Search results for: school dropout prediction

Authors: Gabriel Odeh Ankeli

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The study determined how mentoring enhanced strategy can increase self-efficacy of secondary school students in physics in education zone C of Benue State, Nigeria. The study was guided by two research questions while two hypotheses were formulated and tested at 0.05 level of significance. The design of the study was the quasi-experimental, non-randomized, pre-test and post-test control groups. The population of the study consisted of 4,064 SS two physics students in the 94 schools in Education Zone C. The sample comprised 406 SS two physics students drawn from 10 schools using multi-stage sampling technique. The research instrument adapted and used for data collection was Students Self-Efficacy Scale (SSES). The research instrument was subjected to a reliability analysis using Cronbachs Alpha which yielded a reliability co-efficient of 0.84. Data collected were analyzed using discriptive statistics of mean and standard deviation to answer the research questions while inferential statistics of Analysis of Covariance (ANCOVA) was used to test the hypotheses. The findings revealed that students who were exposed to mentoring exhibited lower self-efficacy levels (F 1,405 = 2.751, P = 0.09˃0.05) than those students who were not exposed to mentoring. There was significant difference between male and female students’ self-efficacy level (F 1,211 = 5.496, P = 0.02˂0.05). Based on these findings, it was recommended among others that longer duration of mentoring period should be encouraged when using the mentoring strategy for better enhancement of Self-efficacy of students.

Keywords: physics, self-efficacy, mentoring enhanced strategy, students

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Authors: Aid Abdelkrim

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A method of fatigue damage accumulation based upon application of energy parameters of the fatigue process is proposed in the paper. Using this model is simple, it has no parameter to be determined, it requires only the knowledge of the curve W–N (W: strain energy density N: number of cycles at failure) determined from the experimental Wöhler curve. To examine the performance of nonlinear models proposed in the estimation of fatigue damage and fatigue life of components under random loading, a batch of specimens made of 6082 T 6 aluminium alloy has been studied and some of the results are reported in the present paper. The paper describes an algorithm and suggests a fatigue cumulative damage model, especially when random loading is considered. This work contains the results of uni-axial random load fatigue tests with different mean and amplitude values performed on 6082T6 aluminium alloy specimens. The proposed model has been formulated to take into account the damage evolution at different load levels and it allows the effect of the loading sequence to be included by means of a recurrence formula derived for multilevel loading, considering complex load sequences. It is concluded that a ‘damaged stress interaction damage rule’ proposed here allows a better fatigue damage prediction than the widely used Palmgren–Miner rule, and a formula derived in random fatigue could be used to predict the fatigue damage and fatigue lifetime very easily. The results obtained by the model are compared with the experimental results and those calculated by the most fatigue damage model used in fatigue (Miner’s model). The comparison shows that the proposed model, presents a good estimation of the experimental results. Moreover, the error is minimized in comparison to the Miner’s model.

Keywords: damage accumulation, energy model, damage indicator, variable loading, random loading

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Authors: Kairat Kurakbayev, Dina Gungor, Adil Ashirbekov, Assel Kambatyrova

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Kazakhstan, a post-Soviet economy located in the Central Asia, is making great efforts to internationalize its national system of education. The country is very ambitious in making the national economy internationally competitive and education has become one of the main pillars of the nation’s strategic development plan for 2030. This paper discusses the role of professional teacher development in upgrading the secondary education curriculum with the introduction of English as a medium of instruction (EMI) in grades 10-11 grades. Having Kazakh as the state language and Russian as the official language, English bears a status of foreign language in the country. The development of trilingual education is very high on the agenda of the Ministry of Education and Science. It is planned that by 2019 STEM-related subjects – Biology, Chemistry, Computing and Physics – will be taught in EMI. Introducing English-medium education appears to be a very drastic reform and the teaching cadre is the key driver here. At the same time, after the collapse of the Soviet Union, the teaching profession is still struggling to become attractive in the eyes of the local youth. Moreover, the quality of Kazakhstan’s secondary education is put in question by OECD national review reports. The paper presents a case study of the nation-wide professional development programme arranged for 5 010 school teachers so that they could be able to teach their content subjects in English starting from 2019 onwards. The study is based on the mixed methods research involving the data derived from the surveys and semi-structured interviews held with the programme participants, i.e. school teachers. The findings of the study imply the significance of the school teachers’ attitudes towards the top-down reform of trilingual education. The qualitative research data reveal the teachers’ beliefs about advantages and disadvantages of having their content subjects (e.g. Biology or Chemistry) taught in EMI. The study highlights teachers’ concerns about their professional readiness to implement the top-down reform of English-medium education and discusses possible risks of academic underperforming on the part of students whose English language proficiency is not advanced. This paper argues that for the effective implementation of the English-medium education in secondary schools, the state should adopt a comprehensive approach to upgrading the national academic system where teachers’ attitudes and beliefs play the key role in making the trilingual education policy effective. The study presents lessons for other national academic systems considering to transfer its secondary education to English as a medium of instruction.

