In this discussion, we will examine the components of research data. Select one of the two graphs and post a hypothetical experiment that corresponds to the graph. Define the groups, conditions (x axis), and outcome (dependent variable) that was measured (y axis).
Find Out More About Experimental Design
Have even more fun (if that’s possible) learning about experimental designs at http://www.itl.nist.gov/div898/handbook/pri/section3/pri3.htm.
A Glossary of Experimental Design
At http://www.stats.gla.ac.uk/steps/glossary/anova.html, Valerie J. Easton and John H. McColl bring you a concise and informative glossary of terms associated with experimental design. The experimental method is one way to determine the presence of cause-and-effect relationships.
Validity Threats and Research Design
Chong-ho Yu and Barbara Ohlund outline the important works of Campbell and Stanley (1963), Cook and Campbell (1979), and Shadish, Cook, and Campbell (2002) at http://www.creative-wisdom.com/teaching/WBI/threat.shtml. They also provide their own examples, which are helpful in showing how different designs may be vulnerable to different validity threats.
For purposes of this discussion I have chosen to utilize graph 2 as shown for the following hypothetical experiment. The different times will be utilized through the graph in order to differentiate motivation between the two groups.
Research Question: Does the time of day effect motivation between students in grade school versus college?
Time: 6 am, 12pm, 6pm
Group 1:4th and 5th graders – this group maintains a steady decline throughout the day
Group 2: Seniors level college students – this group fluctuates from morning to the evening
Motivation which is measured via assessment questions administered at each time to both groups.
The hypothetical study was done within a 6 week time span. Firstly, beginning with the days of Monday, Wednesday, and Friday. Then alternating weeks between Tuesday and Thursday. Each group is provided a short assessment test to analyze their motivation throughout the day. Group 1 which is comprised of elementary students grade 4 and 5 shows a steady decline in motivation through the day, this possibly due to the start of the morning feeling scheduled, however, the repetitiveness of the day may slowly bring about motivational decline from their school work, to homework, and to what every time they are allotted for family or personal time in the evening. Group 2 which is comprised of the senior level college students, fluctuates, this seemingly dependent on the activities of their day, personal or work life, etc. It should also be noted other variables that may affect them, such as stimulants, stresses, etc.
I think more so, as elementary students, the control over their schedule essentially attributes to the decrease of motivation. When I talk on motivation I think it’s important to understand it from the perspective of a child, perhaps more so, exhaustion is what we’re looking for the “I’m tired” aspect of things. As for understanding the construct of motivation among adults I think we could go a deeper level. So perhaps comparing the two wouldn’t be as plausible as it seems unless we are actually laying down a solid definition on motivation. I think more so motivation just looks different between children and adults.
For this week discussion, I selected Graph 1:
Research Question: Did children who took classes online with a live teacher learn more during covid closure than those who had classes online but self-paced?
Independent Variable: GPA
Condition 1: During covid closure
Group 1: Online with a live teacher
Group2: Online self-paced
Condition 2: After Covid-schools open
This hypothetical study was done in two phases. The first phase (Condition 1) was for nine weeks during the first closure in Florida during covid. The second phase was for nine weeks during the reopen and return to schools with the same students from the first phase. The first group was formed of the children who decided to do the online learning with a live teacher during the closure. The second group is formed of the children who had the class online self-paced during the closure. Each group was evaluated by a teacher with regular assessments that measure the learning. At the end of each phase, GPAs were compared. During phase one, both groups had identical average GPA scores. During the second phase, Group 1 had a higher GPA compared to those in Group 2.
It can be deducted that children that had a teacher live learned more than those that were self-paced. However, this research lacked other details, such as support that students had at home if English was the primary language and others that could play a role in children learning.