A five-year follow-up study of the North Vancouver Jansky-de Hirsch screening battery
Bibliographic record
Abstract
Since its publication in 1972, the Jansky-de Hirsch Screening Index has become one of the most widely used early identification batteries in North America. Little research has been completed, however, on the predictive validity of this instrument for identifying at-risk children for reading and spelling difficulties. North Vancouver School District has used the Jansky-de Hirsch Screening Index for the past ten years. This battery consists of five subtests which take approximately 30 minutes to administer and mark. All North Vancouver students are individually assessed with this instrument in January of their kindergarten year. Children who score poorly on the Screening Index are given a diagnostic assessment and classroom intervention strategies are planned if necessary. Each school's learning assistance teacher is responsible for the screening and diagnostic assessments. This five-year follow-up study was initiated in 1980. The major purposes of this correlation study were to: 1) assess the predictive validity of the North Vancouver Jansky-de Hirsch screening program; and 2) to collect and analyze data on a number of predictor and criterion variables of interest to North Vancouver educators. A total of 304 subjects, 155 males and 149 females, took part in the study. These subjects were randomly selected from 756 Grade Five students who had attended a North Vancouver kindergarten in 1975-1976. Twenty-eight of the 31 North Vancouver elementary schools agreed to participate in the research. Thirty predictor and 43 criterion variables were used for the data analysis. The predictor instruments consisted of the Jansky-de Hirsch Screening Index and its follow-up test, the Diagnostic Battery. Age and, sex of student were included as predictor variables. The criterion instruments consisted of the Canadian Tests of Basic Skills (six subtests), the Test of Written Spelling and a student rating scale developed by the researcher. The criterion variables also included background data on the subjects' involvement with school and district special education services. The major statistical computations used in this study were t-test, correlation and multiple regression analyses. Means and standard deviations were calculated for most variables. The predictive validity of the Jansky-de Hirsch Screening Index was assessed by matching the low-risk and high-risk subjects on the Screening Index total score with the low-risk and high-risk subjects on the criterion test variables. The percentage of correctly and incorrectly classified subjects formed the predictive effectiveness or hit rate of this study. Data analysis of the variables revealed a number of interesting research findings. Although few sex differences were found on the kindergarten test measures, female subjects achieved significantly higher marks than male subjects on all the criterion test variables. Few significant age differences were observed at the kindergarten or Grade Five level. Pearson correlation coefficients were computed for most of the variables. The relationship between the predictor and criterion test measures tended to be low to moderate and the intercorrelations between the criterion test variables were generally moderate to high. The predictive effectiveness of the Screening Index total score ranged from 74.26% to 79.93% on the nine criterion test measures. The percentages of correctly predicted students for the CTBS Vocabulary and Comprehension subtests were 79.93% and 78.62%, respectively. The hit rate for the CTBS and TWS spelling measures was slightly lower with an average of 76.65%. These percentages represented correct reading and spelling classification placement for almost four out of five students in this study. The multiple regression analyses of the predictor and criterion test variables and sex of student revealed little difference between the amount of variance for the raw score and converted score kindergarten subtests. Letter Naming contributed the highest proportion of variance to the CTBS vocabulary, comprehension and spelling scores. The rank order of the predictor variables changed considerably on many of the regression analyses and the highest computed R square was 0.377 (CTBS Comprehension).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".