Language sample analysis is really critical when initially evaluating and even monitoring progress, but they can be tedious and slow! If you read my previous post, you are going to love this update (12/2021) with even more helpful tips!!

I’ve got info on how to quickly get language samples through using hacks on Microsoft Word, Google docs, plus my Language Analysis FREEBIE and MLU/PGU Normative charts! Whew! So much good info!

Where are you getting your language sample?

First things first, best practices for language samples (especially for school-aged kids) are narrative or expository language samples, not conversation. After the preschool years, conversation language is typically less advanced that narratives or expository. So make sure you’re getting your students’ best efforts.

Microsoft Word for Language Sample Analysis

In the past, I have done my language sample analysis using Microsoft Word. Yes, you read that correctly! You can do so much using tools you likely already have! And it’s fast! Check out the steps below to complete one of your own:

Step One: Type in 50 utterances. Put each utterance on their own line. I like to use numbered bullets to keep track of how many I have. See an example below:

Make sure to break apart all morphemes with a space between them as shown below:

Step Two: Calculate total words. To do this, get rid of the numbered bullets first!! One you have a document with just the child’s utterances, go to Tools —> Word Count.

Step Three: Divide the number next to Words (113 in this example) by 50 (the total number of utterances). This calculation gives you an MLU of 2.26. Easy, right?!

Step Four: Fill out a Language Sample Analysis Checklist to analyze grammar, vocabulary, pragmatics, narratives, and more! I have a free one in my Teachers Pay Teachers store. Click here to check it out!

Google Docs for Language Sample Analysis

If you’re more of a Google docs fan, you can do a pretty similar process. I can never remember where to find the word count, but if click on Help, then type in “Word count,” it will pop up.

Are you ready to make this process even easier???

Google docs has a speech-to-text option called “Voice Typing.” (Again, if I can’t find it in the menus, I just click “Help” and search for “Voice Typing.”) It might ask you for permission to use the microphone. Then a microphone icon will appear. When you are ready to use the feature, click the microphone and it will turn red. That means that it’s recording.

Here’s the amazing thing: a recent study showed that used Google’s voice typing was actually MORE accurate than seasoned professionals doing transcription when recording narrative samples from 7-11 year old students. The study actually used a pre-recorded sample and they recommend that you let Google do its job, then review the sample once after, just to make sure that you agree with Google. Speech-to-text has come a long way!

So you can let Google transcribe it, then divide into utterances and morphemes to run your word count and figure out your MLU.

MLU – What Does It All Mean?

So you have an MLU calculation, but what does that even mean?

MLU is not necessarily a good benchmark to form goals by, but it does help when making diagnostic decisions.

The most updated information on MLU numbers I could find was in this article. If you look at Table 4, they have a great chart outlining MLU in words and in morphemes among kids aged 2;6-8;11 in 6 month increments with standard deviations, in both SLI groups (labelled “Affected”) and typical groups (labelled “Unaffected”).

For kids older than that, MLU hasn’t really shown to be a good measure, but the sentence structures mentioned above in my checklist might be a better place to start!

One More Language Sample Measure: Percentage Grammatical Utterances (PGU)

A more recent entry on the Language Sample Analysis front is Percentage of Grammatical Utterances, or PGU. MLU tells us if a child’s utterances are generally as long as we would expect them to be. But once children are putting words together, we really need to figure out why they aren’t as long or complicated as we want them to be. PGU gives you a measure of grammaticality and can help you zero in on actual goals for treatment.

Here’s how you figure out PGU (from this recent study):

1. Make sure your language sample is divided into utterances. Include only intelligible, complete, and spontaneous C-units (independent clause with dependent clauses, as well as nonclausal statements that were a complete thought)
2. Count how many contain at least one grammatical error (You can look at the article for all their specific errors, but think verb tenses, pronouns, morphemes like plural -s, etc.)
3. PGU = (Total utterances – Ungrammatical utterances)/(Total utterances) * 100%

I took the information from the article and put it into this lovely chart if you want to see what kind of percentages you should be expecting from typical and atypical language development:

Hope that’s helpful and it saves you some time! There are definitely more in depth ways of doing this, but let’s be honest, we are working under some serious time constraints!

{thanks for reading}

References

Guo, L., Eisenberg, S., Schneider, P., & Spencer, L. Percent grammatical utterances between 4 and 9 years of age for the Edmonton Narrative Norms Instrument: Reference data and psychometric properties. American Journal of Speech–Language Pathology. https://doi.org/10.1044/2019_AJSLP-18-0228/.

Fox, C. B., Israelsen-Augenstein, M., Jones, S., & Gillam, S. L. (2021). An evaluation of expedited transcription methods for school-age children’s narrative language: Automatic speech recognition and real-time transcription. Journal of Speech, Language, and Hearing Research https://doi.org/10.1044/2021_jslhr-21-00096

Rice, M., Smolik. F., Perpich, D., Thompson, T., Rytting, N., & Blossom, M. (2010). Mean length of utterance levels in 6-month intervals for children 3 to 9 Years with and without language impairments. Journal of Speech, Language, and Hearing Research https://doi.org/10.1044/1092-4388(2009/08-0183)