Funding Students with Exceptional Academic Needs

Topic: Education Issues
Words: 1096 Pages: 4

Project Methodology

Social research is a necessary and critical tool for professional projects to assess participants’ subjective perceptions of the context under discussion. The problem of funding students with exceptional academic needs chosen as the central research topic responds to the need for accurate, field-based research to critically analyze the extent to which schools are prepared to do so. Since it has been proposed as a working hypothesis to assume that schools are not adequately funded to assist students with special needs, the current research was designed to confirm or refute this statement. The overall structure of the paper meets the requirements of critical inquiry and consists of a systematic review of the financial bases of regional schools and conducting statistical expertise through a student survey.

Sampling Procedure

The sample for this study was intentionally narrowed to regional educational institutions by school type in order to initially assess the financial strength of schools for a narrow geographic area. An author’s application was sent to as many regional schools as possible as an invitation to participate in the applied research. It was evident that not every school board would be receptive to the study, so the total number of positive responses was measured as the percentage of the total number of invitations that were approved.

In the second part of the research project experiment, sociological questionnaires were administered to the students of only those schools that had agreed to participate in the project. For this reason, creating a sample of volunteers was a secondary step and could only be done after the primary sample of schools was formed. Since the central metric of interest for the survey was numerical data, the minimum expected sample size was calculated using the formula [1] for a confidence interval of 0.95 (Kibuacha, 2021). It was calculated that the minimum sample size should then be 385 people. Invitations to participate in the survey were sent to 800 students from various schools. The overall sampling procedure, therefore, was based on the voluntary response sampling algorithm.

Equation [1]

Minimizing Errors

Because the sampling procedure chosen may have been biased by the volunteers participating in the questionnaire, it was necessary to ensure that possible errors were minimized. Some of the strategies implemented were to invite students based on gender, age, and ethnic diversity. Mentors were encouraged to invite as many diverse participants as possible to ensure that the study was inclusive. This strategy was tested by monitoring participants’ responses in the “Demographic Information” column before the questionnaire. In addition, the survey itself was reasonably short, with no more than seven questions, to widen the scope of the audience willing to participate. Any questionnaires that were not filled out completely or that were faulty were not accepted for processing at further stages.

Participants’ responses were accepted for one week, after which any corrections, additions, or withdrawals of the questionnaires were not possible. Although respondents always have the right to withdraw from the experiment after the fact, in this case, it was necessary to exclude bias on the part of the directorate of educational institutions. In particular, there are no guarantees that after the honest answers from the students, the school management did not decide to impose penalties on them, which in turn could have influenced the decision of the participants to refuse the questionnaires. In order to eliminate this possibility, all questionnaires were completely anonymized and encrypted so that nothing was known about the participant except their school address, gender, age, and ethnicity. In addition, a contract was signed with school administrators prohibiting principals from encouraging students to withdraw papers.

Processing of Results

Because the research project was conducted in two phases, the results processing procedure was also consistent in order to avoid errors. In the first part, school funding data was compiled into a single document: this included the total planned budget for the current year (2021) and separately a line dedicated to providing additional measures for special needs students. By special needs, this draft considered any category of students who require special assistance for effective instruction. This included students with disabilities, students with low mobility, students with advanced disabilities, and students for whom the English language environment is not their native language (ELLs). Thus, the first part of the project assessed the portion of the budget devoted to supporting these students, referred to in further work as “social support in the budget.”

The second part of the project assessed students’ satisfaction with the current measures their school embodies to support students with special needs. This included a direct question to which the answer was binary: yes or no. In this section, the number of positive and negative responses was measured as a fraction of the total number of valid questionnaires for that school. In addition, students were asked to make some recommendations for school leaders on how to help these students learn in a more supportive environment. This was an open-ended type of response, so the frequency of the most common advice — “install ramps,” “hire a professional interpreter psychologist,” for instance — was evaluated and discussed afterward.

As a result of each section of the project, numerical data were obtained, between which levels of correlation and regression could be measured. This step was implemented using SPSS numerical tools, and the final result was a set of pairwise Pearson coefficients and conclusions about the coefficients of determination for linear approximation of the data. As an example, one possible result might have included the following formulation “For school X, which had a social support percentage in the budget of 10%, the correlation with student satisfaction with these measures was 0.35. This indicates a moderate positive relationship between the variables being measured.” Upon completion of the statistical analysis, general conclusions and observational results were created for the entire data set

Ethical Principles

The underlying philosophy of the study was to avoid violating any ethical framework for all concerned. All invitations to participate were purely voluntary, and any refusals to participate were not sanctioned in any way. In addition, the authors declared that there were no financial interests or discrediting of the school institutions. Complete anonymity was ensured for participants to protect their honor and dignity in order to encourage honesty in the questionnaire. In addition, the data collected was an extension of the will of the respondents: no one forced them to write in the “correct” answers. During the analysis, academic ethics were used to eliminate any bias: any pairs and combinations of variables were evaluated, not just those that would be of interest to the authors.

Reference List

Kibuacha, F. (2021) How to determine sample size for a research study. Web.

Attributions and Academic Integrity
Indian Residential School System in Canada