Dynamic assessment, more than a diagnostic tool? Uses for goals, teaching moments, and procedural issues during intervention of speech sound disorder
Bibliographic record
Abstract
Dynamic assessment is typically used for diagnostic and baseline purposes; however, the current study explored expanding the use of dynamic assessment as a curriculum-based measure to additionally capture teaching moments and observe intervention elements during treatment of speech sound disorder (NCT06075303). Teaching moments occur when an SLT presents an antecedent, the child produces a behaviour, and the SLT responds with a consequence related to accuracy; yet, little is known about the characteristics of these elements that are the most essential for improving treatment outcomes. To address this gap, we used the Glaspey Dynamic Assessment of Phonology's scoring system to establish the goal, code teaching moments, describe procedural issues, and evaluate children's skill development. The participants included two English-speaking boys, ages three and six, with speech sound disorder. A modified cycles approach was administered by an SLT and a student clinician with two blocks of targets (minimally and moderately adaptable). Results indicated that coding with dynamic assessment was successfully used for tracking changes within the teaching moments and provided a more complete perspective of treatment efficacy when combined with outcome measures, yet more research is needed to establish goals with dynamic assessment. Both children demonstrated progress in a short period of time, though Participant 1 made more significant gains, which may be attributed to many elements including treatment intensity, target selection, clinician variables, or client variables. Overall, this preliminary research supports that dynamic assessment may lead to dynamic intervention, thus bridging assessment and treatment practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".