Scrolling and hyperlinks: The effects of two prevalent digital features on children's digital reading comprehension
Bibliographic record
Abstract
Background This study examined how children's ability to understand what they read on screens is impacted by two specific digital features: hovering hyperlinks and scrolling. Methods The participants were 75 English‐speaking children ( M = 9.90 years, SD = 0.90 years) in Grades 3 to 5 who participated in an online research study. Using a within‐participants design, children read standardised passages from the Gates–MacGinitie Reading Tests (MacGinitie et al., 2000) and answered multiple‐choice comprehension questions. In one condition, passages were presented without digital features referred to as the clicking condition; in another, children had to scroll to navigate through the passages, in a third, there were hyperlinks that provided a word definition when a participant hovered their cursor over a blue and underlined word, and a final condition included both scrolling and hyperlinks. Results As expected, there was a significant main effect of grade on children's ability to understand what they read, with better performance for children in Grade 5 than 3. Critically, there was a significant main effect of condition on children's performance on the reading comprehension questions, with higher scores for the condition with no digital features compared with the conditions with hovering hyperlinks and both scrolling and hovering hyperlinks. Performance was similar between the clicking and scrolling conditions. There was no significant interaction between grade and condition, showing consistency in effects across the upper elementary school years. Conclusions These findings could inform the optimal design of digital texts by identifying digital features that do and do not interfere with reading comprehension, with hyperlinks providing word level information interfering and scrolling having no negative impacts.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".