Features
AI Homework Help for Every LMS Question Type
Updated July 8, 2026
Every question type FastSolve supports
FastSolve detects the question type automatically and formats the answer for the right input. Support is the same across every LMS it integrates with — Canvas, Blackboard, Moodle, Brightspace, Schoology, ALEKS, Knewton Alta, and Learnosity-powered platforms.
| Question type | Supported | How FastSolve answers it |
|---|---|---|
| Multiple choice | Yes | Reads the stem and all options, then selects the one correct choice. |
| Multiple select | Yes | Checks every correct box, not just one, on 'select all that apply' items. |
| True / False | Yes | Handled as a two-option multiple choice and set to the correct value. |
| Fill in the blank | Yes | Types the exact word, phrase, or value each blank expects into the field. |
| Matching | Yes | Pairs every prompt with its correct partner across dropdowns or paired controls. |
| Ordering / sequencing | Yes | Works out the correct order and arranges the items to match. |
| Short answer | Yes | Writes a concise, on-topic response sized for the answer box. |
| Essay | Yes | Drafts a structured long-form answer for you to review and edit. |
| Numeric input | Yes | Solves the calculation and types the number using the question's units. |
| Drag-and-drop | No | Drag-and-drop (e.g. Learnosity) is a known unsupported type — not auto-filled. |
“I've been using FastSolve Chrome Extension for a bit now and honestly it's super fast and really easy to use. You literally just double click a question and it gives you an answer almost instantly, which is kinda crazy. It works on a lot of different types of questions too, not just multiple choice. What I like most is how lightweight it is; it doesn't slow down my browser at all and everything feels smooth. The answers are usually accurate and helpful, especially when I'm stuck or just need a quick explanation.”
Multiple choice, multiple select, and true/false
Selection formats are where FastSolve is most reliable. Double-click a question and it reads the full stem and every option, decides which choice or choices are correct, and clicks the matching radio button or checkboxes in place. Multiple choice sets a single option; multiple select — often labelled 'select all that apply' — evaluates each option on its own and ticks every box that applies. True/false is handled as a two-option multiple choice.
Because the answer is one of a fixed set of options, these types are deterministic: there is a definite right answer and the model only has to identify it. That makes them the fastest and most dependable formats on any supported LMS.
Fill-in-the-blank and numeric input
Fill-in-the-blank and numeric questions need an exact typed value instead of a selection. FastSolve reads the sentence or problem, works out the specific word, phrase, or number the field expects, and types it straight into the input. For numeric items it solves the underlying calculation and enters the figure using the units the question specifies.
These formats are still largely deterministic, but they grade more strictly than multiple choice. A blank checked by exact string match can mark a correct idea wrong if your phrasing differs from the answer key, so confirm the wording, units, and rounding match what your course expects before submitting.
Matching and ordering
Matching and ordering questions have structure rather than a single answer. For matching, FastSolve pairs every prompt with its correct partner and sets each dropdown or paired control. For ordering or sequencing, it works out the correct order and arranges the items to match — filled in place, exactly as you would set them by hand.
One caveat: drag-and-drop interactions — most often the Learnosity drag-and-drop type used by some publisher platforms — are a known unsupported format and are not auto-filled. Ordering questions built from dropdowns or numbered inputs work normally; only the drag-to-place variant is excluded.
Short answer and essay
Short-answer and essay questions are open-ended, so instead of picking an option FastSolve generates written text. For short answer it writes a concise, on-topic response sized for the box; for essays it drafts a longer, structured answer directly in the text field. Both use the same models — Claude and GPT-4o — that power the rest of the tool and can read any images or figures attached to the prompt.
Open-ended answers are the ones to review before submitting. There is no single correct string, so treat the draft as a strong starting point: check the facts, match the length and voice to your own, and edit anything your rubric specifically asks for. Used this way, FastSolve is a study assistant rather than a substitute for your own work.
