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CSU Students’ Time Estimation

Turned in to "Class Paper" Feedback: Good Job overall, The extra day's...
Course

Natural Disasters (GEOL 1110)

3 Documents
Students shared 3 documents in this course
Academic year: 2017/2018
Uploaded by:
BW
Brianna Walker
Columbus State University
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GEOL 1110

Justin Fairchild March 27, 2018 CSU Students’ Time Estimation A couple of months ago, we (students) started to record how much time has passed. Our first estimate would be recorded after our instructor stopped us at a random point in class (long- time estimate). We would estimate how many minutes have gone by since the beginning of class. He would then notify us that he has started his stopwatch and he would stop it randomly a few minutes later. Then, we would have to estimate and record how many minutes and seconds have gone by (short-time estimate). Throughout this process, we have recorded and analyzed how accurate a CSU student is in estimating how much time has passed. We will now compare these results to other students in the same class. When looking at these results, you can find many recurring trends in the long-time estimates. In Figure 1B, 51% of the chart is ≤ 2 minutes off. In Figures 3C & 4C, students were about 51-53% above the exact time and 37-41% below the exact time. In that 5 minute difference, there is only a slight percentage change. Also in Figure 3B and 4B, as time increases, the exactness of the time estimation decreases, but the percentage of estimations that are 1- minutes off increases. The short-time estimates can be quite different from the long-time estimates. There seems to be a slimmer percentage of students who guessed the time exactly on Figure 2C compared to Figure 1C. In Figure 2B, 38% of the chart is ≤ 30 seconds off. In Figure 5 and 6, there is a one day difference between the two days, so this could be the reason why there is a dramatic percentage change between Figure 5C and 6C. From Figure 5B to 6B, there is a percentage

decrease when time increases. This can be seen from the exact time to the 20 second mark. By looking at both the long-time time and short-time estimate results, one can find many patterns and relate this to a student’s behavior in class. It is shown that students can be very accurate due the large percentage of students who estimated very closely to the exact time. A little bit over half of the students estimated within the two minute mark on Figure 1B and over ⅓ of them estimated within the 30 second mark. This can show that the average CSU student be almost or very precise when making time estimates. It also seems to look like that as time goes on, the less accurate the time estimates are, but students were very close (Figure 3B & 4B; 5B & 6B). From Figure 3B to 4B, the “exact” percentage goes from 10% at 36 minutes to 8% at 41 minutes. From Figure 5B to 6B, the “exact” percentage drops from 1% before 2 ½ minutes to <1% after 2 ½ minutes. It seems that these short-time results are not a good comparison due to the incremental one-day difference. Though, the theory of time vs. accuracy does not seem to be the case when you compare the two sets to each other (Figure 3B & 4B to Figure 5B & 6B). The students were less accurate when they were told to estimate the short-time estimate. Nonetheless, these results show that as time goes on, a student can estimate large amounts of time more accurately than estimating a few minutes at a time. After interpreting all this data, I have come to figure out some of these scenarios. I think that if a student were to predict how much time has passed at 2 minutes and 5 seconds, they would estimate 10 to 20 seconds above the exact time. I believe this due to the 74% of students who guessed above the exact time in Figure 5C and the two highest percentages on Figure 5B is the 10 second (14%) and 20 second (13%) marks. The same thing goes for if a student were to predict the time at 53 minutes. I think they would be a minute or 2 below the exact time. I believe this because from Figure 3C to 4C you can see an increase in the “below” percentage and

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CSU Students’ Time Estimation

Course: Natural Disasters (GEOL 1110)

3 Documents
Students shared 3 documents in this course

University: Columbus State University

Was this document helpful?
GEOL 1110
Justin Fairchild
March 27, 2018
CSU Students’ Time Estimation
A couple of months ago, we (students) started to record how much time has passed. Our
first estimate would be recorded after our instructor stopped us at a random point in class (long-
time estimate). We would estimate how many minutes have gone by since the beginning of class.
He would then notify us that he has started his stopwatch and he would stop it randomly a few
minutes later. Then, we would have to estimate and record how many minutes and seconds have
gone by (short-time estimate). Throughout this process, we have recorded and analyzed how
accurate a CSU student is in estimating how much time has passed. We will now compare these
results to other students in the same class.
When looking at these results, you can find many recurring trends in the long-time
estimates. In Figure 1B, 51% of the chart is
≤2
minutes off. In Figures 3C & 4C, students
were about 51-53% above the exact time and 37-41% below the exact time. In that 5 minute
difference, there is only a slight percentage change. Also in Figure 3B and 4B, as time increases,
the exactness of the time estimation decreases, but the percentage of estimations that are 1-3
minutes off increases.
The short-time estimates can be quite different from the long-time estimates. There seems
to be a slimmer percentage of students who guessed the time exactly on Figure 2C compared to
Figure 1C. In Figure 2B, 38% of the chart is
≤30
seconds off. In Figure 5 and 6, there is a one
day difference between the two days, so this could be the reason why there is a dramatic
percentage change between Figure 5C and 6C. From Figure 5B to 6B, there is a percentage

Students also viewed

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