Search results for: state of learning

Authors: Michael Tunde Ajayi, Oluwakemi Enitan Fapojuwo

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The study assessed employees’ perception of organizational communication in Oyo State Agricultural Development Programme and its effect on their job performance. A simple random sampling technique was used to select 120 employees using a structured questionnaire for data collection. Findings showed that 66.7% of the respondents were males and 60.4% were between the ages of 31-40 years. Most (87.5%) of the respondents had tertiary education and majority of the respondents (73.9%) had working experience of 5 years or less. Major perceived leadership styles used in communicating to the employees were that employees were not allowed to send feedbacks (X=3.23), information was usually inadequately passed across to the employees (X=2.52), information are given with explanation (X=2.04), leaders rarely gave information on innovation (X=1.91) and information are usually passed in form of order (X=1.89). However, majority (61.5%) of the respondents perceived that the common communication flow used is downward communication system. Respondents perceived that the effects of organizational communication on their job performance were that they were able to know the constraints within the organization (X= 4.89), solve the problem occurring in the organization (X=4.70) and achieve organization objectives (X= 4.40). However, major constraints affecting organizational communication were that there were no cordial relationship among workers (X=3.33), receivers had poor listening skills (X=3.32) and information were not in simple forms (X=3.29). There was a significant relationship between organizational communication (r= 0.984, p<0.05) and employees’ job performance. The study suggested that managers should encourage cordial relationship among workers in other to ease communication flow in organizations and also use adequate medium of communication in other to make information common within organizations.

Keywords: employees’ perception, organizational communication, effects, job performance

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Authors: David Barney, Francis Pleban, Muna Muday

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The purpose of this study was to explore gender differences of former physical education students related to reflective experiences of competition in physical education learning environment. In the school environment, students are positioned in competitive situations, including in the physical education context. Therefore it is important to prepare future physical educators to address the role of competition in physical education. Participants for this study were 304 college-aged students and young adults (M = 1.53, SD = .500), from a private university and local community located in the western United States. When comparing gender, significant differences (p < .05) were reported for four (questions 5, 7, 12, and 14) of the nine scaling questions. Follow-up quantitative findings reported that males (41%) more than females (27%) witnessed fights in physical education environment during competitive games. Qualitative findings reported fighting were along the lines of verbal confrontation. Female participants tended to experience being excluded from games, when compared to male participants. Both male and female participants (total population; 95%, males; 98%; and females 92%) were in favor of including competition in physical education for students. Findings suggest that physical education teachers and physical education teacher education programs have a responsibility to develop gender neutral learning experiences that help students better appreciate the role competition plays, both in and out of the physical education classroom.

Keywords: competition, physical education, physical education teacher education, gender

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Authors: P. O. Fatoki, R. S. Olaleye, B. O. Adeniji

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The study investigated farmers’ perception of the effects of climate change on rice production in Nasarawa State, Nigeria. Multi-stage sampling technique was used in selecting a total of 248 rice farmers from the study area. Data for the study were collected through the use of interview schedule. The data were analysed using both descriptive and inferential statistics. Results showed that majority (71.8%) of the respondents were married and the mean age of the respondents was 44.54 years. The results also showed that most adapted strategies for mitigating the effects of climate change on rice production were change of planting and harvesting date (67.7%), movement to another site (63.7%) and increased or reduced land size (58.5%). Relationship between the roles of extension agents in mitigating climate change effects on rice production and farmers’ perception were significant as revealed Chi-Square analysis from the study ; Dissemination of information ( = 2.16, P < 0.05) and use of demonstration methods ( = 2.15, P < 0.05). Poisson regression analysis revealed that educational status, farm size, experience and yield had significant relationship with the perception of the effects of climate change at 0.01 significance level while household size was as well significant at 0.05. It is recommended that some of the adaptive strategies and practices for mitigating the effects of climate change in rice production should be improved, while the extension outfits should be strengthened to ensure adequate dissemination of relevant information on climate change with a view to mitigate its effects on rice production.

Keywords: perception, rice farmers, climate change, mitigation, adaptive strategies

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Authors: Helen Coronel, Will Brewer, Peggy Bergeron, Clarissa Hall, Victoria Casson

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Simulation-based training provides the nurse practitioner (NP) student with a safe and controlled environment in which they can practice a real-life scenario. This type of learning fosters critical thinking skills essential to practice. The expectation of this study was that students would have an increase in their competency and confidence after performing the simulation. Approximately 8.4% of Americans suffer from depression. The state of Alabama is ranked 47th out of 50 for access to mental health care. As a result of this significant shortage of mental health providers, primary care providers are frequently put in the position of screening for and treating mental health conditions, such as depression. Family nurse practitioners are often utilized as primary care providers, making their ability to assess, diagnose and treat these disorders a necessary skill. The expected outcome of this simulation is an increase in confidence, competency and the empowerment of the nurse practitioner student’s ability to assess, diagnose and treat a common mood disorder they may encounter in practice. The Kirkpatrick Module was applied for this study. A non-experimental design using descriptive statistical analysis was utilized. The simulation was based on a common psychiatric mood disorder frequently observed in primary care and mental health clinics. Students were asked to watch a voiceover power point presentation prior to their on-campus simulation. The presentation included training on the assessment, diagnosis, and treatment of a patient with depression. Prior to the simulation, the students completed a pre-test, then participated in the simulation, and completed a post-test when done. Apple iPads were utilized to access a simulated health record. Major findings of the study support an increase in students’ competency and confidence when assessing, diagnosing, and treating an adult patient with depression.

