Evaluating the Benefits of Displaying Word Prediction Lists on a Personal Digital Assistant at the Keyboard Level
Why this work is in the frame
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Bibliographic record
Abstract
Visual-cognitive loads influence the effectiveness of word prediction technology. Adjusting parameters of word prediction programs can lessen visual-cognitive loads. This study evaluated the benefits of WordQ word prediction software for users' performance when the prediction window was moved to a personal digital assistant (PDA) device placed at the keyboard level. Twenty-one young people aged 11-14 (11 new users and 10 experienced users) participated in the study. The Canadian Occupational Performance Measure was used to measure users' self-ratings of performance and satisfaction. Results of two-tailed paired t-tests reveal significantly (p < .05) higher performance and satisfaction ratings when the word prediction list was displayed on the PDA. Users reported that it was easier to look for the words at the keyboard level and to select words directly from the PDA. Visual comparisons of the users' typing speed and accuracy show that experienced users had faster typing rates and new users appeared to have better accuracy when they typed with WordQon the PDA display. Further studies with larger samples of individuals with different diagnoses and ages are required to confirm the benefit of using a PDA display in enhancing typing rate and accuracy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 it