GIS Project Analysis

[MichaelAgunede]

Hello folks.

My team mates and I have been assigned a project on using Geographic Information System (GIS) for Institutional Planning, student recruitment and retention. This project is based on an institution in Calgary, Alberta, Canada. We have created some maps on an international level, a canada wide map, and a map based on province and city of students (International and Local students). We also geocoded also.
Please, we need some more analysis to incorporate to this project to make it look complex. We have just a basic foundation of python programming, else that would have added some complexity to the project (Solutions on creating a python script for an analysis would be appreciated).  Please folks, can anyone come up with some suggestions on some analysis/geoprocessing function to add to this project to make it a bit more complex?

Thanks guys.

[JoshuaChisholm]

Hello Michael,

There are plenty of things you can do from python. I think having a bit more direction would help us come up with some interesting analysis.
What is your objective for this project? Are you trying to find ways to increase student recruitment and retention?
What data do you have at your disposal? It sounds like you have a list of students and their addresses (I assume the client is a University/College). Do you have the current year of the students? Do you have their address before they moved into town to attend school? Do you have a list of students who dropped out? Do you have and academic performance indicators? Any other interesting data?

Thank you,
~Josh

[MichaelAgunede]

Hello Michael,

There are plenty of things you can do from python. I think having a bit more direction would help us come up with some interesting analysis.
What is your objective for this project? Are you trying to find ways to increase student recruitment and retention?
What data do you have at your disposal? It sounds like you have a list of students and their addresses (I assume the client is a University/College). Do you have the current year of the students? Do you have their address before they moved into town to attend school? Do you have a list of students who dropped out? Do you have and academic performance indicators? Any other interesting data?

Thank you,
~Josh

Hello Josh,
Thank you for your response. Yes, the objective of the project is to increase student recruitment and retention for a college. Currently, we have a list of students and their addresses which we used for geocoding. We also the addresses of international students before they moved to Calgary, but at a city level (no postal code, nor address). We also have the students age, gender, and the programs they applied into. And, we have the Calgary community profiles. But we don not have the students academic grades.

Thanks

[JoshuaChisholm]

Hello Michael,

Are you trying to do something cool in python or get some results that might affect real world business decisions?

If you are trying to do something cool in python, I'm having a hard time thinking of anything. You could write a script to see which programs generally live closer to the college and which programs tend to live far away and commute in, but I think you would be able to do this faster manually in ArcMap.

If you are trying to get some results that might affect real world business decisions, I'd suggest contacting the college to ask for more data. If you are trying to increase number of applications to the school (to increase enrollment), you should see if you can get a database of applicants to the college (and where they live). If you have this information you can see where the applicants come from. Maybe they all come from the North side of Calgary (or even Halifax). Maybe they all come from lower income downtown areas (suggesting transit advertisement might be successful). Maybe they all come from mid income suburban areas (suggesting bill boards might be successful). I don't think you could do this analysis with the current student database, because it is likely that many of them moved to attend the school. Besides, current students are not your target audience, prospective students are.

In terms of increasing retention, I would take a similar approach. Try to get a list of students that have dropped out of the program. Are there any patterns? Do they all live in the same place? Etc.
Maybe you can see if these patterns exist in your current student database. This way you could tailor resources to suit the students at high risk of dropping out.

Sorry if that wasn't that helpful.

[MichaelAgunede]

Hello Michael,

Are you trying to do something cool in python or get some results that might affect real world business decisions?

If you are trying to do something cool in python, I'm having a hard time thinking of anything. You could write a script to see which programs generally live closer to the college and which programs tend to live far away and commute in, but I think you would be able to do this faster manually in ArcMap.

If you are trying to get some results that might affect real world business decisions, I'd suggest contacting the college to ask for more data. If you are trying to increase number of applications to the school (to increase enrollment), you should see if you can get a database of applicants to the college (and where they live). If you have this information you can see where the applicants come from. Maybe they all come from the North side of Calgary (or even Halifax). Maybe they all come from lower income downtown areas (suggesting transit advertisement might be successful). Maybe they all come from mid income suburban areas (suggesting bill boards might be successful). I don't think you could do this analysis with the current student database, because it is likely that many of them moved to attend the school. Besides, current students are not your target audience, prospective students are.

In terms of increasing retention, I would take a similar approach. Try to get a list of students that have dropped out of the program. Are there any patterns? Do they all live in the same place? Etc.
Maybe you can see if these patterns exist in your current student database. This way you could tailor resources to suit the students at high risk of dropping out.

Sorry if that wasn't that helpful.

Thanks Josh. This was helpful. I actually got some new ideas from your comment. Thanks again.