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About this tool
Fill-in-the-blank AI prompts for study plans, active recall, essay feedback and exam prep that build understanding.
The Student Prompt Pack is a library of 9 fill-in-the-blank AI prompts built around evidence-backed study methods: the Feynman technique, active recall, spaced repetition, examiner-style marking and rubric-based feedback. Every prompt is written so the model checks, quizzes and critiques your work rather than doing it for you — quiz answers are withheld until you attempt the questions, essay feedback quotes your draft instead of rewriting it, and outlines organise your own thesis and evidence. Fill in the blanks in your browser and copy the finished prompt into any assistant.
Open Student Prompt Pack on AltFTool — it loads instantly in your browser.
Add your input to the workspace.
Adjust the options until the result looks right.
Copy or download the output and put it to work.
Prompts forbid the model from writing your essay or answering its own quiz questions — the structure forces retrieval and revision, which is what produces grades.
Active recall, spacing and self-explanation are among the best-supported techniques in learning research; each prompt operationalises one of them.
Prompt assembly happens in the browser; no account, no API key and nothing you type leaves the page.
It depends on how you use it and your institution's policy. Having AI write assessed work for you is academic misconduct almost everywhere; using it to quiz you, check your own explanation or critique your draft is closer to a study partner. These prompts are deliberately written for the second mode — several explicitly instruct the model not to produce replacement prose — but always check your institution's rules.
Because retrieving information strengthens memory far more than re-exposure to it — the testing effect is one of the most replicated findings in learning research. The quiz prompt builds questions only from your own notes and withholds the answer key until you confirm you have attempted every question on paper.
Expanding gaps of roughly 1 day, then 3, then 7, then 14 work well when an exam is weeks away; the exact numbers matter less than the expansion and the honesty of your available hours. The schedule prompt places weak topics earliest, gives them one extra review, and reserves the final three days for mixed retrieval rather than new learning.
You write your explanation from memory first, then the AI acts as the critical audience: it quotes your imprecisions, lists what a complete explanation includes, and asks follow-up questions it deliberately leaves unanswered. The prompt forbids the model from writing a model explanation, because the learning happens when you rewrite yours.