I returned to master's studies after many years of working and running a business. I brought experience back to the classroom, but also questions that practice had not always helped me answer.
Returning to education helped me understand some of my decisions better. To connect what I had done with the reasons why something had or had not worked. A person can spend years convinced they know something, only to recognise through learning what they had been missing.
It was precisely this meeting of experience and academic knowledge that prompted a question: how could we prepare students even better for the moments when they will have to make decisions independently?
One opportunity I see lies in how we assess knowledge.
Imagine part of an exam taking this form. A student receives a problem they have not considered before. They have access to reading materials, notes and digital tools, with clearly agreed rules for their use. They prepare a proposal, then explain in a discussion with their professor how they arrived at it.
At a faculty of economics, for example, they might analyse a company whose sales are growing while the money in its bank account keeps shrinking. Customers are late paying. Employees expect pay rises. A supplier requires payment in advance.
What would they check first? What information is missing? What can they propose straight away, and which decision still lacks enough information?
The task brings together knowledge from several subjects. The student uses theory to understand the situation, connects the data and considers the consequences of their proposal. Through questions, the professor can see how much the student has understood and where they need further support.
Then the professor introduces a new circumstance:
“Your biggest customer has just ended the business relationship.”
The student now needs to reconsider what they proposed. Which part of the solution still makes sense? What must change? Does the new information also require a different sequence of actions?
An important moment of learning would be when they say, “With this information, I would change my decision,” and can explain why.
An exam like this requires a thorough knowledge of the field. The student must know what to look for in the literature, how to check an answer provided by artificial intelligence, and whether they can apply it to a specific problem. In discussion with the professor, they show how well they understand what they have prepared.
Two students could propose different solutions and both demonstrate a high level of knowledge. They would be assessed on how they justify their proposal, what they have taken into account and whether they have recognised the possible consequences.
This form of assessment would be developed through teaching, case studies and discussions throughout the semester. Students would have opportunities to try, receive feedback and improve their work. Professors would need time, support and the right conditions to follow their progress. The approach would, of course, be adapted to the subject and level of study.
As someone who now brings together the experiences of a student and an employer, I see great value in this. I do not expect a young person to immediately have the confidence of an experienced professional. What I appreciate is their ability to ask a question, recognise what they do not yet know and seek help before making an important decision.
At a time when answers are becoming ever more accessible, the ability to assess their accuracy, meaning and consequences is growing in importance. University is a place where that ability can develop through knowledge, research and discussions that give students room both to make mistakes and to improve.
I would like students to experience, even during an exam, what it means to stand behind their answer. The professor can then ask: “What would lead you to change this answer?” The value of that question remains long after graduation.
Comments