Survey of Satisfaction with Educational Facilities
Plan for Collection of Secondary Data and Primary Data
The obvious definition of primary data is data obtained from the field. This is original data, and it differs from secondary data, because the latter is obtained from other sources, such as interviews. Staffs and Students of the college can fill questionnaires, which helps get an individual response from everyone who is involved in the educational process. In turn, primary data would be collected after the database of such results will be prepared.
The source of secondary data consists of organizations engaged in collecting data from schools and colleges, as well as from any researcher or journal.
Some college areas are equally used by the Staffs and the Students. These areas and a few others are considered in the survey. Such surveys are based on samples selected randomly from the students, as well as from the staffs. Now the first thing that is necessary for the correct survey is the identification of these samples. For such a purpose, there are 30 staffs and 70 students chosen, taking into account a percentage which should represent 50% of each group. Thus, 15% + 35% = 50%. To collect data, now we will use this method. Variables will form a basis for data on levels of satisfaction among participants. Sampling frame should be done when sampling units are finalized. Sampling frame represents information on the area where the sampling has been done. We have to make sure that samples include all the units of a particular population. Writing a list of staffs and students, all segments and classes of the educational facility must be represented.
The satisfaction level is reflected by a Likert scale: 1 (very bad), 2 (bad), 3 (average), 4 (good), and 5 (very good).
Basically, it consists of tables where all subjects can be rated by a rate of the satisfaction level. Using this system, staff and students have to answer several questions. They have to estimate such subjects as:
The entire infrastructure of the college;
- Hostel facilities;
- Laundry facilities;
- Toilet facilities;
- Parking facilities;
Average data is calculated taking into account the whole range of answers. The average indication 3.88 is considered “Good”.
The sector can be improved in case this facility was estimated more than “Average”, but less than “Good”. More attention should be paid to facilities estimated on the “Average” level.
If a sector is estimated below the “Average” mark, it means that it must be repaired. It’s a reason to request more attention from authorities.
To draw valid conclusions, results of the survey can be represented in a form of a diagram. A circular diagram is drawn for each facility, divided into sectors according to the average percentage of people who gave a certain rate.
If most participants choose “Bad”, for example, 47% rated a facility with 4 points, one should take it into consideration. If at the same time many people rated it “Good”, it means that some parts of the facility may require repair more than others. Some results may be complicated. For example, a facility may be rated “Good” by 30% of people and “Bad” by other 30%, with an equal percentage of people estimated it either “Very Good” or “Very Bad”. Such cases require further consideration.
Trend lines are built on the spreadsheet graph. Zero serves as a point of interception. The equation is calculated depending on the trend line and the scatter plot. Thus, the variable “Overall infrastructure” depends on independent variables. There are six of them, and the graph is built considering each independent variable in particular.
All equations are based on different variables. If the value of x is given, than to obtain the value of Y, the equation must be solved. It requires a simple calculation. The “Overall infrastructure” variable depends on other variables, and it reflects the need of repairing the entire college. Variables that form such a dependent variable represent several issues and factors, and they are considered independent variables.
Such a survey simplifies the whole process of decision-making, providing people engaged in improvement with necessary data and helping understand which facilities require the most attention. It also gives certain data on how a particular issue can be solved.