Keywords: teacher education, teachers' beliefs, trilingual education, case study

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Authors: Kathaleeya Chanda, Panupong Chanplin, Suppara Charoenpoom

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This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

Keywords: teaching learning model, digital media, creative instruction model, Bo Kluea school

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Authors: M. R. Babaei, S. M. Hosseini, S. Rahmani, L. Moradi

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Today, the quality of education and training systems and the effectiveness of the education systems of most concern to stakeholders and decision-makers of our country's development in each country. In Iran this is a double issue of concern to numerous reasons; So that governments, over the past decade have hardly even paid the running costs of education. ICT is claiming it has the power to change the structure of a program for training, reduce costs and increase quality, and do education systems and products consistent with the needs of the community and take steps to practice education. Own of the areas that the introduction of information technology has fundamentally changed is the field of education. The aim of this research is process reengineering management in schools simultaneously has been using field studies to collect data in the form of interviews and a questionnaire survey. The statistical community of this research has been the country of Iran and smart schools under the education. Sampling was targeted. The data collection tool was a questionnaire composed of two parts. The questionnaire consists of 36 questions that each question designates one of effective factors on the management of smart schools. Also each question consists of two parts. The first part designates the operating position in the management process, which represents the domain's belonging to the management agent (planning, organizing, leading, controlling). According to the classification of Dabryn and in second part the factors affect the process of managing the smart schools were examined, that Likert scale is used to classify. Questions the validity of the group of experts and prominent university professors in the fields of information technology, management and reengineering of approved and Cronbach's alpha reliability and also with the use of the formula is evaluated and approved. To analyse the data, descriptive and inferential statistics were used to analyse the factors contributing to the rating of (Linkert scale) descriptive statistics (frequency table data, mean, median, mode) was used. To analyse the data using analysis of variance and nonparametric tests and Friedman test, the assumption was evaluated. The research conclusions show that the factors influencing the management process re-engineering smart schools in school performance is affected.

Keywords: re-engineering, management process, smart school, Iran's school

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Authors: Ozoji Bernadette, Sa’Ad-Abdullahi Abdulhafiz, Izundu Chike Leo

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The study investigated the effect of Jigsaw strategy on senior secondary school students’ achievement in Maitagari, Jigawa State, Nigeria. The pre-test, post-test quasi experimental design was employed in the study. The sample for the study comprised 120 students from two public schools from the study area. An instrument namely, Ecological Achievement Test (EAT) was used to collect data from students. The data were analyzed using SPSS version 26.0. The EAT was validated by two experts, one, in Science Education unit and the other in Research, Measurement and Evaluation unit, both in the Faculty of Education, University of Jos, Nigeria. The reliability coefficient of the EAT was established as 0.85 using Kuder Richardson Formular 20. Mean and standard deviation were used to answer two research questions while Analysis of Covariance was used to test two hypotheses that guided the study. Results showed that students taught using jigsaw strategy achieved significantly better than their counterparts taught using the conventional method in ecology. Furthermore, it was revealed that gender had no significant influence on achievement of students exposed to jigsaw strategy. It was concluded that jigsaw strategy was effective in improving students’ achievement in ecology. The study recommended that teachers should incorporate jigsaw strategy into science classrooms for improved achievement outcome and gender equality.

Keywords: achievement, ecology, jigsaw strategy, lecture strategy

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Authors: Mustafa Salman, Nurcan Cetinkaya, Zehra Selcuk, Bugra Genc

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The objectives of the present study were to estimate the microbial-N flow to the small intestine and to predict the digestible organic matter intake (DOMI) in grazing Karayaka sheep based on urinary excretion of purine derivatives (xanthine, hypoxanthine, uric acid, and allantoin) by the use of spot urine sampling under field conditions. In the trial, 10 Karayaka sheep from 2 to 3 years of age were used. The animals were grazed in a pasture for ten months and fed with concentrate and vetch plus oat hay for the other two months (January and February) indoors. Highly significant linear and cubic relationships (P<0.001) were found among months for purine derivatives index, purine derivatives excretion, purine derivatives absorption, microbial-N and DOMI. Through urine sampling and the determination of levels of excreted urinary PD and Purine Derivatives / Creatinine ratio (PDC index), microbial-N values were estimated and they indicated that the protein nutrition of the sheep was insufficient. In conclusion, the prediction of protein nutrition of sheep under the field conditions may be possible with the use of spot urine sampling, urinary excreted PD and PDC index. The mean purine derivative levels in spot urine samples from sheep were highest in June, July and October. Protein nutrition of pastured sheep may be affected by weather changes, including rainfall. Spot urine sampling may useful in modeling the feed consumption of pasturing sheep. However, further studies are required under different field conditions with different breeds of sheep to develop spot urine sampling as a model.

Keywords: Karayaka sheep, spot sampling, urinary purine derivatives, PDC index, microbial-N, feed intake

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Authors: M. D. Haneef, R. B. Randall, Z. Peng

