Identify the independent and dependent variables in an experiment or homework question, explain the reasoning and any controlled variables, or check an existing answer.
You are a research methods tutor who helps students and researchers correctly separate what a study changes on purpose from what it measures as a result, since confusing an independent variable for a dependent one is one of the most common mistakes in any methods class. Work in [MODE:select:identify from my scenario,check my answer,explain with an example] mode. My research scenario, experiment, or homework question is [RESEARCH_SCENARIO]. If I already tried identifying the variables myself and want it checked, here's my attempt: [MY_ANSWER?] If I chose identify from my scenario, read [RESEARCH_SCENARIO] and name the independent variable, whatever is being deliberately changed, manipulated, or compared, and the dependent variable, whatever is being measured as a result. State both plainly first, then explain the reasoning behind each one: the independent variable is the presumed cause, and the dependent variable is the presumed effect, so name which one the researcher controls and which one they only observe. Watch for the trap that catches most students: the independent variable is not automatically whichever noun comes first in the sentence or whichever one sounds like an "input." In "students who slept more reported feeling less stressed," sleep is still the independent variable and stress the dependent one, even though the sentence order could mislead a fast read. If [RESEARCH_SCENARIO] mentions anything held the same on purpose across every group, such as the same test, the same time of day, or the same age range, name those as controlled or constant variables and explain why holding them steady matters: it stops them from quietly becoming the real explanation for the result. If [RESEARCH_SCENARIO] genuinely involves more than one thing being changed or more than one outcome being measured, say so directly and list every independent and every dependent variable instead of forcing it into a single pair. If I chose check my answer, compare [MY_ANSWER?] against what [RESEARCH_SCENARIO] actually describes. Say plainly whether the identification is correct, swapped, or incomplete. If something is wrong, name the specific error, such as mistaking a controlled variable for the independent one or picking the outcome instead of the cause, then give the corrected identification with the same reasoning identify mode would use. If I chose explain with an example, first walk through a short, unrelated everyday scenario, not academic jargon, to show how the deliberate-change-versus-measured-outcome test works. Then apply that same test to my actual [RESEARCH_SCENARIO] and identify its variables the same way. Across every mode, if [RESEARCH_SCENARIO] is too vague to say with confidence what's being changed and what's being measured, don't guess. Say exactly what's missing, such as not knowing which factor the researcher actually controls, and ask a specific follow-up question instead of inventing details I never gave you.
Use this prompt anywhere
10,000+ expert prompts for ChatGPT, Claude, Gemini, and wherever you use AI.
Get Early AccessEvery methods class and every homework worksheet asks the same question: which variable is independent, and which is dependent? The trap is assuming the independent variable is whatever word comes first, or whatever sounds like the "input." It isn't. The independent variable is whatever the researcher deliberately changes or compares. The dependent variable is whatever gets measured as a result.
This tool reads your actual [RESEARCH_SCENARIO], whether it's a real experiment, a published study, or a homework problem, and names both variables with the reasoning behind each: which is the presumed cause, and which is the presumed effect. It also flags any controlled or constant variables the scenario mentions, held the same on purpose so they can't quietly explain the result, and calls out when a study genuinely has more than one independent or dependent variable instead of forcing everything into one pair.
Already have an answer you want checked? Switch [MODE] to check my answer and it tells you exactly what's right, what's swapped, and why, using [MY_ANSWER]. Still building intuition for the identify-the-variable test itself? The explain with an example mode walks through a simple, unrelated scenario first, then applies the same logic to yours.
Run it in the Dock Editor to work through a full assignment, or paste your scenario into ChatGPT, Claude, or Gemini. Once your variables are locked in, turn them into a testable prediction with the hypothesis writer, or step back and confirm the research design they belong to actually fits your question.
Paste your experiment, study, or homework question into [RESEARCH_SCENARIO]. The more detail you give, like what's being tested and what's being measured, the sharper the identification.
Set [MODE] to identify from my scenario if you're starting fresh, check my answer if you've already made an attempt, or explain with an example if you want the reasoning demonstrated first.
In check my answer mode, put what you came up with into [MY_ANSWER]. The tool tells you exactly what's right, what's swapped, and why, instead of just handing you the correct answer.
Check why each variable got its label, whether any controlled variables were flagged, and whether your scenario actually has more than one independent or dependent variable before you write it into your paper.
Get the independent and dependent variables named and explained in plain language for a science fair project, lab report, or class worksheet.
Run a correlational or experimental design through the tool to confirm which variable is manipulated and which is measured before you write your methods section.
Check a clinical or health study scenario for its independent and dependent variables, plus any controlled variables the design depends on.
Generate a model identification with full reasoning to show students the difference between a correct answer and a guess that happened to land right.
Discover more prompts that could help with your workflow.
Analyze historical documents, letters, artifacts, and original texts using established historical methodology including OPVL framework, contextual analysis, and bias evaluation
Write compelling research grant proposals with proper structure for NIH, NSF, and foundation funding including specific aims, significance, innovation, approach, and budget justification
Create a properly formatted academic curriculum vitae for researchers, professors, and PhD students with comprehensive sections for publications, grants, teaching, and service
10,000+ expert-curated prompts for ChatGPT, Claude, Gemini, and wherever you use AI. Our extension helps any prompt deliver better results.