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Riflessione retrospettiva a conclusione del progetto

1.Cosa abbiamo fatto bene e che potremmo dimenticare se non ne parlassimo?

2. Cosa abbiamo imparato?

3. Cosa vorremmo conoscere meglio/ approfondire?

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1: NOI POTREMMO DIMENTICARE I PASSAGGI SE NON LI SCRIVESSIMO.

2: NOI ABBIAMO IMPARATO A LAVORAR CON LA TECNOLOGIA.

3: NOI VORREMMO APROFONDIRE IL NOSTRO SAPERE SULA TECNOLOGIA.

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POTREI DIMENTICARMI DI COME CONDIVIDERE I PROGETTO

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POTREI DIMENTICARMI DI COME CONDIVIDERE I PROGETTO

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il mio compagno davide è stato bravo e simpatico e abbiamo lavorato in modo pulito e collaborativo  e ho imparato a programmare bene e mi è piaciuto molto

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il mio compagno davide è stato bravo e simpatico e abbiamo lavorato in modo pulito e collaborativo  e ho imparato a programmare bene e mi è piaciuto molto

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potremmo dimenticare tutto, ho imparato tanto, voreei aprrofondire altre cose

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ci potremmo dimenticare di scaricare dopo codice ma per altro ci siamo divertite molto e sono stata benissimo con la mia compagna

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1. POTREMMO DIMENTICARE TUTTI I CODICI DI PROGRAMMAZIONE, I PASSAGGI E I NOMI

2. HO IMPARATO A DIVERTIRMI CON LA TECNOLOGIA, COSA CHE NON AVREI MAI PENSATO DI FARE.

3. VORREI CONOSCERE DI PIU SUI MICROBIT E SULLA LORO STORIA

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ci e piaciuto il lavoro e lo rifarei siamo stati bravi e abbiamo imparato cose nuove e forse ce lo possiamo dimenticare

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mi potrei dimenticare di mettere la musica mi è piaciuto programmare e il mio compagno è stato bravo

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

# data[].attributes.attachment_link.description
Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

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Create AI on your BBC micro:bit using movement and machine learning

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

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Black Red White Minimalist Simple Creative Agency Intro Poster (1)

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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SIMON :3 NAD SUCCESS

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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salma e yara

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

# data[].attributes.attachment_link.description
Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

# data[].attributes.attachment_link.description
Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Fatto con ❤️ in Microsoft MakeCode for micro:bit.

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Lesson resources for teachers

Planning and teaching with the micro:bit

Primary ages 7-11

Complete, editable computing units of work and resources with cross-curricular links for art, science, geography and more, curriculum-linked to England KS2 and Code.org elementary CS Fundamentals.
Search primary lessons
Secondary ages 11-14

Units of work with downloadable, editable resources covering computing fundamentals through to cyber security, cryptography and creative design projects, curriculum-linked to England KS3.
Search secondary lessons

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The BBC micro:bit: the pocket-sized computer transforming digital skills learning.