Word Search Generator

Everyone looks at the words. The words are the point, after all: someone chose them, someone will hunt for them, and a teacher may grade the hunt. But most of the letters in a word search were chosen by nobody. They are filler, and the filler is where a word search quietly succeeds or fails.

Filler can hand the answer away. It can hide a second copy of a word, so a solver circles the wrong one and is told they are wrong. It can spell something rude in a corner of a sheet meant for nine-year-olds. And in a language with accents, it can make every accented word glow on the page like a lit window. A fair puzzle is mostly a matter of controlling the letters nobody thinks about.

A puzzle from a want-ad digest

The usual story puts the first word search in Norman, Oklahoma. According to the Wikipedia biography of Norman Gibat, he owned a printing company there from 1968 to 1971 that published a small want-ad digest, given away free in local stores. His first word search ran on March 1, 1968. The hidden words were the names of Oklahoma cities and towns, and his rules already allowed words to run up, down, diagonally, forward or backward. Players circled what they found.

The second puzzle used the streets of Norman. His aim, the article says, was to make waiting in line at the grocery store a little more pleasant.

The same article says teachers soon asked Gibat for copies to use in class, and that one teacher mailed them to friends and colleagues in other cities. The puzzle outlived the digest. It was never patented, which the article gives as one reason the form spread so freely and never settled on a single name.

That account has a rival. EcuRed, the Cuban online encyclopedia, credits the Madrid puzzle maker Pedro Ocón de Oro with the sopa de letras, the Spanish word search, and dates it to 1952, sixteen years before Gibat. EcuRed also says he invented 125 kinds of pastime over almost forty years and later directed a magazine named after the sopa de letras, founded in 1976. Neither source shows the 1952 puzzle itself, and the Gibat article admits it is not entirely certain his was the first. The fair summary is that two claims exist, one dated to the day and described in detail, one older and thinly documented, and nobody has settled it in print that these sources show.

What the research does and does not say

Gibat’s teachers were onto something that classrooms still believe. Tira Nur Fitria’s 2023 systematic review pooled 25 papers that tested word searches against other ways of teaching English vocabulary. Every one used an experimental design with a control class and an experimental class, and the review reports a significant difference between pre-test and post-test means in the classes that used the puzzles. A second review by the same author, limited to studies of Indonesian students published between 2015 and 2022, kept 12 of 30 articles and reached the same verdict.

Those are encouraging results, and they deserve a careful reading. Both reviews come from one author. The second is restricted to one country. The studies compare a class that got something new with a class that did not, so some of the gain may come from novelty, attention and extra time on the word list rather than from the act of scanning a grid. The first review itself says further research is needed.

Claims that go further, that puzzles sharpen the mind in general, rest on weaker ground. In a trial reported by Dustin Souders and colleagues, sixty older adults spent a month either on gamified cognitive training or, as the comparison group, on word and number puzzle games. The authors found little evidence that the training transferred to unrelated tasks. A word search is good practice at finding words in a word search. Whether it builds anything broader is not something these studies show.

What does a solver actually do? Tanya Beelders tracked the eyes of people solving word searches in three languages of differing fluency. Their strategy depended partly on fluency, ranging from a rigid, structured sweep to apparently random searching for the target. Most gaze measures were not significantly affected by word length or language fluency, although fixations lasted longer on shorter words. Short words are not automatically easy.

What makes one hard, and what makes one unfair

Difficulty in a word search comes mostly from three dials. The first is direction. A puzzle that only runs words right and down asks the eye to read the way it already reads; one that allows all eight directions, including the four backward ones, makes every word a pattern to recognise in reverse. The second is overlap: when words cross and share letters, a found word no longer clears its cells, and every letter must be considered more than once. The third is the filler, which supplies the decoys.

