ConductScienceConductScience

Conversation Turn Analyzer

Paste a child-partner dialogue transcript with speaker tags (e.g. C: and P:) and the analyzer returns turns per speaker, average turn length, total speaker-to-speaker turn switches, the child topic-maintenance ratio, a four-tier topic-maintenance classification (poor, emerging, adequate, strong), and a three-tier turn-balance classification (partner-dominant, balanced, child-dominant) in under five minutes. Tier thresholds are derived from Fey (1986), Brinton & Fujiki (1989), Mentis & Prutting (1991), and Timler (2008). Built for school-based SLPs, clinic SLPs, autism-assessment teams, graduate SLP students, and paediatric language researchers screening pragmatic-discourse in children with DLD, ASD, ADHD, and TBI.

Turn-TakingTopic MaintenanceFey 1986Brinton & Fujiki 1989Mentis & Prutting 1991Client-Side
Tool details, related tools, and citation

Paste a child-partner dialogue transcript

One turn per line. Start each line with a speaker tag (e.g. C: for child, P: for partner) followed by the utterance. Append [on] or [off] at the end of each child turn to mark topic maintenance.

Paste a dialogue transcript above to compute turn-taking metrics, topic maintenance, and a pragmatic-discourse classification.

Get the full analysis

Unlock normative comparison and error analysis

This free tool covers the basic case. ConductSpeech adds normative comparison, error categorisation, and a parent-ready report.

Get the full analysis with ConductSpeech
  • Initial screening of a new school-based SLP caseload for pragmatic-discourse concerns — collect one 20-turn dialogue per child and flag children with topic maintenance below 70 %
  • IEP goal writing — use the topic-maintenance ratio and the turn-balance tier to draft a SMART pragmatic-discourse goal that the classroom teacher can report on
  • Weekly progress monitoring during active social-communication intervention — collect a fresh dialogue, re-score, and compare to baseline
  • Autism-assessment team screening — collect a conversational sample as part of a multidisciplinary autism evaluation and report the topic-maintenance ratio alongside the other pragmatic measures
  • ADHD caseload triage — screen children referred for "interrupts a lot" and "goes off on tangents" with a 20-turn dialogue and report the turn-balance and topic-maintenance tiers
  • Traumatic brain injury (TBI) re-evaluation — track conversational-discourse recovery across sessions after paediatric TBI
  • Graduate SLP training — teach pragmatic-discourse analysis with a concrete, reproducible rubric before moving to the full Brinton & Fujiki (1989) or Mentis & Prutting (1991) coding schemes
  • Discharge / dismissal screening — collect two fresh dialogues at the end of an intervention block and confirm that topic maintenance and turn balance have moved into the adequate or strong tier

Don't use for

  • As a stand-alone diagnostic instrument for pragmatic-language disorder, autism spectrum disorder, or social (pragmatic) communication disorder — always pair with a standardised pragmatic measure (CCC-2, CASL-2 Pragmatic Judgment) and the full case history
  • For samples shorter than 20 turns — the topic-maintenance ratio is unstable with fewer than 10 child turns
  • For monologue samples (narrative retells, fiction generation, expository samples) — the analyzer assumes two-party dialogue and the topic-maintenance ratio is not meaningful for monologue
  • For dual-language learners in the second language without considering language exposure — a partner-dominant or poor-topic pattern may reflect L2 attrition rather than a pragmatic deficit
  • For children producing single-word or two-word utterances — turn-taking and topic maintenance assume the child is producing connected discourse
  • As the only pragmatic measure in a formal evaluation report — supplement with a published standardised pragmatic assessment
  • To re-score the same transcript after intervention — collect a fresh sample at every progress-monitoring point to avoid overstating the gain

Why Turn-Taking and Topic Maintenance Matter

Conversational turn-taking and topic maintenance are the two most direct measures of a child's ability to participate in connected, reciprocal discourse with a partner. A child who cannot yield a turn when the partner is speaking, or who cannot stay on topic across three or four exchanges, cannot participate in classroom discussion, peer play, or a structured interview — even when every other language-sample metric is intact. For this reason, turn-taking and topic maintenance are routinely the first pragmatic-discourse measures on the caseload-triage list for school-based SLPs assessing children with developmental language disorder (DLD), autism spectrum disorder (ASD), attention-deficit / hyperactivity disorder (ADHD), and traumatic brain injury (TBI).

Turn-taking and topic maintenance are the pragmatic dimensions the IEP team cares about. Classroom teachers, special-education teachers, and parents describe pragmatic-discourse deficits in the vocabulary of turn-taking ("he interrupts all the time") and topic maintenance ("she goes off on tangents and I can't follow her"). The IEP meeting is held in this vocabulary, and the IEP goal that results is written in this vocabulary. A pragmatic-discourse measure that reports turn-taking and topic-maintenance numbers directly is the measure the IEP team can act on.
The measures are fast to collect and fast to score. A 20-turn child-partner dialogue can be collected in 5-8 minutes during a session and scored in 2-3 minutes with this analyzer. That is fast enough to use on every child on the caseload at triage, fast enough to use as a weekly progress-monitoring metric during active social-communication intervention, and fast enough to use at discharge / dismissal screening. Contrast this with the published standardised pragmatic tests (CCC-2, CELF-5 Pragmatics Profile, CASL-2 Pragmatic Judgment), which each take 20-40 minutes to administer and require a licensed test kit — those are the right tools for a formal evaluation, but they are too slow for weekly progress monitoring.