Keywords: advanced practice, nurse practitioner, simulation, primary care, depression

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Authors: Christopher Thornton, Niina Kolehmainen, Kianoush Nazarpour

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Background: Accelerometers are widely used to measure physical activity behavior, including in children. The traditional method for processing acceleration data uses cut points, relying on calibration studies that relate the quantity of acceleration to energy expenditure. As these relationships do not generalise across diverse populations, they must be parametrised for each subpopulation, including different age groups, which is costly and makes studies across diverse populations difficult. A data-driven approach that allows physical activity intensity states to emerge from the data under study without relying on parameters derived from external populations offers a new perspective on this problem and potentially improved results. We evaluated the data-driven approach in a diverse population with a range of rapidly evolving physical and mental capabilities, namely very young children (9-38 months old), where this new approach may be particularly appropriate. Methods: We applied an unsupervised machine learning approach (a hidden semi-Markov model - HSMM) to segment and cluster the accelerometer data recorded from 275 children with a diverse range of physical and cognitive abilities. The HSMM was configured to identify a maximum of six physical activity intensity states and the output of the model was the time spent by each child in each of the states. For comparison, we also processed the accelerometer data using published cut points with available thresholds for the population. This provided us with time estimates for each child’s sedentary (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data on the children’s physical and cognitive abilities were collected using the Paediatric Evaluation of Disability Inventory (PEDI-CAT). Results: The HSMM identified two inactive states (INS, comparable to SED), two lightly active long duration states (LAS, comparable to LPA), and two short-duration high-intensity states (HIS, comparable to MVPA). Overall, the children spent on average 237/392 minutes per day in INS/SED, 211/129 minutes per day in LAS/LPA, and 178/168 minutes in HIS/MVPA. We found that INS overlapped with 53% of SED, LAS overlapped with 37% of LPA and HIS overlapped with 60% of MVPA. We also looked at the correlation between the time spent by a child in either HIS or MVPA and their physical and cognitive abilities. We found that HIS was more strongly correlated with physical mobility (R²HIS =0.5, R²MVPA= 0.28), cognitive ability (R²HIS =0.31, R²MVPA= 0.15), and age (R²HIS =0.15, R²MVPA= 0.09), indicating increased sensitivity to key attributes associated with a child’s mobility. Conclusion: An unsupervised machine learning technique can segment and cluster accelerometer data according to the intensity of movement at a given time. It provides a potentially more sensitive, appropriate, and cost-effective approach to analysing physical activity behavior in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive across diverse populations.

Keywords: physical activity, machine learning, under 5s, disability, accelerometer

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Authors: Jutharat Sunprasert, Ekapong Hirunsirisawat, Narongrit Waraporn, Somporn Peansukmanee

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Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.

Keywords: hands-on activity, STEM education, computer programming, metal work

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Authors: Tahmina Huq

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This paper presents the findings of an action research study that aimed to investigate the efficacy of a visual dialogue strategy in assisting autistic students with intellectual disabilities in managing their immediate emotions and improving their academic achievements. The research sought to explore the effectiveness of teaching self-regulation techniques as an alternative to traditional approaches involving segregation. The study identified visual dialogue as a valuable tool for promoting self-regulation in this specific student population. Action research was chosen as the methodology due to its suitability for immediate implementation of the findings in the classroom. Autistic students with intellectual disabilities often face challenges in controlling their emotions, which can disrupt their learning and academic progress. Conventional methods of intervention, such as isolation and psychologist-assisted approaches, may result in missed classes and hindered academic development. This study introduces the utilization of visual dialogue between students and teachers as an effective self-regulation strategy, addressing the limitations of traditional approaches. Action research was employed as the methodology for this study, allowing for the direct application of the findings in the classroom. The study observed two 15-year-old autistic students with intellectual disabilities who exhibited difficulties in emotional regulation and displayed aggressive behaviors. The research question focused on the effectiveness of visual dialogue in managing the emotions of these students and its impact on their learning outcomes. Data collection methods included personal observations, log sheets, personal reflections, and visual documentation. The study revealed that the implementation of visual dialogue as a self-regulation strategy enabled the students to regulate their emotions within a short timeframe (10 to 30 minutes). Through visual dialogue, they were able to express their feelings and needs in socially appropriate ways. This finding underscores the significance of visual dialogue as a tool for promoting emotional regulation and facilitating active participation in classroom activities. As a result, the students' learning outcomes and social interactions were positively impacted. The findings of this study hold significant implications for educators working with autistic students with intellectual disabilities. The use of visual dialogue as a self-regulation strategy can enhance emotional regulation skills and improve overall academic progress. The action research approach outlined in this paper provides practical guidance for educators in effectively implementing self-regulation strategies within classroom settings. In conclusion, the study demonstrates that visual dialogue is an effective strategy for enhancing emotional regulation in autistic students with intellectual disabilities. By employing visual communication, students can successfully regulate their emotions and actively engage in classroom activities, leading to improved learning outcomes and social interactions. This paper underscores the importance of implementing self-regulation strategies in educational settings to cater to the unique needs of autistic students.

