Back when I worked to support a data science team, I actually remember taking some of their queries and stripping everything but the select so that I could see what they were trying to do and I could add in the correct parts of the rest.
Think: I have 20 tables with the column `id`
"I want 'id,id,id'"
is bad UX, and is what here is being argued, then when the syntax guide you: "I want 'FROM a: id'" is better
Even in your example, first and last could refer to student or teacher. But presumably you know you're looking for student data before knowing the exact columns.
Like, how would you send this question to someone? Or how would you expect it to be sent to you? If your boss doesn't tell you from what table they want some data, do you just not answer?
And sure, there could be ambiguities here. But these are not really fixed by listing the sources first? You would almost certainly need to augment the select to give the columns names that disambiguate for their uses. For example, when you want the teacher and the student names, both.
And this is ignoring more complications you get from normalized data that is just flat out hard to deal with. I want a teacher/student combination, but only for this specific class and term, as an example. Whether you start the from at the student, the class, or the term rosters feels somewhat immaterial to how you want to pull all of that data together for why ever you are querying it.