PROBLEM SOLVING USING SELF-GENERATED DATA: LEARNING CONCEPT OF SPEED AT UPPER PRIMARY STAGE

Working on self-generated data contextualizes learning and students see relevance of their learning in their day-to-day life. An attempt has been made to examine, ‘can solving problems using self- generated data by performing activities facilitate students at upper primary stage to learn concept of speed in better way?’ It is observed that this approach can bridge the gap between their classroom experiences and everyday life experiences and remove fear of solving numerical problems. The study highlights the importance of actively engaging the students in the construction of knowledge and learning scientific concepts by self-generated data. Teachinglearning of science needs to be transformed from the process of knowledge transfer to knowledge generation

Laboratory Experiences for Prospective Science Teachers: A Meta-analytic Review of Issues and Concerns

Prospective science teachers need to be prepared for making laboratory experiences integral part of teaching-learning of science in order to facilitate students to nurture their natural curiosity. This can engage students towards acquiring proficiency in the processes that can lead them to inquiry and generation and validation of scientific knowledge. This study is guided by the research question, “what is the status of laboratory experiences for prospective teachers?” and “what is missing in prospective science teachers’ preparation programme in order to bring excellence in science education?” An attempt has been made to carry out a meta-analytical review of the relevant literature to address some of the issues and concerns for providing laboratory experiences to prospective science teachers. Major issues emerging from the review of literature in this area are– recognizing need and understanding objectives of laboratory work from pedagogical prospective; integrating it with theory and providing laboratory experiences infused with inquiry

PROBLEM SOLVING USING SELF-GENERATED DATA: LEARNING CONCEPT OF SPEED AT UPPER PRIMARY STAGE

Working on self-generated data contextualizes learning and students see relevance of their learning in their day-to-day life. An attempt has been made to examine, ‘can solving problems using self- generated data by performing activities facilitate students at upper primary stage to learn concept of speed in better way?’ It is observed that this approach can bridge the gap between their classroom experiences and everyday life experiences and remove fear of solving numerical problems. The study highlights the importance of actively engaging the students in the construction of knowledge and learning scientific concepts by self-generated data. Teachinglearning of science needs to be transformed from the process of knowledge transfer to knowledge generation

PROSPECTIVE SCIENCE TEACHERS’ REFLECTIONS ON THE USE OF LEARNING STRANDS IN DEVELOPING LESSON DESIGN

Learning strands as a framework seem to give an alternative to the fixed way of planning and provide the needed space to the students for constructing knowledge in a classroom. In order to facilitate process of teaching-learning of science in a more flexible paradigm, prospective teachers need to be convinced that developing lesson design is an open-ended activity and there should always be space for redesigning learning experiences by observing reactions and responses of students. This will help in catering to the learning needs of diverse human potentials in classroom. In the present study, an attempt has been made to study reflections of the prospective teachers on the use of learning strands in developing lesson design in a more flexible paradigm. It is concluded that use of learning strands in developing lesson design can substitute specific objectives used in traditional form of lesson plan where rigid adherence of the processes of teaching learning with pre-conceived notions is emphasized. Teacher educators might look at the lesson planning framework in the light of using learning strands in the development of lesson design

Argumentation Mining System for Corpus-based Discourse Analysis based on Structured Arguments

An Argumentation mining system can analyze a large volume of text data through a variety of sources. Nowadays it is highly useful in the areas of business, economics, and finance with digital marketing being the most promising field along with social media. It is the study of corpus-based discourse analysis that involves the automatic identification of argumentative structure in text. Initially, AM talks about extracting structured arguments from natural text, often unstructured or noisy text. Theoretical approaches of AM and pragmatic schemes that satisfy the needs of social media generated data, recognizing the need for adapting more flexible and expandable schemes, capable of adjusting to argumentation conditions that exist in social media. In this scenario it is a very challenging argumentation scheme able to identify the distinct sub-task and capture the needs of social media text, revealing the need for adopting a more flexible and extensible framework. Corpus-based Machine Learning of linguistic annotations has enabled researchers to identify repetitive linguistic patterns of language use and to uncover hidden meaning in all areas of Natural Language Processing

Awareness and sources of the digital transactions schemes: a cross sectional study in a rural block of Jabalpur, Madhya Pradesh, India

Background: India is a developing country and is on the road of rapid progress, in every aspect. So, to further boost the development process, India joined many other developing countries and showed an intent to promote a cashless economy. However, this penetration is not much in the rural areas which constitute the building blocks of the country. Awareness regarding digital transaction schemes of government of India is imperative to success of such schemes. Hence, the current study for assessing the awareness of the digital transaction schemes and finding out the sources in their implementation will help cater these issues.Methods: A  descriptive cross sectional study was conducted among 60 respondents belonging to different age groups, socio economic strata and with different education status, to explore the awareness and acceptance percentage of respondents in rural block Paragraph  in relation to digital transaction schemes and methods and the their sources of information. Study was done in three-month duration from1st July 2018 to 30th September 2018.Results: It was found that the awareness for mobile banking among all the age groups was  a massive 93.36% while that of the Digital Dakiya scheme is a meagre 8.30%.It was inferred from the study that social interaction  was the major information source (51%) and there was a significant association between the use of mobile banking and younger age of the individual.Conclusions: Awareness among the older population and rural females is lesser as compared to counterparts and was massive for mobile banking. Disparity about awareness the of schemes points that overall usage needs to be promoted.