Keywords: action research, self-regulation, autism, visual communication

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Authors: B. O. Diyaolu

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Viability and competency during competition is the dream of every team sports so as to have a good result. But it seems factors abound which deter the performance of even a good sports team. Different individuals with different state of mind all come together to perform in team sports with different degree of satisfaction. This study investigated the role of satisfaction on performance among Afe Babalola University team sports. Descriptive survey research design was used and the population consists of all male and female athletes in the team sports that participated in the last 2019 Ekiti State Higher Institution games (ESHIGA). Total enumeration technique was used for the three team sports; football (44), basketball (24) and volleyball (24). A total of 92 participants were involved in the research. The instrument used for the study was a modified Athlete Satisfaction Scale (ASS). The questionnaire was divided into two sections. The Cronbach’s Alpha reliability coefficient of 0.71 was obtained. The hypotheses were tested at 0.05 significant levels. The completed questionnaire was collated, coded, and analyzed using descriptive statistics of frequency counts and percentage and inferential statistics of chi-square (X²). Findings of this study revealed that satisfaction significantly influences team sports performance among Athletes of Afe Babalola University. The responsibility of satisfying athlete lies on the coaches, fans, sports administrators as well as organizers of such event, as it is not only financial reward that gives satisfaction. The performance of a team sports is quiet important and its being determined by the degree of satisfaction of each individual that make up the team. All effort must be made to satisfy athlete in order to guarantee optimum performance.

Keywords: athlete satisfaction, optimum achievement, optimum performance, sports performance and team sports

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Authors: Yash Bingi, Yiqiao Yin

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Reduction of child mortality is an ongoing struggle and a commonly used factor in determining progress in the medical field. The under-5 mortality number is around 5 million around the world, with many of the deaths being preventable. In light of this issue, Cardiotocograms (CTGs) have emerged as a leading tool to determine fetal health. By using ultrasound pulses and reading the responses, CTGs help healthcare professionals assess the overall health of the fetus to determine the risk of child mortality. However, interpreting the results of the CTGs is time-consuming and inefficient, especially in underdeveloped areas where an expert obstetrician is hard to come by. Using a support vector machine (SVM) and oversampling, this paper proposed a model that classifies fetal health with an accuracy of 99.59%. To further explain the CTG measurements, an algorithm based on Randomized Input Sampling for Explanation ((RISE) of Black-box Models was created, called Feature Alteration for explanation of Black Box Models (FAB), and compared the findings to Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME). This allows doctors and medical professionals to classify fetal health with high accuracy and determine which features were most influential in the process.

Keywords: machine learning, fetal health, gradient boosting, support vector machine, Shapley values, local interpretable model agnostic explanations

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Authors: Iwuchukwu J. C., Mbah C.

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There seems to be dearth on information on how oil bean is being exploited, processed and conserved locally. This gap stifles initiatives on the evaluation of the suitability of the methods used and the invention of new and better methods. The study; therefore, assesses activities of processors in domestication/conservation and processing of oil bean (Pentaclethra macrophylla) Enugu State, South East Nigeria. Three agricultural zones, three blocks, nine circles and seventy-two respondents that were purposively selected made up the sample for the study. Data were presented in percentage, chart and mean score. The result shows that processors of oil bean in the area were middle-aged, married with relatively large household size and long years of experience in processing. They sourced oil bean they processed from people’s farmland and sourced information on processing of oil bean from friends and relatives. Activities involved in processing of oil bean were boiling, dehulling, washing, sieving, slicing, wrapping. However, the sequence of these activities varies among these processors. Little or nothing was done by the processors towards the conservation of the crop while poor storage and processing facilities and lack of knowledge on modern preservation technique were major constraints to processing of oil bean in the area. The study concluded that efforts should be made by governments and processors through cooperative group in provision of processing and storage facility for oil bean while research institute should conserve and generate improved specie of the crop to arouse interest of the farmers and processors on the crop which will invariably increase productivity.