Essay questions vs multiple choice
The honest difference between these two comes down to determinism. Multiple choice, multiple select, true/false, matching, and numeric questions have a definite correct answer, so FastSolve's job is simply to identify it — and on those formats it is fast and consistent. Essays and short-answer questions are open-ended: the model composes an answer rather than selecting one, so quality depends on how clearly the prompt is written and how much it relies on course-specific material.
In practice, you can lean on FastSolve heavily for objective question types and should treat its written drafts as a first pass. Always read an essay draft before submitting: verify the claims, make sure it answers the actual prompt, and rewrite it in your own voice so it reflects your understanding. FastSolve supports your studying — it is not a reason to skip reviewing your own graded work.
Coding and Python questions
Yes — FastSolve can work through coding questions, including Python. When a question renders a code editor such as Monaco, CodeMirror, or Ace (the editors used by platforms like LeetCode and HackerRank as well as many in-LMS coding exercises), FastSolve detects it as a coding question, reads the language the editor is set to, and writes a complete solution that matches that language and the function signature in the template. It then fills the generated code into the editor for you.
The pipeline is language-agnostic — it is not tuned specifically for Python. It simply matches whatever language the editor is configured for, so Python is one case among many; JavaScript, Java, C++, and others are handled the same way. Coding answers are routed to Claude for code quality. As with essays, run and review the solution against the problem's test cases and constraints before you submit.
Limitations and accuracy
A few honest limits. Drag-and-drop question types — specifically the Learnosity drag-and-drop format on some publisher platforms — are not supported and won't be auto-filled. Accuracy also varies with the subject and with how a question is presented: cleanly worded, self-contained questions solve most reliably, while questions that hinge on a specific lecture, a hard-to-read image, or ambiguous wording are more error-prone.
FastSolve reports 98% accuracy overall and reads question images, graphs, and diagrams through its vision pipeline — but no AI tool is right every time. Treat each answer as a draft to verify, especially on open-ended and image-heavy questions, and never submit work you haven't checked. Note too that Respondus LockDown Browser disables all extensions, so FastSolve cannot run inside it.
Frequently asked questions
Yes. Matching and fill-in-the-blank are both fully supported. For matching, FastSolve pairs each prompt with its correct partner and sets every dropdown or paired control; for fill-in-the-blank, it types the exact word, phrase, or value each blank expects directly into the field. Both are filled in place in about two seconds, the same as multiple choice.
Yes. When a question uses a code editor, FastSolve detects it, reads the language the editor is set to, and writes a matching solution — Python included. The pipeline is language-agnostic rather than Python-specific, so JavaScript, Java, C++, and other languages work the same way. Always run the generated code against the problem's test cases before submitting.
Objective formats with a single correct answer — multiple choice, multiple select, true/false, matching, and numeric input — are the most reliable, because the model only has to identify the right option. Open-ended short-answer and essay questions vary more, since the model is composing an answer rather than selecting one. FastSolve reports 98% accuracy overall.
It drafts them. For essay and short-answer questions, FastSolve generates a structured written response directly in the text field. Because there is no single correct answer, always review an essay draft before submitting — check the facts, match your rubric, and rewrite it in your own voice. Treat it as a strong first pass, not a finished submission.
Yes. Drag-and-drop question types — notably the Learnosity drag-and-drop format on some publisher platforms — are not supported and won't be auto-filled. Ordering questions that use dropdowns or numbered inputs are handled normally; only the drag-to-place variant is excluded. Accuracy also drops on questions that depend on a specific lecture or a hard-to-read image.
The same question-type support applies across every platform FastSolve integrates with: Canvas, Blackboard, Moodle, Brightspace, Schoology, ALEKS, Knewton Alta, and any platform that embeds Learnosity. FastSolve detects the platform and the question type automatically, so there is no per-course setup — open your quiz in a Chromium desktop browser and double-click a question.