Digitalisation, Artificial Intelligence and Vocational Occupations and Skills

web, network, programming

geralt (CC0), Pixabay

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.

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,

 

 

 

Four domains of learning

four development domaninspng

I came upon this text today when I was seeking to extend on an article I was writing that included the idea of learning in four domains. It was produced, I think, for the EmployID MOOC on the Changing World of Work and was probably written by Alan Brown and Jenny Bimrose.Sadly, I was so tied up with producing my own materials for the MOOC and didn’t get to read all of the other peoples. But at a time when there is a growing need to question to division between humanities and technical subjects, I think this offers a good way forward.

Relational development – learning with and from interacting with other people

A major route for relational development is learning through interactions at work, learning with and from others (in multiple contexts) and learning as participation in communities of practice (and communities of interest) while working with others. Socialisation at work, peer learning and identity work all contribute to individuals’ relational development. Many processes of relational development occur alongside other activities but more complex relationships requiring the use of influencing skills, engaging people for particular purposes, supporting the learning of others and exercising supervision, management or (team) leadership responsibilities may benefit from support through explicit education, training or development activities.

Jack from the UK had switched career and now who worked as a carer. From the outset Jack learned much about his work from engaging with residents in the care home as well as learning from other staff. He had received letters from residents expressing their gratitude, which had boosted his confidence. His manager encouraged him to become a trainer in the care home, and although nervous and unsure he delivered the training and his self-efficacy increased.

Cognitive development – acquiring knowledge and thinking skills

A major work-related route for cognitive development involves learning through mastery of an appropriate knowledge base and any subsequent technical updating. This form of development makes use of learning by acquisition and highlights the importance of subject or disciplinary knowledge and/or craft and technical knowledge, and it will be concerned with developing particular cognitive abilities, such as critical thinking; evaluating; synthesising etc.

Bernard, a Czech automotive worker, participated in a short internal company technical training programme which positively surprised him in terms of practical outcomes and motivated him to actively work on his vocational development. ‘You had to know your stuff, the trainer was extremely competent, he knew his field very well, but sometimes I had difficulties to follow him. Anyway, it was really done by professionals who knew their stuff, and I appreciated it very much. I was very satisfied. I learned lots of things that were later very useful for my work […] It was very interesting to meet people from a completely different and a rather specialised area. I learned a lot of things and I was proud of it. I think this was the moment that made me change my attitude towards learning. I became much more curious.’

Practical development – learning by doing, by experience, by taking on challenges

For practical development the major developmental route is often learning on the job, particularly learning through challenging work. Learning a practice is also about relationships, identity and cognitive development but there is value in drawing attention to this idea, even if conceptually it is a different order to the other forms of development highlighted in this representation of learning as a process of identity development. Practical development can encompass the importance of critical inquiry, innovation, new ideas, changing ways of working and (critical) reflection on practice. It may be facilitated by learning through experience, project work and/or by use of particular approaches to practice, such as planning and preparation, implementation (including problem-solving) and evaluation. The ultimate goal may be vocational mastery, with progressive inculcation into particular ways of thinking and practising, including acceptance of appropriate standards, ethics and values, and the development of particular skill sets and capabilities associated with developing expertise.

Davide, an Italian carpenter, saw learning as a practice-based process driven by curiosity, a spirit of observation, and trial and error. A major role was played by his passion for the transformation of matter, which he perceived as an almost sacred event: ‘It really struck me to see that from a piece of wood one can create a piece of furniture’.

Emotional development – making sense of your own feelings and how others feel 

For emotional development, the major developmental routes are learning through engagement,  reflexiveness that leads to greater self-understanding, and the development of particular personal qualities. Much emotional development may occur outside work, but the search for meaning in work, developing particular mind-sets, and mindfulness may be components of an individual’s emotional development. Particular avenues of development could include understanding the perspectives of others, respect for the views of others, empathy, anticipating the impact of your own words and actions, and a general reflexiveness, which includes exploring feelings. Identity development at work may also be influenced by changing ideas individuals have about their own well-being and changing definitions of career success (Brown & Bimrose 2014).