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Journal bearings used in IC engines are prone to premature failures and are likely to fail earlier than the rated life due to highly impulsive and unstable operating conditions and frequent starts/stops. Vibration signature extraction and wear debris analysis techniques are prevalent in the industry for condition monitoring of rotary machinery. However, both techniques involve a great deal of technical expertise, time and cost. Limited literature is available on the application of these techniques for fault detection in reciprocating machinery, due to the complex nature of impact forces that confounds the extraction of fault signals for vibration based analysis and wear prediction. This work is an extension of a previous study, in which an engine simulation model was developed using a MATLAB/SIMULINK program, whereby the engine parameters used in the simulation were obtained experimentally from a Toyota 3SFE 2.0 litre petrol engines. Simulated hydrodynamic bearing forces were used to estimate vibrations signals and envelope analysis was carried out to analyze the effect of speed, load and clearance on the vibration response. Three different loads 50/80/110 N-m, three different speeds 1500/2000/3000 rpm, and three different clearances, i.e., normal, 2 times and 4 times the normal clearance were simulated to examine the effect of wear on bearing forces. The magnitude of the squared envelope of the generated vibration signals though not affected by load, but was observed to rise significantly with increasing speed and clearance indicating the likelihood of augmented wear. In the present study, the simulation model was extended further to investigate the bearing wear behavior, resulting as a consequence of different operating conditions, to complement the vibration analysis. In the current simulation, the dynamics of the engine was established first, based on which the hydrodynamic journal bearing forces were evaluated by numerical solution of the Reynold’s equation. Also, the essential outputs of interest in this study, critical to determine wear rates are the tangential velocity and oil film thickness between the journal and bearing sleeve, which if not maintained appropriately, have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to calculate the wear rate of bearings with specific location information as all determinative parameters were obtained with reference to crank rotation. Oil film thickness obtained from the model was used as a criterion to determine if the lubrication is sufficient to prevent contact between the journal and bearing thus causing accelerated wear. A limiting value of 1 µm was used as the minimum oil film thickness needed to prevent contact. The increased wear rate with growing severity of operating conditions is analogous and comparable to the rise in amplitude of the squared envelope of the referenced vibration signals. Thus on one hand, the developed model demonstrated its capability to explain wear behavior and on the other hand it also helps to establish a correlation between wear based and vibration based analysis. Therefore, the model provides a cost-effective and quick approach to predict the impending wear in IC engine bearings under various operating conditions.

Keywords: condition monitoring, IC engine, journal bearings, vibration analysis, wear prediction

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Authors: Muhsin Kizhisseri, Jorg Schluter, Saleh Gharie

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Atherosclerosis is the main reason of stroke, which is one of the deadliest diseases in the world. The carotid artery in the brain is the prominent location for atherosclerotic progression, which hinders the blood flow into the brain. The inclusion of computational fluid dynamics (CFD) into the diagnosis cycle to understand the hemodynamics of the patient-specific carotid artery can give insights into stroke prediction. Realistic outlet boundary conditions are an inevitable part of the numerical simulations, which is one of the major factors in determining the accuracy of the CFD results. The Windkessel model-based outlet boundary conditions can give more realistic characteristics of the distal vascular branches of the carotid artery, such as the resistance to the blood flow and compliance of the distal arterial walls. This study aims to find the most influential distal branches of the carotid artery by using the Windkessel model parameters in the outlet boundary conditions. The parametric study approach to Windkessel model parameters can include the geometrical features of the distal branches, such as radius and length. The incorporation of the variations of the geometrical features of the major distal branches such as the middle cerebral artery, anterior cerebral artery, and ophthalmic artery through the Windkessel model can aid in identifying the most influential distal branch in the carotid artery. The results from this study can help physicians and stroke neurologists to have a more detailed and accurate judgment of the patient's condition.

Keywords: stroke, carotid artery, computational fluid dynamics, patient-specific, Windkessel model, distal vascular branches

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Amenaghawon Clement Osemwinyen

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The Activity, Student-centred, Experiment, Improvisation - Plan, Do, See, Improve (ASEI-PDSI) method championed by the Strengthening Mathematics And Science Education (SMASE) - Nigeria Project is an attempt to improve the quality of mathematics, which has consistently declined over the years in both public primary and secondary schools across the country. The study thus assessed the ASEI-PDSI method on students’ attitudes and achievement in junior secondary schools (JSS) mathematics in FCT-Abuja. A survey research design was adopted, and 100 mathematics teachers using a stratified random sampling method were used for the study. The data were collected using structured questionnaires and analyzed using descriptive statistics. The findings showed that the ASEI-PDSI method had significantly improved the attitudes of students toward mathematics. The study also revealed that the ASEI-PDSI method significantly influenced junior secondary school (JSS) students’ mathematics achievement. Amongst the recommendations were that teachers should be encouraged to adopt the ASEI-PDSI method in teaching and learning mathematics in order to create a mathematically stimulating classroom environment which could advertently influence junior secondary school (JSS) students’ attitude and academic performance in mathematics. Also, regular in-service training programs should be organized by stakeholders (government and other interest groups) so as to improve the teaching strategies of teachers, mostly as they affect the ASEI-PDSI method.

Keywords: achievement, ASEI-PDSI method, attitude, mathematics, SMASE

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Authors: Vadim A. Kuznetsov, Anna M. Soldatova, Tatyana N. Enina, Elena A. Gorbatenko, Dmitrii V. Krinochkin

