Educational research refers to a
systematic attempt to gain a better understanding of the educational process,
generally with a view in improving its efficiency. It is an application of the scientific
method to the study of educational problems.
Definitions.
1. Good. “Educational
research is the study and investigation in the field of education.”
2. Munroe. “The final
purpose of educational research is to ascertain principles and develop procedures
for use in the field of education.”
3.Mulay. “Any systematic study designed to promote the development of education as a science can be
considered educational research.”.
4. Crawford. “Educational
research is a systematic and refined technique of thinking, using special tools
in order to obtain a mere adequate solution to a problem.”
5. J. W. Best. “Educational
research is that activity which is directed towards the development of a science of
behaviour in educational situations. The ultimate aim of such a science is to
provide knowledge that will permit the educator to achieve his goals by the
most effective methods.”
6. W. M.
Traverse. “Educational
research is that activity which is directed towards the
Development of science of
behavior in educational situations.”
Characteristics.
1.Educational
research is directed towards the solution of a problem in the field of
education. It may attempt to answer a question or to determine the relation
between two or more variables.
2.It
emphasizes the development of generalizations, principles or theories that will
be helpful in predicting future
occurrences.
3.Educational research usually goes beyond the
specific objects, groups or situations
Investigated
and infers characteristics of a target population from the sample observed.
4. Educational research involves
getting new data from primary or first hand
sources or using existing data for a new
purpose.
4.Educational
research accepts only what can be verified by observation. Certain interesting questions
do not tend to research procedures.
5.Although a research activity may at times be somewhat random and unsystematic, it is more often
characterized by carefully designed procedures, always applying rigorous
analysis. Although trial and error are often involved, research is rarely a
blind, shotgun investigation trying something to see what happens.
6.Research
strives to be objective and logical, applying every possible test to validate
the procedures employed, the data collected, and the conclusions reached. The
researcher attempts to eliminate personal bias.
7.Research
requires expertise. The researcher knows what is already known about the problem and how others have investigated.
8.Educational
research involves the quest for answers to unsolved problems. Pushing back the frontiers
of ignorance is its goal and originality is frequently the quality of a good
research project.
9.Educational
research is based on insight and imagination. It needs the service of a man who looks
beyond the present.
10.Educational
research requires an interdisciplinary approach. It is related to the study of
complex relations about facts.
11.Educational
research is not so exact a research as physical science. In the latter, we can
control the events but in educational research, it is not possible.
12.Educational
research has a great field. Educational psychology, educational philosophy, methodology,
class organization and management, child development and other subjects are the
fields of research in education.
As a part of m- Ed curriculum
the first-year m -ed student of N SS
TRANING COLLEGE OTTAPALAM was conducted on a workshop on 19-8-2019 till
26-8-2019. The workshop was inaugurated by sri
-RAJEEV WARRIR and coordinated by DR
DS SAJAN (ASSIST Professor NSS TRAINING COLLEGE)
After the inauguration section, we started our lab work, sajan sir, already assigned five tasks. then the first-day product is word text
matter is converted into an APA format and how to insert table, graph, picture,
etc....The next day 20-8-2019 sir introduce the next product Zotero how to apply the APA format to add a reference.
And the third work is how to effective and attractive, simplyconstruct the powerpoint Then afternoon
sajan sir introduce mobile apps. the next day 22-8-2019 introduce Edmodo, link
din, slide share, then audacityit means
how to effectively audio presentation without any noiseand the fourth one is a product is du
recorded its effectively editing the voice with the help of powerpointand the product is how to construct the blog
and how to upload the text matter, video, audio, powerpoint, voice recorder,
du recorderand multiple choice
questions and resume etc....and finallyproduct is Tumblr to upload to the blog.
Sajan sir helped each student individually when desire
after these five days at 5pm workshop was finished .all the student create
they're on blogs and upload their document successfully and at last Sajan sir
take feedback about the workshop. The feedback presented by AKHIL and KAVITHA
spoke about its effectiveness .after Sajan sir introducing HTTML tag for running words the
studentshave effectively
participatedin the workshop
Sampling
is a sampling technique in which sample from a larger population are chosen
using a method based on the theory of probability. For a participant to be
considered as a probability sample, he/she must be selected using a random
selection(“Probability
Sampling: Definition, Types, Advantages, and Disadvantages—Statistics How To,” n.d.).
The most important requirement of probability sampling is that everyone in your
population has a known and an equal chance of getting selected. For example, if
you have a population of 100 people every person would have odds of 1 in 100
for getting selected. Probability sampling gives you the best chance to create
a sample that is truly representative of the population.Probability sampling uses statistical theory
to select randomly, a small group of people (sample) from an existing
large population and then predict that all their responses together will match
the overall population.
Types of Probability Sampling
There
are mainly 4 types of probability sampling that are following.
Simple random sampling
The name suggests is a completely random
method of selecting the sample. This sampling method is as easy as assigning
numbers to the individuals (sample) and then randomly choosing from those
numbers through an automated process. Finally, the numbers that are chosen are
the members that are included in the sample(“Simple
Random Sampling: Definition and Examples,” n.d.).
