TEQSA are about to release guidelines on assessment reform for the age of artificial intelligence. Traditional approaches to assessment were already under threat from contract cheating (Ellis et al., 2020). The advent of generative artificial intelligence agents has exacerbated those challenges. TEQSA’s draft guiding principles call for assessment that allows us to form trustworthy judgements about student learning. This will require multiple, inclusive and contextualised approaches to assessment. One approach is to examine the processes of student learning in concert with the artefacts students produce.
Another driver of assessment reform is the realisation that problem solving, design thinking, collaborative practice and a host of other ‘soft skills’ are more important attributes of graduates in today’s rapidly changing workplaces than the retention of a set of concepts and frameworks (see for example in the FinTech industry, Doherty & Stephens, 2023).
Assessing soft skills
Educators in higher education institutions have already been modifying their assessments in response to these drivers. They are building staged assessments, developing reflective practice, building in peer feedback, designing multi-modal assessments. Educational Innovation at the University of Sydney, for example, have put together comprehensive advice on assessment types that include visibility into the processes of student learning. But the descriptions of the requirements of these assessments still tend to be anchored in the language of constructive alignment (Biggs & Tang, 2011). I am not suggesting that we do away with learning outcomes and constructive alignment. I am suggesting that it might be time to start rethinking the language that we use in putting together learning outcomes, and the assessment rubrics that map to them.
The language of assessment
Learning outcomes generally describe what a student should be able to do at the end of a course. The language used in them is therefore focused on knowledge and skills, and how students deploy these. Often the language comes from learning taxonomies, such as John Bigg’s SOLO taxonomy, or the most pervasive of them all, Bloom’s Cognitive Domain (Anderson & Krathwohl, 2001). The language differentiates the levels or complexities of understanding a student has displayed. There is also a broader argument for rethinking how we describe student attainment. If institutions are claiming to be creating life-long learners, to be offering transformative education, there is something missing. How can we describe and assess how students are responding to their learning?
Back to the source
The team of educational psychologists responsible for the original iteration of the cognitive domain and its associated taxonomy actually produced three Handbooks on learning domains. The third was on the Psychomotor Domain, which we mention for completeness. The second was on the Affective Domain – dealing with emotional and behavioural response to education. I am not providing a link here, as the Handbook is not available online. The authors felt that affective behaviours of students should be considered separately to their cognitive behaviours. They challenged the belief that if cognitive objectives are developed, there will be a corresponding development of appropriate affective behaviours. They give an apt example of a literature course that instills ‘knowledge of the details of particular works of literature, while at the same time producing an aversion to, or at least a lower level of interest in, literary works’.
The affective domain
I have summarised in Table 1 the five levels of affective response a student may display towards a learning experience. I have drawn the descriptors directly from the source material.
| Receiving | Student passively attends to the experience. The student brings their prior experience which may facilitate or hinder their recognition of the phenomena to which the teacher is trying to sensitise them. |
| Responding | Student actively attends to the experience and responds in some way to it. |
| Valuing | Student shows a level of commitment to the ideas they have been exposed to, they express a belief or an attitude in their behaviour. |
| Organisation | Student has incorporated the value or idea into their existing beliefs, they have an abstract conceptualisation of the value or idea. |
| Characterisation | Student has changed their entire character and value system as a result of their experiences, they exhibit consistency of the new behaviour in all social roles they assume, in public and in private life. |
The authors of the Handbook acknowledge that the fifth level, ‘characterisation’, is extremely unlikely to be achieved over the course of a semester. More detail on each level exists in the Handbook. If you would like to have an in depth discussion on developing verbs, or building out sub-levels of the domain, you are invited to contact the author of this post.
Using the taxonomy
A small amount of literature has been published on use of the affective domain in characterising student learning. This tends to be in the area of experiential learning, where how the student responds to experiences is just as important as the knowledge and skills they acquire (see, for example, Davis & Knight, 2023).
Marina Harvey’s team turned to this domain when searching for a way to fully characterise her students’ short reflections (Harvey et al, 2019). They found that reflective frameworks didn’t quite capture what the team was seeing. Nor did Bloom’s cognitive domain alone. They combined the affective domain and cognitive domain descriptors into a new framework they called ’emo-cog’. They found that it had higher explanatory power than reflective frameworks, or the cognitive domain descriptors alone.
Table 2 demonstrates how one might use Bloom’s affective domain to build a richer marking rubric for a student reflection assessment piece. The traditional descriptor row is taken from an existing reflection assessment from a course the author has taught into.
| High Distinction | Distinction | Credit | Pass | |
| Traditional descriptors | Critically reflects on personal and peer experiences in the course | Critically reflects on personal experiences in the course | Some reflection on personal experiences in the course | Describes personal experiences in the course |
| Affect descriptors | Articulates values recognised, developed, and adopted related to experiences with peers, course material and self-reflection. | Describes process of growth related to experiences with peers, course material and self-reflection. | Responds to experiences with peers, course material and self-reflection. | Recognises or describes experiences with peers, course material and self-reflection. |
Further work
The levels of response in the affective domain of learning presented here show great promise in describing how students are affected by their educational experiences. Start to consider how you would like your students to respond in your course. Could you incorporate affective response into your assessment descriptions and rubrics? You could also think about making students aware of the levels of affect they should aspire to, as we do the complexities of cognitive attainment.
Lifelong learners don’t just have the skills that enable them to critically analyse new information, or to leverage their colleagues’ experiences. They also need to value learning, to search out different viewpoints, to compare their existing beliefs to those of others. Some students will do this instinctively. Some are going to need to be guided by the language of the affective domain.
Banner image was generated in Adobe Firefly. Book photos are author’s own.
