Classrooms are setups that have been used for many years in the dissemination of knowledge. Other formal ways have been introduced for instance, the use of video records in teaching, however, as much as these methods have attempted to address the limitations presented by the classroom form of teaching, several important aspects have been overlooked. It may be the oldest method of teaching, but it still beats the rest, hands down.
Several methods of making teaching as effective as possible have been formulated, specifically with an aim of improving the quality of teaching and comprehension of the students in class. The main issue that has been researched in this work is whether or not rewarding students is effective in assimilation of knowledge. Is there a difference in performance between students who are rewarded and those who are not rewarded? This research attempts to find out if indeed these differences exist, and if they exist, where in particular?
Research questions
What are the differences in class performance between students who are rewarded and those who are not rewarded?
If students who are rewarded perform better, what are the aspects of performance that differ?
Methods of selection
Participants of the study will be students who will be selected using a multistage form of selection, this will involve selection of schools randomly, and dividing them into strata, in each stratum, each school will have the classes participating in the study randomly chosen and divided into each strata, and each class strata will be used in randomly choosing the students who would participate in the study. The research will be a double blind one to ensure that teachers and students behaved normally, and the data would be unbiased, robust and representative.
Procedures
Four high schools are expected to take part in the study, about two classes each having ten students. The use of examining tests will be applied. This will be done periodically during exam periods to record the marks scored in particular exams.
Briefly, the variables in the study will be results of four subjects, that is, mathematics, social sciences, physics, and languages and class levels. The first four variables are data of numerical type and are scalar. The different class levels will form a categorical type of data, and specifically ordinal. Names of participants in the study will be excluded from the study; confidentiality will be maintained at all times. For the numerical data, statistical manipulation will be carried out, however, for the categorical ones, the use of comparative analysis will only be used.
Results
The type of data that will be used in this case is numerical data of type scalar. This data will help in formulating descriptive hypotheses, and performing different inferences. It is also important to note that, the following hypotheses will be formulated to help address the issues at hand.
Null hypothesis (H0) = Students who are rewarded perform better compared to those who are not rewarded
Alternative hypothesis (H1) = students who are rewarded do not perform better compared to those who are rewarded
H0: μ1=μ2=μ3=μ4
H1: μi ≠μ j
i = 1,2,3,4
j = 1,2,3,4
i ≠ j
The following statistical model will be used;
Yij =M + αi + eij
If the test statistics will be greater compared to the F-Tabular value, the null hypothesis is rejected, otherwise the null hypothesis is true, and the treatment is the same, that is, students who are rewarded do not perform any better compared to the ones who are not rewarded.
Discussion
There may be however, small biasness presented simply because the data collected is not enough to be a representative of the whole population data. The assumption is that the error value is homoscedastic, and randomly identically independent. The pilot results will be used in determining which type of tests are the best representative of the study, the type of instruments suitable in the collection of data, and if the data collected are suitable in estimating the parameters in the model provided. If the null hypothesis is rejected, it means that there exists differences in the means. This implies that determination of which means are significant will have to be calculated, for instance, using particular subjects, classes and other relevant variables. Post- hoc method is essential in determining which means have an effect in the difference of the means. This will follow after the ANOVA analysis is carried out.
Conclusion
This study will attempt to bridge the gap left by different academic and professional researches, time constraints may be an issue, but, it will surely give an estimation of what is expected. This research will be very essential in evaluating the issues that need to be improved in classrooms to enable the students perform better in class, it will give an insight into whether rewarding students have meaningful importance, and thus a course of action to be applied. The statistical methods used are easy to understand and the use of simple statistical software for instance R and SPSS will be applied in an analysis of the data that will be collected
References
Rudolf N. Cardinal, M. R. (2005). ANOVA for the Behavioural Sciences Researcher. New York: Routledge.