Decoys are where fairness enters. A good decoy is a letter that belongs to the puzzle’s own alphabet, so that the start of a word looks like many other starts. A bad decoy is a letter set that differs from the words. Jay Kunz, writing for teachers of German in 2002, noticed that one popular puzzle website of the time did not accept the sharp s as a letter and filled its grids without any umlauted vowels. A word containing an umlaut then stood out at a glance. The fix is simple to state: draw filler letters from the words themselves, in proportion to how often each letter appears.

The other unfairness is the accidental twin. Random filler can spell a listed word a second time, or two crossing words can line up to spell a third. The solver who circles the twin has found the word and is still marked wrong. The only remedy is to read the finished grid exactly as a solver would, in all eight directions, and count. Every listed word must appear exactly once. A palindrome such as LEVEL reads the same both ways along the same cells, so it counts once, not twice; a pair such as STOP and POTS cannot both be fair, because each would hide inside the other.

Here is a worked example you can reproduce in the generator on this page. Take fourteen flowers, from Sunflower to Dahlia, in a 13 by 13 grid with seed 1968, Medium directions and crossings allowed. The words hold 84 letters. They occupy 82 cells, because two cells are shared where words cross, which leaves 87 filler cells. The letter L makes up 11 of the 84 word letters, so each filler cell draws an L about 13 percent of the time, exactly as often as the words would suggest. The tool then reads the full grid and confirms each flower appears once.

The same example shows why a filter matters. With the rude word filter turned off, 46 of 200 seeds of this innocent flower list put one of the blocked words through a filler cell. That is nearly one sheet in four. With the filter on, the count was zero, because any filler cell on such a run is drawn again until the run is gone.

The hidden message, and other honest tricks

The best-loved variation turns the filler from noise into a reward. Instead of random letters, the cells no word uses, read row by row, spell a message. In the flower example, the 23 letters of BLOOM WHERE YOU ARE PLANTED fill the first 23 of the 87 free cells, and the rest stay ordinary filler. Kunz’s survey mentions programs that already offered hidden-message puzzles in 2002, and a physiology teaching paper by Bailey, Hsu and DiCarlo used hidden messages alongside word searches as tools for active learning.

The message has a cost that is worth knowing. Its letters are fixed, so the filler can no longer be redrawn there to break up an accidental twin or a rude run. A generator has to plan for that and start again when the message itself causes the problem. It also needs enough free cells: a long message in a crowded grid simply does not fit, and the honest response is to say how many cells are missing rather than squeeze.

Letters themselves need care once you leave plain English. A letter such as an accented e can be stored as one code point or as a base letter followed by a combining accent. MDN’s documentation of string normalization shows two spellings of the same name that look identical and still compare as different until both are normalized. The standard way to split text into what a reader sees as letters is a grapheme segmenter, which MDN describes as splitting text at user-perceived character boundaries. One visible letter, one cell.

A few practical tips follow from all of this. Pick a theme and keep the list to words of four letters or more; very short words turn up by chance everywhere. Do not list a word that sits inside another, such as IRIS beside IRISES. Match the directions to the reader, right and down for early readers, all eight for adults. Bailey and colleagues went a step further and encouraged students to make puzzles of their own.

For print, make the letters large and the answer key unmistakable. Large print is one of the aids ADA.gov lists for communicating with people who have vision loss. The W3C’s guidance on color makes the companion point: color should never be the only way information is shown, so a found word deserves a loop and a strike-through, not just a tint. Keep the answer key on a separate page, so the sheet can be photocopied without giving the game away.

What a generator cannot promise

No filter is complete. The blocklist in this generator is short, written in English for this tool, and it will not catch a rude word in another language or a new coinage.

A seeded generator can reproduce any puzzle from its seed, from a random number generator whose author says it should have a period of 2 to the 32, exactly, but a seed is only a recipe: change the version of the program and the same seed may give a different grid. And no generator can tell you whether the puzzle teaches anything. The research above suggests it can help with vocabulary when a teacher builds it around the words that matter. The filler, at least, can be made honest.