

Keywords: public expenditure, government spending, taxes, revenues public, economics

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Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

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The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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Authors: R. Abdulrahman, A. Eardley, A. Soliman

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The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.

Keywords: mobile learning, nursing institute students’ acceptance of m-learning activity in Saudi Arabia, unified theory of acceptance and use of technology model (UTAUT), structural equation modelling (SEM)

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Authors: Naser Alajmi, Ali Alobaidly, Mubarak Alhajri, Salem Salamah, Muhammad Alsubaie

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Iterative Learning Control (ILC) known to be a controlling tool to overcome periodic disturbances for repetitive systems. This technique is required to let the error signal tends to zero as the number of operation increases. The learning process that lies within this context is strongly dependent on the initial input which if selected properly tends to let the learning process be more effective compared to the case where a system starts from blind. ILC uses previous recorded execution data to update the following execution/trial input such that a reference trajectory is followed to a high accuracy. Error convergence in ILC is generally highly dependent on the input applied to a plant for trial $1$, thus a good choice of initial starting input signal would make learning faster and as a consequence the error tends to zero faster as well. In the work presented within, an upper limit based on the Singular Values Principle (SV) is derived for the initial input signal applied at trial $1$ such that the system follow the reference in less number of trials without responding aggressively or exceeding the working envelope where a system is required to move within in a robot arm, for example. Simulation results presented illustrate the theory introduced within this paper.

Keywords: initial input, iterative learning control, maximum input, singular values

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Authors: Payal Maheshwari, Maheaswari Brindavan

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The present study aimed at studying the level of perceived self-efficacy of children with learning disability and their mother’s perception about the efficacy of the child and the relationship between the two. The study further aimed at finding out the relationship between the level of perceived self-efficacy of children with learning disability and their academic achievement and their mother’s perception about the Efficacy of the child and child’s Academic Achievement. The sample comprised of 80 respondents (40 children with learning disability and their mothers). Children with learning disability as their primary condition, belonging to middle or upper middle class, living with both the parents, residing in Mumbai and their mothers were selected. Purposive or judgmental and snowball sampling technique was used to select the sample for the present study. Proformas in the form of questionnaires were used to obtain the background information of the children with learning disability and their mother’s. A self-constructed Mother’s Perceived Efficacy of their Child Assessment Scale was used to measure mothers perceived level of efficacy of their child with learning disability. Self-constructed Child’s Perceived Self-Efficacy Assessment Scale was used to measure the level of child’s perceived self-efficacy. Academic scores of the child were collected from the child’s parents or teachers and were converted into percentage. The data were analyzed quantitatively using frequencies, mean and standard deviation. Correlations were computed to ascertain the relationships between the different variables. The findings revealed that majority of the mother’s perceived efficacy about their child with learning disability was above average as well as majority of the children with learning disability also perceived themselves as having above average level of self-efficacy. Further in the domains of self-regulated learning and emotional self-efficacy majority of the mothers perceived their child as having average or below average efficacy, 50% of the children also perceived their self-efficacy in the two domains at average or below average level. A significant (r=.322, p < .05) weak correlation (Spearman’s rho) was found between mother’s perceived efficacy about their child, and child’s perceived self-efficacy and a significant (r=.377, p < .01) weak correlation (Pearson Correlation) was also found between mother’s perceived efficacy about their child and child’s academic achievement. Significant weak positive correlation was found between child’s perceived self-efficacy and academic achievement (r=.332, p < .05). Based on the findings, the study discussed the need for intervention program for children in non-academic skills like self-regulation and emotional competence.

Keywords: learning disability, perceived self efficacy, academic achievement, mothers, children

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Authors: Suriya

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Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

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Authors: Khan Zeenat, S. B. Dandegaonkar

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Dyslexia is a neurological disorder which affects the reading and writing ability of children. A sample of 72 dyslexic children (36 from English medium and 36 from Marathi medium schools) of class V from English and Marathi medium schools were selected. The Experimental method was used to study the effect of Remedial Teaching Programme on the Learning outcome of Dyslexic students. The findings showed that there is a Positive effect of remedial teaching programme on the Learning outcome of English and Marathi medium students.

Keywords: remedial teaching, Dyslexic students, learning outcome, neurological

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Authors: Ngoc Dao

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State Paid Leave Programs (PFL) complement the Federal Family and Medical Leave Act (FMLA) by offering workers time off to take care of their newborns or sick family members with supplemental income, and further job protection. Up to date, four states (California, New Jersey, Rhode Island, and New York) implemented paid leave policies. This study adds further understanding of how state PFL policies help working families with elder parents improve their work balance by examining the paid leave policies on labor outcomes. Early findings suggest State Paid Leave Policies reduced the likelihood to exit the labor market by 1.6 percentage points, with larger effects among paid leave policies with job protection feature. In addition, the results imply job protection in paid leave policies matters in helping employed caregivers attach to the labor market.

Keywords: family paid leave, working caregivers, employment, social welfare

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Authors: Asra Yousuf, Ajaykumar Tannirkulum

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Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.

Keywords: development, migration, internal migration, machine learning, prediction

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Authors: Peng Liu

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Deep Q networks (DQNs) represent a significant advancement in reinforcement learning, utilizing neural networks to approximate the optimal Q-value for guiding sequential decision processes. This paper presents a comprehensive introduction to reinforcement learning principles, delves into the mechanics of DQNs, and explores its application in portfolio optimization. By evaluating the performance of DQNs against traditional benchmark portfolios, we demonstrate its potential to enhance investment strategies. Our results underscore the advantages of DQNs in dynamically adjusting asset allocations, offering a robust portfolio management framework.

