TOEFL Speaking scoring series · Language Use
LingoLeap Research Team · September 2026
Quick answer
Across 54,247 Take an Interview answers in the reported 2–4.5 AI bands, the combined grammar/vocabulary score and syntactic complexity are higher in higher bands: grammar/vocabulary runs about 2→4.4 (0–5) and the complex-sentence share about 26.1%→43.3%. But the share of advanced (B2+) vocabulary stays low (4.1%–6.6%) and barely moves across bands. The between-band difference shows up more in sentence control than in rare words. These are associations, not causes.
This is the Language Use chapter of the TOEFL Speaking scoring series. Many learners read “improve your language” as “memorise harder words.” This chapter asks, on real answer data, what actually differs between bands — the difficulty of the vocabulary, or the control of the sentences.
Language Use is often split into vocabulary, grammar, and sentence structure. We wanted to know which of these differs most across AI score bands — how many rare words an answer uses, or its grammatical control and sentence structure. Up front: everything below is a descriptive association across bands, not a causal claim.
Three questions: (1) does the combined grammar/vocabulary score differ across bands? (2) does the share of advanced vocabulary? (3) does the share of complex sentences?
Data comes from real, voluntary TOEFL 2026 Take an Interview answers, anonymised and aggregated by each answer’s AI score band. Vocabulary is graded by CEFR level (“advanced” = B2/C1/C2); syntactic complexity is derived from a sentence-type distribution (simple / compound / complex / compound-complex). These are AI signals mapped to the public dimension names, not ETS scoring. Aggregates only, no transcripts. Bands below 2.0 are excluded as short-answer artefacts.
The combined grammar/vocabulary score (0–5) is about 2 in the 2 band and 4.4 in the 4.5 band — the language signal with the clearest between-band difference here.
| Band | Attempts | Grammar/vocab | Sentence variety |
|---|---|---|---|
| 2 | 434 | 2 | 1.8 |
| 2.5 | 6,779 | 2.4 | 1.9 |
| 3 | 14,187 | 2.9 | 2 |
| 3.5 | 24,796 | 3.2 | 2.1 |
| 4 | 6,912 | 4 | 2.4 |
| 4.5 | 1,139 | 4.4 | 2.8 |
grammar_vocabulary is a single number the LLM assigns from the answer text, compressing whether grammar is correct and word choice apt; because it belongs to the same scoring, its between-band gap partly reflects internal consistency of the rubric, not proof that better grammar causes a higher score. Sentence variety rises modestly across bands too, but by less.
The combined share of complex and compound-complex sentences rises from about 26.1% into the low-40s%, easing slightly at the top band — the association on the sentence-structure side.
| Band | Attempts | Complex-sentence share |
|---|---|---|
| 2 | 434 | 26.1% |
| 2.5 | 6,779 | 32.0% |
| 3 | 14,187 | 36.1% |
| 3.5 | 24,796 | 40.6% |
| 4 | 6,912 | 44.8% |
| 4.5 | 1,139 | 43.3% |
A higher complex-sentence share may reflect an ability to use clauses and connectors, which is entangled with fluency, length, and overall proficiency and cannot be separated here. The slight easing at the top band is a reminder that piling on complex sentences does not necessarily track with a higher band — complexity you cannot control cleanly may not help.
The share of advanced (B2+) vocabulary is only 4.1%–6.6% in every band, with no clear rise across bands — the most counter-intuitive point here.
| Band | Attempts | Advanced-vocab share |
|---|---|---|
| 2 | 434 | 6.6% |
| 2.5 | 6,779 | 4.3% |
| 3 | 14,187 | 4.1% |
| 3.5 | 24,796 | 4.4% |
| 4 | 6,912 | 5.0% |
| 4.5 | 1,139 | 6.1% |
Spoken answers lean on common words, so a low advanced share is unsurprising; what is notable is the absence of a clear difference between low and high bands. That runs against the intuition that memorising hard words raises a score. One reading: speaking rewards real-time organisation and precise meaning more than rare vocabulary. CEFR auto-grading is also imperfect, and share alone cannot distinguish “a few advanced words used well” from “many used awkwardly.”
Of the three signals, grammar/vocabulary control and sentence structure differ clearly across bands, while the rarity of the vocabulary barely does. Taken together, “sophistication” in Language Use here looks more like saying complex things correctly with ordinary words than reaching for exotic ones.
That points at a practice direction — though still as correlation, not cause: rather than drilling word lists, practise clauses, connectors, and precise word choice you can control. The content side is in the series pillar; the sound side is in the Delivery chapter.
This observational data cannot prescribe one strategy, but it does not support ‘memorise hard words to score higher’. More worth practising: using common words precisely and controlling clauses and connectors.
LingoLeap Research Team. (2026). TOEFL Speaking Language Use: Vocabulary vs Sentence Control. LingoLeap Research, version 1.0.
https://lingoleap.ai/research/toefl-speaking-language-use
Sample: 55,614 answer records across 14,884 sessions; this chapter analyses 54,247 answers in bands 2.0–4.5.
In this data, not obviously. The share of advanced (B2+) words in an answer stays low — roughly 4–7% — and is about the same in low and high score bands. What differs more across bands is the combined grammar/vocabulary rating and the use of complex sentences. This is an association, not a rule: it suggests control and structure travel with the bands more than rare words do.
Language Use is one of the three public scoring dimensions, alongside Delivery and Topic Development. It covers vocabulary range and precision, grammatical control, and sentence variety. Here it is measured by LingoLeap AI signals mapped to that dimension — not ETS scoring.
Higher bands do have a higher share of complex and compound-complex sentences in this dataset, rising from about 26% to the low-40s% before levelling off. But this is a correlation; complexity may travel with fluency, length, and overall proficiency. Complex sentences you cannot control cleanly are unlikely to help.
No. These are LingoLeap AI scores mapped to the public dimension names, from real practice answers — not official ETS results, and not a reproduction of ETS's rubric. They describe patterns useful for practice.