Keywords: conservation, domestication, oil bean, processing

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Kudrat-E-Khuda Babu

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Rohingya refugees are the most marginalized and persecuted section of people in the world. The heinous brutality of Myanmar has forced the Muslim minority community to flee themselves to their neighboring country, Bangladesh for quite a few times now. The recent atrocity of the Buddhist country has added insult to injury on the existing crisis. In lieu of protection, the rights of the Rohingya community in Myanmar are being violated through exclusion from citizenship and steamroller of persecution. The mass influx of Rohingya refugees to Bangladesh basically took place in 1978, 1992, 2012, and 2017. At present, there are around one million Rohingyas staying at Teknaf, Ukhiya of Cox’s Bazar, the southern part of Bangladesh. The country, despite being a poverty-stricken one, has shown unprecedented generosity in sheltering the Rohingya people. For sheltering half of the total refugees in 2017, the Prime Minister of Bangladesh, Sheikh Hasina is now being regarded as the lighthouse of humanity or the mother of humanity. Though Bangladesh is not a ratifying state of the UN Refugee Convention, 1951 and its Additional Protocol, 1967, the country cannot escape its obligation under international human rights jurisprudence. Bangladesh is a party to eight human rights instruments out of nine core instruments, and thus, the country has an indirect obligation to protect and promote the rights of the refugees. Pressure from international bodies has also made Bangladesh bound to provide refuge to Rohingya people. Even though the demographic vulnerability and socio-economic condition of the country do not suggest taking over extra responsibility, the principle of non-refoulment as a part of customary international law reminds us to stay beside those persecuted or believed to have well-founded fear of persecution. In the case of HM Ershad v. Bangladesh and Others, 7 BLC (AD) 67, it was held that any international treaty or document after signing or ratification is not directly enforceable unless and until the parliament enacts a similar statute howsoever sweet the document is. As per Article 33(2) of the 1951 Refugee Convention, there are even exceptions for a state party in case of serious consequences like threat to national security, apprehension of serious crime and danger to safeguard state population. Bangladesh is now at a cross-road of human rights and national interest. The world community should come forward to resolve the crisis of the persecuted Rohingya people through repatriation, resettlement, and reintegration.

Keywords: Rohingya refugees, human rights, Bangladesh, Myanmar

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Authors: Alisha Sinha, Laxmi Kant Sharma

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Forest fires are a recurring issue in many parts of the world, including India. These fires can have various causes, including human activities (such as agricultural burning, campfires, or discarded cigarettes) and natural factors (such as lightning). This study presents a comprehensive and advanced methodology for assessing wildfire susceptibility by integrating diverse environmental variables and leveraging cutting-edge machine learning techniques across Rajasthan, India. The primary goal of the study is to utilize Google Earth Engine to compare locations in Sariska National Park, Rajasthan (India), before and after forest fires. High-resolution satellite data were used to assess the amount and types of changes caused by forest fires. The present study meticulously analyzes various environmental variables, i.e., slope orientation, elevation, normalized difference vegetation index (NDVI), drainage density, precipitation, and temperature, to understand landscape characteristics and assess wildfire susceptibility. In addition, a sophisticated random forest regression model is used to predict land surface temperature based on a set of environmental parameters.

Keywords: wildfire susceptibility mapping, LST, random forest, GEE, MODIS, climatic parameters

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Authors: Abdullah Abdulsalam, Adamu Balami, Olajide Olubanji Olowe, Maryam Abdu Abdulkadir

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The development and persistence of low back pain may be influenced by several factors which include lifestyle factors, previous pain symptoms, psychological factors, workplace factors as well as socio-demographic variables. The focus of this study was to determine the socio-demographic and work related variables as a predictor of persistence of back pain and disability among civil servants receiving physiotherapy in tertiary health institutions in Kano, Nigeria. One hundred and twenty nine newly referred low back pain patients for physiotherapy participated in the study. This study was a cross sectional study involving patients that were newly diagnosed of back pain, referred and received physiotherapy. The convenience sampling technique was used to select the patients based on the inclusion criteria. The data obtained was analysed using simple percentage and multiple regression for stated hypothesis at 0.05 level of significance. The findings reveal that all the variables are not significant predictor of persistence of back pain and disability. The study recommended that determinants of low back pain recovery by clinician should include other clinical factors not only reduction in pain intensity.