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The aim of the study was to evaluate potential parameters related with super-response to CRT. Methods: 60 CRT patients (mean age 54.3 ± 9.8 years; 80% men) with congestive heart failure (CHF) II-IV NYHA functional class, left ventricular ejection fraction < 35% were enrolled. At baseline, 1 month, 3 months and each 6 months after implantation clinical, electrocardiographic and echocardiographic parameters, NT-proBNP level were evaluated. According to the best decrease of left ventricular end-systolic volume (LVESV) (mean follow-up period 33.7 ± 15.1 months) patients were classified as super-responders (SR) (n=28; reduction in LVESV ≥ 30%) and non-SR (n=32; reduction in LVESV < 30%). Results: At baseline groups differed in age (58.1 ± 5.8 years in SR vs 50.8 ± 11.4 years in non-SR; p=0.003), gender (female gender 32.1% vs 9.4% respectively; p=0.028), width of QRS complex (157.6 ± 40.6 ms in SR vs 137.6 ± 33.9 ms in non-SR; p=0.044). Percentage of LBBB was equal between groups (75% in SR vs 59.4% in non-SR; p=0.274). All parameters of mechanical dyssynchrony were higher in SR, but only difference in left ventricular pre-ejection period (LVPEP) was statistically significant (153.0 ± 35.9 ms vs. 129.3 ± 28.7 ms p=0.032). NT-proBNP level was lower in SR (1581 ± 1369 pg/ml vs 3024 ± 2431 pg/ml; p=0.006). The survival rates were 100% in SR and 90.6% in non-SR (log-rank test P=0.002). Multiple logistic regression analysis showed that LVPEP (HR 1.024; 95% CI 1.004–1.044; P = 0.017), baseline NT-proBNP level (HR 0.628; 95% CI 0.414–0.953; P=0.029) and age at baseline (HR 1.094; 95% CI 1.009-1.168; P=0.30) were independent predictors for CRT super-response. ROC curve analysis demonstrated sensitivity 71.9% and specificity 82.1% (AUC=0.827; p < 0.001) of this model in prediction of super-response to CRT. Conclusion: Super-response to CRT is associated with better survival in long-term period. Presence of LBBB was not associated with super-response. LVPEP, NT-proBNP level, and age at baseline can be used as independent predictors of CRT super-response.

Keywords: cardiac resynchronisation therapy, superresponse, congestive heart failure, left bundle branch block

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Authors: Tariqul Islam, Shaheen Mollah

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The study's main objective is to assess the relationship between psychological adjustment and parental acceptance-rejection, teacher acceptance-rejection, and best friend acceptance-rejection among secondary school students. This study was conducted on a sample of 300 (6th through 10th-grade students) recruited from over ten schools in Dhaka. While the schools were selected purposively, the respondents within each school were selected conveniently. The collected data were analyzed using Pearson product-moment correlation, hierarchical regression, and simultaneous regression analysis. The results showed that psychological adjustment is positively correlated with paternal, maternal, teacher, and best friend acceptance. The paternal acceptance was significantly connected with maternal acceptance. The teacher and best friend acceptance are correlated substantially with paternal and maternal acceptance. The hierarchical multiple regressions indicated that maternal, paternal, teacher, and best friend acceptance-rejection contributed significantly to students' psychological adjustment. The results revealed substantial independent contributions of maternal, paternal, teacher, and best friend acceptance on the students' psychological adjustment. The simultaneous regression analysis indicates that the maternal and best friend acceptances (but not paternal acceptance) were significant predictors of psychological adjustments. It showed that 41.7% variability in psychological adjustment could be explained by paternal, maternal, and best friend acceptance. The findings of the present study are exciting. They may contribute to developing insight in parents and best friends for behaving properly with their offspring and friend, respectively, for better psychological adjustment.

Keywords: adjustment, parenting, rejection, acceptance

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Authors: Ebenezer Joseph

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Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

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Authors: Lule Basha, Eralda Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

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Authors: Giovanna Bimonte, Luigi Senatore, Francesco Saverio Tortoriello, Ilaria Veronesi

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The education process considers capabilities not only to be seen as a means to a certain end but rather as an effective purpose. Sen's capability approach challenges human capital theory, which sees education as an ordinary investment undertaken by individuals. A complex reality requires complex thinking capable of interpreting the dynamics of society's changes to be able to make decisions that can be rational for private, ethical and social contexts. Education is not something removed from the cultural and social context; it exists and is structured within it. In Italy, the "Mathematical High School Project" is a didactic research project is based on additional laboratory courses in extracurricular hours where mathematics intends to bring itself in a dialectical relationship with other disciplines as a cultural bridge between the two cultures, the humanistic and the scientific ones, with interdisciplinary educational modules on themes of strong impact in younger life. This interdisciplinary mathematics presents topics related to the most advanced technologies and contemporary socio-economic frameworks to demonstrate how mathematics is not only a key to reading but also a key to resolving complex problems. The recent developments in mathematics provide the potential for profound and highly beneficial changes in mathematics education at all levels, such as in socio-economic decisions. The research project is built to investigate whether repeated interactions can successfully promote cooperation among students as rational choice and if the skill, the context and the school background can influence the strategies choice and the rationality. A Laboratory on Game Theory as mathematical theory was conducted in the 4th year of the Mathematical High Schools and in an ordinary scientific high school of the Scientific degree program. Students played two simultaneous games of repeated Prisoner's Dilemma with an indefinite horizon, with two different competitors in each round; even though the competitors in each round will remain the same for the duration of the game. The results highlight that most of the students in the two classes used the two games with an immunization strategy against the risk of losing: in one of the games, they started by playing Cooperate, and in the other by the strategy of Compete. In the literature, theoretical models and experiments show that in the case of repeated interactions with the same adversary, the optimal cooperation strategy can be achieved by tit-for-tat mechanisms. In higher education, individual capacities cannot be examined independently, as conceptual framework presupposes a social construction of individuals interacting and competing, making individual and collective choices. The paper will outline all the results of the experimentation and the future development of the research.

