Digitalisation, Artificial Intelligence and Vocational Occupations and Skills

web, network, programming

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The Taccle AI project on Artificial Intelligence and Vocational Education and Training, has published a preprint  version of a paper which has been submitted of publication to the VET network of the European Research Association.

The paper, entitled  Digitalisation, Artificial Intelligence and Vocational Occupations and Skills: What are the needs for training Teachers and Trainers, seeks to explore the impact AI and automation have on vocational occupations and skills and to examine what that means for teachers and trainers in VET. It looks at how AI can be used to shape learning and teaching processes, through for example, digital assistants which support teachers. It also focuses on the transformative power of AI that promises profound changes in employment and work tasks. The paper is based on research being undertaken through the EU Erasmus+ Taccle AI project. It presents the results of an extensive literature review and of interviews with VET managers, teachers and AI experts in five countries. It asks whether machines will complement or replace humans in the workplace before going to look at developments in using AI for teaching and learning in VET. Finally, it proposes extensions to the EU DigiCompEdu Framework for training teachers and trainers in using technology.

The paper can be downloaded here.

European Union, AI and data strategy

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is the rapporteur for the industry committe for European Parliament’s own-initiative  on data strategy and  a standing rapporteur on the World Trade Organization e-commerce negotiations in the European Parliament’s international trade committee.

Writing in Social Europe she says:

Building a human-centric data economy and human-centric artificial intelligence starts from the user. First, we need trust. We need to demystify the data economy and AI: people tend to avoid, resist or even fear developments they do not fully understand.

Education plays a crucial role in shaping this understanding and in making digitalisation inclusive. Although better services—such as services used remotely—make life easier also outside cities, the benefits of digitalisation have so far mostly accrued to an educated fragment of citizens in urban metropoles and one of the biggest obstacles to the digital shift is lack of awareness of new possibilities and skills.

Kampula-Natri draws attention to the Finnish-developed, free online course, ‘Elements of AI’. This started as a course for students in the University of Helsinki but has extended  its reach to over 1 per cent of Finnish citizens.

Kampula-Natri points out that in the Nordic countries, the majority of participants on the ‘Elements of AI’ course are female and in the rest of the world the proportion exceeds 40 per cent—more than three times as high as the average ratio of women working in the technology sector. She says that after the course had been running in Finland for a while, the number of women applying to study computer science in the University of Helsinki increased by 80 per cent.

Pathways to Future Jobs

people, special, different

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Even before the COVIP 19 crisis and the consequent looming economic recession labour market researchers and employment experts were concerned at the prospects for the future of work due to automation and Artificial Intelligence.

The jury is still out concerning the overall effect of automation and AI on employment numbers. Some commentators have warned of drastic cuts in jobs, more optimistic projections have speculated that although individual occupations may suffer, the end effect may even be an increase in employment as new occupations and tasks emerge.

There is however general agreement on two things. The first is that there will be disruption to may occupations, in some cases leasing to a drastic reduction in the numbers employed and that secondly the tasks involved in different occupations will change.

In such a situation it is necessary to provide pathways for people from jobs at risk due to automation and AI to new and hopefully secure employment. In the UK NESTA are running the CareerTech Challenge programme, aimed at using technology to support the English Government’s National Retraining Scheme. In Canada, the Brookfield Institute has produced a research report ‘Lost and Found, Pathways from Disruption to Employment‘, proposing a framework for identifying and realizing opportunities in areas of growing employment, which, they say “could help guide the design of policies and programs aimed at supporting mid-career transitions.”

The framework is based on using Labour Market Information. But, as the authors point out, “For people experiencing job loss, the exact pathways from shrinking jobs to growing opportunities are not always readily apparent, even with access to labour market information (LMI).”

The methodology is based on the identification of origin occupations and destination occupations. Origin occupations are jobs which are already showing signs of employment. Decline regardless of the source of th disruption. Destination jobs are future orientated jobs into which individuals form an origin occupation can be reasonably expected to transition. They are growing, competitive and relatively resilient to shocks.

