A Systematic Review of the Probes Method in Research with Children and Families
Why this work is in the frame
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Bibliographic record
Abstract
Since their introduction, there has been wide discussion about how probes are used in human computer interaction (HCI) research. This variation can be problematic for researchers and designers who plan on using probes in the child computer interaction space, as it can be difficult to know which approach is best suited to address their design situation. In this review, we surveyed the ways that HCI researchers have used probes in studies with children and families. Based on 25 articles, we analysed the methodological decisions that researchers have taken in their empirical studies, relating to: a.) the goals for using the probes, b.) the probe itself, c.) participant involvement, and d.) the data and data use. Based on our methodological findings, we highlight four key tensions—including probes as sources of information versus creative input–and consider questions that can guide decision making for developing probes studies with children and families.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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