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Contract Notice

Personalised Learning Bot

  • First published: 23 January 2020
  • Last modified: 23 January 2020

Contents

Summary

OCID:
ocds-kuma6s-098195
Published by:
Cardiff and Vale College
Authority ID:
AA0421
Publication date:
23 January 2020
Deadline date:
10 February 2020
Notice type:
Contract Notice
Has documents:
Yes
Has SPD:
No
Has Carbon Reduction Plan:
N/A

Abstract

Cardiff and Vale College (CAVC) is seeking to appoint a supplier as part of an innovative project to develop a personalised learning assistant (bot). The project will involve building a personalised learning bot that will drive adaptive and contextual Learning and Teaching, driven by advanced Artificial Intelligence (AI) and Deep Learning to help improve attainment in GCSE English and Maths. Anticipated core features and expectations include: • The teachers can be augmented with a self-learning Artificial Intelligence capable of creating a single knowledge from various learning sources while anticipating specific needs and personalising content. • Using machine learning and deep learning, the system will enable personalised self-service through a common canvas of proactive engagement that is led by contextual tasks and activities, this will include embedding nudges to increase motivation and engagement. • The learning assistant will reduce the marking workload of staff, improve feedback to students, drive individual capability-based learning (which has been proven to have a huge impact on learners’ achievement), and provide a personalised learning path for the individual. • The system will be driven by a voice ready, natural language typed exchange that will reduce the barrier to adoption while manifested within any other channel. • Whilst a teacher is marking a piece of work, the AI assistant will provide suggested content recommendation based on the marks and feedback of the teacher. The teacher will select the appropriate content for the learner to go alongside the marks and written or audio feedback to the learner. This content is pulled in from existing sources, like the VLE, and is personalised to the learners needs, but saves time for the teacher in having to search for the content. It will also provide richer feedback for the learner as generally feedback just contains text, rather than content to support the areas of weakness. • The AI assistant can then follow up with the learner after they have received the feedback to find out if the content was useful, to ensure that learning has taken place, and to offer further support. • The AI assistant can gamify and scan learners’ work for any dyslexia patterns before carrying out further diagnostics, which will notify the necessary support staff of requirements for further ALN support. This will reduce the likelihood of learners who require additional support remaining undiagnosed, resulting in a more proactive approach to ALN. • The system will be bilingual using a language translation module. The project is being supported through the Welsh Government Digital 2030 capital grant funding. The project needs to be delivered by May 2020. The College is inviting initial interested suppliers to register their expression of interest with a view to launching a formal invitation to tender process in January 2020. The maximum budget is £150,000, with a desirable requirement to exclude annual license fees following development of the product.

Full notice text

CONTRACT NOTICE – NATIONAL

SUPPLIES

1 Authority Details

1.1

Authority Name and Address


Cardiff and Vale College

Procurement, One Canal Parade, Dumballs Road,

Cardiff

CF10 5BF

UK

Alex Ley

+44 2920250352

tenders@cavc.ac.uk

www.cavc.ac.uk
www.sell2wales.gov.wales

1.2

Address from which documentation may be obtained


Cardiff and Vale College

Procurement, One Canal Parade, Dumballs Road,

Cardiff

CF10 5BF

UK

Alex Ley

+44 02920250352

tenders@cavc.ac.uk

www.cavc.ac.uk

1.3

Completed documents must be returned to:


Cardiff and Vale College

Procurement, One Canal Parade, Dumballs Road,

Cardiff

CF10 5BF

UK

Alex Ley

+44 02920250250

tenders@cavc.ac.uk

www.cavc.ac.uk

2 Contract Details

2.1

Title

Personalised Learning Bot

2.2

Description of the goods or services required

Cardiff and Vale College (CAVC) is seeking to appoint a supplier as part of an innovative project to develop a personalised learning

assistant (bot).

The project will involve building a personalised learning bot that will drive adaptive and contextual Learning and Teaching, driven

by advanced Artificial Intelligence (AI) and Deep Learning to help improve attainment in GCSE English and Maths.

Anticipated core features and expectations include:

• The teachers can be augmented with a self-learning Artificial Intelligence capable of creating a single knowledge from various

learning sources while anticipating specific needs and personalising content.

• Using machine learning and deep learning, the system will enable personalised self-service through a common canvas of proactive

engagement that is led by contextual tasks and activities, this will include embedding nudges to increase motivation and

engagement.

• The learning assistant will reduce the marking workload of staff, improve feedback to students, drive individual capability-based

learning (which has been proven to have a huge impact on learners’ achievement), and provide a personalised learning path for the

individual.

• The system will be driven by a voice ready, natural language typed exchange that will reduce the barrier to adoption while

manifested within any other channel.

• Whilst a teacher is marking a piece of work, the AI assistant will provide suggested content recommendation based on the marks

and feedback of the teacher. The teacher will select the appropriate content for the learner to go alongside the marks and written or

audio feedback to the learner. This content is pulled in from existing sources, like the VLE, and is personalised to the learners needs,

but saves time for the teacher in having to search for the content. It will also provide richer feedback for the learner as generally

feedback just contains text, rather than content to support the areas of weakness.

