“Investigating the Impact of Texting on Pedestrian Traffic Crossing Behaviors at SDSU Campus Intersections”

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For this study, we are going to see if texting is related to traffic crossing behaviors on
campus. To collect this data, please go to a “pedestrian traffic intersection” on
SDSU campus. This can be “pedestrian” traffic (where two walkways intersect),
“bike” traffic (where a bike lane intersects with a pedestrian walkway), or
“automobile” traffic (where a car lane intersects with a pedestrian walkway, like a
crosswalk). Make a chart like the one below on a piece of paper so that you can
simply mark checks in the appropriate box. You are to observe and collect data for
at least 20 minutes at a “pedestrian traffic intersection.” You are going to be
observing people walking in and around these “pedestrian traffic intersections” (not
the behaviors of people on bikes or in cars).
● NOTE. You cannot have any empty cells. That means you cannot have a box with
0 observations in it. You need to have at least 5 in all of your cells so please make
sure to observe a “traffic intersection” with at least moderate traffic (i.e., do not
observe a remote corner of campus at night when no one is walking around).
● We are going to observe two different variables: texting and traffic crossing
Texting: People texting on a cell phone would be a “yes” under the texting column. All
other people would be a “no” under the texting column (including those who do not have
cell phones and those who are talking on the phone and not texting).
Traffic crossing behaviors: People who carefully cross into traffic (look both ways,
stops if there are others present) would be “safe” on the traffic crossing behavior row.
People who do not carefully cross into traffic (do not look both ways, bumps into
someone) would be “risky” on the traffic crossing behavior row.
● *To make this easier, you may want to collect this data in pairs, with one person
observing and the other recording the data. If you do collect data with another
student, please write down their name, so that we know whose data matches whose.
● Once you have collected your data, please write the number (not marks) in the table
above and the name of the student you worked with: ______________________.
● *Show your observed data to your TA for the 3 prelab points*
Data collection table
No Yes
behavior Risky
Prelab—Outline for Method Section (3 points)
Complete this outline before lab. Your TA will check to make sure you have completed
this. You may write in fragments for the outline.
● Who were the participants? How many people did you observe?
(NOTE. We do not have participant data on these drivers, but usually, we would
describe variables like age and gender in this section.)
Apparatus/Materials (N/A)
● (NOTE. If we used any special equipment or surveys, we would describe them here.
But since we essentially used paper and pen/pencil, there is no need to put this
section in this paper. However, we mention it because we will be using this
subsection in the survey project lab.)
● How did we collect the data? Be specific so that this study could be replicated.
What are our variables? How did we operationally define our variables?
● Did you collect alone or in pairs?
● Where did you collect the data? What type of “traffic intersection” did you observe
(pedestrian, bike, automobile)?
● How long did you watch?
● What time of day did you make your observations?



In recent years, the widespread use of mobile devices and technology has drastically changed the way people communicate and interact with their surroundings. One observable behavior is texting while walking, which raises concerns about its impact on pedestrian traffic crossing behaviors. In this study, we aim to investigate the relationship between texting and pedestrian traffic crossing behaviors at intersections on the SDSU campus.


To collect data for this study, participants were instructed to observe a pedestrian traffic intersection for at least 20 minutes. The intersection could be either a pedestrian, bike, or automobile traffic intersection, but the observation should be focused only on pedestrians’ behaviors. The participants were asked to use a chart to mark the occurrences of pedestrians texting and crossing the intersections, with the requirement that all cells in the chart should have at least 5 observations. Participants were also advised to choose an intersection with moderate traffic and avoid remote areas with low pedestrian activity.


The two variables observed in this study were texting and traffic crossing behaviors. Texting was defined as the act of using a mobile device while walking, while traffic crossing behaviors were defined as the actions taken by pedestrians when crossing the intersection, such as looking both ways, using a crosswalk, etc.


This study aims to contribute to the understanding of the relationship between texting and pedestrian traffic crossing behaviors. The findings from this study will provide valuable information for developing interventions and strategies to promote safe pedestrian practices and reduce the risks of pedestrian-vehicle conflicts at intersections.

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