Question

Many universities and colleges have instituted supplemental instruction (SI) programs, in which a student facilitator meets regularly with a small group of students enrolled in the course to promote discussion of course material and enhance subject mastery. Suppose that students in a large statistics course (what else?) are randomly divided into a control group that will not participate in SI and a treatment group that will participate. At the end of the term, each student’s total score in the course is determined.

a. Are the scores from the SI group a sample from an existing population? If so, what is it? If not, what is the relevant conceptual population?
b. What do you think is the advantage of randomly dividing the students into the two groups rather than letting each student choose which group to join?
c. Why didn’t the investigators put all students in the treatment group? Note: The article "Supplemental Instruction: An Effective Component of Student Affairs Programming" (J. of College Student Devel., 1997: 577–586) discusses the analysis of data from several SI programs.

Answer 1

The scores from the SI group are a sample from the population of all students enrolled in the large statistics course. Randomly assigning students to control and treatment groups helps reduce bias and allows for a clear assessment of the effect of SI. A control group is necessary to provide a baseline for comparison.

Step-by-step explanation:

Supplemental Instruction (SI) programs involve an experimental group that participates in SI and a control group that does not. The scores from the SI group are indeed a sample from an existing population; the relevant population is that of all students enrolled in the large statistics course. The advantage of randomly dividing the students into two groups rather than self-selection is that it minimizes bias and ensures that both groups are comparable, providing a clearer assessment of the effect of SI on student performance.

Researchers might choose not to place all students in the treatment group to establish a control group for comparison, ensuring there is a baseline to measure the effects of the SI against. Random assignment helps ensure the integrity of the study's findings, as it reduces the chance that external variables will influence the outcome. The comparisons between control and experimental groups after the intervention yield insights into the effectiveness of SI.

Answer 2

Step-by-step explanation:

Let many universities and colleges have conducted supplemental instruction(SI) programs. In that a student facilitator he meets the students group regularly who are enrolled in the course to promote discussion of course material and enhance subject mastery.

Here the students in a large statistics group are classified into two groups:

1). Control group: This group will not participate in SI and

2). Treatment group: This group will participate in SI.

a)Suppose they are samples from an existing population, Then it would be the population of students who are taking the course in question and who had supplemental instruction. And this would be same as the sample. Here we can guess that this is a conceptual population - The students who might take the class and get SI.

b)Some students might be more motivated, and they might spend the extra time in the SI sessions and do better. Here they have done better anyway because of their motivation. There is other possibility that some students have weak background and know it and take the exam, But still do not do as well as the others. Here we cannot separate out the effect of the SI from a lot of possibilities if you allow students to choose.

The random assignment guarantees ‘Unbiased’ results - good students and bad are just as likely to get the SI or control.

c)There wouldn't be any basis for comparison otherwise.