Engaging or Distracting: Children's Tablet Computer Use in Education
Bibliographic record
Abstract
Communications studies and psychology offer analytical and methodological tools that when combined have the potential to bring novel perspectives on human interaction with technologies.In this study of children using simple and complex mathematics applications on tablet computers, cognitive load theory is used to answer the question: how successful are tablet computer educational applications at directing children's attention towards intrinsic and germane content?An eye tracker collected gaze data and cognitive tasks were performed to assess memory and attention.The results show that simple applications are able to direct a child's attention to intrinsic and germane content, regardless of the child's cognitive ability.Children assessed as high executive functioning found the germane content of the complex applications helpful whereas children assessed as lower executive functioning did not take advantage of the germane content.Claims that the cognitive structure of the individual is intimately linked to the forms or systems of communication used were partially supported.The research showed that tablet computers and their applications offer a learning experience that appears to be inherently highly interactive-thereby introducing challenges to the cognitive load of children as users.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".