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Why 2023-2024 will be remembered as the academic year that education embraced AI
Last month saw the publication of a study which examines the implications of generative AI for higher education and proposes a first-of-its-kind framework for its strategic adoption at the institutional, departmental and classroom level.
After a rocky start in 2023 (aka the year of AI Detection), an increasing amount of experimentation, training and formal policy creation suggests that the academic year 2023-2024 will likely prove to be a defining year for higher education: the year higher education embraced AI.
Seen alongside developments like the release of the UK Russel Group Universities’ principles on the use of AI in education (also published in July 2023) and formal exploration by K12 school leaders of the opportunities offered by AI , we are witnessing an increasing number of signals that the education system more broadly is taking an increasingly proactive approach to AI.
In this week’s blog post I’ll provide a summary of the current education landscape and share my thoughts on why I think 2023-2024 will become remembered as the year that education embraced AI.
Let’s go! 🚀
Perceptions of AI in the Education System
A comprehensive AI policy education framework for university teaching and learning, published last month, surveyed 457 students and 180 teachers from Hong Kong universities. The goal was to get an up to date understanding of higher education’s views on AI in education and its likely implications.
The key findings of the study echo those shared in a number of other publications published in the last couple of months, including the UK Russel Group Universities’ principles on the use of AI in education which was also published in July.
Here’s the TL;DR on current trends in the AI Education conversation:
Educators and students have limited experience but plenty of optimism - Most educators and students had limited exposure to AI education tools, but believe AI could positively transform learning and teaching.
An urgent need for guidance on ethics - Students and teachers alike agree that institutions need to manage potential risks like misconduct through the creation of clear AI policies.
AI Training is urgent & critical - Providing training, specifically in how to evaluate the reliability of AI and use it responsibly was seen as urgent and essential.
Rethinking assessments - There’s a growing consensus that assessments need to be revised to maintain integrity, with a new focus placed on the assessment of process & skills.
Top 4 Concerns
The study raised a number of concerns about the integration of AI in higher education which echo concerns raised in the broader debate:
Cheating - Using AI to complete assignments enables academic misconduct and compromises academic integrity.
Privacy/security risks - AI relies heavily on data input, raising concerns about how student data is utilised.
Biases and ethical issues - Without necessary oversight, AI models could perpetuate biases and misinformation.
Unfair advantage - Wealthy students with paid access to AI may be advantaged over peers who cannot afford powerful AI tools.
Top 4 Opportunities
In terms of the opportunities offered by AI adoption, we again see themes in the study which echo themes of the broader conversation about AI and education:
Administrative efficiencies - AI can have a potentially transformative impact on education by automating repetitive administrative tasks, freeing educators up to focus on higher-value work, including research and student support.
Scalable personalised learning - AI has huge potential to customise the learning experience for each student's needs, at infinite scale. For higher education which has struggled with the wicked problem of scale for decades, this could be transformative.
More efficient & effective assessment - By enabling immediate, automated feedback on assignments, AI can save teachers' time and drive better student outcomes.
Workplace relevance - AI skills prepare graduates for an increasingly tech-driven job market.
The AI Ecological Education Policy Framework
Based on its findings, the study proposes a comprehensive “ecological” AI policy framework to enable higher education institutions to holistically and strategically implement AI.
The first-of-its-kind multidimensional framework suggests a practical but nuanced approach which provides guidelines for all key stakeholders across the education infrastructure. As such, it provides a helpful blueprint for education and other (e.g. L&D departments) for thinking about how to navigate the AI landscape.
The framework has three interdependent elements:
This dimension is owned by university leadership and is where AI transformation starts.
This foundational part of the strategy is responsible for developing and implementing guiding policies at the institution level.
Its goal is to manage the risks, ethics, integrity, privacy, security and accountability questions raised by AI.
This dimension is owned by departmental leaders.
Its purpose is to create and implement a set of pedagogical standards for the selection and use of AI tools at the departmental and classroom level.
Its goal is to ensure that AI is used to enhance teaching, learning, assessment, and skills development.
This dimension is owned by IT teams and teaching staff.
Its purpose is to deliver training and to support the implementation, adoption and evaluation of AI tools.
Its goal is to ensure that faculty are trained and supported to meaningfully integrate AI into the curriculum (design) and classroom (delivery).
Conclusion: The Road Ahead
After a rocky start, more and more evidence suggests that the academic year 2023-2024 will likely prove to be a defining year for higher education: the year higher education embraced AI.
Over the course of the next academic year, we will likely see three main changes in the world of education:
More education institutions will embrace AI & develop policies & guidance on its appropriate use at the institution, department & classroom level.
We will see a wave of assessment reform, with a new focus on the assessment of learners’ process and skills, including the effective use of AI.
To enable this chance, we will see a rapid increase in the provision of AI training for leaders, educators and administrators.
While risks and barriers to entry remain real, supported by well-rounded strategic frameworks, the education system has the potential to leverage AI reinvent itself and improve its ability to deliver on the promise to deliver real-world-relevant education.
Watch this space!
PS: Applications for the September cohort of my AI-Powered Learning Science Bootcamp are now open! Learn more and apply now!