Keywords: socio-demographic, work related variables, Kano state, back pain and disability

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Authors: Inikpi Ameh, Grace Kia, A. K. B. Sackey, Joy Atawodi, Richard Whittington

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Ranaviruses are belonging to the viral Family Iridoviridae, are a group of globally emerging pathogens recognized as major viral pathogens of cold-blooded vertebrates. They cause systemic infection in fishes, amphibians, and reptiles. Ranaviruses have been associated with numerous disease outbreaks in natural and cultured populations of fish, amphibians, and reptiles. To investigate the presence of the ranavirus in fish and edible frogs sourced from dams and ponds in Zaria, Kaduna State, Nigeria. A total of 425 frogs (Rana spp.) and fishes (n=215 and n=200, respectively) were randomly collected based on consent and availability. Liver, kidney, and spleen tissue samples from each animal were pooled and homogenized. The samples were screened for ranavirus using the Indirect Enzyme linked Immunosorbent assay (ELISA). An overall prevalence of 46.1% (196/425) was obtained from the study. Frogs had a prevalence of 51.2% (110/215) while fish had 43% (86/200). This is the first study on ranavirus in fish and edible frogs in Nigeria. This study has established that edible frogs (Rana spp) and fishes sold in Zaria, Nigeria were infected with ranavirus which may have great economic importance to the nation’s aquaculture. In view of occasional massive economic losses observed in fishery industry due to deaths of unknown origin, this preliminary investigation is useful in directing veterinarians, policy makers and researchers on need to survey for ranavirus and also enlighten the relevant stakeholders on its prevention and control in Nigeria.

Keywords: fish, frogs, Nigeria, Ranavirus

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Authors: Aminu Alhaji Bala

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The Jama’atu Izalatil Bid’ah Wa-Iqamatis Sunnah is a Da’wah organization and reform movement launched in Jos - Nigeria in 1978 as a purely reform movement under the leadership of late Shaykh Ismai’la Idris. The organization started a full fledge preaching sessions at National, State and Local Government levels immediately after its formation. The contributions of this organization to da'wah activities in Nigeria are paramount. The organization conducted its preaching under the council of preaching with the help of the executives, elders and patrons of the movement. Teaching and preaching have been recognized as the major programs of the society. Its preaching activities are conducted from ward, local, state and national levels throughout the states of Nigeria and beyond. It also engaged itself in establishing Mosques, schools and offers sermons during Friday congregation and Eid days throughout its mosques where its sermon is translated into vernacular language, this attracted many Muslims who don’t understand Arabic to patronize the its activities. The organization however split into two faction due to different approaches to Da’wah methodology and some seemingly selfish interests among its leaders. It is upon this background that this research was conducted using analytical method to compare and contrast the da’wah methodology applied by the two factions of the organization. The research discussed about the formation, Da’wah activities of the organization. It also compared and contrast the Da’wah approach and methodology of the two factions. The research finding reveals that different approach and methods applied by these factions is one of the main reason of their split in addition to other selfish interest among its leaders.

Keywords: activities, Da’wah, methodology, organization

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Authors: Anamika Devi

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Based on Vygotsky’s cultural, historical theory and Hedegaard’s concept of transition, this study aims to investigate to propose strategies to maintain digital wellbeing of children and parents during and post COVID pandemic. Due COVID 19 pandemic, children and families have been facing new challenges and sudden changes in their everyday life. While children are juggling to adjust themselves in new circumstance of onsite and online learning settings, parents are juggling with their work-life balance. A number of papers have identified that the COVID-19 pandemic has affected the lives of many families around the world in many ways, for example, the stress level of many parents increased, families faced financial difficulties, uncertainty impacted on long term effects on their emotional and social wellbeing. After searching and doing an intensive literature review from 2020 and 2021, this study has found some scholarly articles provided solution or strategies of reducing stress levels of parents and children in this unprecedented time. However, most of them are not underpinned by proper theoretical lens to ensure they validity and success. Therefore, this study has proposed strategies that are underpinned by theoretical lens to ensure their impact on children’s and parents' emotional wellbeing during and post COVID-19 era. The strategies will highlight on activities for positive coping strategies to the best use of family values and digital technologies.

Keywords: onsite and online learning, strategies, emotional wellbeing, tips, and strategies, COVID19

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Authors: Zachary Huffman, Joana Rocha

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Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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Authors: Eisa Y. Adam, Anas A. Fadlelmula, Ali E. Ali

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Sorghum head bug is a key insect pest of sorghum, and it is important to pay attention to the peak time of the pest abundance. The objective of this study was to study the effect of planting date on head bugs population. Field experiment was conducted during 2007/08 – 2008/09 and 2013/14 - 2014/15 cropping seasons at the Damazine Research Station Farm, Blue Nile State to determine sorghum head bugs incidence and abundance through the sowing date. Different sowing dates (early, mid and late sowing) and a susceptible sorghum variety known as Wad Ahmed variety were used the experiment. The experimental design used was randomized complete block design (RCBD). Data were collected on the number of head bug adults and nymphs/panicle, damage percent, coloration and a puncture due to bug feeding and oviposition, 1000 seeds weight and yield. The results showed that significantly (P<0.05) higher number of bugs and damage percent were recorded on the late sowing date for the four seasons followed by the mid sowing, while the early sowing gave low number of bugs, damage percent and high1000 weight. There were significant differences between protected and unprotected heads. The late sowing (August) is a critical sorghum planting time because it coincided with highest numbers of the head bugs.

