Reimagining Assessment and Opportunity

Article 3 

The Summative Assessment Dilemma

In my previous article, I advocated for school educators to focus solely on formative assessment, leaving summative judgements to external parties. This proposition, while addressing some issues, undoubtedly raises concerns. Transferring summative decisions from educators to private businesses is fraught with ethical pitfalls and potential conflicts of interest.

However, before we address these concerns, we must confront an uncomfortable truth: why does summative assessment exist at all?

Education’s Unspoken Secret

Like an elephant in the room, we often avoid discussing a fundamental aspect of our education system. Whilst we emphasise the acquisition of knowledge and skills, a significant portion of the education industry serves another purpose entirely – addressing the economic problem of scarcity.

In a world of 8 billion people and limited resources, we can’t all have equal access to our needs, let alone our wants. Despite generally improving global living standards, vast inequalities persist both within and across nations.

So how does one secure more than their “fair share”? Unless born into wealth, the answer typically involves securing a high-paying job. But herein lies the problem: not everyone can have these coveted positions.

The Qualification Conundrum

Human advancement has come through the process of specialisation where tasks are completed by those most suited and skilled at that task. This is exactly what employers are looking to achieve. They want to employ the person who can do the job the best. In an ideal world, employers would thoroughly vet every candidate through references and interviews to find the most suitable candidate. However, the time and cost implications of such a process are prohibitive. What’s more, as the world has globalised and ever more people have a chance to apply for desirable jobs, this has become even further from our grasp. Enter our profitable education qualification system.

Whilst cloaked in ideals of learning and growth, this system often functions as a glorified ranking mechanism. Ten GCSEs, an Oxford degree, and a master’s from Harvard? Your application makes the shortlist. Five GCSEs and no degree? It’s likely headed for bin.

As a teacher, I always tell my students that my aim isn’t just to educate them, but to keep as many doors of opportunity open as possible by allowing them to create a CV that will find its way onto everybody’s shortlist.

AI: The Catalyst for Change?

However, AI could be the catapult of change to this ugly system. Most exam boards are already spending a fortune looking at AI to reduce costs in marking exams. Some even more forward-looking exam boards are exploring the potential of exams being interactive with AI. Of course, the anti-high stakes exam fanatics are very excited about AI’s potential to offer continual summative assessment through a medium that suits the individual, potentially yielding more representative results.

These are exciting times, but whilst we’re dwelling in the realm of potential, I believe we should be looking even further ahead.

A World Without Summative Assessment?

Perhaps AI can create a world without summative assessment. Let’s revisit the original reason for degrees, certificates, and rankings: employers who can’t afford the time or resources to thoroughly assess every candidate’s merits.

But if AI capabilities continue to grow at their current rate, it’s not unreasonable to foresee a world where employers can immediately and affordably delegate selection to AI. Imagine an AI system trained in psychology, HR assessment, and all other necessary skills. An AI free from human bias that can administer tests tailored to each individual’s needs and skillset, fairly assigning roles to those best suited for them.

This AI-driven approach could potentially:

1. Eliminate the need for traditional qualifications as gatekeepers
2. Assess candidates based on their actual skills and potential, rather than their ability to pass standardised tests
3. Reduce bias in hiring processes
4. Match individuals to roles where they can truly excel and find fulfilment

A Reality Check

We’re not there yet – not even close. Current generative AI is still riddled with biases and often amplifies discrimination and stereotypes rather than diminishing them. But it’s still in its infancy, and it’s learning. It’s learning fast.

Conclusion

These musings might seem like the result of overexposure to the AI hype cycle. But at the very least, they’ve allowed me to envision a world where education is purely about the accumulation of knowledge and the acquisition of skills rather than the collection of shiny badges that help us climb an arbitrary human ranking system.

This future would undoubtedly come with its own set of challenges and ethical considerations. How do we motivate students in the short term? How do we ensure the AI systems are truly unbiased? How do we maintain privacy and prevent the misuse of personal data? To name name but a few.

Perhaps they are insurmountable, but for the moment, though, I hugely enjoy envisioning a world where I, as a teacher, never again have to summarise a student as less than average.