• The AI assistant can then follow up with the learner after they have received the feedback to find out if the content was useful, to

ensure that learning has taken place, and to offer further support.

• The AI assistant can gamify and scan learners’ work for any dyslexia patterns before carrying out further diagnostics, which will

notify the necessary support staff of requirements for further ALN support. This will reduce the likelihood of learners who require

additional support remaining undiagnosed, resulting in a more proactive approach to ALN.

• The system will be bilingual using a language translation module.

The project is being supported through the Welsh Government Digital 2030 capital grant funding. The project needs to be delivered

by May 2020.

The College is inviting initial interested suppliers to register their expression of interest with a view to launching a formal invitation

to tender process in January 2020. The maximum budget is £150,000, with a desirable requirement to exclude annual license fees

following development of the product.

NOTE: To register your interest in this notice and obtain any additional information please visit the Sell2Wales Web Site at https://www.sell2wales.gov.wales/Search/Search_Switch.aspx?ID=99172.

2.3

Notice Coding and Classification

72000000 IT services: consulting, software development, Internet and support
72200000 Software programming and consultancy services
72210000 Programming services of packaged software products
72211000 Programming services of systems and user software
72212000 Programming services of application software
72220000 Systems and technical consultancy services
72240000 Systems analysis and programming services
72250000 System and support services
72260000 Software-related services
1022 Cardiff and Vale of Glamorgan

2.4

Total quantity or scope of tender

3 Conditions for Participation

3.1

Minimum standards and qualification required

4 Administrative Information

4.1

Type of Procedure

Single stage

4.2

Reference number attributed to the notice by the contracting authority

CAVC-IT-19-021

4.3

Time Limits

Time-limit for receipt of completed tenders
    10-02-2020  Time  12:00

Estimated award date
 17-02-2020

4.5

Language or languages in which tenders or requests to participate can be drawn up

EN 

4.6

Tender Submission Postbox

5 Other Information

5.1

Additional Information

(WA Ref:99172)

Under the terms of this contract the successful supplier(s) will be required to deliver Community Benefits in support of the authority’s economic and social objectives. Accordingly, contract performance conditions may relate in particular to social and environmental considerations. The Community Benefits included in this contract are:

Community benefits are an important consideration and outcome for Cardiff and Vale College within our procurement activities, to ensure that wider social and economic issues are taken into account when spending public money.

We are committed in developing a vibrant Welsh economy capable of delivering strong and sustainable economic growth by providing opportunities for everyone in Wales.

The College urges bidders to consider what they can do to improve the quality of life and life opportunities to the communities in which the College serves and as such, the College seeks to generate community benefits through the award of this contract.

Please outline within your proposal any potential community benefits in which your company would generate as a direct result of the award of this College contract.

Some examples of community benefits would be:

• Sponsoring a College run community event or trip.

• Willingness to take on a College work experience student or apprentice.

• Participating in College charity partner events and activities.

• Supporting local charity run employment schemes

• Training to community groups

• Education contributions through career advice, career talks

5.2

Additional Documentation

(200120) - (CAVC-IT-19-021) - (Personalised Learning Bot) - ITT

5.3

Publication date of this notice

 23-01-2020

Coding

Commodity categories

ID Title Parent category
72000000 IT services: consulting, software development, Internet and support Computer and Related Services
72212000 Programming services of application software Programming services of packaged software products
72210000 Programming services of packaged software products Software programming and consultancy services
72211000 Programming services of systems and user software Programming services of packaged software products
72200000 Software programming and consultancy services IT services: consulting, software development, Internet and support
72260000 Software-related services Software programming and consultancy services
72250000 System and support services Software programming and consultancy services
72240000 Systems analysis and programming services Software programming and consultancy services
72220000 Systems and technical consultancy services Software programming and consultancy services

Delivery locations

ID Description
1022 Cardiff and Vale of Glamorgan

Alert region restrictions

The buyer has restricted the alert for this notice to suppliers based in the following regions.

ID Description
There are no alert restrictions for this notice.

Document family

Notice details
Publication date:
11 December 2019
Notice type:
Speculative Notice
Authority name:
Cardiff and Vale College
Publication date:
23 January 2020
Deadline date:
10 February 2020 00:00
Notice type:
Contract Notice
Authority name:
Cardiff and Vale College
Publication date:
04 April 2022
Notice type:
Contract Award Notice
Authority name:
Cardiff and Vale College

About the buyer

Main contact:
tenders@cavc.ac.uk
Admin contact:
tenders@cavc.ac.uk
Technical contact:
N/a
Other contact:
tenders@cavc.ac.uk

Further information

Date Details
No further information has been uploaded.

Q&A

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Additional Documents

The following additional documents have been attached to this notice. To obtain these documents please select the individual file names below.

Current documents

docx
docx113.21 KB
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Replaced documents

There are no previous versions of these documents.


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