Keywords: abundance, damage, headbugs, panicle

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Authors: Naveed Ahmad Fazili

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More than 20 human diseases involve the fibrillation of a specific protein/peptide which forms pathological deposits at various sites. Hereditary lysozyme amyloidosis is a systemic disorder which mostly affects liver, spleen and kidney. This conformational disorder is featured by lysozyme fibril formation. In vivo lysozyme fibrillation was simulated under in vitro conditions using a strong denaturant GdHCl at 3M concentration. Sharp decline in the ANS fluorescence intensity compared to the partially unfolded states, almost 20 fold increase in ThT fluorescence intensity, increase in absorbance at 450 nm suggesting turbidity, negative ellipticity peak in the far-UVCD at 217 nm, red shift of 50 nm compared to the native state in congo red assay and appearance of a network of long rope like fibrils in TEM analysis suggested HEWL fibrillation. Anti-fibrillation potency of baicalein against the preformed fibrils of HEWL was investigated following ThT assay in which there was a dose dependent decrease in ThT fluorescence intensity compared to the fibrillar state of HEWL with the maximum effect observed at 150 μM baicalein concentration, loss of negative ellipticity peak in the far-UVCD region, dip in the Rayleigh scattering intensity and absorbance at 350 nm and 450 nm respectively together with a reduction in the density of fibrillar structure in TEM imaging. Thus, it could be suggested that baicalein could prove to be a positive therapeutics for hereditary human lysozyme amyloidosis.

Keywords: amyloid fibrils, baicalein, congo red, negative ellipticity, therapeutics

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Authors: Victoria L. Malakhova

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The research is devoted to multimodal content and its effectiveness in developing students’ linguistic and intercultural communicative competences as an indefeasible constituent of their future professional activity. Description of multimodal content both as a linguistic and didactic phenomenon makes the study relevant. The objective of the article is the analysis of creolized texts and the effect they have on fostering higher education students’ skills and their productivity. The main methods used are linguistic text analysis, qualitative and quantitative methods, deduction, generalization. The author studies texts with full and partial creolization, their features and role in composing multimodal textual space. The main verbal and non-verbal markers and paralinguistic means that enhance the linguo-pragmatic potential of creolized texts are covered. To reveal the efficiency of multimodal content application in English teaching, the author conducts an experiment among both undergraduate students and teachers. This allows specifying main functions of creolized texts in the process of language learning, detecting ways of enhancing students’ competences, and increasing their motivation. The described stages of using creolized texts can serve as an algorithm for work with multimodal content in teaching English as a foreign language. The findings contribute to improving the efficiency of the academic process.

Keywords: creolized text, English language learning, higher education, language and communication competences, multimodal content

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Authors: Richard White, Anne Drabble, Maureen O’Neill

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The University of the Sunshine Coast (USC) offers secondary school students in the final two years of school (Years 11 and 12, 16 – 18 years of age) an opportunity to participate in a program which provides an accelerated pathway to tertiary studies. Whilst still at secondary school, the students undertake two first year university subjects that are required subjects in USC undergraduate degree programs. The program is called Integrated Learning Pathway (ILP) and offers a range of disciplines, including business, design, drama, education, and engineering. Between 2010 and 2014, 38% of secondary students who participated in an ILP program commenced undergraduate studies at USC following completion of secondary school studies. The research reported here considers “before and after” literacy and numeracy competencies of students to determine what impact participation in the ILP program has had on their academic skills. Qualitative and quantitative data has been gathered via numeracy and literacy testing of the students, and a survey asking the students to self-evaluate their numeracy and literacy skills, and reflect on their views of these academic skills. The research will enable improved targeting of teaching strategies so that students will acquire not only course-specific learning outcomes but also collateral academic skills. This enhancement of academic skills will improve undergraduate experience and improve student retention.

Keywords: academic skills enhancement, accelerated pathways, improved teaching, student retention

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Authors: Shilpagauri Prasad Ganpule

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The teaching of drama is considered as the most significant and noteworthy area in an ESL classroom. Diverse innovative techniques can be used to make the teaching of drama worthwhile and interesting. The paper presents the different innovative techniques that can be used while teaching Henrik Ibsen’s A Doll’s House [2007]. The innovative techniques facilitate students’ understanding and comprehension of the text. The use of the innovative techniques makes them explore the dramatic text and uncover a multihued arena of meanings hidden in it. They arouse the students’ interest and assist them overcome the difficulties created by the second language. The diverse innovative techniques appeal to the imagination of the students and increase their participation in the classroom. They help the students in the appreciation of the dramatic text and make the teaching learning situation a fruitful experience for both the teacher and students. The students successfully overcome the problem of L2 comprehension and grasp the theme, story line and plot-structure of the play effectively. The innovative techniques encourage a strong sense of participation on the part of the students and persuade them to learn through active participation. In brief, the innovative techniques promote the students to perform various tasks and expedite their learning process. Thus the present paper makes an attempt to present varied innovative techniques that can be used while teaching drama. It strives to demonstrate how the use of innovative techniques improve and enhance the students’ understanding and appreciation of Ibsen’s A Doll’s House [2007].