Both origin and destination occupations are identified by an analysis of employment data.

They are matched by analysing the underlying skills, abilities, knowledge, and work activities they require. This is based on data from the O*Net program. Basically, the researchers were looking for a high 80 or 90 per cent match. They also were looking for destination occupations which would include an increase in pay – or at least no decrease.

But even then, some qualitative analysis is needed. For instance, even with a strong skills match, a destination occupation might require certification which would require a lengthy or expensive training programme. Thus, it is not enough to rely on the numbers alone. Yet od such pathways can be identified then it could be possible to provide bespoke training programmes to support people in moving between occupations.

The report emphasises that skills are not the only issue and discusses other factors that affect a worker’s journey, thereby, they say “grounding the model in practical realities. We demonstrate that exploring job pathways must go beyond skills requirements to reflect the realities of how people make career transitions.”

These could include personal confidence or willingness or ability to move for a new job. They also include the willingness of employers to look beyond formal certificates as the basis for taking on new staff.

The report emphasises the importance of local labour market information. That automation and AI are impacting very differently in different cities and regions is also shown in research from both Nesta and the Centre for Cities in the UK. Put quite simply in some cities there are many jobs likely to be hard hit by automation and AI, in other cities far less. Of course, such analysis is going to be complicated by COVID 19. Cities, such as Derby in the UK, have a high percentage of jobs in the aerospace industry and these previously seemed relatively secure: this is now not so.

In this respect there is a problem with freely available Labour Market Information. The Brookfield Institute researchers were forced to base their work on the Canadian 2006 and 2016 censuses which as they admit was not ideal. Tn the UK data on occupations and employment from the Office of National Statistics is not available at a city level and it is very difficult to match up qualifications to employment. If similar work is to be undertaken in the UK, there will be a need for more disaggregated local Labour Market Information, some of it which may already be being collected through city governments and Local Economic Partnerships.

CareerChat Bot

chatbot, bot, assistant

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Pontydysgu is very happy to be part of a consortium, led by DMH Associates, selected as a finalist for the CareerTech Challenge Prize!

The project is called CareerChat and the ‘pitch’ video above expalisn the ideas behind the project. CareerChat is a chatbot providing a personalised, guided career journey experience for working adults aged 24 to 65 in low skilled jobs in three major cities: Bristol, Derby and Newcastle. It offers informed, friendly and flexible high-quality, local contextual and national labour market information including specific course/training opportunities, and job vacancies to support adults within ‘at risk’ sectors and occupations

CareerChat incorporates advanced AI technologies, database applications and Natural Language Processing and can be accessed on computers, mobile phones and devices. It allows users to reflect, explore, find out and identify pathways and access to new training and work opportunities.

Nesta is delivering the CareerTech Challenge in partnership with the Department for Education as part of their National Retraining Scheme

  • Nesta research suggests that more than six million people in the UK are currently employed in occupations that are likely to radically change or entirely disappear by 2030 due to automation, population aging, urbanisation and the rise of the green economy.
  • In the nearer-term, the coronavirus crisis has intensified the importance of this problem. Recent warnings suggest that a prolonged lockdown could result in 6.5 million people losing their jobs. [1] Of these workers, nearly 80% do not have a university degree. [2]
  • The solutions being funded through the CareerTech Challenge are designed to support people who will be hit the hardest by an insecure job market over the coming years. This includes those without a degree, and working in sectors such as retail, manufacturing, construction and transport.

You can find out more information about the programme here: https://www.nesta.org.uk/project/careertech-challenge/ and email Graham Attwell directly if you would like to know more about the CareerChat project

Case study. The Ada chatbot: personalised, AI-driven assistant for each student.

As part of the AI and vocational education and training project funded through the EU Erasmus plus project we are producing a series of case studies of the use of AI in VET in five European countries. Here is my first case study – the Ada chatbot developed at Bolton College.

