Monday, March 16, 2020

Issues related with implementation of curriculum

ISSUES IN CURRICULUM IMPLEMENTATION IN CLASSROOM

Definition of Curriculum 
Implementation

 Curriculum implementation entails putting into practice the officially prescribed courses of study, syllabuses and subjects. The process involves helping the learner acquire knowledge or experience. It is important to note that curriculum implementation cannot take place without the learner. The learner is therefore the central figure in the curriculum implementation process. Implementation takes place as the learner acquires the planned or intended experiences, knowledge, skills, ideas and attitudes that are aimed at enabling the same learner to function effectively in a society.
Curriculum implementation therefore refers to how the planned or officially designed course of study is translated by the teacher into syllabuses, schemes of work and lessons to be delivered to students.

IMPORTANCE OF CURRICULUM IMPLEMENTATION:

If you define curriculum as a set of skills and knowledge that the students are expected to achieve by the end of a period of time then curriculum is important because it is a measureable standard that keeps students and teachers accountable for their learning.
A curriculum is a road map of where you are going it can be as simple as an outline of topics to be covered; it can be more complex listing resources to be used, a pacing guide for instruction, and tasks students will be assigned to ensure that they have learned what you set out to teach them.


CURRICULUM ISSUES AND CONCERNS:

There are several issues and challenges that are alarmingly faced in the 21st century by teachers in classrooms as well as schools. This growing concern had brought light into this and made teachers and other faculties more aware about the issues and concerns. Some of the most commonly faced issues are jotted down below:

1)Issues on the varied implementation of the curriculum: 
Among schools and teachers seem to be one of the reasons for the prevailing low performance of schools all over the country.

2)Poor academic performance of learners: 
There is no effective teaching without learners. Learners are the ones that make teaching effective. But despite of effective curriculum the poor and lagging academic performance of learners is also one of the issues that make curriculum ineffective.

3)Books and resources:
Perennial complaints about books and other instructional materials for both teacher as well as students.

4)Overcrowded classrooms: 
overcrowded classrooms do not provide a good learning environment for students.

5)Teachers: The teachers has been identified as one of the influencing factors in the varied implementation of the curriculum. Issues like ill prepared teachers , poor attitudes towards change and low morale have been recent causes for the poor implementation of curriculum.

6)Lack of leadership support from Principals: 
Newly implemented curriculum must be supported by the principals so as to arrange every necessary needs to implement it for students and school.

7)Some curricular are results of bandwagon but are not well supported by managers: 
In the desire of some schools to be the part of the global educational scenario, changes and innovations are drastically implemented even if the school is not ready.

8)Lack of monitoring and evaluation: Inadequate monitoring activities to find out the curricular strength or weaknesses and problems are being encountered.
Innovations results to teacher burn out: With so many new changes taking place in the curriculum, many teachers are getting burn out. They get tired easily and motivation is very low. It is because they cannot cope with the rapid changes that take place.

9)Lack of communication: 
In several situations the newly implemented curriculum are only know to the managers or principals or teachers but are not properly communicated to the students. Which is one the major reason in the failure of the curriculum.

NATURE OF CASE STUDY

CASE STUDY
The case study is a way of organising social data for the purpose of viewing social reality.It examine a social unit as a whole.The unit may be a person,a family,a social group,a social institution or a community.
The purpose is to understand the life cycle or an important part of the cycle of the unit.The case study probes deeply and analyzed interaction between the factors that explain present status or that influence change or growth.

Nature of case study

1. A descriptive study
a. (I.e. the data collected constitute descriptions of psychological processes and events, and of the contexts in which they occurred (qualitative data).
b. The main emphasis is always on the construction of verbal descriptions of behaviour or experience but quantitative data may be collected.
c. High levels of detail are provided.

2. Narrowly focused.
a. Typically a case study offers a description of only a single individual, and sometimes about groups.
b. Often the case study focuses on a limited aspect of a person, such          as their psychopathological symptoms.

3. Combines objective and subjective data
a. i.e. the researcher may combine objective and subjective data: All are regarded as valid data for analysis, and as a basis for inferences within the case study.

i. The objective description of behaviour and its context

ii. Details of the subjective aspect, such as feelings, beliefs,
impressions or interpretations. In fact, a case study is uniquely able to offer a means of achieving an in-depth understanding of the   behaviour and experience of a single individual.

4. Process-oriented.
a. The case study method enables the researcher to explore and describe the nature of processes, which occur over time.
b. In contrast to the experimental method, which basically provides a stilled snapshot of processes, which may be continuing over time like for example the development of language in children over time.

5.Longitudinal approach
  The case study method showing development over a period of time.

6.The number of unit to be studied is small.

7.It studies a social unit deeply and thoroughly.

8.It is qualitative as well as quantitative.

9.It covers sufficient wide cycle of time.

10.It has continuity in nature.

Friday, August 23, 2019

CLUSTER SAMPLING


Cluster sampling
Cluster sampling is defined as a sampling method where multiple clusters of people are created from a population where they are indicative of homogeneous characteristics and have an equal chance of being a part of the sample. In this sampling method, a simple random sample is created from the different clusters in the population(‘Cluster sampling—Wikipedia’, n.d.) .

