Focus on...
the impact of AI on teaching, learning and working
The rapid rise and uptake of artificial intelligence (AI), particularly of generative AI (GenAI), is being felt in many aspects of our lives. Learning institutions and businesses are having to engage quickly with the rapidly evolving technology, transforming how we teach, learn and work. This issue of Focus on... presents recent research exploring the impact AI, in particular GenAI, is having on teaching and learning practices, and on the way we work.
The impact of GenAI on teaching and learning
Impact on institutional practices
Educators and training providers are grappling with the challenges of AI and its impact on preparing students for the world of work. This includes adapting teaching and assessment practices and designing curriculum that integrates AI skills. As mentioned in Artificial intelligence and vocational education and training: how to shape the future, 'it will be VET teachers and trainers who will design and deliver continuing professional development to upgrade the skills and knowledge of the present workforce and provide retraining for those displaced by the impact of AI and automation on workforce labour demands' (p. 5). The report makes five policy recommendations of which two are key for training providers: update and develop curricula to include AI skills; and build AI competencies into training for VET practitioners so they have the skills necessary to instruct students.
These ideas are also evident in Understanding the impact of artificial intelligence on skills development. This report details the use of AI in technical and vocational education and training (TVET), providing an overview of current trends, programs, and policies. It covers practices relating to planning and governance, ethics, values and skills, teaching and learning, and opportunities for lifelong learning. Of the numerous recommendations presented, several focus on how training providers could respond to the era of AI, including researching available AI tools, making continuous efforts to integrate AI into educational administration and teaching and learning, and guaranteeing the ethical use of AI and student data.
Guidance for generative AI in education and research provides an extensive overview of GenAI and education. After a section describing GenAI and how it works, the guide looks at a number of implications for education, including worsening digital poverty, violation of intellectual property rights, and the bias often displayed by AI models. GenAI systems, such as ChatGPT, are trained using material on the Internet which can contain errors and may marginalize the voices of minority groups. 'Researchers, teachers and learners need to be aware that GenAI systems are capable of outputting offensive and unethical materials' (p. 16). The guide also discusses steps to regulate GenAI in education and outlines strategies for institutions to ensure the responsible and creative use of GenAI.
- AI and education: guidance for policymakers
- The AI generation: how universities can prepare students for the changing world
- ChatGPT and artificial intelligence in higher education: quick start guide
- Leadership is needed for ethical ChatGPT: character, assessment, and learning using artificial intelligence (AI)
Impact on teaching and assessment
One of the other issues for trainers and providers is the possibility of students using GenAI to 'cheat' on their assessment tasks. As the Tertiary Education Quality and Standards Agency (TEQSA) state: 'It is challenging to design non-invigilated assessment tasks that preclude substantial use of generative AI, and it appears almost impossible to detect if these technologies have been used in the production of assessment products in a reliable way' (p. 1). TEQSA's report, Assessment reform for the age of artificial intelligence, provides a set of guiding principles relating to higher education assessment. These are used as the foundation for a set of aspirational ideas aiming to assist institutions approach assessment in the world of AI. These key propositions state that assessment should emphasise:
- appropriate, authentic engagement with AI;
- a systemic approach to program assessment aligned with disciplines/qualifications;
- the process of learning;
- opportunities for students to work appropriately with each other and AI; and
- security at meaningful points across a program to inform decisions about progression and completion.
Although trainers and training providers are aware that students are most likely using GenAI to assist with their learning and to produce their work for assessment, research shows that they are more focused on how to adjust pedagogical and assessment practices in light of GenAI. In Generative artificial intelligence in Canadian post-secondary education: AI policies, possibilities, realities, and futures, administrators and practitioners across Canada were surveyed on their perspectives of GenAI. The findings indicate that the respondents anticipate AI becoming a normal and common part of higher education. Due to this, some respondents reflected that educators were using GenAI to help create lesson plans, learning scenarios, and draft fictional case studies for classes. Some educators were also designing assessment tasks that required students to use GenAI, for example getting students to assess a ChatGPT response for strengths, weaknesses and accuracy. This age of GenAI is making trainers and providers rethink education and training, to change the narrative from 'cheating using GenAI' to incorporating GenAI into the learning experience.
- AI pioneers: developing a community of practice for artificial intelligence (AI) and vocational education and training
- Bridging resource gaps in adult education: the role of generative AI
- ChatGPT: leveraging AI to support personalized teaching and learning
- ChatGPT and its impact on education
- Evaluation of new data science and artificial intelligence postgraduate conversion courses: final report
The impact of GenAI on students
Impact on higher education learning experience
It is widely accepted the impact GenAI is having on higher education. What that impact looks like and how student experiences have changed is considered in GenAI in higher education: Fall 2023 update Time for class study. The study explores how the learning outcomes of students using AI writing tools are enhanced, finding an increase in productivity and effectiveness. Several challenges are identified including: data privacy and accessibility; impact of plagiarism on academic integrity; and the need for policy development to evolve in step with advances in technology.
Preparing students for the technological disruptions that are changing the future of work is vital. How best to do this preparation is discussed in Digital transformation in global TVET: methodology and practices. According to the report, bridging the digital skills gap and equipping students for changing job markets means that they require hands-on experiences with new technologies, critical thinking skills, and a lifelong learning mindset.
- ChatGPT and the digitisation of writing
- Ethics of AI in education: towards a community-wide framework
- The AI generation: how universities can prepare students for the changing world
Student perception of the impact of AI
Adoption of AI among young people has been rapid. AI amplified: what Gen Zs think of AI found that Gen Zs are the first to use AI for their education - at school, tertiary level and at the start of their careers. It surveyed 1048 students with 40% stating they learnt to use AI at school. There has been a strong uptake, but trust in the technology is not growing at the same rate. To maximise AI benefits, trust must underpin skill development. If students do not believe AI has a positive impact, its uptake and progress may slow, and the full potential will not be realised.