About Bolton College

Bolton College is one of the leading vocational education and training providers in the North West of England, specialising in delivering training – locally, regionally and nationally – to school leavers, adults and employers. The college employs over 550 staff members who teach over 14,500 full and part time students across a range of centres around Bolton. The college’s Learning Technology Team has a proven reputation for the use of learning analytics, machine learning and adaptive learning to support students as they progress with their studies.

The Ada Chatbot

The Learning Technology Team has developed a digital assistant called Ada which went live in April 2017. Ada, which uses the IBM Watson AI engine, can respond to a wide range of student inquiries across multiple domains. The college’s Learning Technology Lead, Aftab Hussain, says “It transforms the way students get information and insights that support them with their studies.” He explains: “It can be hard to find information on the campus. We have an information overload. We have lots of data but it is hard to manage. We don’t have the tools to manage it – this includes teachers, managers and students.” Ada was first developed to overcome the complexity of accessing information and data.

Student questions

Ada is able to respond to student questions including:

  1. General inquiries from students about the college (for example: semester dates, library opening hours, exam office locations, campus activities, deadline for applying for university and more);
  2. Specific questions from students about their studies (for example: What lessons do I have today/this afternoon/tomorrow? Who are my teachers? What’s my attendance like? When is my next exam? When and where is my work placement? What qualifications do I have? What courses am I enrolled in? etc.)
  3. Subject specific inquiries from students. Bolton College is teaching Ada to respond to questions relating to GCSE Maths, GCSE English and the employability curriculum.

Personalised and contextualised learning

Aftab Hussein explains: “We are connecting all campus data sets. Ada can reply to questions contextually. She recognises who you are and is personalised according to who you are and where you are in the student life cycle. The home page uses Natural Language Processing and the Watson AI engine. It can reply to 25000 questions around issues such as mental health or library opening times etc. It also includes subject specific enquiries including around English, Mathematics and business and employability. All teachers have been invited to submit the top 20 queries they receive. Machine learning can recognise the questions. The technical process is easy.” However, he acknowledges that inputting data into the system can be time consuming and they are looking at ways of automatically reading course documentation and presentations.

All the technical development has been undertaken in house. As well as being accessible through the web, Ada, has both IOS and Android apps and can also be queried though smart speakers.

The system also links to the college Moodle installation and can provide access to assignments, college information services and curriculum materials. The system is increasingly being used in online tutorials providing both questions for participants and access to learning materials for instance videos including for health and social care.

It is personalised for individuals and contextualised according to what they are doing or want to find out. Aftab says: “We are looking at the transactional distance – the system provides immediate feedback reducing the transactional distance. “

Digital assessment

Work is also being undertaken in developing the use of the bot for assessment. This is initially being used for the evaluation of work experience, where students need to provide short examples of how they are meeting objectives – for example in collaboration or problem solving. Answers can uploaded, evaluated by the AI and feedback returned instantly.

Nudging

Since March 2019, the Ada service has provided nudges to students with timely and contextualised information, advice and guidance (IAG) to support their studies. The service nudges students about forthcoming exams, their work placement feedback and more. In the following example, a student receives feedback regarding his work placement from his career coach and employer.

The College is currently implementing ProMonitor, a service which will offer teachers and tutors with a scalable solution for managing and supporting the progress made by their students. Once ProMonitor is in place, Ada will be in a position to nudge students about forthcoming assignments and the grades awarded for those assignments. She will also offer students advice and guidance about staying on track with their studies. Likewise, Ada will nudge teachers and student support teams to inform them about student progress; allowing for timely support to be put in place for students across the College.

A personal lifelong learning companion

For Aftab Hussein the persona of the digital agent is important. “In the future”, he says, “every child will have a personal lifelong learning companion which will support teaching and learning.” He thinks they will probably come from the big platform suppliers. Children will have their digital assistant from age the age of 3 or 4 and will have a Personal Learner Number allowing data to be exchanged between different institutions,