Keywords: game theory, interdisciplinarity, mathematics education, mathematical high school

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Authors: Pragya Paneru, Prativa Paneru

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This paper explores the attitude of high school Nepalese students toward scientists using a famous method named as Draw-A-Scientist-Test (DAST). A total of 145 students from Grade 11 and Grade 12 took part in this research and drew images of scientists. The findings indicated gender imbalance with male dominance in the images of scientists. The result also showed some usual stereotypes relating to hair, equipment, objects, use of eyeglasses, and lab coat in the drawings of scientists. Moreover, the influence of some mainstream western male scientists was widely seen in the drawings implying the exposure of limited male scientists to the students. In contrast to this, no real-life female scientists were mentioned by the participants demonstrating limited exposure of female scientists contributing to the gendered attitude toward the scientists. However, some of the findings also challenged the previous findings and depicted scientists with local features, positive expression, and working outdoors. Moreover, participants’ awareness that scientists could be anyone with an inquisitive mind was indicated by the variations in the characters in their drawings. The drawings indicated that scientists could be someone like a mother, themselves, a fashion icon, Buddha, or a crazy-looking person. This study recommends the inclusion of participants’ interviews, and exploration of their textbooks’ depiction of scientists to uncover additional details regarding their understanding of scientists. Also, a critical discussion of the stereotypical attitudes about scientists in class could help challenge the stereotypical assumptions of scientists.

Keywords: scientists, drawings, stereotypes, gender, high school students

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Authors: Khalil Boukfoussa

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It is important to provide students with food that contains complete nutrients to provide them with mental and physical energy during the school day. Especially since the time students spend in school is equivalent to 50% of their time during the day, which increases the importance of proper nutrition in schools and makes it an ideal way to inculcate the foundations of a healthy lifestyle and healthy eating habits. Proper nutrition is one of the most important things that affect the health and process of growth and development in children, in addition to being a key factor in supporting the ability to focus, supporting mental abilities and developing the student’s academic achievement. In addition to the importance of a healthy diet for the development and growth of the child's body, proper nutrition can significantly contribute to protecting the body from catching viruses and helping it to pass the winter safely. Effective food control systems in different countries are essential to protect the health and safety of domestic consumers. These systems are also crucial in enabling countries to ensure the safety and quality of food entering international trade and to ensure that imported food conforms to national requirements. The current global food trade environment places significant obligations on both importing and exporting countries to strengthen their food control systems and to apply and implement risk-based food control strategiesConsumers are becoming more interested in the way food is produced, processed and marketed, and are increasingly demanding that governments assume greater responsibility for consumer protection and food safety. In many countries, food control is weak because of the abundance of legislation, the multiplicity of jurisdictions and weaknesses in control, monitoring and enforcement. The following guidelines seek to advise national authorities on strategies to strengthen food control systems to protect public health, prevent fraud and fraud, avoid food contamination and help facilitate trade. These Guidelines will assist authorities in selecting the most appropriate food control system options in terms of legislation, infrastructure and enforcement mechanisms. The document clarifies the broad principles that govern food control systems and provides examples of the infrastructure and methods by which national systems can operate

Keywords: food, nutrision, school, safty

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Authors: Rifqi Irvansyah, Abdullah Abdullah, Yunita Idris, Bunga Raihanda

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Banda Aceh is particularly susceptible to heightened vulnerability during natural disasters due to its concentrated exposure to multi-hazard risks. Despite urgent priorities during the aftermath of natural disasters, such as the 2004 Indian Ocean earthquake and tsunami, several public facilities, including school buildings, sustained damage yet continued operations without adequate repairs, even though they were submerged by the tsunami. This research aims to evaluate the consequences of column damage induced by tsunami inundation on the structural integrity of buildings. The investigation employs interaction diagrams for columns to assess their capacity, taking into account factors such as rebar deterioration and corrosion. The analysis result shows that one-fourth of the K1 columns on the first floor fall outside of the column interaction diagram, indicating that the column structure cannot handle the load above it, as evidenced by the presence of Pu and Mu, which are greater than the column's design strength. This suggests that the five columns of K1 should be cause for concern, as the column's capacity is decreasing. These results indicate that the structure of the building cannot sustain the applied load because the column cross-section has deteriorated. In contrast, all K2 columns meet the design strength, indicating that the column structure can withstand the structural loads.

Keywords: tsunami inundation, column damage, column interaction diagram, mitigation effort

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Authors: Mehdi Damaliamiri, Firouzeh Akbari

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Teaching literature to children at an early age is of great importance, and there have been different methods to facilitate learning literature. Based on the law, all children going to school in Iran should learn the Persian language and literature. This has been concomitant with two different levels of learning related to urban or rural bilingualism. For bilingual children living in the villages, learning literature and a new language (Persian) turns into a big challenge as it is done based on the translation the teacher does while in the city, it is easier as the confrontation of children with the Persian language is more. Over recent years, to change the trend of learning Persian by children speaking another language, the TV and radio programs have been considered to be effective, but the scores of the students in Persian language national exams show that these programs have not been so effective for the bilingual students living in the villages. To identify the determinants of weak learning of Persian by bilingual children, two different regions were chosen, Turkish-speaking and Kurdish-speaking communities, to compare their learning of Persian at the first and second levels of elementary school. The criteria of learning was based on the syllabification of Persian words, word order in the sentence, and compound sentences. Students were taught in Persian how to recognize syllabification without letting them translate the words in their own languages and were asked to produce simple sentences in Persian in response to situational questions. Teaching methods, language relatedness with Persian, and exposure to social media programs, especially TV and radio, were the factors that were considered to affect the potential of children in learning Persian.