Henrik from Denmark switched career, moving into caring and developed a new relationship with his work, which he found much more emotionally engaging. While studying for his skilled worker qualification, Henrik immersed himself in individual assignments of his own choice. In one assignment, he developed a ‘product’ to help improve a pupil’s ability to communicate, an ability which was being lost due to a rare disease. When Henrik talked about the assignment he was very engaged and showed insight into the syndrome. Because the assignment was closely related to his experience and practice, he saw meaning in undertaking it: ‘It was as though there was a circle I could complete on my own.’ He received a top grade for the assignment, and it is evident that positive learning experiences and the perception of entering into learning processes that are meaningful to his life and work situation are strong motivating factors in his engagement in further learning.

Data and the future of universities

I’ve been doing quite a lot of thinking about how we use data in education. In the last few years two things have combined – the computing ability to collect and analyse large datasets, allied to the movement by many governments and administrative bodies towards open data.

Yet despite all the excitement and hype about the potential of using such data in education, it isn’t as easy as it sounds. I have written before about issues with Learning Analytics – in particular that is tends to be used for student management rather than for improving learning.

With others I have been working on how to use data in careers advice, guidance and counselling. I don’t envy young people today in trying to choose and  university or college course and career. Things got pretty tricky with the great recession of 2009. I think just before the banks collapsed we had been putting out data showing how banking was one of the fastest growing jobs in the UK. Add to the unstable economies and labour markets, the increasing impact of new technologies such as AI and robotics on future employment and it is very difficult for anyone to predict the jobs of the future. And the main impact may well be nots o much in new emerging occupations,or occupations disappearing but in the changing skills and knowledge required n different jobs.

One reaction to this from many governments including the UK has been to push the idea of employability. To make their point, they have tried to measure the outcomes of university education. But once more, just as student attainment is used as a proxy for learning in many learning analytics applications, pay is being used as a proxy for employability. Thus the Longitudinal Education Outcomes (LEO) survey, an experimental survey in the UK, users administrative data to measure the pay of graduates after 3, 5 and 0 years, per broad subject grouping per university. The trouble is that the survey does not record the places where graduates are working. And once thing we know for a certainty is that pay in most occupations in the UK is very different in different regions. The LEO survey present a wealth of data. But it is pretty hard to make any sense of it. A few things stand out. First is that UK labour markets look pretty chaotic. Secondly there are consistent gender disparities for graduates of the same subject group form individual universities. The third point is that prior attainment before entering university seems a pretty good predictor of future pay, post graduation. And we already know that prior attainment is closely related to social class.

A lot of this data is excellent for research purposes and it is great that it is being made available. But the collection and release of different data sets may also be ideologically determined in what we want potential students to be able to find out. In the same way by collecting particular data, this is designed to give a strong steer to the directions universities take in planning for the future. It may well be that a broader curriculum and more emphasis on process and learning would most benefits students. Yet the steer towards employability could be seen to encourage a narrower focus on the particular skills and knowledge employers say they want in the short term and inhibit the wider debates we should be having around learning and social inclusion.

 

Who wants to be a teacher

From OECD:

PISA in Focus shows, in many countries the teaching profession is having a hard time making itself an attractive career choice – particularly among boys and among the highest-performing students.

PISA 2006 asked students from the 60 participating countries and economies what occupation they expected to be working in when they are 30 years old. Some 44% of 15-year-olds in OECD countries reported that they expect to work in high-status occupations that generally require a university degree; but only 5% of those students reported that they expect to work as teachers, one of those professional careers.

The numbers are even more revealing when considering the profile of the students who reported that they expect to work as teachers. If you read our report on gender equality in education published earlier this year, you may remember that girls tend to favour “nurturance-oriented” careers more than boys do – and teaching is one of those careers. In almost every OECD country, more girls (6%) than boys (3%) reported that they expect to work as teachers. This statistic is particularly worrying when you recall that the majority of overall low achievers in school are boys, who could benefit from the presence of more male role models at school.