After researching for schools that offer Master’s in I/O Psych programs, I faced another problem: I had no framework to figure out which school should I apply to.
Back then, I ended up choosing based on my preference, which was a combination of my research about the schools, my random biases, and also my mood.
And you may already no – biases and mood are not a reliable source of judgment.
Later, I learned how companies use to decide which candidates to hire in my master, and it suddenly clicked. I could have used the same methods to choose grad school back then.
If I were to choose grad school again, here are the method I would use to pick which grad schools to apply.
Content
There are two rounds in total. The 1st round is used to decide whether the school and its program is worth it to attend or not, and the 2nd round is used to choose the top schools among those that pass the 1st round.
1. Step 1: Setting the basic requirements
This step helps reduce the number of school you actually have to research in details. Having this step first will save you a bunch of time, especially when your program of interest is popular.
Consider this as setting a checklist that help you determine a school “passes” or “fails”
Very simple rules: If the school checks ALL the bullet points in your list, then it passes. If it misses EVEN ONE bullet point, then it fails.
First, you will need to decide the basic requirements that a school must have, considering the factors that
- Restrict your ability to attend; and
- Determine whether it is worth it to attend or not
If you don’t know what are the factors you should consider, check out my previous blog post: 21 Factors to Consider Before Choosing a Graduate School
When you have all your list of basic requirements, you look up related information from each school.
If the school meets all basic requirements, then the school is included. If the school does not meet all your criteria, it is eliminated.
Example
Let’s work on an example to make it more concrete.
Among the 21 factors, I decided that my basic requirements are: STEM program and its admission requirement, because:
- If I cannot meet admission requirement, there is no way I can get in (factor restricts your ability to attend)
- If it is not STEM, I would have a hard time finding jobs later (factor determines whether it is worth it to attend or not)
Among the 10 schools that offer my program, only 5 schools satisfy both. I cross out all the schools that satisfies only 1 or do not satisfy both.
2. Step 2: Ranking the schools
After eliminating schools in step 1, you may still have a lot more schools to choose from or wonder which school you should prioritize.
The next step is to rank the schools and pick out the finalists from your ranking.
If you know about regression, this step is basically create a linear regression (don’t worry if you are not familiar with the term)
Here, you will create a new list that includes the factors that make a school desirable (from good to great). Then, decide how many percentage each factor accounts for your satisfaction about grad school decision.
To make your life easier: make sure the percentage you assigned to each factor is summed up to 100%.
Then, you go through each school and rate it on each factor from 1-lowest/extremely bad to 5-highest/extremely good
Tip 1: make sure you define what each score from 1 to 5 means BEFORE you start your research (to reduce biases)
Tip 2: you can change the scale, just make sure all factors are rated on the same scale.
Then, you want to calculate the total score of each school using these formula:
Each factor total score =
rating score (from 1 to 5) x percentage of its contribution to satisfaction
School 1 total score =
Factor1 total score + Factor2 total score + … + Last Factor total score
After getting the final score or each school, you can rank the schools from highest score to lowest score.
Voilà, you just finish ranking the schools!
Example
Back to the previous example: Now, I have a list of school that I can apply, but I want to pick out only 2 of them.
I first decides that the school is more desirable if it focuses on application of I/O Psych (factor 1), and offers graduate assistantship for Master’s level (factor 2).
I also decides application focus /factor 1 accounts for 40% of my satisfaction while offering graduate assistantships/factor 2 accounts for 60%
I then define my scale: From 1 to 3 (yes! instead of 1 to 5 like I recommended)
1 – Do not have
2 – Have some/depending on availabilities
3 – 100% guaranteed
I then go online to research, and rate all the schools on a scale of 3 for each factor, the 5 schools in my list receive scores as follow:
| School | Apply-focused | Assistantship |
| School A | 5 | 1 |
| School B | 3 | 5 |
| School C | 2 | 3 |
| School D | 3 | 5 |
| School E | 4 | 4 |
Finally, I calculate the final score of the 5 schools
School A: 5 x 40% + 1 x 60% = 2.6
School B: 3 x 40% + 5 x 60% = 4.2
School C: 2 x 40% + 3 x 60% = 2.6
School D: 3 x 40% + 5 x 60% = 4.2
School E: 4 x 40% + 4 x 60% = 4
Based on the results, the schools are ranked as follow
1st – School B & D (4.2)
3rd – School E (4)
4th – School A & C (2.6)
So now, I know that I should apply for school B and school D.
4. Final notes
Above is a way to quantify your decision, help reduce any confusion or biases when you decide which school(s) to apply to.
If after step 1, the list of schools is already short enough, you can stop there. Step 2 is only necessary if you need to choose among the ones that meet all basic requirements.
You can also use step 2 to make the decision on which school you will attend if you receive multiple offer letters.
This is obviously not the only way to make grad school decisions, but I think it is systematic and easy enough to follow.
I hope this framework work. Let me know what other methods you can think of to pick and choose your school(s).
Inspiration
For anyone who wonders where I got the inspiration from: check out this blog post about scientific selection from Dr. Paul Spector – (And also thanks Dr. Cheryl Gray for introducing his blog and textbook in her class)
