What are we assessing? How?

How we can create a better assessment system, without penalties, that works in a grade-free environment? Let’s provide a foundation for this discussion by looking at assessment today.

Bloom’s Revised Taxonomy

We have many different ways of understanding exactly how we are assessing knowledge. Bloom’s taxonomy allows us to classify the objectives that we set for students, in that we can determine if we’re just asking them to remember something, explain it, apply it, analyse it, evaluate it or, having mastered all of those other aspects, create a new example of it. We’ve also got Bigg’s SOLO taxonomy to classify levels of increasing complexity in a student’s understanding of subjects. Now let’s add in threshold concepts, learning edge momentum, neo-Piagetian theory and …

Let’s summarise and just say that we know that students take a while to learn things, can demonstrate some convincing illusions of progress that quickly fall apart, and that we can design our activities and assessment in a way that acknowledges this.

I attended a talk by Eric Mazur, of Peer Instruction fame, and he said a lot of what I’ve already said about assessment not working with how we know we should be teaching. His belief is that we rarely rise above remembering and understanding, when it comes to testing, and he’s at Harvard, where everyone would easily accept their practices as, in theory, being top notch. Eric proposed a number of approaches but his focus on outcomes was one that I really liked. He wanted to keep the coaching role he could provide separate from his evaluator role: another thing I think we should be doing more.

Eric is in Physics but all of these ideas have been extensively explored in my own field, especially where we start to look at which of the levels we teach students to and then what we assess. We do a lot of work on this in Australia and here is some work by our groups and others I have learned from:

• Szabo, C., Falkner, K. & Falkner, N. 2014, ‘Experiences in Course Design using Neo-Piagetian Theory’
• Falkner, K., Vivian, R., Falkner, N., 2013, ‘Neo-piagetian Forms of Reasoning in Software Development Process Construction’
• Whalley, J., Lister, R.F., Thompson, E., Clear, T., Robbins, P., Kumar, P. & Prasad, C. 2006, ‘An Australasian study of reading and comprehension skills in novice programmers, using Bloom and SOLO taxonomies’
• Gluga, R., Kay, J., Lister, R.F. & Teague, D. 2012, ‘On the reliability of classifying programming tasks using a neo-piagetian theory of cognitive development’

I would be remiss to not mention Anna Eckerdal’s work, and collaborations, in the area of threshold concepts. You can find her many papers on determining which concepts are going to challenge students the most, and how we could deal with this, here.

Let me summarise all of this:

• There are different levels at which students will perform as they learn.
• It needs careful evaluation to separate students who appear to have learned something from students who have actually learned something.
• We often focus too much on memorisation and simple explanation, without going to more advanced levels.
• If we want to assess advanced levels, we may have to give up the idea of trying to grade these additional steps as objectivity is almost impossible as is task equivalence.
• We should teach in a way that supports the assessment we wish to carry out. The assessment we wish to carry out is the right choice to demonstrate true mastery of knowledge and skills.

If we are not designing for our learning outcomes, we’re unlikely to create courses to achieve those outcomes. If we don’t take into account the realities of student behaviour, we will also fail.

We can break our assessment tasks down by one of the taxonomies or learning theories and, from my own work and that of others, we know that we will get better results if we provide a learning environment that supports assessment at the desired taxonomic level.

But, there is a problem. The most descriptive, authentic and open-ended assessments incur the most load in terms of expert human marking. We don’t have a lot of expert human markers. Overloading them is not good. Pretending that we can mark an infinite number of assignments is not true. Our evaluation aesthetics are objectivity, fairness, effectiveness, timeliness and depth of feedback. Assignment evaluation should be useful to the students, to show progress, and useful to us, to show the health of the learning environment. Overloading the marker will compromise the aesthetics.

Our beauty lens tells us very clearly that we need to be careful about how we deal with our finite resources. As Eric notes, and we all know, if we were to test simpler aspects of student learning, we can throw machines at it and we have a near infinite supply of machines. I cannot produce more experts like me, easily. (Snickers from the audience) I can recruit human evaluators from my casual pool and train them to mark to something like my standard, using a rubric or using an approximation of my approach.

Thus I have a framework of assignments, divide by level, and I appear to have assignment evaluation resources. And the more expert and human the marker, the more … for want of a better word … valuable the resource. The better feedback it can produce. Yet the more valuable the resource, the less of it I have because it takes time to develop evaluation skills in humans.

Tune in tomorrow for the penalty free evaluation and feedback that ties all of this together.