ACM CSCW
Published in

ACM CSCW

What did we aim to do?

We wanted to understand how we might design technology-enabled interventions that could address two assumptions that underpin these challenges of cost and out-of-class facilitation: First is the expectation that learning needs to rely on didactic in-person workshops, with the implication that children have to then ‘apply’ the skills when needed without further support. Second is the assumption that such programs need to be ‘adult-led’, with the children being taught by a trained adult (whether that is a parent or a teacher in school).

How did we do this?

We started by interviewing parents and children in a particular low income community to understand how they currently deal with emotional moments. What are the strategies that seems to be helpful and what seems not to work? What are their beliefs about emotions and what support do they offer each other if a strong emotion arises?

What did we build?

The interactive capabilities of the toy and theory of change for the intervention

So … does it work?

We first deployed these prototypes with 14 families for 3 to 4 days (together with a photo diary), interviewing the children afterwards. Our findings indicate that even in the limited amount of time children had the toy at their homes, all children appeared to form a strong emotional connection which in turn drove consistent daily engagement. Moreover, the children’s interview responses as well as the photo data suggested that playing with the `creature’ not only had a soothing effect, but that the children also explicitly engaged with it to calm down.

What next?

While we are already really excited about the results so far, there is still plenty of work to do to develop this proof-of-concept into a full intervention: This goes beyond the possible usefulness of our little `lost alien’; more importantly, we see this data as providing a preliminary validation for the situated interventions model more broadly.

Number of GoogleScholar results for social-emotional learning, per year.

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Research from the ACM conference on computer-supported cooperative work and social computing

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Petr Slovak

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