Pith. sign in

REVIEW

Teaching AI and Robotics to Children in a Mexican town

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2303.03956 v1 pith:WJVCONNB submitted 2023-03-05 cs.CY

classification cs.CY
keywords roboticschallengeschildrenparticipantspilotteachinginclusivelow-
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
abstract

In this paper, we present a pilot study aiming to investigate the challenges of teaching AI and Robotics to children in low- and middle-income countries. Challenges such as the little to none experts and the limited resources in a Mexican town to teach AI and Robotics were addressed with the creation of inclusive learning activities with Montessori method and open-source educational robots. For the pilot study, we invited 14 participants of which 10 were able to attend, 6 male and 4 female of (age in years: mean=8 and std=$\pm$1.61) and four instructors of different teaching experience levels to young audiences. We reported results of a four-lesson curriculum that is both inclusive and engaging. We showed the impact on the increase of general agreement of participants on the understanding of what engineers and scientists do in their jobs, with engineering attitudes surveys and Likert scale charts from the first and the last lesson. We concluded that this pilot study helped children coming from low- to mid-income families to learn fundamental concepts of AI and Robotics and aware them of the potential of AI and Robotics applications which might rule their adult lives. Future work might lead (a) to have better understanding on the financial and logistical challenges to organise a workshop with a major number of participants for reliable and representative data and (b) to improve pretest-posttest survey design and its statistical analysis. The resources to reproduce this work are available at \url{https://github.com/air4children/dei-hri2023}.

Discussion (0). Continue with ORCID to comment.

Pith tools