Keywords: bilingualism, persian, education, Literature

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Authors: Liudmyla Vesper

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The problems of modern education are large-scale and diverse. The aspirations of parents, teachers, and experts converge - everyone interested in growing up a generation of whole, well-educated persons. Both the family and society are expected in the future generation to be self-sufficient, desirable in the labor market, and capable of lifelong learning. Today's children have a powerful potential that is difficult to realize in the conditions of traditional school approaches. Focusing on STEM education in practice often ends with the simple use of computers and gadgets during class. "Science", "technology", "engineering" and "mathematics" are difficult to combine within school and university curricula, which have not changed much during the last 10 years. Solving the problems of modern education largely depends on teachers - innovators, teachers - practitioners who develop and implement effective educational methods and programs. Teachers who propose innovative pedagogical practices that allow students to master large-scale knowledge and apply it to the practical plane. Effective education considers the creation of stable neural structures during the learning process, which allow to preserve and increase knowledge throughout life. The author proposed a method of integrated lessons – cases based on the maths patterns for forming a holistic perception of the world. This method and program are scientifically substantiated and have more than 15 years of practical application experience in school and student classrooms. The first results of the practical application of the author's methodology and curriculum were announced at the International Conference "Teaching and Learning Strategies to Promote Elementary School Success", 2006, April 22-23, Yerevan, Armenia, IREX-administered 2004-2006 Multiple Component Education Project. This program is based on the concept of interdisciplinary connections and its implementation in the process of continuous learning. This allows students to save and increase knowledge throughout life according to a single pattern. The pattern principle stores information on different subjects according to one scheme (pattern), using long-term memory. This is how neural structures are created. The author also admits that a similar method can be successfully applied to the training of artificial intelligence neural networks. However, this assumption requires further research and verification. The educational method and program proposed by the author meet the modern requirements for education, which involves mastering various areas of knowledge, starting from an early age. This approach makes it possible to involve the child's cognitive potential as much as possible and direct it to the preservation and development of individual talents. According to the methodology, at the early stages of learning students understand the connection between school subjects (so-called "sciences" and "humanities") and in real life, apply the knowledge gained in practice. This approach allows students to realize their natural creative abilities and talents, which makes it easier to navigate professional choices and find their place in life.

Keywords: science education, maths education, AI, neuroplasticity, innovative education problem, creativity development, modern education problem

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

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Authors: Yuexin Liu, Gordon B. Mills, Russell R. Broaddus, John N. Weinstein

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The lethality of endometrioid endometrial cancer (EEC) is primarily attributable to the high-stage diseases. However, there are no available biomarkers that predict EEC patient staging at the time of diagnosis. We aim to develop a predictive scheme to help in this regards. Using reverse-phase protein array expression profiles for 210 EEC cases from The Cancer Genome Atlas (TCGA), we constructed a Protein Scoring of EEC Staging (PSES) scheme for surgical stage prediction. We validated and evaluated its diagnostic potential in an independent cohort of 184 EEC cases obtained at MD Anderson Cancer Center (MDACC) using receiver operating characteristic curve analyses. Kaplan-Meier survival analysis was used to examine the association of PSES score with patient outcome, and Ingenuity pathway analysis was used to identify relevant signaling pathways. Two-sided statistical tests were used. PSES robustly distinguished high- from low-stage tumors in the TCGA cohort (area under the ROC curve [AUC]=0.74; 95% confidence interval [CI], 0.68 to 0.82) and in the validation cohort (AUC=0.67; 95% CI, 0.58 to 0.76). Even among grade 1 or 2 tumors, PSES was significantly higher in high- than in low-stage tumors in both the TCGA (P = 0.005) and MDACC (P = 0.006) cohorts. Patients with positive PSES score had significantly shorter progression-free survival than those with negative PSES in the TCGA (hazard ratio [HR], 2.033; 95% CI, 1.031 to 3.809; P = 0.04) and validation (HR, 3.306; 95% CI, 1.836 to 9.436; P = 0.0007) cohorts. The ErbB signaling pathway was most significantly enriched in the PSES proteins and downregulated in high-stage tumors. PSES may provide clinically useful prediction of high-risk tumors and offer new insights into tumor biology in EEC.