Design An Optimal Scheduling Algoritm That Minimize The Cost And Task Comletion Time

Cloud computing has emerged as a popular computing model to support on demand services. It is a style of computing where massively scalable resources are delivered as a service to external customers using Internet technologies. The aim is to make effective utilization of distributed resources and put them together in order to achieve higher throughput. In this paper, a scheduling algorithm is proposed which addresses the major challenges of task scheduling in cloud. It overcomes the problems of high task execution cost, improper resource utilization and improves the task completion time. the proposed algorithm also obtains optimum resource utilization. The proposed model is implemented and tested on simulation toolkit. We analyze the performance of proposed algorithm. The analysis results are also compared with existing scheduling approach used by the simulator. The results validate the correctness of the framework

Asymptotic and Numerical Solutions of Three-Dimensional Boundary-Layer Flow Past a Moving Wedge

We consider a laminar boundary‐layer flow of a viscous and incompressible fluid past a moving wedge in which the wedge is moving either in the direction of the mainstream flow or opposite to it. The mainstream flows outside the boundary layer are approximated by a power of the distance from the leading boundary layer. The variable pressure gradient is imposed on the boundary layer so that the system admits similarity solutions. The model is described using 3‐dimensional boundary‐layer equations that contains 2 physical parameters: pressure gradient (β) and shear‐to‐strain‐rate ratio parameter (α). Two methods are used: a linear asymptotic analysis in the neighborhood of the edge of the boundary layer and the Keller‐box numerical method for the full nonlinear system. The results show that the flow field is divided into near‐field region (mainly dominated by viscous forces) and far‐field region (mainstream flows); the velocity profiles form through an interaction between 2 regions. Also, all simulations show that the subsequent dynamics involving overshoot and undershoot of the solutions for varying parameter characterizing 3‐dimensional flows. The pressure gradient (favorable) has a tendency of decreasing the boundary‐layer thickness in which the velocity profiles are benign. The wall shear stresses increase unboundedly for increasing α when the wedge is moving in the x‐direction, while the case is different when it is moving in the y‐direction. Further, both analysis show that 3‐dimensional boundary‐layer solutions exist in the range −1<α<∞. These are some interesting results linked to an important class of boundary‐layer flows

Study of microalbuminuria as early risk marker of nephropathy in type 2 diabetic subjects

 Background: Diabetic nephropathy (DN) is a common complication of diabetes mellitus that lead to end-stage of kidney disease (ESKD). Detection of early-stage can slow loss of kidney function and improve patient outcomes with use of diagnostic biomarker detection of DN. Aims and objectives of this study is to evaluate the possible association between glycated hemoglobin and urinary microalbumin as a predictor of diabetic nephropathy in type 2 diabetic patients.Methods: Total 162 subjects were included in this study comprises uncontrolled diabetes 54 cases, controlled diabetes 54 cases and healthy controlled 54 controls. Micro albumin was measured by urinary microalbumin (turbidimetric immunoassay), glycated hemoglobin (HbA1c) measured by ion exchange resin method and fasting blood glucose estimated by GOD-POD method. The inclusion of age group was between 35 to 74 years. Statistical analysis was done by using SPSS, version 16.0. p values were calculated by ANOVA unpaired t-test. The p<0.05 was considered a statistically significant.Results: Urinary microalbumin levels were statistically significant increase in type 2 diabetes mellitus with nephropathy in comparison to uncontrolled diabetes mellitus and controlled diabetes mellitus (138.9±13.7 mg/l vs 67.7±14.1 mg/l and p<0.005**).  HbA1c, which acts as a biomarker of diabetes was significant higher diabetic nephropathy, in comparison to uncontrolled diabetes mellitus, controlled diabetes mellitus and healthy control (8.0±1.1% vs 7.1±0.9% and 5.7±0.4%).Conclusions: The present study was demonstrated impaired glycaemic control is associated with elevations in urinary micro albumin levels and it may be considered as risk marker of diabetic nephropathy

Knowledge and treatment seeking behavior regarding malaria among the residents of tribal dominated areas of Mandla district in central India – A cross-sectional study

Background: Malaria is both a result and a cause of a lack of development. Dearth of information, education, and communication activities and awareness, knowledge regarding malaria is poor particularly in tribal population of Mandla. Aims and Objectives: The aim of the study was to assess the malaria knowledge and treatment-seeking behavior among the residents of the tribal dominated areas of Mandla district and to study their association with the sociodemographic characteristics. Materials and Methods: A total of eight villages were selected from which 25 households were randomly selected making a total sample size of 200 households, from these 200 households, 200 adult respondents were identified for administration of the study questionnaire. Results: The age of the respondents ranged from 18 to 80 years, with a mean age of 37 years (SD=14.7). Overall, 48.5% of respondents had correct knowledge about perceived cause of getting malaria. The treatment seeking behavior of the respondents were associated with sociodemographic profile of the participants the age of the participants, the association was found to be highly statistically significant (P=0.001). Conclusion: Malaria prevention campaigns should be tailored according to knowledge gaps, practices, environment, resources, and preferences in different areas of the Mandla District, using the health education/awareness most likely to outreach the far corners of the district where most residents were tribals