As I write this article, all I can think of is all the films I have watched that attempted to depict how life would be in 50 years and being so wrong – iRobot, Blade Runner and so on. For example, could the days of in-person learning be replaced by holograms of the tutor? Who knows, but hopefully this represents the learning environments we will see in the coming years – learning that is technology enabled, highly personalised and data driven.
As academics (whether you’re a tutor, teacher, lecturer or other), we pride ourselves on the real-life examples we give students to enrich their understanding of the syllabus based on our previous work experience or other examples. But learners will be pushing us as learning providers to provide more than just practical, real-life examples. This means learning should embed and simulate the work environment with support from technology. For example, using virtual reality or augmented reality to replicate different working situations, such as a meeting with an audit client. Think like the old SIMS game for trainee accountants.
This will also mean exam boards need to follow this to embed more than just practical, real-life case studies and scenarios in the exam to make assessments that more authentic. Technology, again, will be a fundamental pillar to support this and the ICAEW are leading this with embedding Inflo into the Corporate Reporting, Data and Assurance exam and the new Technology Hub to explore using tools such as Dext’s automation capabilities or KNIME’s data analytics capability (among many others). This allows students to demonstrate their learning by interrogating and communicating insights from data rather than using small datasets that don’t reflect real-life.
Both of the above emphasise the need for a collaboratively working relationship between learning providers, employers, exam boards and others to enhance the quality of the learning experience.
There will be a continuing momentum towards qualifications (and therefore learning) adapting to the increasing sustainability-related learning needs. International Sustainability Standards are creating the long-demanded transparency and accountability so we will become more aware of how deeply impactful environmental sustainability issues could affect businesses. Learning contexts and case studies / scenarios will increasingly be built around highlighting sustainability-related issues. And maybe even the traditional comparison of ‘financial accounting’ vs ‘management accounting’ will start to see ‘carbon accountant’ or ‘ESG reporting manager’ appear, as well as the equivalent ESG auditors.
Learning will continue to be increasingly individualised and personalised support to each learner’s needs, which has been proven to improve attainment in lower-level studies.1 Students can individualise some aspects, whether it is putting a self-study video on 2x speed or using AI to recreate the content in their preferred learning style, but there is plenty of progress.
Alongside this, there is an increasingly ‘instantaneous’ nature to our world – instead of asking a search engine a question and trying to find an answer, we can now get a more definite answer by using AI tools (e.g. ChatGPT). This model replicates a live classroom environment or where there is a strong student-support model and will continue to expand the necessity for AI-assisted tools. For example, AI marking of questions or mocks, AI chatbots embedded in learning environments to answer exam-related queries or even more tailored assessments (e.g. computer-adaptive assessments). Things will have come a long way since the days of ‘Clippy’ providing tips for writing a letter!
This use of AI will amplify the need for engaging conversations on how to use tools responsibly, such as reviewing their sources of information and asking for evidence of their reasoning. This requires at least one whole extra article but the key is that the learning environment (and assessment model) needs to increasingly require data literacy, critical thinking of outputs and responsible or ethical AI use.
For example, reviewing and correcting the income tax computation produced by a junior who used AI to create it instead of creating it from scratch. This will also be supported by learning that focusses on prompt engineering (i.e. how to effectively ask AI questions) that will improve the efficacy of the outcomes e.g. providing examples or guidelines that guide AI to know the personality of the user.
This is just a taster of what we might see in the future. Some methods or tools cannot yet be seen or imagined but technological change means things will continue to develop in the most amazing ways. This will enhance the student experience, create depth of learning and ultimately improve the future of qualified accountants worldwide.
*the views expressed are the author’s and not ICAEW’s