VISC
My son is taking the high-school entrance examination this year.
Nanjing recently opened applications for specialty-student programs, so I have been reviewing admissions information from different high schools and considering a practical question: could this route give my son one more opportunity?
For parents at this stage, the question is no longer simply whether to push harder. We have to help a child make a more suitable choice from limited and fragmented information.
I already use AI frequently for work and daily life. This time, I used it to help compare schools offering specialty-student admissions.
I was not asking general questions or trying AI for novelty. I gave it a concrete and complicated task that was directly in front of me: identify suitable schools to which my son could apply.
The process in Nanjing works roughly like this.
First, families submit information through a school’s designated channel for preliminary review. This usually includes examination results from the first semester of ninth grade, class and school rankings, and competition awards from junior high school.
Second, they wait for a phone call. Schools generally contact only students who pass the preliminary review.
Third comes the official application through the education authority’s platform. In practice, some students who were not contacted after preliminary review can still submit an official application.
Fourth, families wait for the school’s final confirmation. If the student is accepted for the next stage, the examination follows.
Many high schools opened preliminary applications during the same week. The amount of information grew immediately. Schools had different requirements, schedules, and program directions. Parents could easily spend all day reading, asking, and comparing, only to become more confused.
I wanted to give the most disorganized part of that process to AI first.
My request was direct:
Based on my son’s circumstances, recommend about three specialty high schools to which he could apply.
I sent screenshots or photos of his examination scores and class and school rankings. AI could recognize the information from the images.
Then I provided the recently announced admissions information. Some training organizations had already collected the schools into image summaries, which made the process convenient: I could send the images directly and let AI read them.
At that point, AI had two groups of information:
- My son’s own academic profile.
- The current set of schools accepting applications.
That was not enough.
School selection is not only about whether a student is eligible to apply. It is also about whether applying is worthwhile. I therefore added more criteria and asked AI to narrow the list further.
I asked it to consider each school’s high-school entrance cutoff scores over the previous two years and its later university-entrance outcomes.
Two measures mattered particularly to me.
The first was the proportion of students reaching strong university-admission thresholds. This provides a rough sense of the school’s final outcomes.
The second was the school’s ability to help students progress beyond the level at which they entered. Some schools do not begin with the strongest student population, but teach well and move students upward over three years. Such a school may deserve serious consideration.
Specialty-school selection should not focus only on reputation, nor only on the possibility of admission at a lower score.
For families, a specialty route naturally offers another chance. A student who may not reach a school’s ordinary cutoff might still have an opportunity through a particular strength.
But the school is not offering a loophole. It is also selecting the strongest candidates.
That creates a realistic middle ground. Students whose overall conditions are too weak are unlikely to be chosen, while exceptionally strong students may not need this route. The group requiring the most careful comparison consists of students in the middle: they have a viable academic foundation and a relevant strength, and an additional effort may create more room.
That judgment is time-consuming because it is not a simple yes or no.
Grades, rankings, awards, school requirements, recent cutoff scores, later outcomes, and the family’s own preferences all need to be considered together.
A parent can collect and compare everything manually. The problem is that this period is already stressful, and the information is scattered. Often, parents are capable of understanding it, but become lost while trying to hold all of it in their heads.
AI’s greatest help was not making the decision for me. It was straightening the line of reasoning first.
I supplied my son’s situation, the range of available schools, and the criteria that mattered to me. AI performed an initial screening and returned a clearer structure, including:
- Three recommended schools.
- Why each school was recommended.
- Where my son’s profile matched each one.
- Where an opportunity appeared stronger and where risks remained.
Instead of starting without direction among a large number of schools, I now had a smaller range to verify and compare.
I would not completely trust AI’s conclusions.
Admissions contain many changing factors: policy details, a school’s interpretation, the number of applicants in a given year, and a child’s performance on the day. AI cannot guarantee any of these.
My understanding has remained clear: AI can organize information, perform an initial screen, and support logical analysis, but the final decision still belongs to the parents.
Even within that boundary, it helped me substantially.
The hardest part of a problem like this is often not the judgment itself, but the preparation. Materials are scattered, information is inconsistent, criteria are numerous, and there are many schools. Simply arranging everything coherently in one mind is exhausting.
With AI, at least half of that first stage can be handled more quickly.
That is practical help to me.
It did not solve every problem, but it made a complicated problem feel far less chaotic.