Nursery
Christchurch Kindergarten @ Queensbury | Ofsted Reports, Reviews (2025)
Christchurch Kindergarten @ Queensbury
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Christchurch Kindergarten @ Queensbury
- Nursery
- Brent HA8 5ND
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Ofsted report
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| The quality of education | Good |
| Behaviour and attitudes | Good |
| Personal development | Good |
| Leadership and management | Good |
| Overall effectiveness at previous inspection | Requires Improvement |
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Diverse Books and Toys: Staff support children to build a love of stories and books.
Indoor and Outdoor Facilities: Children enjoy using chalks outside and painting and drawing pictures.
Philosophy: The manager has a clear curriculum and designs it to meet children's individual needs.
Activities: Children choose where they would like to play, and staff are readily available to extend their learning.
Skills , Knowledge and Behavior: Staff willingly assist children in mark making and numbers, praising their efforts to build children's confidence.
Communication: Staff have a good relationship with parents and meet regularly to discuss children's individual learning needs and next steps.
Programs and Resources: All children, including those with special educational needs and/or disabilities, receive encouragement to participate and take part.
Staff Training: Staff follow advice from professionals to close any gaps in learning which a child may have.
Welcoming and Professional Staff: Staff comment that they feel well supported by the manager.
Safeguarding Training: They are trained to understand the provider's safeguarding policies and procedures.
Play and Learning Integration: Children enter the pre-school happily, choosing where they would like to play.
Diversity Management: There is strong support for children who speak English as an additional language.
Child Safety Management: The managers and staff demonstrate a good awareness of safeguarding practice.
Children's Safety and Security: Older children effortlessly carry out good hygiene procedures.
Nutritional Menu: Children enjoy nutritious snacks which are freshly prepared at the pre-school.
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About Us
Christchurch Kindergarten @ Queensbury is a Nursery, Nursery located in Greater London, London.
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FootfallCam, a privately held firm that was founded in 2002, is the top provider of solutions for counting people worldwide.
We have a team of highly skilled engineers who produce all of the hardware and software in-house at our U.K. headquarters, using their specialties to address business problems over time.
We have tirelessly serviced organisations all over the world in industries ranging from retail, fast food restaurants, and museums to smart buildings and airports, for more than ten years, with the help of a global network of reseller partners and ongoing effort in research and development.
Research and development (R&D) is important to our business and is a key component of our core strategy.
We have an internal R&D team devoted to the creation of FootfallCam's hardware and software.
FootfallCam is able to maintain its position at the forefront of the people counting market through constant product development.
Our main product, FootfallCam 3D Max, was successfully created because to our creative approach to product development.
We are the first company in the world to integrate Wi-Fi analytics and people counts into a single device.
We are dedicated to upholding our position as the industry leader by providing the level of strategic insight that our clients demand.
By opening sales offices in a number of nations, including the United Kingdom, the United States, Hong Kong, and Malaysia, FootfallCam increases its footprint across the globe.
FootfallCam has established sales offices in more than 100 nations, including Ireland, France, Italy, Spain, the United Arab Emirates, South Africa, Thailand, Singapore, Indonesia, Germany, Australia, and others. In addition, it has built up a solid partner network.
We have created hardware and software for solutions involving people counting for more than 100 years.
Stereoscopic (3D image processing) being able to discern intelligently between a human and non-human objects and follow a walking human's course of travel.
Support Vector Machine (SVM) neural network modelling is used in artificial intelligence to train our machines to recognise objects.
Read more
We have a team of highly skilled engineers who produce all of the hardware and software in-house at our U.K. headquarters, using their specialties to address business problems over time.
We have tirelessly serviced organisations all over the world in industries ranging from retail, fast food restaurants, and museums to smart buildings and airports, for more than ten years, with the help of a global network of reseller partners and ongoing effort in research and development.
Research and development (R&D) is important to our business and is a key component of our core strategy.
We have an internal R&D team devoted to the creation of FootfallCam's hardware and software.
FootfallCam is able to maintain its position at the forefront of the people counting market through constant product development.
Our main product, FootfallCam 3D Max, was successfully created because to our creative approach to product development.
We are the first company in the world to integrate Wi-Fi analytics and people counts into a single device.
We are dedicated to upholding our position as the industry leader by providing the level of strategic insight that our clients demand.
By opening sales offices in a number of nations, including the United Kingdom, the United States, Hong Kong, and Malaysia, FootfallCam increases its footprint across the globe.
FootfallCam has established sales offices in more than 100 nations, including Ireland, France, Italy, Spain, the United Arab Emirates, South Africa, Thailand, Singapore, Indonesia, Germany, Australia, and others. In addition, it has built up a solid partner network.
We have created hardware and software for solutions involving people counting for more than 100 years.
Stereoscopic (3D image processing) being able to discern intelligently between a human and non-human objects and follow a walking human's course of travel.
Support Vector Machine (SVM) neural network modelling is used in artificial intelligence to train our machines to recognise objects.
Admission
Holidays & terms
Holidays 2024/25
| Holidays | Date |
|---|---|
| Autumn Half Term Holidays | 21st Oct 2024 - 25th Oct 2024 |
| Winter Holidays | 23rd Dec 2024 - 3rd Jan 2025 |
| Spring Half Term Holidays | 17th Feb 2025 - 21st Feb 2025 |
| Spring Holidays | 7th Apr 2025 - 21st Apr 2025 |
| Summer Half Term Holidays | 26th May 2025 - 30th May 2025 |
| Summer Holidays | 28th Jul 2025 - 29th Aug 2025 |
Terms Dates 2024/25
| Terms | Dates |
|---|---|
| Autumn Term | 2nd Sep 2024 - 20th Oct 2024 |
| Autumn Term-2 | 26th Oct 2024 - 22nd Dec 2024 |
| Spring Term | 4th Jan 2025 - 16th Feb 2025 |
| Spring Term-2 | 22nd Feb 2025 - 6th Apr 2025 |
| Summer Term | 22nd Apr 2025 - 25th May 2025 |
| Summer Term-2 | 31st May 2025 - 27th Jul 2025 |
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