There are two ways in which the
samples are chosen in this method of sampling: the Lottery system and using number
generating software/ random number table. This sampling technique usually works
around a large population and has its fair share of advantages and disadvantages.
Stratified Random sampling
Involves a method where a larger
population can be divided into smaller groups.That usually doesn’t overlap but represents the entire population
together. While sampling these groups can be organized and then draw a sample
from each group separately.
A common method is to arrange or classify by sex,
age, ethnicity and similar ways. Splitting subjects into mutually exclusive
groups and then using simple random sampling to choose members from groups.
Members
in each of these groups should be distinct so that every member of all groups
get equal opportunity to be selected using simple probability. This sampling
method is also called “random quota sampling” Cluster random
sampling is a way to randomly select participants when they are
geographically spread out. For example, if you wanted to choose 100
participants from the entire population of the U.S., it is likely impossible to
get a complete list of everyone. Instead, the researcher randomly selects areas
(i.e. cities or counties) and randomly selects from within those
boundaries.
Cluster sampling
analyzes a particular population in
which the sample consists of more than a few elements, for example, city,
family, university, etc. The clusters are then selected by dividing the greater
population into various smaller sections.
Systematic
Sampling
It is when you choose every “nth” individual to
be a part of the sample. For example, you can choose every 5th person to be in
the sample. Systematic sampling is an extended implementation of the same
old probability technique in which each member of the group is selected at
regular periods to form a sample. There’s an equal opportunity for every
member of a population to be selected using this sampling technique.
Probability Sampling
Example
Let us take an example to understand this sampling
technique. The population of the US alone is 330 million, it is practically
impossible to send a survey to every individual to gather information but
you can use probability sampling to get data which is as good even if it is
collected from a smaller population.
For example, consider hypothetically an organization that has 500,000 employees sitting at different geographic locations. The
organization wishes to make a certain amendment in its human resource policy, but
before they roll out the change they wish to know if the employees will be
happy with the change or not. However, it’s a tedious task to reach out to all
500,000 employees. This is where probability sampling comes handy. A sample
from the larger population i.e.; from 500,000 employees can be chosen. This
sample will represent the population. A survey now can be deployed to the sample.
From the responses received, management will now be able to know whether
employees in that organization are happy or not about the amendment.
What are the
steps involved in Probability Sampling.
ØChoose
your population of interest carefully:
Carefully think and choose from the population, people you think whose opinions
should be collected and then include them in the sample.
ØDetermine
a suitable sample frame: Your frame
should include a sample from your population of interest and no one from
outside in order to collect accurate data.
ØSelect
your sample and start your survey: It can sometimes be challenging to
find the right sample and determine a suitable sample frame. Even if all
factors are in your favor, there still might be unforeseen issues like cost
factor, quality of respondents and quickness to respond. Getting a sample to
respond to true probability survey might be difficult but not impossible.
But, in most cases, drawing a probability sample
will save you time, money, and a lot of frustration. You probably can’t send
surveys to everyone but you can always give everyone a chance to participate,
this is what probability sample is all about
When to use Probability Sampling.
§When
the sampling bias has to be reduced:
This sampling method is used when the bias has to be minimum. The
selection of the sample largely determines the quality of the research’s
inference. How researchers select their sample largely determines the
quality of a researcher’s findings. Probability sampling leads to higher quality
findings because it provides an unbiased representation of the population.
§When
the population is usually diverse:
When your population size is large and diverse this sampling method is
usually used extensively as probability sampling helps researchers create
samples that fully represent the population. Say we want to find out how many
people prefer medical tourism over getting treated in their own country, this
sampling method will help pick samples from various socio-economic strata,
backgrounds, etc to represent the bigger population.
§To
create an accurate sample: Probability sampling help researchers
create an accurate sample of their population. Researchers can use proven
statistical methods to draw an accurate sample size to obtained well-defined data.
Advantages of
Probability Sampling
§It’s
Cost-effective: This process is both
cost and time effective and a larger ssample can also be chosen based on numbers assigned to the samples and
then choosing random numbers from the bigger sample. Work here is done.
§It’s
simple and easy: Probability sampling is an easy way of
sampling as it does not involve a complicated process. It's quick and saves
time. The time saved can thus be used to analyze the data and draw conclusions.
§. It non-technical: This method of
sampling doesn’t require any technical knowledge because of the simplicity with
which this can be done. This method doesn’t require complex knowledge and its
not at all lengthy.
Probability
Sampling V/S Non-Probability Sampling
Table
1.merits and demerits of probability
sampling and nonprobability sampling
Probability
sampling
None
probability sampling
Merit
ØAvoid sectional bias
ØEnable generalization from the sample to the wider
population
Demerit
ØRisk omitting
important resonance through chance
Merit
ØControl over
selection process
ØInclusion of
political actors
Demerit
ØGreater scope
for sectional bias
ØLimited
potential to generalize from the sample to the broader population
§REFERENCES
.
https//buc.kim/d/6kODnt1mjMfJ?pub-link
.
https//buc.kim/d/13bNgzZ4vQj?pub -link
§(“Cluster
Sampling,” 2018)
§(“Probability Sampling:
Definition,Types, Advantages and Disadvantages—Statistics How To,” n.d.)