How to Collect a Conversational Sample

A good conversational sample has three properties: (1) the topic is rich enough that the child has something to say, (2) the partner asks open-ended rather than closed-ended questions, and (3) the partner waits 3-5 seconds after each child turn to give the child a chance to initiate. The combination produces a balanced dialogue in which the child has a genuine opportunity to maintain topic, yield turns, and repair breakdowns.

Recommended prompts. Use open-ended prompts keyed to the child's interests: "Tell me about your favourite thing to do at recess" for a school-age child, "What did you do at the park yesterday?" for a preschooler, or "Tell me about your favourite game" for an older child. Avoid yes / no questions, which pull the sample toward a partner-dominant pattern, and avoid topic shifts by the adult, which confound the child topic-maintenance count.
Transcription. Audio-record the sample and transcribe verbatim. Use "C:" for the child and "P:" for the partner (or other recognised tags — see the FAQ). After transcription, go back through the child turns and mark each one as "[on]" or "[off]" for topic maintenance, using the previous turn as the anchor. The Mentis & Prutting (1991) topic-maintenance definition is: the child turn is on-topic if it maintains, shades, or extends the topic set by the previous turn; it is off-topic if it introduces a new topic, re-introduces a previous topic, or does not relate to any prior topic.

Interpreting the Metrics

Average turn length (in words). Typically-developing school-age children produce 4-10 word turns in structured dialogue. Shorter average turns are common in DLD and in dual-language learners in L2; longer average turns are common in ADHD and pragmatic-language disorder (rapid, tangential turns). Compare child average turn length to partner average turn length — a large gap in either direction is clinically meaningful.
Turn switches. In a perfectly alternating dialogue, turn switches = total turns − 1. Fewer switches than that indicate consecutive same-speaker turns, which are common when one speaker produces multiple short utterances in a row. Turn switches are less diagnostic than topic maintenance and turn balance but are useful as a reproducibility check.
Child topic maintenance. The most diagnostic metric in the analyzer. A ratio at or below 50 % is a conservative clinical red flag — fewer than half of child turns stay on topic. A ratio of 51-70 % is emerging — the child can stay on topic some of the time but not reliably. A ratio of 71-89 % is adequate — the child can carry a structured dialogue across several turns. A ratio of 90 % or higher is strong — topic maintenance is a relative strength. The tier classification is an interpretation framework, not a cutoff — always pair the ratio with the full case history and clinical judgement.
Turn balance. A child share between 40 % and 60 % is balanced — the clinical target. Below 40 % is partner-dominant — the adult is carrying the conversation, which is common in DLD and ASD. Above 60 % is child-dominant — the child monopolises the floor and does not yield turns, which is common in ADHD and pragmatic-language disorder.

IEP Goal Examples from Analyzer Output

The analyzer is designed to feed directly into the IEP goal-writing process. Here are three example IEP goals keyed to the three most common patterns the analyzer identifies.

Pattern 1: Poor topic maintenance (ratio ≤\leq 50 %). "Given a 15-turn child-partner dialogue on a preferred topic with open-ended prompts, [child] will maintain topic across at least 4 consecutive turns on 4 of 5 progress-monitoring probes across 8 weeks, as measured by the ConductScience Conversation Turn Analyzer." Pair with explicit topic-maintenance instruction using scripted dialogue, visual topic anchors, and partner-implemented cuing (Timler 2008).
Pattern 2: Partner-dominant balance (child share < 40 %). "Given a 20-turn child-partner dialogue with 3-5 second wait-time and comment-based stimuli, [child] will produce at least 40 % of total turns on 4 of 5 progress-monitoring probes across 8 weeks, as measured by the ConductScience Conversation Turn Analyzer." Pair with conversational-assertiveness intervention using comment-based stimuli, wait-time scaffolds, and modelled initiation (Fey 1986).
Pattern 3: Child-dominant balance (child share > 60 %). "Given a 20-turn child-partner dialogue on a non-preferred topic, [child] will yield the conversational floor after each turn (producing between 40 % and 60 % of total turns) on 4 of 5 progress-monitoring probes across 8 weeks, as measured by the ConductScience Conversation Turn Analyzer." Pair with turn-yielding intervention using visual turn-tokens, stop-signals, and partner-implemented cues (Brinton & Fujiki 1989).

Frequently Asked Questions

Next Steps

Narrative Scoring Scheme (NSS) Calculator — score a narrative sample on the 0-5 Heilmann 2010 rubric for each macrostructure dimension

Read guide →

Story Grammar Scorer — tick the six Stein & Glenn (1979) story grammar elements and get a completeness tier in under five minutes

Read guide →

MLU Calculator — compute baseline mean length of utterance from the same dialogue sample

Read guide →

Lexical Diversity Calculator — compute NDW, TTR, and tokens from the dialogue sample

Read guide →

IPSyn Calculator — compute Index of Productive Syntax for a full microstructure picture

Read guide →

DSS Calculator — compute Developmental Sentence Score for a second microstructure reference

Read guide →

IEP Goal Generator — write SMART pragmatic-discourse IEP goals from the analyzer output

Read guide →

Therapy Frequency Recommender — draft evidence-based service minutes for a child with a pragmatic-discourse goal

Read guide →

Language Sample Worksheet — print a fillable worksheet to transcribe a fresh dialogue sample

Read guide →

Need Help?

Get a quote on equipment or talk to our team.

Request quote →