EXPLORA: A teacher-apprentice methodology for eliciting natural child-computer interactions

要旨

Investigating child-computer interactions within their contexts is vital for designing technology that caters to children’s needs. However, determining what aspects of context are relevant for designing child-centric technology remains a challenge. We introduce EXPLORA, a multimodal, multistage online methodology comprising three pivotal stages: 1) building a teacher-apprentice relationship, 2) learning from child-teachers, and 3) assessing and reinforcing researcher-apprentice learning. Central to EXPLORA is the collection of attitudinal data through pre-observation interviews, offering researchers a deeper understanding of children’s characteristics and contexts. This informs subsequent online observations, allowing researchers to focus on frequent interactions. Furthermore, researchers can validate preliminary assumptions with children. A means-ends analysis framework aids in the systematic analysis of data, shedding light on context, agency and homework-information searching processes children employ in their activities. To illustrate EXPLORA’s capabilities, we present nine single case studies investigating Brazilian child-caregiver dyads (children ages 9-11) use of technology in homework information-searching.

著者
Vanessa Figueiredo
University of British Columbia, Vancouver, British Columbia, Canada
Catherine Ann Cameron
University of British Columbia, Vancouver, British Columbia, Canada
論文URL

https://doi.org/10.1145/3613904.3642070

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Learning and Teaching CS and STEAM

313C
5 件の発表
2024-05-16 01:00:00
2024-05-16 02:20:00