Drag-and-drop versus point-and-click mouse interaction styles for children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research investigates children's use of two common mouse interaction styles, drag-and-drop and point-and-click, to determine whether the choice of interaction style impacts children's performance in interactive learning environments. The interaction styles were experimentally compared to determine if either method was superior to the other in terms of speed, error rate, or user preference, for children. The two interaction styles were also compared based on children's achievement and motivation, within a commercial software environment. Experiment I used an interactive learning environment as children played two versions of an educational puzzle-solving game, each version utilizing a different mouse interaction style; experiment II used a mouse-controlled software environment modeled after the educational game. The results were similar to previous results reported for adults: the point-and-click interaction style was faster; fewer errors were committed using it; and it was preferred over the drag-and-drop interaction style. Within the context of the puzzle-solving game, the children solved significantly fewer puzzles, and they were less motivated using the version that utilized a drag-and-drop interaction style as compared to the version that utilized a point-and-click interaction style. These results were also explored through the use of state-transition diagrams and GOMS models, both of which supported the experimental data gathered.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 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 it