Keywords: ESL classroom, innovative techniques, students’ participation, teaching of drama

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Authors: Nikoloz Jalabadze, Roin Chedia, Lili Nadaraia, Levan Khundadze

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Nanocrystalline materials in powder condition can be manufactured by a number of different methods, however manufacture of composite materials product in the same nanocrystalline state is still a problem because the processes of compaction and synthesis of nanocrystalline powders go with intensive growth of particles – the process which promotes formation of pieces in an ordinary crystalline state instead of being crystallized in the desirable nanocrystalline state. To date spark plasma sintering (SPS) has been considered as the most promising and energy efficient method for producing dense bodies of composite materials. An advantage of the SPS method in comparison with other methods is mainly low temperature and short time of the sintering procedure. That finally gives an opportunity to obtain dense material with nanocrystalline structure. Graphene has recently garnered significant interest as a reinforcing phase in composite materials because of its excellent electrical, thermal and mechanical properties. Graphene nanoplatelets (GNPs) in particular have attracted much interest as reinforcements for ceramic matrix composites (mostly in Al2O3, Si3N4, TiO2, ZrB2 a. c.). SPS has been shown to fully densify a variety of ceramic systems effectively including Al2O3 and often with improvements in mechanical and functional behavior. Alumina consolidated by SPS has been shown to have superior hardness, fracture toughness, plasticity and optical translucency compared to conventionally processed alumina. Knowledge of how GNPs influence sintering behavior is important to effectively process and manufacture process. In this study, the effects of GNPs on the SPS processing of Al2O3 are investigated by systematically varying sintering temperature, holding time and pressure. Our experiments showed that SPS process is also appropriate for the synthesis of nanocrystalline powders of alumina-graphene composites. Depending on the size of the molds, it is possible to obtain different amount of nanopowders. Investigation of the structure, physical-chemical, mechanical and performance properties of the elaborated composite materials was performed. The results of this study provide a fundamental understanding of the effects of GNP on sintering behavior, thereby providing a foundation for future optimization of the processing of these promising nanocomposite systems.

Keywords: alumina oxide, ceramic matrix composites, graphene nanoplatelets, spark-plasma sintering

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Authors: Soumya Bhattacharjya, Avinandan Sahoo, Gaurav Datta

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Wind fragility analysis of chimney is often carried out disregarding temperature effect. However, the combined effect of wind and temperature is the most critical limit state for chimney design. Hence, in the present paper, an efficient fragility analysis for concrete chimney is explored under combined wind and temperature effect. Wind time histories are generated by Davenports Power Spectral Density Function and using Weighed Amplitude Wave Superposition Technique. Fragility analysis is often carried out in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, in the present paper, an efficient adaptive metamodelling technique is adopted to judiciously approximate limit state function, which will be subsequently used in the simulation framework. This will save substantial computational time and make the approach computationally efficient. Uncertainty in wind speed, wind load related parameters, and resistance-related parameters is considered. The results by the full simulation approach, conventional metamodelling approach and proposed adaptive metamodelling approach will be compared. Effect of disregarding temperature in wind fragility analysis will be highlighted.

Keywords: adaptive metamodelling technique, concrete chimney, fragility analysis, stochastic extreme wind load, temperature effect

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Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

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Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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Authors: G. Singer, M. Golan