Building such trust is considered in Provide or punish?: students' views on generative AI in higher education. Its key recommendations are that students be supported to access the right tools, and that students want support to address the digital divide. The divide is greater for minority groups with gender, ethnicity, and privilege impacting on a student’s uptake of AI tools. Groups with better access to resources and with increased digital literacy have adapted to the technology quicker, integrating it into their studies in sophisticated ways.
- Evaluation of new data science and artificial intelligence postgraduate conversion courses: final report
- What ChatGPT means for universities: perceptions of scholars and students
Impact on job prospects
There is a link between the GenAI skills a student has upon graduation and their ability to secure a job interview. In IZA's Artificial intelligence capital and employment prospects study it found that students with AI 'capital' received more invitations to interview for jobs upon graduation. Their definition of capital includes students who possess knowledge, skills and capabilities associated with AI technology. The study concluded that 'AI capital' may impact upon a student's employment prospects and opportunity to earn a higher wage in large firms.
- Is education losing the race with technology?: AI's progress in maths and reading
- Learning analytics for lifelong career development: a framework to support sustainable formative assessment and self-reflection in programs developing career self-efficacy
- AI and the future of skills, volume 1: capabilities and assessments
- AI and the future of skills, volume 2: methods for evaluating AI capabilities
The impact of GenAI on employment
Impact on the labour market
Technological innovation has the capacity to influence the labour market in various ways - through the creation of new job opportunities, the loss of jobs replaced by automation, and transformation of existing jobs where people are assisted in their roles and tasks by innovative technology such as GenAI. The OECD's employment outlook 2023: artificial intelligence and the labour market finds that, in many areas, it is hard to tell the difference between the outputs of AI from that of humans and, combined with the falling costs of developing and adopting AI systems, suggests that OECD countries may be on the verge of a technological revolution that could essentially change the workplace.
The Burning Glass Institute, in Generative artificial intelligence and the workforce, proposes that the latest developments in GenAI will have the greatest effect on high-skilled, professional work - jobs traditionally thought of as protected from automation. It will be important therefore for employers to anticipate the repercussions for their workforce and develop adaptive strategies.
- Artificial intelligence and the labor force: a data-driven approach to identifying exposed occupations
- ChatGPT: organizational and labour implications
- Generative AI and the future of work in America
- GPTs are GPTs: an early look at the labor market impact potential of large language models
- Occupational heterogeneity in exposure to generative AI
- The impact of Artificial Intelligence on the labour market: what do we know so far?
- 'This time it's different': generative artificial intelligence and occupational choice
Impact on work and skill needs
Within jobs, GenAI has the potential to transform routine work and significantly boost creative and knowledge work. For employers the challenge will be to understand the likely ramifications of GenAI on their particular industry. In Australia, the Future Skills Organisation studied the influence of GenAI on occupations and training using estimates of impact on human abilities. Impact of generative AI on skills in the workplace finds that within the VET system, higher level qualifications are more likely to face disruption, such as those in the Financial Services training package that prepare people for roles in accounting and clerking for financial services firms, software development and programming roles in ICT, and administration and call centre roles in Business Services.
According to OECD findings in Artificial intelligence and the changing demand for skills in the labour market, most workers who will be exposed to AI will not require specialised AI skills (e.g. machine learning, natural language processing, etc.) but AI will change the tasks these workers do and the skills they require. Estimates of the effect of AI on skills demand for jobs with high exposure but not requiring specialised AI skills, found that management and business skills, including skills in general project management, finance, administration and clerical tasks, were the most sought-after.
- Emerging trends in AI skill demand across 14 OECD countries
- Gen-AI: artificial intelligence and the future of work
- The age of uncertainty and opportunity: work in the age of AI
- The AI-ready workforce: how leaders and workers can prepare for a reshaped future of work
- What's working?: navigating the AI revolution and the shifting future of work
- Work, workforce, workers: reinvented in the age of generative AI
Impact on quality of work and equity
For workers, GenAI has the power to either augment or automate job tasks, so employment effects will vary widely according to occupational exposure. In previous technological waves the repercussions were mainly for manual workers, but this time, with the ability of computers to perform non-routine, cognitive tasks, the impact is being felt instead by 'knowledge workers'. In Generative AI and jobs: a global analysis of potential effects on job quality and quality, the ILO assesses the possible exposure of occupations to GenAI, particularly GPT-4. It predicts that the overwhelming effect will be to augment occupations rather than to automate them. Jobs held by women, the highly educated and younger workers are more exposed to GenAI. It is anticipated that the brunt of this will fall on high and upper-middle income countries due to their greater share of employment in clerical occupations, an important source of female employment.
Alternatively, in Using AI in the workplace: opportunities, risks and policy responses, the OECD finds that AI can bring significant benefits to the workplace. In surveys of employers and workers, four in five workers say that AI improved their performance at work and three in five say that it increased their enjoyment of work. The benefits of AI depend though on addressing associated risks, e.g., increased work intensity, the collection and use of data, and increasing inequality.
- Algorithmic management practices in regular workplaces: case studies in logistics and healthcare
- Applying AI to rebuild middle class jobs
- Artificial intelligence and wage inequality
- Automation hits the knowledge worker: ChatGPT and the future of work
- The effects of AI on the working lives of women
- Using AI to support people with disability in the labour market: opportunities and challenges
- Which US workers are more exposed to AI on their jobs?
Published: May 2024