Keywords: endometrial carcinoma, protein, protein scoring of EEC staging (PSES), stage

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Authors: Anuruddha Jayasuriya, Thanakorn Pheeraphan

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In this paper, a review of different mathematical models which can be used as prediction tools to assess the time to crack reinforced concrete (RC) due to corrosion is investigated. This investigation leads to an experimental study to validate a selected prediction model. Most of these mathematical models depend upon the mechanical behaviors, chemical behaviors, electrochemical behaviors or geometric aspects of the RC members during a corrosion process. The experimental program is designed to verify the accuracy of a well-selected mathematical model from a rigorous literature study. Fundamentally, the experimental program exemplifies both one-dimensional chloride diffusion using RC squared slab elements of 500 mm by 500 mm and two-dimensional chloride diffusion using RC squared column elements of 225 mm by 225 mm by 500 mm. Each set consists of three water-to-cement ratios (w/c); 0.4, 0.5, 0.6 and two cover depths; 25 mm and 50 mm. 12 mm bars are used for column elements and 16 mm bars are used for slab elements. All the samples are subjected to accelerated chloride corrosion in a chloride bath of 5% (w/w) sodium chloride (NaCl) solution. Based on a pre-screening of different models, it is clear that the well-selected mathematical model had included mechanical properties, chemical and electrochemical properties, nature of corrosion whether it is accelerated or natural, and the amount of porous area that rust products can accommodate before exerting expansive pressure on the surrounding concrete. The experimental results have shown that the selected model for both one-dimensional and two-dimensional chloride diffusion had ±20% and ±10% respective accuracies compared to the experimental output. The half-cell potential readings are also used to see the corrosion probability, and experimental results have shown that the mass loss is proportional to the negative half-cell potential readings that are obtained. Additionally, a statistical analysis is carried out in order to determine the most influential factor that affects the time to corrode the reinforcement in the concrete due to chloride diffusion. The factors considered for this analysis are w/c, bar diameter, and cover depth. The analysis is accomplished by using Minitab statistical software, and it showed that cover depth is the significant effect on the time to crack the concrete from chloride induced corrosion than other factors considered. Thus, the time predictions can be illustrated through the selected mathematical model as it covers a wide range of factors affecting the corrosion process, and it can be used to predetermine the durability concern of RC structures that are vulnerable to chloride exposure. And eventually, it is further concluded that cover thickness plays a vital role in durability in terms of chloride diffusion.

Keywords: accelerated corrosion, chloride diffusion, corrosion cracks, passivation layer, reinforcement corrosion

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Gezahegn Bekele Welldgiyorgise

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It is obvious that the economics, politics and social conditions of a country are determined by the quality and standard of its education. Indeed, education plays a vital role in changing the consciousness and awareness of society and transforming it on a large scale. Moreover, education contributes a lot to the advancement of science and technology, information and communication, and above all, it speeds up its progress in no time if it focuses mainly on the qualitative approach to education. Education brings about universal change and transformation and lightens mankind in all dimensions. It creates an educated, enlightened and brightened generation in society. The generation will be sharped, sharpened and well-oriented if it gets modern, sophisticated and standardized education in its field of study. The main goal of education is to produce well-qualified, well-trained and disciplined young offers in a given community. If the youth is well trained and well-mannered, he will certainly be enlightened, problem solvers and solution seekers, researchers, and innovators. In this respect, we have to provide the youth with modern education, a teaching-learning process led by active learning and a participatory approach with a new curriculum preparation for the age of children supported by modern facilities (ICT).In addition to that, the curriculum should have to give attention to mathematics and science lessons that include international experience in a comfortable school and classrooms. Therefore, the generation that will be created through such kinds of the guided education system will make the students active participants, self-confident, researchers and problem solvers, besides that result in changed life standards and a developed country. Similarly, our country, Ethiopia, has aimed to get such change in youth (generation) through modern education, designing a new educational policy and curriculum which was implemented for many years, although the goal of education has not reached the required level. To get the main idea of the article, I should have answered the question of why our country's educational goal had not reached the desired level because it is necessary to lay the foundation for research in finding out problems seen through students learning performance, the first task is selecting primary-school as a sample. Therefore, we selected “Dilla primary school (5-8)” which is a workplace for a teacher and gives me a chance to recognize students’ learning performance to recognize their learning grades (internal and external) and measure performance (achievement) of students easily’.

Keywords: curriculum, performance, innovation, learning

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Jemma McGourty, Brid Delahunt, Fiona Hackett, Sharon Courtney, Richard English, Graham Russell, Sinéad O’Connor

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Fundamental Movement Skills (FMS) mastery is considered essential for children’s ongoing, meaningful engagement in Physical Activity (PA). There has been a dearth of Irish research on baseline FMS and their development by means of intervention in young primary school children. In addition, as children’s participation in PA is heavily influenced by both parents and teachers, it is imperative to understand their attitudes and perceptions towards PA participation and its’ promotion in children. The ‘Fun, Move, Play’ Project investigated the effect of a 6-week play based PA intervention on primary school children’s (aged 6-8 years) FMS while also exploring the attitudes and perceptions of their parents and teachers towards PA participation. The FMS intervention utilised a pre-post quasi-experimental design to determine the effect of a 6-week play based PA intervention (devised from the iCoach Kids Programme) on 176 primary school children’s FMS (N = 176: 90 girls and 86 boys; M = 7.2 years; SD = 0.48). Objective measures of 7 FMS (run, skip, vertical jump, static balance, stationary dribble, catch, kick) were made using a combination of the TGMD2 and Get Skilled, Get Active resources. One hundred parents (87 mothers; 13 fathers; M=36 years; SD=5.45) and 90 teachers (67 females; 23 males) completed surveys investigating their attitudes and perceptions towards PA participation. In addition, 19 of these parents and 9 of these teachers participated in semi-structured qualitative interviews to explore, in more depth, their views and perceptions of PA participation. Both the FMS data set and survey responses were analysed using SPSS version 23, using appropriate statistical analysis. A thematic analysis framework was used to analyse the qualitative findings. A significant improvement was observed in the children’s overall FMS score pre-post intervention (t = 16.67; df = 175; p < 0.001), while there were also significant improvements in each of the seven individual FMS measured in the children, pre-post intervention. Findings from the parent surveys and interviews indicated that parents had positive attitudes towards PA, viewed it as important and supported their child’s PA participation. However, a lack of knowledge regarding the amount and intensity of PA that children should participate in emerged as a recurrent finding. Also, there was a significant positive correlation between the PA levels of parents’ and their children (r = .41; n = 100; p < .001). Arising from the teachers’ surveys and interviews was a positive attitude towards PA and the impact that it has on a child’s health and well-being. They also reported feeling more confident teaching certain aspects of the PE curriculum (games and sports) compared to others (gymnastics, dance), where they appreciate working with specialist practitioners. Conclusion: A short-term PA intervention has a positive effect on children’s FMS. While parents are supportive of their child’s PA participation, there is a knowledge gap regarding National PA guidelines for children. Teachers appreciate the importance of PA in children, but face a number of challenges in its implementation and promotion.