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Providing students with learning disabilities (LD) with extra time to grant them equal access to the exam is a necessary but insufficient condition to compensate for their LD; there should also be a clear indication that the additional time was actually used. For example, if students with LD use more time than students without LD and yet receive lower grades, this may indicate that a different accommodation is required. If they achieve higher grades but use the same amount of time, then the effectiveness of the accommodation has not been demonstrated. The main goal of this study is to evaluate the effect of including parameters related to LD and extended exam time, along with other commonly-used characteristics (e.g., student background and ability measures such as high-school grades), on the ability of ordinal decision-tree algorithms to predict exam performance. We use naturally-occurring data collected from hundreds of undergraduate engineering students. The sub-goals are i) to examine the improvement in prediction accuracy when the indicator of exam performance includes 'actual time used' in addition to the conventional indicator (exam grade) employed in most research; ii) to explore the effectiveness of extended exam time on exam performance for different courses and for LD students with different profiles (i.e., sets of characteristics). This is achieved by using the patterns (i.e., subgroups) generated by the algorithms to identify pairs of subgroups that differ in just one characteristic (e.g., course or type of LD) but have different outcomes in terms of exam performance (grade and time used). Since grade and time used to exhibit an ordering form, we propose a method based on ordinal decision-trees, which applies a weighted information-gain ratio (WIGR) measure for selecting the classifying attributes. Unlike other known ordinal algorithms, our method does not assume monotonicity in the data. The proposed WIGR is an extension of an information-theoretic measure, in the sense that it adjusts to the case of an ordinal target and takes into account the error severity between two different target classes. Specifically, we use ordinal C4.5, random-forest, and AdaBoost algorithms, as well as an ensemble technique composed of ordinal and non-ordinal classifiers. Firstly, we find that the inclusion of LD and extended exam-time parameters improves prediction of exam performance (compared to specifications of the algorithms that do not include these variables). Secondly, when the indicator of exam performance includes 'actual time used' together with grade (as opposed to grade only), the prediction accuracy improves. Thirdly, our subgroup analyses show clear differences in the effect of extended exam time on exam performance among different courses and different student profiles. From a methodological perspective, we find that the ordinal decision-tree based algorithms outperform their conventional, non-ordinal counterparts. Further, we demonstrate that the ensemble-based approach leverages the strengths of each type of classifier (ordinal and non-ordinal) and yields better performance than each classifier individually.

Keywords: actual exam time usage, ensemble learning, learning disabilities, ordinal classification, time extension

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Sunil Mekale, Debasish Chowdhury, Sanchita Patnaik, Amitav Das, Ashok Agarwal

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Background: Odisha is a low HIV prevalence state in India (ANC-HIV positivity of 0.42% as per HIV sentinel surveillance 2010-2011); however, it is an important source migration state with 3.2% of male migrants reporting to be PLHIV. USAID Public Health Foundation of India -PIPPSE project is piloting a source-destination corridor programme between Odisha and Gujarat. In Odisha, the focus has been on developing a comprehensive strategy to reach out to the out migrants and their spouses in the place of their origin based on their availability. The project has made concerted attempts to identify vulnerable districts with high out migration and high positivity rate. Description: 48 out of 97 ICTCs were selected from nine top high out migration districts through multistage sampling. A retrospective descriptive analysis of HIV positive male migrants and their spouses for two years (April 2013-March 2015) was conducted. A total of 3,645 HIV positive records were analysed. Findings: Among 34.2% detected HIV positive in the ICTCs, 23.3% were male migrants and 11% were spouses of male migrants; almost 50% of total ICTC attendees. More than 70% of the PLHIV male migrants and their spouses were less than 45 years old. Conclusions: Couple HIV testing approach may be considered for male migrants and their spouses. ICTC data analysis could guide in identifying the locations with high HIV positivity among male migrants and their spouses.

Keywords: HIV testing, migrants, spouse of migrants, Integrated Counselling and Testing Centre (ICTC)

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Authors: Faride Hashemiannejad, Shima Oloomi

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Imagination is one of the important elements of creative thinking which as a skill needs attention by the educational system. Although most students learn reading, writing, and arithmetic skills well, they lack high level thinking skills like creative thinking. Therefore, in the information age and in the beginning of entry to knowledge-based society, the educational system needs to think over its goals and mission, and concentrate on creativity-based curriculum. From among curriculum elements-goals, content, method and evaluation “method” is a major domain whose reform can pave the way for fostering imagination and creativity. The purpose of this study was examining the relationship between creativity development and curriculum. Research questions were: (1) is there a relationship between the cognitive-emotional structure of the classroom and creativity development? (2) Is there a relationship between the environmental-social structure of the classroom and creativity development? (3) Is there a relationship between the thinking structure of the classroom and creativity development? (4) Is there a relationship between the physical structure of the classroom and creativity development? (5) Is there a relationship between the instructional structure of the classroom and creativity development? Method: This research is a applied research and the research method is Correlational research. Participants: The total number of participants in this study included 894 students from High school through 11th grade from seven schools of seven zones in Mashad city. Sampling Plan: Sampling was selected based on Random Multi State. Measurement: The dependent measure in this study was: (a) the Test of Creative Thinking, (b) The researcher-made questionnaire includes five fragments, cognitive, emotional structure, environmental social structure, thinking structure, physical structure, and instructional structure. The Results Show: There was significant relationship between the cognitive-emotional structure of the classroom and student’s creativity development (sig=0.139). There was significant relationship between the environmental-social structure of the classroom and student’s creativity development (sig=0.006). There was significant relationship between the thinking structure of the classroom and student’s creativity development (sig=0.004). There was not significant relationship between the physical structure of the classroom and student’s creativity development (sig=0.215). There was significant relationship between the instructional structure of the classroom and student’s creativity development (sig=0.003). These findings denote if students feel secure, calm and confident, they can experience creative learning. Also the quality of coping with students’ questions, imaginations and risks can influence on their creativity development.

Keywords: imagination, creativity, curriculum, bioinformatics, biomedicine

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