ECE6071 Chap.9 Embodied and Culturally Responsive AI Curriculum
Embodied and Culturally Responsive AI Curriculum
The how question
The AI curriculum reading answers its third question, how young children should learn about AI, with two commitments: the curriculum should be embodied, and it should be culturally responsive.
Both are presented as ways to make STEM pathways available to every child, against a history in which the traditional STEM subjects were stereotyped as belonging to a narrow group.
Embodied and situated
The embodied argument draws on theories aligned with constructionism and sociocultural learning.
Its practical form is situative embodiment: learning should sit in a context relevant to children’s experience, carried by a storyline that gives a meaningful goal, expected actions and a background.
The AI session restates three principles for helping children learn AI: real-life experience, the interaction of body and mind, and interaction with AI as a tool for the curriculum.
Culturally responsive
Cultural responsiveness treats children’s cultural tools, resources and experiences as strengths.
The reading adopts four conditions for achieving it: establish inclusion, develop a positive attitude, enhance meaning and engender competence, with assessment placed in the last condition and built on feedback, authentic tasks, portfolios, artefacts and self-assessment.
An ocean project in Hong Kong
The exemplar curriculum, AI for Kids, was designed by the reading’s author and team and run in a Hong Kong kindergarten around ocean protection, chosen because Hong Kong is a coastal city.
It has three learning goals: how AI infers results from information, how it makes judgements by key features, and that AI has prejudices and makes errors. Six whole-class AI activities ran alongside ocean activities, and the AI session shows children training a robot dog by voice, sorting waste and watching an ocean-cleaning robot tested by the sea.
What this chapter covers
- 01
Embodied learning and situative storylines
- 02
Three principles for helping children learn AI
- 03
Cultural responsiveness as a strength-based approach
- 04
Four conditions from inclusion to competence
- 05
The ocean protection project and its goals
- 06
Evaluating children’s AI learning
- 07
New themes for culturally responsive AI units
Worked example · free
Diagnose a unit against the four conditions
- 4Assess the event against each of the four conditions.
- 2Propose a storyline tied to children’s experience.
- 2Replace the certificate with an assessment the reading would accept.
Key terms
- Embodied Learning
- Learning in which the body, mind and environment interact, so that children act out and physically engage with ideas rather than only hearing them.
- Situative Embodiment
- The design principle that content should be tied to a context from learners’ experience through a storyline with a goal, actions and a background.
- Establish Inclusion
- The first culturally responsive condition, creating a welcoming, connected atmosphere through cooperative and peer learning.
- Engender Competence
- The culturally responsive condition in which children show what they can do through authentic tasks, portfolios and self-assessment.
- AI for Kids
- The exemplar curriculum in the AI curriculum reading, run in a Hong Kong kindergarten around ocean protection, that teaches how AI learns and errs.
Embodied and Culturally Responsive AI Curriculum FAQ
What makes an AI curriculum culturally responsive?
It builds on children’s own cultural tools and experiences and follows four conditions: establish inclusion, develop a positive attitude, enhance meaning and engender competence. The ocean project is an example, chosen because Hong Kong children know the coast from daily life.
What does embodied learning look like in an AI unit?
Children act out and handle ideas as well as hearing them: role-playing a problem, moving to commands, training a robot by voice, or sorting real objects before a machine does. The storyline gives the bodily activity a purpose the children understand.
How should children’s learning about AI be evaluated?
The reading recommends assessment tied to real problem-solving contexts, using timely feedback, authentic tasks, portfolios, artefacts and self-assessment. The exemplar also asks teachers to observe enthusiasm, understanding and problem solving, and invites children to draw what they imagine AI to be.
Assessment move
Pick a theme from your own community and sketch a three-week AI unit using the four conditions as headings. If you struggle with the positive attitude heading, the theme is probably not close enough to children’s lives.
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