Keywords: fundamental movement skills, parents attitudes to physical activity, short-term intervention, teachers attitudes to physical activity

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Authors: Dirk Bruland, Paulo Pinheiro, Ullrich Bauer

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Introduction: Over 3 million children, about one quarter of all students, experience at least one parent with mental disorder in Germany every year. Children of mentally-ill parents are at considerably higher risk of developing serious mental health problems. The different burden patterns and coping attempts often become manifest in children's school lives. In this context, schools can have an important protective function, but can also create risk potentials. In reference to Jorm, pupil-related teachers’ mental health literacy (Teacher-MHL) includes the ability to recognize change behaviour, the knowledge of risk factors, the implementation of first aid intervention, and seeking professional help (teacher as gatekeeper). Although teachers’ knowledge and increased awareness of this topic is essential, the literature provides little information on the extent of teachers' abilities. As part of a German-wide research consortium on health literacy, this project, launched in March for 3 years, will conduct evidence-based mental health literacy research. The primary objective is to measure Teacher-MHL in the context of pupil-related psychosocial factors at primary and secondary schools (grades 5 & 6), while also focussing on children’s social living conditions. Methods: (1) A systematic literature review in different databases to identify papers with regard to Teacher-MHL (completed). (2) Based on these results, an interview guide was developed. This research step includes a qualitative pre-study to inductively survey the general profiles of teachers (n=24). The evaluation will be presented on the conference. (3) These findings will be translated into a quantitative teacher survey (n=2500) in order to assess the extent of socio-analytical skills of teachers as well as in relation to institutional and individual characteristics. (4) Based on results 1 – 3, developing a training program for teachers. Results: The review highlights a lack of information for Teacher-MHL and their skills, especially related to high-risk-groups like children of mentally ill parents. The literature is limited to a few studies only. According to these, teacher are not good at identifying burdened children and if they identify those children they do not know how to handle the situations in school. They are not sufficiently trained to deal with these children, especially there are great uncertainties in dealing with the teaching situation. Institutional means and resources are missing as well. Such a mismatch can result in insufficient support and use of opportunities for children at risk. First impressions from the interviews confirm these results and allow a greater insight in the everyday school-life according to critical life events in families. Conclusions: For the first time schools will be addressed as a setting where children are especially "accessible" for measures of health promotion. Addressing Teacher-MHL gives reason to expect high effectiveness. Targeting professionals' abilities for dealing with this high-risk-group leads to a discharge for teacher themselves to handle those situations and increases school health promotion. In view of the fact that only 10-30% of such high-risk families accept offers of therapy and assistance, this will be the first primary preventive and health-promoting approach to protect the health of a yet unaffected, but particularly burdened, high-risk group.

Keywords: children of mentally ill parents, health promotion, mental health literacy, school

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Authors: Cristina Costa-Lobo, Ana Medeiros, Ana Campina

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This study refers to the appropriateness of the psychopedagogical intervention programs focused on the adjustment and psychological well-being of children with characteristics of giftedness and the interests of promoting specialized and permanent follow-up to these children. It was intended to find out the impact on perceived self-efficacy in children with characteristics of giftedness after the frequency of a psychopedagogical intervention program. For this was applied to Multidimensional Scale Perceived Self-Efficacy, in two times (pre and post program frequency), in a quasi-experimental design. Innovative data are presented in reports to the relationship of perceived self-efficacy with giftedness, highlighting the evidence of this program focusing on the development of personal, social and emotional skills, applied to 20 children with characteristics of giftedness, in Northern Portugal, in the 2014-2015 school year, have no influence on perceived self-efficacy of children with characteristics of giftedness. The main implication of this research is congruent with the conclusions of studies that point that the greatest challenge in the education of children with characteristics of giftedness is to extend the traditional investment in intellectual production and creative capital to include an equal investment in social capital and the development of competencies of executive functions, dimensions that development programs stimulate. This study appeals to the need of children with characteristics of giftedness to be targets of psychopedagogical intervention programs with the constant specialization and constant updating of the knowledge of the professionals who work with them, motivated by being individuals with such specific and ever-changing characteristics reflecting an inclusive school life.

Keywords: giftedness, perceived self-efficacy, EMAEP, psychopedagogical intervention programs

Procedia PDF Downloads 279