All the health care professionals must take an extensive effort to educate the people to identify the learning difficulties. Researcher felt the need of conducting the research on reduction of learning difficulties among primary school teachers as it is a major modifiable risk factor in the world.
A descriptive research approach was used and the research design adopted for the present study was descriptive. The target population for the study was primary school children at selected schools in Urban and Rural Area of Greater Noida, UP. Sample size was 100 ,50 teachers in Rural Area and 50 teachers in Urban Area . The data analysis was done on the basis of objectives and hypothesis of the study.
The aim of the study was to assess the knowledge of risk factors on learning difficulties in primary school children.
Introduction
I. OBJECTIVES
To assess the knowledge regarding identifying learning difficulties of primary school children among primary school teachers of rural and urban primary schools.
To compare the knowledge regarding identifying learning difficulties of primary school children among the primary school teachers of rural and urban primary schools.
To find out the association between knowledge regarding identifying learning difficulties of rural and urban primary school teachers with selected demographic variables.
II. METHODOLOGY
Quantitative research approach was adopted for this study and descriptive research design was selected for this study. The setting of the study was primary schools in urban and rural area, Greater Noida, U.P. The sample consists of 50 teachers in urban areas and 50 teachers in rural areas of selected schools in Greater Noida and samples were selected by using purposive sampling technique. Knowledge of risk factor were assessed by using questionnaires. The investigator developed Sister Callista Roy Adaptation Model for conceptual framework. Demographic data was collected and knowledge related to risk factor of learning difficulties was assessed by structured questionaries’
III. RESULTS
The collected data was analyzed by using descriptive and inferential statistics. The distribution of the majority of the school teachers from urban (44%) and rural (46%) were in the age group of 21-30 years, most of them females i.e., 76% of urban teachers and 82% of rural, teachers, most of them were married i.e., 62% of urban teachers and 64% of rural teachers , majority of them were having highest qualification of BA.BED i.e., 58% of urban teachers and 76% of rural teachers , around 32% of urban teachers were having 8-11 years of experience and 34% of rural teachers were having 0-3 years of experience and majority of them source of information from school activity i.e., 60% of urban teachers and 78% of rural teachers got information from school activity or school programs.
The distribution of the subjects according to that, the mean difference of knowledge scores between urban and rural school teachers was 1.43 and the mean difference was not statistically significant.
It shows that there was no much difference on knowledge regarding identifying learning difficulties of school children among rural and urban Primary school teachers.
The association (p<0.05 significant level) between the level of score and socio demographic variable. There is no significant association between knowledge scores with demographic variables of urban primary school teachers except for gender (p=0.02) and source of information (p=0.007). Hence researcher accepted the null hypothesis (H02).
Conclusion
Its concludes that distribution of the subjects according to their Year of experience.
In the Rural areas majority of the primary school teachers 17 (34 %) of them belong to the age group of 0-3 years, 10 (20%) of them belong to the age group of 4-7 years, 9 (18%) of them belong to the age group of 8-11 years and 14 (28%) above 11 years.
In Urban areas majority of the primary school teachers 13 (26 %) of them belong to the age group of 0-3 years, 15 (30%) were in the age group of 4-7 years, 16 (32 %) were in the age group of 8-11 years, and 6 (12%) were in the age above 11 years. There is no significant association between level of knowledge with demographic variables
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