Aligning Professional Development With Service Coordinator Knowledge and Skills
Bibliographic record
Abstract
Service coordinators under Part C of the Individuals With Disabilities Education Act (IDEA, 2004) help families navigate the early intervention (EI) system and ensure regular communication among team members so services are aligned with family priorities and recommended EI practices. To meet the demands of service coordination, personnel entering the EI field who will serve as service coordinators must receive high-quality professional development to orient them to their unique roles and responsibilities. The purpose of this program evaluation was to examine the effectiveness of one state's service coordination training program and its alignment with the Knowledge and Skills for Service Coordinators (KSSC), a resource document in the Division for Early Childhood and IDEA Infant Toddler Coordinators Association (DEC & ITCA) Joint Position Statement: Service Coordination in Early Intervention (2020). Survey results suggested that the training program was associated with increased knowledge and skills for service coordinator participants in many of the KSSC areas. Participants also reported using what they learned in their work with families. The rubric used to evaluate this training program could be a resource for state-level professional development providers to evaluate alignment of current and future training for service coordinators with the KSSC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".