Keywords: deep reinforcement learning, deep Q networks, portfolio optimization, multi-period optimization

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Authors: G. S. Androulakis, G. Deli, M. Kaisari, N. Mihos

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Teaching practices at the university level have changed and developed during the last decade. Implementation of inverted classroom method in secondary education consists of a well-formed basis for academic teachers. On the other hand, distance learning is a well-known field in education research and widespread as a method of teaching. Nonetheless, the new pandemic found many Universities all over the world unprepared, which made adaptations to new methods of teaching a necessity. In this paper, we analyze a model of an inverted university classroom in a distance learning context. Thus, the main purpose of our research is to investigate students’ difficulties as they transit to a new style of teaching and explore their learning development during a semester totally different from others. Our teaching experiment took place at the Business Administration department of the University of Patras, in the context of two courses: Calculus, a course aimed at first-year students, and Statistics, a course aimed at second-year students. Second-year students had the opportunity to attend courses in the university classroom. First-year students started their semester with distance learning. Using a comparative study of these two groups, we explored significant differences in students’ learning procedures. Focused group interviews, written tests, analyses of students’ dialogues were used in a mixed quantity and quality research. Our analysis reveals students’ skills, capabilities but also a difficulty in following, non-traditional style of teaching. The inverted classroom model, according to our findings, offers benefits in the educational procedure, even in a distance learning environment.

Keywords: distance learning, higher education, inverted classroom, mathematics teaching

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Authors: Olukemi E. Adetuyi-Olu-Francis

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Learning is natural for living. One stops learning when life ends. Hence, there is no negotiating life-long learning. An individual has the innate ability to learn as many languages as he/she desires as long as life exists. French language education to every Nigerian teacher-trainee is a necessity. Nigeria’s geographical location requires that the French language should be upheld for economic and cultural co-operations between Nigeria and the francophone countries sharing borders with her. The French language will enhance the leadership roles of the teacher-trainees and their ability to function across borders. The 21st century learning tools are basically digital, and many apps are complementing the actual classroom interactions. This study examined the communicative competence in the French language to equip Nigerian teacher-trainees in the new-normal society using mobile apps as a lifelong learning tool. Three research questions and hypotheses guided the study, and the researcher adopted a pre-test, a post-test experimental design, using a sample size of 87 teacher-trainees in South-south geopolitical zone of Nigeria. Results showed that the use of mobile apps is effective for learning the French language. One of the recommendations is that the use of mobile apps should be encouraged for all Nigerian youths to learn the French language for enhancing leadership roles in the world of work and for international interactions for socio-economic co-operations with Nigerian neighboring countries.

Keywords: communicative competence, french language, life long learning, mobile apps, new normal society, teacher trainees

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Authors: Eva Laryea, Clement Yeboah Authors

Abstract:

A pretest-posttest within subjects, experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising, as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers, and will continue to be a dynamic and rapidly evolving field for years to come.

Keywords: pretest-posttest within subjects, experimental design, achievement, statistics-related anxiety

Procedia PDF Downloads 64

Authors: Agah Tugrul Korucu

Abstract:

Significant changes have taken place for the better in the bulk of information and in the use of technology available in the field of education induced by technological changes in the 21st century. It is mainly the job of the teachers and pre-service teachers to integrate information and communication technologies into education by means of conveying the use of technology to individuals. While the pre-service teachers are conducting lessons by using technology, the methods they have developed are important factors for the requirements of the lesson and for the satisfaction levels of the students. The study of this study is to examine the satisfaction levels of pre-service teachers as regards e-learning in a technological environment in which there are lesson activities conducted through an online learning environment in terms of various variables. The study group of the research is composed of 156 pre-service teachers that were students in the departments of Computer and Teaching Technologies, Art Teaching and Pre-school Teaching in the academic year of 2014 - 2015. The qualitative research method was adopted for this study; the scanning model was employed in collecting the data. “The Satisfaction Scale regarding the E-learning Process”, developed by Gülbahar, and the personal information form, which was developed by the researcher, were used as means of collecting the data. Cronbach α reliability coefficient, which is the internal consistency coefficient of the scale, is 0.91. SPSS computerized statistical package program and the techniques of medium, standard deviation, percentage, correlation, t-test and variance analysis were used in the analysis of the data.

Keywords: online learning environment, integration of information technologies, e-learning, e-learning satisfaction, pre-service teachers

Procedia PDF Downloads 354

Authors: Manthekeleng Linake, Fesi Liziwe

Abstract:

The ongoing argument over the use of English as a learning and teaching language in schools was examined in this study. The nature of the language proficiency gap is particularly relevant in light of the present emphasis on learning and educational quality in contemporary debates, as well as the education sustainable development goal. As a result, an interpretivist paradigm, a qualitative technique, and a case study-based research design were used in the work. Two school principals, two teachers, two members of the School Governing Body (SGB), and four learners were chosen using purposive sampling from two schools in the Amathole West Education District. The researchers were able to acquire in-depth information on the disputes surrounding the use of English as a language of learning and teaching by using semi-structured interview questions and focus groups. Despite knowing that they do not have the potential to do well in English, teachers found that despite appreciating the value of mother tongue and cultural identity, they prefer to use English as the language of teaching in schools. The findings, on the other hand, revealed that proponents of mother-language-based education argue that learning one's mother tongue is a human right.

Keywords: English first additional language learners, social justice, human capabilities, language proficiency

Procedia PDF Downloads 144