It is becoming increasingly difficult to assess how much university students have learned. In his work as a mathematical statistics lecturer, Michael von Maltitz has made an effort new way Motivating students to learn, and assessing what they have absorbed and retained. Students must show and discuss how they reached an understanding of the topic. They can't rely on memorization alone, because he interviews them as if they are applying for a job.

What inspired you to try something new?

“We understand, but how will this be asked in the test?” This is a question that was repeatedly raised with me in 2019 when I began lecturing on a module in mathematical statistics in the second year of university level.

I knew I had to make a change. I already understood that students were stressed, tended to memorize and cram material before tests and exams, and used shortcuts to get good grades rather than learning anything.

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Then what did you do differently?

The module was unfamiliar to me so I decided to allow students to approach the course content in the same way I was doing: gathering information from different sources and combining it digitally and reflecting on how it helps meet certain objectives or learning outcomes.

These portfolios of evidence of learning will include curriculum and outcome information, content knowledge (including theorems and proofs), examples with solutions, showpiece assignments, links to online tutorials or videos and discussions, and paragraphs of self-reflection. Readers may refer to these portfolios as “study notes on steroids.”

Portfolio assessment will be an exercise in evaluating the learning process rather than a memorized product.

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This process was challenging but it offered a reward for me and my students – one of discovery. seemed to be students really learning.

In addition to checking their portfolios, I needed a way to assess progress that didn't fall into old habits of memorization and “teaching to the test.” I needed to ensure that a student had created his or her portfolio and could defend the content within it. And I needed an assessment method that would take no more time and effort than giving a unique written test or examination, preparing a typeset memo and marking over 100 answer scripts, providing feedback that students would probably never see.

I decided to test this form of deep learning using a workplace methodology – interviews. In 30-minute online interviews with each student, I asked questions about their understanding of the module material, as well as questions related to their own portfolios. Each student had to defend the information collected and reflected upon.

The interview worked perfectly when paired with the portfolio. I evaluated a set of portfolios one evening, provided typed feedback, and then interviewed the creators of those portfolios the next day. Feedback was immediate, and the interview assessment became a learning experience for me and the student.

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If I made an error in portfolio assessment, they were able to defend their portfolio, and I could quickly answer any interview question that would have caught them off guard.

Later, the recording of the interview can be given to the student, and if they feel I am being unfair at all, they can compare their interview with another student's interview. By doing this, students themselves can take control of my assessment practice.

What results did you see?

After teaching and assessing this way for a year or two, I noticed that my students began to understand more of the material. They retained more in their final year, were fluent in “statistical” communication and had better time management and self-reflection skills.

Students told me that they were asked the same questions in their first job interviews that I asked in my module, and that they felt much more comfortable in those first few job interviews.

How did you confirm these results?

To formally test the growth I saw in my students, I conducted research on the Class of 2022, which was published in conference proceedings and one Article.

This study revealed that students experienced significant learning in every aspect of the educational framework Fink's classification: :

  • basic knowledge
  • Applications and Communication
  • Integration of content in other areas
  • self reflection
  • Interest
  • Learning how to learn.

Thus, the method of learning and evaluation within statistics can be formally called successful.

Can this approach be used in other courses?

Yes. One could argue that if this method can be employed for mathematical modules, it can be used anywhere. Mathematical modules include theorems, proofs, definitions, theoretical and practical problem solving – items that may seem difficult to assess through verbal communication. But it's an understanding of the ideas behind the theorems stories And the tricks used within proofs, application to theoretical problems, which are so important in an age where your favorite AI can provide content knowledge.