Self-Talk with Superhero Zip: Supporting Children’s Socioemotional Learning with Conversational Agents
Why this work is in the frame
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Bibliographic record
Abstract
Socioemotional competencies are fundamental for children’s growth and success, and prior work shows that in some instances, technology can support children in acquiring these skills. Here, we examine whether children can learn to use a socioemotional strategy known as “self-talk” from a conversational agent (CA). To investigate this question, we designed and built “Self-Talk with Superhero Zip,” an interactive CA experience, and deployed it for one week in ten family homes to pairs of siblings between the ages of five and ten (N = 20). We found that children could recall and accurately describe the lessons taught by the intervention, and we saw indications of children applying self-talk in daily life. Targeting sibling pairs rather than individual users proved to be a design challenge in its own right, and families suggested design ideas for supporting this context, such as UI to manage conversational flow and reduce competition, and visuals and embodied activities to encourage focus. The dual-user context coupled with the audio modality prompted “preinput huddles” in which children conversed in whispers before responding to the system. We contribute evidence that CAs can support children in learning to use self-talk as well as design guidance for creating multi-user conversational interfaces.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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