Figure 1.cluster sampling
In this sampling technique, analysis is carried out on a sample which consists of multiple sample parameters such as demographics, habits, background – or any other population attribute which may be the focus of conducted research. This method is usually conducted when groups that are similar yet internally diverse form a statistical population. Instead of selecting the entire population of data, cluster sampling allows the researchers to collect data by bifurcating the data into small, more effective groups (Phillips, 2015).
Another example of this would be; let’s consider a scenario where an organization is looking to survey the performance of smartphones across Germany. They can divide the entire country’s population into cities (clusters) and further select cities with the highest population and also filter those using mobile devices. This multiple stage sampling is known as cluster sampling.
Cluster Sampling: Steps And Tips
Some steps and tips to use cluster sampling for market research, are:
Sample.  Decide the target audience and also the size of the sample.
Create and evaluate sampling frames.  Create a sampling frame by using either an existing frame or creating a new one for the target audience. Evaluate frames on the basis of coverage and clustering and make adjustments accordingly.
Determine groups.  Determine the number of groups by including the same average members in each group. Make sure each of these groups are distinct from one another.
Select clusters.  Choose clusters randomly for sampling.
Geographic segmentation.  Geographic segmentation is the most commonly used cluster sample.
Sub-types.Cluster sampling is bifurcated into one-stage and multi-stage subtypes on the basis of the number of steps followed by researchers to form clusters.
Cluster Sampling Methods With Examples
There are two ways to classify cluster sampling. The first way is based on the number of stages followed to obtain the cluster sample and the second way is the representation of the groups in the entire cluster.The first classification is the most used in cluster sampling. In most cases, sampling by clusters happens over multiple stages. A stage is considered to be the steps taken to get to a desired sample and cluster sampling is divided into single-stage, two-stage, and multiple stages.
Single Stage Cluster Sampling.  As the name suggests, sampling will be done just once. An example of Single Stage Cluster Sampling –An NGO wants to create a sample of girls across 5 neighboring towns to provide education. Using single-stage cluster sampling, the NGO can randomly select towns (clusters) to form a sample and extend help to the girls deprived of education in those towns.

Two-Stage Cluster Sampling.   A sample created using two-stages is always better than a sample created using a single stage because more filtered elements can be selected which can lead to improved results from the sample. In two-stage cluster sampling, instead of selecting all the elements of a cluster, only a handful of members are selected from each cluster by implementing systematic or simple random sampling

Multiple Stage Cluster Sampling.   For effective research to be conducted across multiple geographies, one needs to form complicated clusters that can be achieved only using multiple-stage cluster sampling technique. Steps of listing and sampling will be used in this sampling method. An example of Multiple Stage Cluster Sampling –Geographic cluster sampling is one of the most extensively implemented cluster sampling technique. If an organization intends to conduct a survey to analyze the performance of smartphones across Germany. They can divide the entire country’s population into cities (clusters) and further select cities with the highest population and also filter those using mobile devices.
Why Cluster Sampling?
In an ideal world, research practitioners would love to survey the entire population and select their respondents randomly to make sure everyone is accounted for and therefore ensure their research results are as accurate as possible. This is referred to as random sampling. Unfortunately, there are two issues associated with this approach – cost and feasibility. However, by dividing and classifying the population into groups (cluster sampling), this provides the researcher the ability to account for individuals with a common interest, relative to the larger population. By using the cluster sampling technique, the sample data set is smaller, which helps keep research costs reasonable.
When using cluster sampling methods, it is critical to keep in mind that only one variable (element) can be assigned to a cluster. In most cases, clusters are created by geography. For example, if Apple wanted to gauge the performance of the iPad in Spain, the researcher would create clusters by all cities in Spain. The larger cities would be accounted for and cluster analysis would determine the usage of iPad by each city.
Cluster Sampling Advantages And Disadvantages
There are multiple advantages and disadvantages of using cluster sampling, they are:               
Table 1advantages and disadvantages of cluster sampling
Advantages
Disadvantages
consume less time and cost
May not reflect the diversity of the community
convenient access
clusters may share similar characteristics
least loss in accuracy of data
provides less information
ease of implementation
standard error estimates are high compared to others
differentiates into clusters
biased samples


Applications Of Cluster Sampling
·         This sampling technique is used in an area or geographical cluster sampling for market research
·         A widespread geographical area can be expensive to survey in comparison to surveys that are sent to clusters which are divided on the basis of area (Phillips, 2015)
·         The sample numbers have to be increased to achieve accurate results but the cost savings involved make this process of increasing clusters attainable.

Incidental Sampling

Accidental or incidental is that type of sampling in which a researcher pick up data or information’s from those who fall into hand or present at the time of research. It continues the process till the completion of the sample size. It is accidental because it is selected accidentally from all type of people comes to face like, teacher, students, house wife, tailors, workers, etc..Accidental sampling, also known as grab or opportunity sampling, is a form of non-probability sampling that involves taking a population sample that is close at hand, rather than carefully determined and obtained. For instance, a person who is obtaining opinions for a political poll at a shopping mall by randomly selecting passers-by is using a form of accidental sampling. Accidental samples are not as experimentally sound as using random sampling and random assignment.




CLUSTER SAMPLING PPT from kpsilpa


References
1.Adi Bhat, Global VP Sales and Marketing at Question Pro (https://www.questionpro.com/blog/cluster-sampling/)
2.  Jackson, S.L. (2011) “Research Methods and Statistics: A Critical Approach” 4th edition, Cengage Learning(https://research-methodology.net/sampling-in-primary-data-collection/cluster-sampling/)
4.Cluster sampling—Wikipedia. (n.d.). Retrieved 20 August 2019, from https://en.wikipedia.org/wiki/Cluster_sampling
Phillips, G. W. (2015). Impact of Design Effects in Large-Scale District and State Assessments. Applied Measurement in Education28(1), 33–47. https://doi.org/10.1080/08957347.2014.973561

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